Annual Radiology Newsletter | 2007 - Department of Radiology

UNIVERSITY OF
CHICAGO
Department Of
Radiology
NEWSLETTER & ANNUAL REPORT
2007-2008

Table Of Contents
Chairmans Report . . . . . . . . . . . . . . . . . 1
Department News . . . . . . . . . . . . . . . . . 3
Clinical Sections . . . . . . . . . . . . . . . . . . . 7
Abdominal Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Breast Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Musculoskeletal Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
Neuroradiology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Nuclear Medicine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Pediatric Imaging. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Thoracic Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Vascular and Interventional Radiology. . . . . . . . . . . . . . . . . . . . . . 16
Research . . . . . . . . . . . . . . . . . . . . . . . . . 17
Paul C. Hodges Alumni Society . . . 42
Educational Programs . . . . . . . . . . . . 44
Fellowship Programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
Diagnostic Radiology Residency . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Medical Student Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
Graduate Program in Medical Physics . . . . . . . . . . . . . . . . . . . . . . 47
Faculty Achievements . . . . . . . . . . . . . . . . . . . . . 54
Honors & Awards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
Society Offices & Committees. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
Editorial Board Memberships . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
Manuscript Reviewers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
Scientific Presentations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Invited Presentations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
Exhibits. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
Patents. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
Peer-Reviewed Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
Invited Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
Abstracts and Proceedings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
Chapters, Books, and Review Articles . . . . . . . . . . . . . . . . . . . . . . 74
Grants and Contracts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
Radiology Celebrates . . . . . . . . . . . . . . . . . . . . . . 78
Department Administration . . . . . . . . . . . . 81

Chairman’s Report
Dr. Richard L. Baron,
Professor and Chairman,
Department of Radiology.
1.5T MR center in Mitchell Hospital Radiology opened
in fall of 2007, but did not increase capacity as we closed
one unit for renovation. The new clinical 3T MR scanner
installation has been delayed until early 2009. Despite the
lack of new equipment, CT and MR volumes continued
to increase compared with most recent years as shown in
the accompanying graphs:
The 2007 – 2008 academic year was one of many accomplishments
for the Department of Radiology. The key
role the department holds at the University of Chicago
Medical Center is evident throughout this report in all
aspects of our missions -- forefront and compassionate
clinical care, outstanding educational programs, and
leading basic and clinical research. This report provides
depth and detail on the department activities but as
Chair I would like to highlight some of the activities of
the Department.
Figure 1
Clinical Service
Clinical activity in the Department continued to expand
at a seemingly endless pace. Key perspectives on this
growth became clear to me when I came across an old
document from a few years back detailing the growth in
clinical activity for the Department between 1998 and
2004. I thought it of interest to look at a decade’s growth
to 2008 of radiology activity at the University of Chicago
Medical Center. Total procedural volume grew from
184,000 to nearly 300,000 procedures, almost doubling.
This statistic in itself is misleading in terms of clinical
activity, as general radiology, our simplest least time
consuming procedure showed a basically flat volume of
approximately 100,000 procedures. The CT volume grew
from 22,600 to 61,300; the MR volume from 7000 to
17,000! These current volumes represent more than a
doubling of the effort of the faculty and staff and a substantially
increased impact on patient care. And in addition,
in 2004, the Department began providing radiology
services at Weiss Hospital.
The 2007 – 2008 year was one of increasing productivity
with little increases in new equipment. The CT team
awaits the installation of the new 256 slice scanner, originally
scheduled for February of 2008, but construction
delays have backed this up to early fall. The new
Figure 2
With the installation of our new speech recognition dictation
system from Commissure, our report turnaround
time markedly decreased, and now averages 12 hours for
all studies, with most completed in several hours. The
impact we now provide to patient care has substantially
increased in many ways --- patient studies can be completed
and the patient seen in specialty clinics immediately
following with a report in the medical record system.
What a dramatic change from just several years ago
(2004) when the average turnaround time was 84 hours!
Teaching Programs
Throughout this report you will see the contributions of
our trainees from the radiology residency and the medical
physics programs towards all of our missions. The
diagnostic radiology residency program remains
approved for 28 positions, but late in the year we started
planning for the new academic affiliation with North
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Shore University Health System (formerly Evanston
Northwestern Hospital). It is anticipated that our radiology
residents will have some of their educational rotations
at that site, and that we will increase our residency
size correspondingly. The residency program and its
new curricular changes had demonstrable and measurable
evidence of its quality and impact in the 2008 academic
year. The residents from the University of
Chicago taking the American Board of Radiology
physics examination averaged the #1 highest scores
among all North American residency programs. And at
the American College of Radiology In Service examination
given to all North American radiology residency
programs in February, 2008 our first year residents as a
group performed at the 99th percentile, and the second
year residents at the 98th percentile.
Our medical physics program, in conjunction with faculty
from Radiation Oncology through the Committee on
Medical Physics had 30 predoctoral students during the
year. As always the doctoral candidates had an outstanding
academic year with five graduating. Their
research accomplishments are reflected in the 24 awards
(RSNA, SPIE, etc.) and 49 papers accepted for publication
during the year! Currently ten of the 30 graduate
students have U.S. Army predoctoral scholarships and
others are funded by our Department NIH training
granted. Our department has always been very popular
with medical students not just for clinical elective rotations,
but we have always had large numbers of students
working in our research programs. All of our
trainees continue to bring vitality and new ideas to our
department.
submitted federal grant proposals during the year, a
remarkable achievement in consideration of the current
NIH funding climate.
Figure 3
Research Programs
This was an exciting year for our research programs. The
Department faculty received its fourth NIH shared
instrumentation grant (Dr. Chen) in 3 years and resulted
in our installing a new microPET/SPECT/CT. Planning
and construction continued for the installation of the new
research 3T MR scanner supported by Dr. Jia-Hong Gao’s
$2 million NIH large instrumentation grant received during
the year with extensive renovations and sited adjacent
to the new 1.5T rampable to 3T MR unit that will
house the research MR guided focused ultrasound ablation.
Construction delays have turned back anticipated
opening to November, 2008. While all investigators
nationwide, including ours, are impacted by the increasingly
difficult NIH funding lines, this past year once
again was a strong funding year for the Department of
Radiology. The accompanying graph shows that during
this academic year the Department expenditures were
essentially the same as in FY 2007, reflecting over $6 million
(direct and indirect) of federal grant funding, sustaining
the growth from earlier in the decade.
Department faculty had a success rate of over 20% on all
Figure 4
Faculty Appointments
And Promotions
The primary resource in the Department of Radiology has
always been our faculty and through key recruits and
growth we are able to provide new areas of expertise
expanding into new clinical and research areas. During
2007 - 2008 new faculty joined several section. Delilah
Burrowes, MD, trained in adult and pediatric neuroradiology,
joined our faculty as assistant professor after
serving on the Northwestern Medical School faculty
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primarily at Children’s Memorial Hospital. Vivek
Sehgal, MD, a diagnostic neuoradiologist who had
trained in our department and served on our faculty in
the past, was recruited from a faculty position at Wayne
State University to rejoin our neuroradiology section as
assistant professor. Steve Zangan, MD, a former chief
resident from our program completed an interventional
radiology fellowship with us and joined our faculty as
an assistant professor in the Interventional Radiology
and Chest sections. Two faculty were promoted during
the year reflecting on their accomplishments. Emil
Sidky, PhD, was promoted to Research Associate
(Associate Professor), and Brian Funaki, MD, chief of
interventional radiology, was promoted to Professor.
The faculty, staff, and trainees in the department can be
proud of the accomplishments described in this report.
The Department clearly embodies the missions and goals
of the University of Chicago and represents our institutions
well. I hope you will take the time read this report
and see the full extent of our department’s accomplishments.
I am confident in doing so you will share the
excitement that is evident in the department on a daily
basis that characterizes the Department of Radiology. We
continue to build a solid foundation for the Department
and the institution to continue to be a leader in medical
care and imaging for years to come.
Department News
Teaching Radiology to Medical Students in the 21st
Century and Changing the Curriculum at the
University of Chicago
The Radiology Department has recently been identified
by the University of Chicago community as a leader in
medical student education. The last several years have
produced a successful drive to be innovative and construct
cutting edge student programming into a new
radiology curriculum for early medical student education.
An internal evaluation of the entire Pritzker Medical
School curriculum was recently completed as part of a
planning process for a new overall curriculum structure
to be phased in over the next several years. The
Radiology Department’s educational efforts were particularly
cited by the BSD Dean for our innovation and we
have begun to aggressively implement additional new
programming that will bring imaging education front
and center, integrated into a team approach to patient
care, and ensuring that graduating students are well
versed in imaging principles and how radiologists work
in optimizing patient outcomes.
Our largest change was implementing radiology imaging
education into the classroom early in the first two
years of Medical School. The previous curriculum
offered radiology as an elective course in the senior year.
The change with concomitant teaching of pertinent
material with existing required medical school basic
courses serves two significant benefits. It exposes students
to the imaging options and modalities and most
importantly emphasizes the integration of imaging with
all aspects of patient care. Radiology material not only
helps coalesce concepts from basic anatomy to pathological
processes; but it is appearing to have the added effect
in better overall use of our hospitals imaging resources
and equipment by affecting ordering habits and awareness
of more focused and dedicated imaging options.
Radiology has made itself more available across the curriculum
to make sure material is taught by radiologists.
This move into the classroom brings a cohesive thread
through the students’ curriculum and more importantly
a clinical excitement to the first two years of training. The
human morphology course was a natural fit at combining
imaging with the lecture and dissection components
and has resulted in a course that is very popular with
students. This new combination precipitated the installation
of flatscreen projections and use of digital imaging
not just within lecture but directly and in real time to
their lab sessions. Radiology went from a passive supplement
to an integrated occurrence with dedicated daily
sessions representing 20 % of the overall material and
exam in this key course.
Direct anatomic correlation is stressed in lab, integrating
the knowledge and relationship of structures. This is
opposed to the more traditional memorization of structures
of the past. This also fosters an integrated understanding
of the anatomy as seen through radiology
imaging, solidifying vocabulary and an understanding
which will be used for the remainder of their careers. The
chance to incorporate an early dose of clinical pertinence
additionally gels the experience into one which
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emphasizes the fundamental concepts and is fruitful
regardless of the student’s future subspecialty.
A similar approach has been employed with the Clinical
Pathophysiology and Treatment course, which continues
to represent the backbone of the non clinical program.
Imaging is being incorporated into existing sections and
proving that a picture can speak for a 1000 words.
Second year students are at this point familiar with a
variety of modalities and projections, so there is little
explanation needed other than discussing the pathological
process being taught.
Course number 305 was completely reformulated and
offered in the spring. This course is designed to appeal
to first and second year students and uses pathology to
reinforce basic concepts as well as exposes students to
our field in more depth. It is used for Step 1 board exam
preparation and is a significant pathway in bringing first
year students into departmental research. Many take the
course and follow up their interest with a project or the
SRP program.
Students now enter the clinical clerkships with a solid
awareness of what role imaging plays in patient care
and basic skills to interpret studies. Our early observation
is showing a suspicion that students are far more
likely to use our services more effectively and efficiently.
There is the hope to create and implement dedicated
student level radiology rounds within the third year
clerkships and this last step would complete the envisioned
radiology curriculum changes, leaving the senior
year free to pursue a more challenging experience that is
focused on a topic or collaboration which will benefit
the individual student in their chosen career.
Seniors are now offered one of several targeted electives.
Listed courses have additionally been altered and
updated to align with the premise that students ought to
be incorporated into the daily department workflow and
not just listen passively. Dedicated student lectures and
online programming have been utilized and the installation
of a computer lab eases access. Students are also
using as well developing dedicated MIRC teaching files.
Research and personalized projects have also remained
available.
The newest component, in its final development, is a
new spring senior course aimed at preparing all seniors
for internship. We have seen a steady rise in our specialty’s
interest above the average and the overall increase
noted nationally. This past year alone, 10 students chose
to apply and match in our field; 40 % of the AOA recipients
of the 2009 class.
The end result of these changes has been to increase our
department teaching role and availability and the
response has been overwhelming and positive.
Giger, PhD Elected
President of AAPM
Maryellen L. Giger, PhD
Maryellen L. Giger, PhD, Professor of Radiology, the
Committee of Medical Physics, and the College has been
elected President of AAPM, the American Association of
Physicists in Medicine. She is finishing her President-
Elect year in 2008, followed by serving as President in
2009 and Chairman of the Board in 2010. Dr. Giger
Board in 2010. Dr. Giger is also Vice Chair of Radiology
for Basic Science Research, and Chair of the Committee
on Medical Physics at the University of Chicago, on
which she serves as director of our CAMPEP-accredited
Graduate Programs in Medical Physics.
The mission of the AAPM is to advance the practice of
physics in medicine and biology by encouraging innovative
research and development, disseminating scientific
and technical information, fostering the education and
professional development of medical physicists, and promoting
the highest quality medical services for patients.
The AAPM is a scientific, educational, and professional
organization of more than 5,000+ medical physicists and
is a member of the American Institute of Physics. Its publications
include the scientific journal Medical Physics.
Headquarters are located at the American Center for
Physics in College Park, Maryland.
Many AAPM members also participate in the annual
meeting of the RSNA. The AAPM enjoys a productive
relationship with the RSNA in arranging the physics sessions
and refresher courses at the annual RSNA meeting
as well as working together on initiatives. Recent joint
initiatives include the advancement of quantitative imaging
in research, clinical trials, and practice, and the development
of physics teaching modules for radiology residents.
Dr. Giger is most noted for her research in CAD – computer-aided
diagnosis – especially in multi-modality
breast imaging. Her lab has extended its research on
mammography, breast ultrasound, and MRI CAD to the
development of image-based methods for cancer risk
assessment and for prognostic and predictive markers. In
addition, her lab is investigating image-based methods of
assessment of osteoporosis and osteolysis on skeletal
images, analysis of cardiac CT for improved image quality
and interpretation, and analysis of prostate MR images
as well as investigations into effective and efficient methods
for presenting CAD outputs to the end user. Her
research is supported by NCI, NIBIB, NIAMS, DOD, and
DOE, and she serves as co-P.I. of the University of
Chicago Breast SPORE.
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A New MicroPET/SPECT/CT and
Ultrasound Laboratory for Imaging of
Small Animals
The Department of Radiology, in collaboration with the
Section of Cardiology of the Department of Medicine,
has recently established a Joint Small Animal Imaging
Laboratory that is equipped with a Gamma Medica
Ideas (GMI) Triumph Multi-Modality Pre-Clinical
MicroPET/SPECT/CT Imaging System (now distributed
exclusively by GE), purchased in part with an NIH
Shared Instrumentation Grant (P.I.: Chin-Tu Chen, PhD),
and two VisualSonics Vevo 770 Micro-Ultrasound
Imaging Systems. Chin-Tu Chen, PhD, of Radiology and
Chief of Cardiology in Medicine, Stephen Archer, MD,
are Faculty Co-Directors of this new laboratory.
Together with the existing Optical Imaging Core Facility
(Chin-Tu Chen, PhD, and Patrick La Riviere, PhD,
Faculty Co-Directors) and the MRI/MRS Core Facility
(Gregory Karczmar, PhD, and Brian Roman, PhD,
Faculty Co-Directors), these animal imaging capabilities
enable Radiology and our faculty, as well as their
research collaborators throughout the BSD, to employ
and utilize a full spectrum of various imaging modalities
to conduct investigations involving small animal models
for cancer, cardiovascular diseases, brain and behavioral
disorders, and other biomedical research.
Small animal imaging methods have become powerful
tools for biomedical investigation of in vivo
structural/functional norms in health and alternations in
disease, as well as their biochemical and physiologic
bases. Imaging of small live animals longitudinally over
time can provide more reliable observations and
improved quantitative measures of the normal and
abnormal, disease progression, tissue recovery, and
responses to drugs and other therapies. Incorporation of
small animal imaging has become an integral and essential
component in routine biomedical research.
Establishment of this state-of-the-art animal imaging
laboratory to perform PET, SPECT, CT and ultrasound
imaging of small animals allows Radiology and our faculty
to expand their research horizon and enhance their
research potentials. Initial research projects utilizing these
new imaging capabilities range from imaging for evolution
biology and paleontology, evaluation of novel tracers
and image-enhancing agents, investigation of cardiopulmonary
functions, imaging for drug development and
assessment of drug effects, brain imaging of animal models
of various brain and behavioral disorders, to quantitative
measurements of responses to radiation therapy and
gene therapy, etc.
Continuous Quality Improvement
Initiatives in the Department
The structure of the Continuous Quality Improvement
(CQI) Committee was revamped in 2008, to optimize
planning and reporting of Departmental and physician
indicators. A core group, consisting of Monica Geyer,
Assistant Director of Specialty Imaging, Milton Griffin,
Assistant Director of General Medical Imaging, Dr. David
M. Paushter, Vice Chair of Operations and Departmental
Quality Chair, and Amanda Schmitz, representative from
the Center on Quality, provided leadership and planning
for ongoing and new projects. Physician Section Heads
and Departmental managers worked in tandem with this
core group as the CQI Committee.
Key Departmental indicators were tracked continuously
during the year, to allow rapid comparison with goals
and implementation of improvement initiatives as needed.
The Department made great strides in several areas
directly relating to patient safety and service. Key
improvements included:
• The Nuclear Medicine/Nuclear Cardiology/PET
Section developed and implemented policies to bring
radiopharmaceutical preparation in line with USP 797
regulations and JCAHO medication management standards.
The policies require specific training and education
initiatives with annual competency evaluation and
daily environment inspection.
• CT and MRI developed and implemented policies to
align contrast administration with JCAHO medication
management standards and Leapfrog Survey requirements.
Pharmacy was actively involved in the development
of the policies. The policies increase the safety of
the administration of contrast with regard to screening
for reaction risk and nephrotoxicity and include
mandatory MRI safety screening for implanted metal
objects.
MicroPET/SPECT/CT pre-clinical imaging system in the new
animal imaging laboratory with sampled images...
• CT also worked collaboratively with the Emergency
Department (ED) to reduce the exam turnaround time
for ED patients. The turnaround time was reduced by
45% and efforts are ongoing to further reduce this
result.
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Physician projects were both Departmental and section
driven, to provide both a broad evaluation of fundamental
parameters for all clinical Faculty as well as sectionspecific
projects. At the Departmental level, installation
of a new voice dictation system, coupled with significant
improvements in PACS functionality resulted in a reduction
in report turnaround time from 24 to 15 hours.
During prime working hours, completed exams are
often reviewed with finalization of reports in less than
one hour. Migration of the Radiology peer review system
to a PACS-based function allowed physicians to
enter and retrieve data efficiently, and an electronic database
provided material for comparison with national
norms.
At the section level, specific projects included:
• Abdominal Imaging: Sources of Diagnostic Error
Utilizing a PACS-based Peer Review System. With an
ultimate goal of improving radiologist performance
and patient care, the Section initiated a two year project
to analyze errors recognized as part of the
Department’s peer review program. Errors considered
significant are reviewed during a meeting of all
Section members, and categorized by potential cause
of inaccuracy.
• Breast Imaging: Integration of the Digital Enterprise
for Breast Imaging. The Section has worked in conjunction
with the Information Technology group on a
two year project to devise software solutions to
decrease patient wait time, decrease technologist exam
time, improve file room personnel work flow, reduce
physician report time, and develop a database to
ensure the timeliness and quality of patient care.
• Thoracic Imaging: Frequency and Nature of Errors in
Radiological Reports Associated with Voice
Recognition. Section members reviewed chest x-ray
and chest CT reports for significant errors prior to and
after the institution of a voice dictation system. A negligible
error rate using conventional dictation and
transcription increased to 24% of CT and 10% of chest
x-ray reports immediately after conversion to a voice
system. By report review and section discussion, a significant
reduction in errors was achieved on initial follow
up sampling.
• Vascular and Interventional Radiology: Detection and
Treatment of Peripheral Vascular Disease in
Hemodialysis Patients. The Section, recognizing the
strong association of peripheral arterial disease (PAD)
and severe renal disease, screened hemodialysis
patients without known PAD by using noninvasive
testing. Nearly 25% of patients were discovered to
have significant disease, not previously identified in
90%. These patients with PAD were then treated with
intervention or medical therapy, possibly avoiding significant
future complications.
• Musculoskeletal Imaging: Analysis of the Adult
Radiographic Skeletal Survey Examination at the
University of Chicago. This project found that the number
of skeletal radiographs obtained as part of a skeletal
survey for malignancy could be reduced without
diminishing clinical results. This decreased technologist
time by 14% per examination, with an associated
decrease in radiation dose to the patient.
• Pediatric Imaging: Hand Hygiene in Fluoroscopic
Procedures before and after an Educational
Intervention. In accordance with the National Patient
Safety Goals, the Section instituted monitoring of hand
washing adequacy by World Health Organization criteria
prior to patient interaction. A goal of 100% compliance
was achieved after repetitive education, although
it was noted that repeated monitoring and intervention
is required for success.
• Neuroradiology: Improving Temporal Bone CT
Evaluation. Concern with variation in temporal bone
CT imaging parameters, post processing and appropriate
reconstruction from raw data led to standardization
of techniques, educational efforts geared to the technologists
and formulation of new protocols that were
machine specific. These interventions significantly
improved the quality of examinations, including 100%
compliance with the new outpatient protocols.
• Nuclear Medicine: Improving Detection of the Sentinel
Lymph Nodes in Breast Lymphoscintigraphy. This project
demonstrated a statistically significant improvement
in sentinel lymph node detection for operative guidance
of patients with breast cancer, by varying the
dosage of the radionuclide Tc-99m Sulfur Colloid.
Robert N. Beck, 80,
Leader in
Advancing
Scanning for
Medical
Diagnoses, Dies
Robert N. Beck
Robert Nason Beck, a pioneer in nuclear medicine and
professor emeritus in the Department of Radiology, died
on August 6, 2008, at the age of 80.
He was born March 26, 1928, in San Angelo, Texas, a
small town about 350 miles southwest of Dallas. He
attended and received two degrees from the University
of Chicago and began working on early imaging instruments
for the nuclear medicine group in the newly
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created Argonne Cancer Research Hospital (ACRH) in
1954, and met fellow student, Ariadne Plumis, whom he
married in 1958.
Professor Beck was a key member of a University of
Chicago research team that was one of the first to investigate
several of the tools of modern nuclear medicine.
They are perhaps best known for introducing technetium-99m
into clinical practice in the early 1960s as a
radiotracer agent. He was also known for his fundamental
role in developing the theoretical framework at the
core of much of nuclear medicine and for bringing mathematical
rigor to imaging systems, such as SPECT and
PET scans.
From 1976 to 1994, Professor Beck was Chief of the
Section of Radiological Sciences. In 1977 he was named
Director of the University of Chicago's Franklin McLean
Memorial Research Institute, which replaced the Argonne
Cancer Research Hospital. He helped to acquire a PET
scanner and an MRI system, and to develop ways to
improve the display of PET, MRI other scans. In 1986 he
founded and became Director of the Center for Imaging
Science, designed to pull together the many disciplines at
the University and Argonne National Laboratory that rely
on all sorts of imaging tools and methods.
Professor Beck is survived by his wife, Ariadne, of Indian
Head Park, and two sisters, Mary Ann Beck and Dorothy
Corbell of San Angelo, Texas.
Clinical Sections
Abdominal Imaging
The Section of Abdominal Imaging. Sitting (from left): Dr.
Paul Chang, Dr. David Paushter, Dr. Kirti Kulkarni, Dr.
Abraham Dachman. Standing (from left): Dr. Michael
Vannier, Dr. Aytekin Oto, Dr. Richard Baron, Dr. Brian
Funaki, Dr. Arunas Gasparaitis.
The 2008 academic year was a year of programmatic
expansion for the Section of Abdominal Imaging including
diagnostic clinical techniques, research initiatives,
resident and medical student education and quality
assurance. Clinically, the Section added prostate MR
imaging and spectroscopy for suspected or proven
prostate cancer, under the guidance of Drs. Aytekin Oto
and Michael Vannier as well as expanded programs in
MR enterography and diffusion imaging. CT protocols
were honed to remain cutting edge, with an emphasis on
providing clinically relevant information with a minimum
of radiation exposure to the patient. Virtual
Colonography, long pioneered by Dr. Abraham
Dachman, expanded as a clinical tool, both for colon
screening and problem solving. Pediatric and adult
ultrasound were combined under a single administrative
structure with sharing of personnel to improve flexibility
in patient scheduling and sonographer availability. To
accomplish this, a “cross-training” program for the technical
staff was successfully implemented and completed
by all personnel. Improvements in the Department’s pic
ture archiving and communication system (PACS) and
full implementation of a voice dictation system under
the leadership of Section member Paul Chang, MD, significantly
decreased exam reporting time and provided
direct electronic reporting to the Emergency Department.
The Section has invested considerable time in enhancing
its educational programs for medical students, residents
and fellows. The medical student experience was completely
redesigned at a Departmental level, with more
extensive involvement of faculty in the didactic and clinical
educational process. The Sectional teaching program
has also been revamped, to more fully emphasize the
clinical relevance of imaging findings. Residents and fellows
now attend relevant multidisciplinary conferences
with faculty, and present instructive cases at a subsequent
daily Abdominal Imaging teaching conference. In
addition, information on studies that have had pertinent
follow up and illustrative, interesting or difficult cases
are presented on a daily basis. The Abdominal MR rotation
has been reorganized and expanded by the Director
of Body MR, Aytek Oto, MD. The Section continues to
provide two didactic conferences per week to the trainees
of the entire Department. The Abdominal Imaging teaching
file has been greatly expanded, due to the ease of
entering cases from our PACS system, allowing case
entry during clinical work as well as more formal case
entry into the MIRC system.
The Abdominal Imaging fellowship program, under the
leadership of Fellowship Director Abraham Dachman,
7

MD, had a successful year with completion of the program
by Dr. Kirti Kulkarni, who excelled clinically and
completed significant research projects, both within the
Section and in conjunction with the Section of Breast
Imaging. Dr. Kulkarni joined the Department as a member
of both sections in July of this year. Her broad based
expertise will further enhance the clinical, teaching and
research capabilities of the Section.
The Section has continued to be an active participant in
the Radiology Departmental quality assurance program.
Taking advantage of the information technology expertise
of Dr. Paul Chang and University of Chicago Medical
Center personnel, the biopsy results tracking system, a
PACS-based function, has been utilized to compare invasive
procedure efficacy with national standards and historical
performance. As a major project, the Section is
currently evaluating sources of diagnostic error, utilizing
our PACS-based peer review system, with the ultimate
goal of improving radiologist performance and patient
care. Both of these initiatives have been accepted as
scientific presentations at the Radiological Society of
North America meeting in November, 2008.
Abdominal Imaging faculty continue to excel in service
to the imaging community and recognition by their
peers. Dr. Richard Baron, Departmental Chair, was
Chair of the Educational Exhibits Committee of the
Radiological Society of North America (RSNA) and president
of the Society of GI Radiology. He was awarded an
Honorary Fellowship in the European Society of
Gastrointestinal and Abdominal Radiology, and made
an Honorary Member of La Sociedad Argentina de
Radiologia and the Federacion Argentina de
Asociaciones de Radiologia, Diagnostico por Imagenes y
Terapia Radiante.
Dr. David Paushter, Section Head and Vice Chair of
Operations, was named as Chair of the Clinical
Standards Committee of the American Institute of
Ultrasound in Medicine (AIUM) and liaison between the
AIUM and the American College of Radiology (ACR).
Dr. Paushter was also named a Fellow of the ACR in a
ceremony in May of this year.
Dr. Abraham Dachman served on multiple committees
for the ACR, the RSNA, the ARRS and the SGR, and
continued with significant appointments in conjunction
with his work on virtual colonography for the National
Institutes of Health (NIH). He also served as presiding
Officer for Scientific Sessions at the 2007 RSNA annual
meeting. Dr. Dachman’s pioneering work in virtual
colonography has provided a basis for multiple funded
grants, including NIH/NCI and ACRIN trials. He has
just completed a seven year tenure as Managing Editor
of the Radiology book of the eMedicine Project. Dr.
Dachman, through his research on virtual colonography,
was involved in eight funded projects during the academic
year
Dr. Michael Vannier, Vice Chair of Research, was a member
of the Advanced Technology Center Steering
Committee, Radiation Research Program of the National
Cancer Institute. He also served as Chairman for an NIH
site review, and participated as an external advisor to
multiple health care systems. Dr. Aytek Oto, Director of
Body MR, was involved in three newly funded grants
during the past year.
Dr. Paul Chang provided service to multiple societies in
key roles, including the Society for Computer
Applications in Radiology, the Association of University
Radiologists, the National Library of Medicine of the NIH
and the RSNA. He received the Association of University
Radiologists (AUR) Herbert Stauffer award for best clinical
paper in 2007. He has continued to provide service to
SIIM/SCAR in multiple capacities, and plays a pivotal
role in the development of radiology informatics for the
RSNA.
All section members were actively involved as manuscript
reviewers for such journals as Radiology, the
American Journal of Roentgenology, Radiographics, the
Journal of Computer Assisted Tomography, and
Computerized Medical Imaging and Graphics. Dr.
Michael Vannier served as Editor-in-Chief of the
Sagittal 3-D CT image of the Thoracic Aorta and Great Vessels
Sagittal CT Image of the
Chest, Abdomen and
Pelvis Demonstrating
Enlarged Lymph Nodes
8

International Journal of Computer Assisted Radiology
and Surgery and Automedica, and sat on the editorial
boards of The American Journal of Orthopedics, Medical
Image Analysis and Computerized Medical Imaging and
Graphics. Dr. Richard Baron was an Associate Editor for
Liver Transplantation. Dr. Paul Chang served as
Associate Editor for Computers in Radiology, and has
participated on the editorial board of the Radiology and
Imaging Letter, the Journal of Digital Imaging and
Cancer Informatics. Dr. Abraham Dachman continued to
serve as Managing Editor of the Radiology content of
the eMedicine project, and received the Editor’s Award
from Radiology.
The Section’s active involvement in research resulted in
nearly 100 scientific and invited presentations and publications.
Section members presented nine times at the
RSNA 2007 annual meeting. Dr. Paul Chang helped kick
off the convention with his lecture, “Leveraging
Informatics to Enhance Radiology Relevance and Value”
at the President’s Address and Opening Session. Dr.
Baron and Dr. Dachman served as Exhibit and Scientific
Chairs respectively for the meeting. A Certificate of Merit
from the RSNA was presented to Dr. Aytekin Oto and
his co-presenters for a web-based broadcast during the
meeting.
As the Section looks forward to the 2009 academic year, it
is expected that the current levels of clinical, educational
and academic achievement will continue to escalate. New
challenges will include helping to define the roles of 256
slice CT and 3T MR in clinical practice, and continuing
the refinement of our educational programs. Academic
activities including funded grants and scientific publications
will further mature as a result of mentoring and faculty
growth within the Section. Our involvement in novel
methods of measuring and reporting disease will also
contribute to continued clinical excellence.
Breast Imaging
The Section of Breast Imaging (left to right): Dr. Gillian
Newstead, Dr. Robert Schmidt, Dr. Charlene Sennett, Dr.
Michael Vannier, Dr. Akiko Shimauchi (Clinical Fellow), Dr.
Susan Sung (Clinical Fellow), Dr. Hiroyuki Abe.
The mission of the Section of Breast Imaging is to provide
excellent comprehensive screening and diagnostic
breast health care for our patients. We provide a full
spectrum of mammographic, ultrasound, magnetic resonance
imaging, and breast interventional procedures.
The screening clinic provides service to the surrounding
community and we are a referral center for the evaluation
of patients with difficult diagnostic problems and
those with newly diagnosed breast cancer. We conduct a
busy high-risk screening program using mammography,
ultrasound and MRI, in collaboration with Dr. F.
Olopade in the department of Medicine. We work daily
with the breast medical and radiation oncologists, surgeons
and pathologists, and participate actively in a
weekly management interdisciplinary conference. We
have experienced increasing numbers of outside referred
patients, sent to Breast Clinic for radiological and surgical
consultation, and this has
resulted in an ever-growing need for multimodality
assessment of imaging findings. The complexity/difficulty
of interventional procedures has increased significantly
in recent years, with many more patients undergoing
axillary lymph node sampling, multiple biopsies, and
multiple wires placed at needle localization. Current faculty
includes Hiroyuke Abe, MD, Gillian Newstead, MD,
Robert A Schmidt, MD, Charlene Sennett, MD, and
Michael Vannier, MD, Kirti Kulkarni, MD, joined us in
July after completing two fellowships, one in breast imaging
and the other in abdominal imaging.
Our comprehensive Continuous Quality Improvement
project this past year was aimed at improving workflow
for patients, physicians, technologists, administrative
assistants and file personnel. Breast faculty members
have spent a great deal of time this past year working
with an IT team group, led by Dr Paul Chang. The goal
has been to develop a workflow program which will integrate
the specific Breast Imaging Center needs, for viewing,
reporting and auditing, into the hospital and radiology
IT networks. Although this project is not yet completed
and is still in the early phase of implementation, we
have received continuous comprehensive support from
the IT section during the past year. We look forward to an
all-digital section with optimized workflow in the future.
Our clinical research pursuits encompass investigation of
multimodality diagnostic and therapeutic techniques for
breast cancer detection and evaluation in both human
and animal models. The major sectional research interests
this past year have included both clinical investigative
models conducted by faculty, fellows and residents, and
translational research involving close collaboration with
9

our physicist colleagues. Broadly writ, the main topics of
interest continue to be: multimodality assessment of
lymph nodes for detection of metastases, development
of new breast MR protocols for improved cancer detection
and analysis, functional assessment of normal breast
tissue, computer-aided visualization and analysis
(CAVA) of breast lesions and the study of DCIS and
high-risk lesions using MRI and mouse models.
Musculoskeletal Imaging
Amajor research initiative, under the leadership of Dr.
Olufunmilayo Olopade, has resulted in funding of an
NIH Specialized Programs of Research Excellence
(SPORE), in Breast Cancer. This award of $11.5 million
over five years will enable us to implement a multifaceted
strategy of translational research designed to
reduce the death and disability caused by breast cancer
worldwide. This effort focuses on developing geneticbased
approaches to the treatment, prevention, and
detection of breast cancers in women who are at risk of
developing an aggressive form of the malignancy at a
young age.
Sunny Jansen, a physics graduate student, who works
closely with faculty and clinical fellows, presented her
prize-winning paper on DCEMR findings in benign and
malignant breast lesions, at RSNA 2007.
We have received grant funding from a variety of organizations:
NIH, industry and philanthropic sources, have
presented 24 scientific papers at national and international
meetings, and have published 9 manuscripts.
35 year old, post right
axillary node biopsy:
positive for
adenocarcinoma.
Mammography
normal. MRI shows
a breast cancer.
The Section of Musculoskeletal Imaging: Dr. Scott Stacy and
Dr. Larry Dixon. Not pictured: Dr. Christopher Straus.
The Musculoskeletal Radiology Section continues to provide
state-of-the-art multimodality imaging and imageguided
interventional procedures for patients of the
University of Chicago Medical Center. The busy
Orthopedic Oncology Service has long been an example
of a team-approach to patient care, and Drs. Dixon and
Stacy provide comprehensive services as part of the
University of Chicago Musculoskeletal Oncology Group.
The Musculoskeletal Radiology Section also works closely
with the Section of Sports Medicine to offer services to
all athletes (including the Chicago Blackhawks professional
hockey team), as well as the Section of
Rheumatology to diagnose complex disorders of joints.
With the introduction of the Department’s speech recognition
system, report turnaround time has decreased dramatically,
and during the workday clinicians will often
have access to the dictated reports before they see their
patients.
The Section works closely with the imaging technologists
to provide excellence in care to all patients. As part of an
ongoing quality improvement initiative, the Section, with
the help of the MRI technologists, evaluated factors that
contributed to the overall duration of routine knee magnetic
resonance imaging studies in an effort to increase
patient comfort and throughput. This allowed the section
to significantly shorten the standard knee MRI protocol
while adding a new dedicated pulse sequence for exquisite
depiction of articular cartilage defects. The project
10

accepted a position at St. Johns Hospital, in Springfield,
Illinois, affiliated with Southern Illinois University
Medical School, and will begin July 1st as an Assistant
Professor.
Academically, the Section maintains a national presence
with scientific and educational presentations at the annual
meetings of the American Roentgen Ray Society and
the Society of Skeletal Radiology. Dr. Stacy and Dr.
Rodney Corby (senior radiology resident and future musculoskeletal
radiologist) received the Silver Medal from
the ARRS for their educational exhibit “Benign and
malignant masses of high signal intensity on T2-weighted
MRI studies of the knee: An interactive tutorial” at the
Society’s annual meeting in Washington, DC.
“3D” reformatted CT image of shoulder shows
Bankart fracture (arrow) of glenoid
Medical student education continues to flourish, with
dedicated musculoskeletal imaging lectures given during
the Gross Anatomy and Human Morphology courses for
the first-year students, as well as an arthritis review for
the second-year students as part of their Physical
Diagnosis Course. The musculoskeletal imaging rotation
continues to be popular with fourth-year medical students,
especially those pursuing residencies in radiology
and orthopaedics.
Neuroradiology
Transverse CT image of femur shows patient
undergoing radiofrequency ablation of
eosinophilic granuloma.
was a highlight of the 2007 Quality Fair sponsored by
the Center for Quality, and was one of three prize-winning
exhibits for the entire Medical Center. This year’s
quality improvement project involves a detailed evaluation
of the radiographic skeletal survey for staging of
patients with multiple myeloma in an attempt to
decrease examination time and radiation dose.
Dr. Stacy was promoted to Associate Professor of
Radiology in July of 2007 and assumed the role of
Section Chief in September, a position that Dr. Dixon
held for 15 years while delivering clinical service highly
respected by both patients and clinicians. Dr. Dixon continued
in his role as Director of the Musculoskeletal
Imaging Fellowship. Dr. Saad Naseer, the 2007-2008
Musculoskeletal Imaging Fellow, followed in Dr. Dixon’s
footsteps as a favorite educator among the residents.
Both Dr. Naseer and Dr. Stacy received awards for their
efforts in preparing the senior residents for the oral
Board Certification Examination. Dr. Naseer has
The Section of Neuroradiology (left to right): Dr. Cheng Hong
(Clinical Fellow), Dr. Fang Zhu (Clinical Fellow), Dr. Vivek
Sehgal, Dr. Delilah Burrowes, Dr. Jordan Rosenblum, Dr.
Saeid Mojtahedi.
11

Neurosurgery to rebuild the neurovascular program at
The University of Chicago. Dr. Ansari has an interest in
molecular imaging research which he plans to continue
in collaboration with Dr. Brian Roman.
A B C
a. Cerebral perfusion study in 50y/o women with acute onset
hemiplegia demonstrates an area of decreased cerebral blood
flow (green) and decreased cerebral blood volume (red). The
green area represents the ischemic penumbra that is still
viable if re-perfused.
b. Corresponding diffusion weighted image from an MRI
demonstrates restricted diffusion corresponding to the area of
decreased cerebral blood volume. This is irreversibly damaged
tissue.
c. CT angiogram demonstrates occlusion of a middle cerebral
artery branch by embolus.
The Section has undergone major changes within the last
academic year. At year end we have successfully recruited
three new faculty members and as a result, there
have been exciting new changes in clinical expertise,
research interests and new clinical programs. During the
past year we have begun actively imaging brain tumors
with MR perfusion and DTI tractography. These techniques
are now an integral part of several research projects,
and are performed routinely in appropriate
patients. Planning is underway to begin fMRI in clinical
patients and to restore full neuro-interventional services
in late 2008. Faculty recruits include:
Dr. Delilah Burrowes joined us from Children’s
Memorial in Chicago. Dr. Burrowes is sub-specialty
trained in both adult and pediatric neuro-radiology with
special expertise in MR spectroscopy. This is our first
formally trained pediatric neuroradiologist and her contributions
have already generated a great deal of enthusiasm
from pediatric surgery, neurology and neurooncology.
Dr. Vivek Sehgal also joined the section. Dr. Sehgal
trained here at the University of Chicago, completing a
two year fellowship followed by several years as a junior
faculty member before moving to Wayne State
University in Detroit. In Detroit, Dr. Sehgal was actively
involved in running the MRI section and gained expertise
in fMRI as well as spectroscopy and advanced imaging
techniques. He was involved in a number of research
projects involving susceptibility weighted imaging, a
novel technique that has been pioneered at Wayne State.
Dr. Sameer Ansari, who is currently at the University
of Michigan, will join our section as a Neurointerventionalist
in late 2008. Dr. Ansari trained at the University
of Illinois and then at The University of Michigan after
which he worked as a faculty member at Michigan.
He will work with our colleagues in Neurology and
We had two fellows the past year. Cheng Hong, MD,
PhD, began his clinical fellowship in August of 2007. Dr.
Hong trained in China and completed his PhD work in
Germany. He has been involved in radiology research for
the past seven years. He has made a very smooth transition
back into clinical medicine and has begun two interesting
research projects in the evaluation of carotid artery
plaque and the association with intra-cranial disease. Dr.
Hong was awarded a 2008 Roentgen Resident/Fellow
Research Award from the RSNA for his efforts.
Fang Zhu, MD, PhD, joined us in August as a research
associate. She immediately became involved in a number
of research projects involving quantification of white
matter disease, perfusion and DTI imaging in tumors,
and DTI imaging in the evaluation of white matter disease.
She received partial funding for her project in DTI
imaging in white matter disease. She will begin clinical
training in 2008.
The past year has been an exciting one for the section of
Neuroradiology. At year end we have successfully
recruited three new faculty members and two fellows.
We have new programs in tumor imaging and white
matter disease. We have made plans for revitalization of
our pediatric neuroradiology program as well as our
Head and Neck imaging, and we are beginning the planning
process for neuro-interventional radiology when Dr.
Ansari joins us. Research activities have begun in tumor
imaging with several abstracts submitted in this
Axial fiber track
(FT) image at the
level of the internal
capsule. It shows
the normal corpus
callosum, thalamus
and internal
capusule fiber connection.
Axial FT image
generated from an
ROI of the chronic
stroke (Female,
59-year-old),
shows decreased
fiber connections
around the subcortex
of the right
affected temporooccipital
lobe compared
with the
branching pattern
of the normal contralateral
occipital
cortex.
Axial and coronal
FT image generated
from an ROI of the
intracranial hemorrhage
(Male, 48-
year-old), shows loss
of fibers in the right
cortical-spinal tract,
and posterior displacement
of the
right side of the
splenium of the corpus
callosum fibers
compared with normal
side.
12

exciting area. Active collaboration is underway with our
neuro-oncologists, neurologists interested in white matter
disease, and with our neurosurgery colleagues in a
number of different projects.
Teaching in the section has expanded via the faculty
recruits with new pediatric radiology conferences, follow-up
conference and teaching conferences on
advanced imaging techniques. We are also able to actively
participate in a number of inter-disciplinary conferences
with better staffing levels. We have two fellows
with one completing his first year of clinical fellowship
and the second completing her first year in the lab, and
now beginning her clinical training.
Nuclear Medicine
A novel approach to inflammatory bowel disease evaluation
developed at The University of Chicago using FDG-PET/CT
identified a patient, thought to be in remission, as having
active ulcerative colitis of the sigmoid (arrows).
procedures in a sterile environment. We look forward to
the results of similar renovations, just commenced, in cardiac
nuclear medicine which we expect to complete during
the coming year.
The Section of Nuclear Medicine (left to right): Dr. Yonglin
Pu, Dr. Bill O’Brien-Penney, Dr. Daniel Appelbaum. Not
pictured: Dr. Christopher Straus.
The past year the Section of Nuclear Medicine has seen
significant structural improvements, completing a major
renovation of its general nuclear clinic, moving into a
beautiful, brand-new facility. The four new gamma camera
rooms with the latest imaging equipment, technologist
work room, physician reading room, patient interview
and injection rooms, and coordinator’s and manager’s
offices comprise a terrific infrastructure for performing
state-of-the-art nuclear imaging and therapy while
maximizing patient comfort. The renovation coincided
with the new United States Pharmacopeia (USP) 797 regulation
mandating that radiopharmaceuticals be treated
with the same sterile rigor as all prepared pharmaceuticals.
As a result, our new radiopharmacy was the first
and still one of the very few in the country to be USP
797 compliant, with our strict adherence to sterile
In our continued efforts to promote clinical quality for
patients and referring clinicians alike, the Section undertook
a quality improvement program aimed at optimizing
sentinel node detection in patients newly diagnosed
with breast cancer and undergoing a lymphoscintigraphy
prior to surgical axillary dissection. The goal was to find
the ideal volume and dose of radiotracer administered to
maximize conspicuity of the sentinel lymph node for the
surgeon while minimizing radiation to the patient. The
results have thrilled our referring surgical clinicians while
significantly improving patient care.
Sectional academic output continues to be prodigious and
acclaimed in the scientific and lay communities alike.
Research endeavors are quite varied, ranging from basic
imaging science to clinical whole body and brain studies
with FDG-PET/CT. Our work on computer aided diagnosis
(CAD) and temporal subtraction in bone scintigraphy
resulted in a patent which we are working to translate
into an intelligent workstation for use by medical centers
across the world. Our NIH funded study utilizing brain
PET to assess the effects of sleep deprivation on obesity
was recently featured on CBS’s 60 Minutes, capturing the
public’s imagination. Additional work collaborating with
our clinical colleagues includes a novel technique in evaluating
inflammatory bowel disease utilizing whole body
FDG-PET/CT to assess for disease activity and response
13

to therapy. And we are increasingly involved in oncology
trials utilizing PET/CT to stage and monitor new
therapies for a host of tumor types.
Our faculty continues to excel individually and as a unit.
Dr. Pu, long certified in nuclear medicine recently added
to his credentials, attaining board certification in radiology.
He now joins section chief Dr. Appelbaum in forming
one of the very few academic nuclear departments
where all members are certified by both the ABNM and
ABR. While rare, this section-wide dual training is
increasingly important as molecular and anatomic imaging
continue to merge, as exemplified by PET/CT and
SPECT/CT. Dr. Appelbaum remains an active member
on national educational committees at both the
American Board of Radiology and the Society of Nuclear
Medicine. He is also a frequent invited lecturer at both
the regional and national levels. Our experienced physicist,
Dr. O’Brien Penney, who recently completed his
term as national secretary for the Computer and
Instrumentation Council of the SNM, keeps the clinic
operating at a very high level while providing invaluable
research and teaching support to the Section and
University as a whole.
Education remains a critical mission for the Section
which is an active participant at the medical student, resident
and doctoral candidate levels. The noon conference
program has been reformatted into a standardized lecture
format, while resident case-taking approaches are
refined at daily board-size sessions and during level-specific
end of rotation exams. Dr. Straus has been leading
the Department’s redesign of medical student education,
which includes new lectures exposing students’ to
nuclear and molecular concepts at an early level.
And so, as we move into our beautiful new facility, the
Section is stronger and more energized than ever before.
The structural improvements will provide an incredible
platform as they continue to build their high-quality
patient care, research, and educational initiatives to even
greater heights in the coming year.
Pediatric Imaging
comprising technologists, nurses, child-life experts, and
clinic coordinators, are dedicated pediatric care professionals
who are instrumental in the efficient, safe, and
sympathetic function of the radiology department. The
sedation team, lead by Pediatric Intensive Care physicians,
is based in the pediatric radiology department. The
sedation team works closely with the radiology department
to ensure that children who need to stay immobile
for long magnetic resonance, CT, or nuclear medicine
exams are able to have their tests performed.
The Section of Pediatric Imaging (left to right): Dr. Kate
Feinstein, Dr. Mario Zaritzky, Dr. David Yousefzadeh.
The Section of Pediatric Radiology remains dedicated to
the care of neighborhood children as well as those from
around the world. Our patients have very complex medical
conditions, mirroring our referral base. We care for
many extremely premature infants, children with cancers,
children with chronic diseases, and children who
have suffered major physical traumas. All of the staff,
The Section uses web-based modules as the backbone for
its curriculum. The education of radiology residents,
pediatric residents and medical students has been
enhanced by this methodology. The curriculum is supplemented
by textbooks, journal articles, lectures and clinical
conferences. The radiology residents, under the guidance
of the faculty, participate in several interdisciplinary
conferences: pediatric tumor board, pediatric surgerypathology
conference, and pediatric gastroenterology
conference. An essential part of the curriculum is learning
how to care for all of our patients, from the extremely
low gestational age neonates who weigh less than one
pound to our young adult patients who are making the
transition from pediatrician to internist.
The residents work with the faculty in order to become
competent at the hands-on examinations such as fluoroscopy
and ultrasonography. They also learn the use
and development of low-dose CT techniques as another
principal part of the curriculum. Publications and
14

presentations for the past academic year include: variability
of observer assessment of brain sonograms, sonographic
and Doppler evaluation of growing cartilage,
the use of magnets in the treatment of esophageal atresia,
and sonographic evaluation of musculoskeletal
infections.
Color Doppler ultrasound of two year old boy’s swollen ankle
after IV removal shows the Yin-Yang sign. The Yin-Yang sign
is due to turbulent blood flow in an arterial pseudoaneurysm.
Color Doppler ultrasound
with vascular
tracing confirms the
arterial nature of the
blood flow. The early
diagnosis of pseudoaneurysm
allowed
prompt surgical resection
to prevent life-threatening
complications.
Thoracic Imaging
Screen shot showing new interface for automated detection,
measurement and serial comparison of pulmonary nodules
The Section has maintained a high level of clinical service
in spite of constantly increasing volume of CT scans, and
steady volume of chest radiography. With the implementation
of voice recognition dictation with Commissure in
October 2007, report turnaround time decreased dramatically,
while productivity was only minimally impaired
during the initial implementation.
Our Section has been strengthened in the past year by the
addition of Dr. Chris Straus, and by the contributions of
Dr. Steve Zangan and Dr. Brent Greenberg.
These new part time members of the Section have provided
greater flexibility with staffing, and have brought
valuable skill sets in teaching and in other areas of radiology,
which complement the existing group.
We remain at the cutting edge of new technology with
planned installation of a new dual energy chest radiography
unit, as well as a flat panel detector instant readout
portable radiography unit. Our clinical experience with
dual energy imaging is summarized in the current issue
of The Journal of Thoracic Imaging, for which Dr.
MacMahon is the guest editor.
In CT we have exploited the potential of our 64-slice
scanners by routinely performing comprehensive sets of
image reconstructions, and by archiving source images on
all cases as of January 2008.
The Section of Thoracic Imaging (left to right): Dr. Steve
Montner, Dr. Steve Zangan, Dr. Heber MacMahon, Dr.
Christopher Straus, Dr. Phil Caliguiri, Dr. Alexandra Funaki.
Not pictured: Dr. Brent Greenberg.
The Chest Section has continued its successful collaboration
with the Radiological Sciences Section during the
past year. The current challenge is to involve younger faculty
and residents in research, and to maintain the present
level of productivity in the face of increasing pressure
of clinical work and limited staffing.
15

Vascular and
Interventional Radiology
Alarge meandering artery on mesenteric angiography.
The Section of Vascular and Interventional Radiology (left to
right): Dr. Steve Zangan, Dr. Brian Funaki, Dr. Sidney
Regalado, Dr. Jonathan Lorenz, Dr. Thuong VanHa. Not pictured:
Dr. Jeff Leef.
The Vascular and Interventional Radiology Section continued
to thrive in 2007-2008 despite many challenges.
Our current interventional radiology suites and combined
holding and clinic area have enabled us to meet
the ever expanding demand for services. We have been
able to provide prompt service with most procedural
requests addressed within 24 hours. Our role in evaluation
and management continues to expand and we continue
to provide the entire gamut of diagnostic and therapeutic
Vascular and Interventional Radiology procedures.
We have added microwave ablation and drug
eluting beads to our local regional cancer therapy program.
In addition, we have acquired equipment necessary
to initiate a varicose vein clinic spearheaded by Drs.
Thuong Van Ha and Steve Zangan.
As a continuing quality improvement program, we initiated
an outreach and screening program for nephrology
patients with untreated peripheral vascular disease. We
found that 25% of our dialysis patients had undiagnosed
Median arcuate ligament compression shown by CTA.
and untreated peripheral arterial disease. All of these
patients are being treated and followed longitudinally in
our clinic.
Academically, our Section remains active on a national
and international level. Dr. Brian Funaki continues his
role as editor-in-chief of Seminars in Interventional
Radiology and serves on the editorial board of Radiology
Case Reports and the Journal of Vascular and
Interventional Radiology. He is a fellow in the Society of
Interventional Radiology and currently co-chairs the
Volunteers Committee in the society. He is the associate
program director of the 2008 American Roentgen Ray
Society annual meeting as well as organizer for numerous
courses at this meeting. Dr. Funaki was promoted to
the rank of Professor of Radiology and recently accepted
the position of Chairman of the American College of
Radiology’s Appropriateness Criteria Expert Panel on
Interventional Radiology. All full-time faculty lectured at
all major radiology meetings including SIR, RSNA,
ARRS, and CIRSE. The Teaching Atlas of Vascular and
Interventional Radiology by Drs. Brian Funaki, Jonathan
Lorenz and Thuong Van Ha was published by Thieme. A
total of 25 peer-reviewed and invited articles were published
by section members during the academic year.
Much of the Section’s efforts are dedicated to training
residents and fellows. Under the supervision of fellowship
director, Dr. Lorenz, we trained two fellows in our
one year ACGME accredited fellowship and have continued
to refine an educational curriculum for residents and
fellows. Both fellows from the past year pursued academic
careers and accepted assistant professor positions:
Dr. Steve Zangan joined our faculty and Dr. Grace
Knuttinen joined the faculty of the University of Illinois
where she also serves as resident program director.
In summary, the Vascular and Interventional Radiology
Section maintains excellence in its clinical, teaching and
academic endeavors.
16

Research
Computed Tomography
Advanced Cone-Beam CT
Graduate students Junguo Bian, Sengryong Cho, Xiao
Han, and Dan Xia, along with Emil Sidky, PhD, Michael
Vannier, MD, Richard Baron, MD, and Xiaochuan Pan,
PhD, are performing research on advanced CT imaging.
CT remains one of the dominant medical imaging techniques.
In particular, the research on helical cone-beam
CT has been extremely active because of its high volume-scanning
speed and temporal resolution. Indeed,
helical cone-beam CT would allow for new imaging protocols
that were not possible with conventional CT. The
researchers have made significant breakthroughs in CT
research and enjoy a leading status in this area.
Specifically, they have developed computationally efficient
and numerically stable algorithms for obtaining
images in helical cone-beam CT, have designed innovative
scanning strategies and algorithms for obtaining
images with improved resolution properties, and have
developed the new strategy and algorithms for reconstructing
images within regions of interest (ROIs) from
much reduced data. Most importantly, they have developed
and refined new concepts and algorithms that
would allow the design of innovative imaging protocols
that may have significant clinical implications, e.g., for
breast imaging, liver imaging, and cardiac imaging. One
of the important advances made in the past year was the
development of algorithms for image reconstruction
from highly incomplete data, which are expected to find
significant applications to a wide variety of imaging
problems in medicine, security scan, and other areas.
System and Algorithm Development of Micro-CT and
Its Applications
Graduate students Junguo Bian, Sengryong Cho, and
Xiao Han, along with Xiaochuan Pan, PhD, are developing
micro-CT and its applications to small animal imaging.
Micro-CT plays an important role in animal and
molecular imaging. In the past year, in collaboration
with Charles Pelizzari, PhD, and Chin-Tu Chen, PhD,
they have developed the first micro-CT system for animal
imaging on the campus. This system can provide 3D
images with isotropic resolution at 30µm to 50µm. They
have been using this system to perform imaging studies
of lung cancer, bone cancer, and vascular vessels in
small animals from various laboratories in the BSD. The
researchers are also using this system to perform a wide
Imaging Sciences Faculty: Chien-Min Kao, PhD, Greg
Karczmar, PhD, Bill O’Brien-Penney, PhD, Robert Nishikawa,
PhD, Brian Roman, PhD, Maryellen Giger, PhD, Samuel
Armato, PhD, Patrick La Riviere, PhD, Xiaochuan Pan, PhD,
Kenji Suzuki, PhD, Chin-Tu Chen, PhD, Yulei Jiang, PhD,
Jia-Hong Gao, PhD. (Not pictured Kunio Doi, PhD, and
Charles Metz, PhD.)
variety of studies aiming at understanding the physical
properties of the system and reconstruction algorithms.
They expect that a large number of studies on small animal
imaging and on imaging physics and algorithms will be
conducted on this system and that a large amount of data
and results will be generated, which can form the basis for
the development of advanced micro-CT with the capability
of performing innovative scanning tasks. In the past year,
more than 150 mice have been scanned using their laboratory-made
micro-CT.
Improving Image Quality in Low-Dose and
Low-Contrast CT
Patrick La Riviere, PhD, and graduate student Phillip
Vargas are working with Michael Vannier, MD, and
researchers at Philips Medical Systems to develop computationally
efficient sinogram-domain approaches that help
improve image quality in low-dose and non-contrast CT
exams. Continuing technological innovations have spurred
growth in the number of CT exams performed annually,
which has prompted concern over the associated rise in
CT-related radiation dose to the population. The ability to
reduce CT dose without sacrificing image quality would
have significant beneficial public-health consequences. This
is especially pertinent given that widespread use of CT in
screening for lung and colon cancer is currently being considered.
The data measured in a low-dose scan is necessarily
noisier than data measured in a standard scan, and this
can lead to an overall mottled appearance in the images as
well as to noise-induced streak artifacts than can obscure
subtle lesions. In the past few years, this group has developed
a novel strategy for CT data processing that entails
application of a statistically principled penalized likelihood
estimation of the ideal, low-noise line integrals needed for
image reconstruction from the noisy degraded transmission
measurements. The preliminary results suggest that
dose reductions of 30% or more might be achievable relative
to current clinical standard-exposure scans, and even
larger dose reductions may be possible for the low-dose
screening scans.
17

Positron Emission
Tomography
Ultra-Sensitive MicroPET Scanner
Graduate student Yun Dong, MS, Qingguo Xie, PhD,
Chin-Tu Chen, PhD, and Chien-Min Kao, PhD, are
developing a microPET prototype scanner that provides
ultra-high sensitivity by using two large-area HRRT
(High Resolution Research Tomograph) detector heads
in a compact geometry (Figure 5) and employing
advanced image reconstruction algorithms. At activity
levels of interest for rodent imaging, the effective sensitivity
of the prototype is about an order of magnitude
better than most other existing micro PET scanners
Figure 5
The microPET prototype
employs two
HRRT detectors
(from Siemens) in a
compact configuration
to provide
~30% central sensitivity.
In comparison,
the sensitivity
of most existing
microPET systems
is

Time-of-Flight (TOF) PET Imaging
Chien-Min Kao, PhD, has developed a new theory and a
new class of image reconstruction algorithms for TOF-
PET. The new theory reveals previously unrecognized
benefits of TOF-PET imaging, and the new algorithms
create new modes for TOF-PET imaging. Figure 9 shows
a situation in which the new reconstruction algorithms
can significantly reduce the negative effects of data noise
associated with a hot structure to the quality of nearby
structures of interest. The use of the new theory and
algorithms can lead to new TOF-PET system designs.
Figure 9
(Left) An image that contains two small structures within a
region of interest (ROI) nearby a large, hot structure. Such
situation can occur in prostate imaging in which the two
small structures are the prostates and the large structure is
the bladder; (Middle) Image generated by using the new TOF-
PET reconstruction algorithm for the ROI; (Right) Image
within the ROI obtained by using a conventional TOF-PET
image reconstruction algorithm. The new reconstruction algorithm
significantly improves the visualization and qualification
of the structures of interest.
Single-Photon Emission
Computed Tomography
Super-Resolution SPECT
Visiting Scholar Ching-Han Hsu, PhD, from the
Department of Biomedical Engineering and
Environmental Sciences of the National Tsing-Hua
University in Taiwan, Chien-Min Kao, PhD, and Chin-Tu
Chen, PhD, are collaborating with Ling-Jian Meng, PhD,
of the Department of Nuclear, Plasma, and Radiological
Engineering of the University of Illinois at Urbana-
Champaign to utilize electron-magnifying CCD
(EMCCD) technology to build single-photon emission
microscopes (SPEM) that can offer very high spatial resolution
better than 100 microns. These super-resolution
imaging devices present special research challenges in
system calibration, image reconstruction, experimental
protocol designs, etc., and also offer unique opportunities
in imaging of brain and other immobilized organs or
tissues to acquire super-resolution images unattainable
previously. Together with Ming-Chi Shih, MD, PhD,
they are also collaborating with Dr. Rodrigo Bressan of
the Albert Einstein Institute in Brazil to design and build
special high-resolution multi-pinhole collimators and
the associated image reconstruction and analysis algo
rithms as well as software libraries. These special collimators
will be used in conjunction with regular clinical
SPECT imaging systems for animal imaging studies in
investigation of brain and behavioral disorders.
Applications of Imaging Techniques to Radiation
Therapy
Graduate students Sengryong Cho and Erik Pearson, and
Xiaochuan Pan, PhD, are performing research on imageguide
radiation therapy. Radiation therapy remains one
of the most important procedures for treating cancer. The
goal of conformal radiation therapy is to deliver a high
radiation dose to the tumor volume, while minimizing
the radiation exposure of healthy tissues that surround
this volume. Therefore, treatment planning is a critical
step for accurate and effective radiation therapy. Because
treatment planning is conceptually related to a reverse
process of SPECT imaging the insights and techniques
attained in our research on SPECT can shed the light on
the development of effective methods for accurate treatment
planning in radiation therapy. In collaboration with
Dr. Charles Pelizzari of the Department of Radiation and
Cellular Oncology, they have been investigating and
developing dose-efficient image guided treatment methods
for detecting patient positioning errors in conformal
radiation therapy treatments. Unlike previously proposed
approaches, these methods will be based upon the theory
of local tomography, and, consequently, will only utilize
treatment radiation that passes through or very near the
tumor volume to form the reconstructed image of the
tumor volume. Also, this ROI imaging strategy provides
an excellent opportunity for imaging the targeted tumor
region with considerably reduced radiation dose.
Applications of PET/SPECT/CT Imaging to Biomedical
Research
Graduate Student Yun Dong, Research Professional
Christian Wiethold, PhD, Ming-Chi Shih, MD, PhD,
Research Associate Qingguo Xie, PhD, Visiting Research
Fellow Antonio Machado, MD, Chien-Min Kao, PhD,
Patrick La Riviere, PhD, Xiaochuan Pan, PhD, and Chin-
Tu Chen, PhD, have been collaborating with many faculty
members in the Departments of Radiology, Radiation and
Cellular Oncology, Medicine, Surgery, Pathology,
Biochemistry and Molecular Biology, etc., on using CT,
PET, and SPECT methodologies for biomedical research
in a variety of applications. The topics range from investigation
and characterization of new imaging probes
including nanoparticles, imaging of animal models of
breast, prostate, lung, bone, and other cancers, development
of image-guided therapy strategies for radiation
therapy, chemotherapy, and gene therapy, imaging for
drug evaluation and development, investigation of cardiac
and pulmonary functions under various healthy and
diseased conditions, studies of brain function and imaging
for brain and behavioral disorders, etc.
19

MRI
New Florsheim Magnet
Installation of the new Florsheim 9.4 Tesla MRI scanner
was completed and the scanner is now producing
extraordinary high resolution images. For example,
Figure 10 compares scans of a mouse mammary gland
obtained on the old scanner at 120 micron resolution
with images from the new magnet acquired with 65
micron resolution. The new scanner shows DCIS in the
mammary gland with impressive detail.
INJECT WITH GD-DTPA, SACRIFICE 2 MIN AFTER INJECTION
Gd Concentration Map
H&E
Duct with DCIS
Duct lumen
100µm
0mM
Figure 11
0.91mM
Old magnet: 120 micro
resolution
Figure 10
New magnet: 65 micro
resolution
Studies of Early Breast/Mammary Cancer
Sunny Jansen (a graduate student in Medical Physics)
studied early cancer in the mouse and has produced
exciting results. Ms. Jansen (with Dr. Tatanja Paunescu
and Dr. Gayle Woloschak from Northwestern
University) demonstrated that Omniscan – a low molecular
weight MR contrast agent - enters mammary ducts
containing DCIS (see Figure 11). This demonstrates that
in clinical MRI, enhancement of DCIS post contrast
injection is largely due to leakage of contrast agent molecules
into ducts. By serially imaging mouse mammary
glands over a period of 10 weeks, Ms. Jansen also
demonstrated that not all DCIS in mice progresses to
invasive cancer. Previously it was believed based on
indirect evidence that DCIS is a ‘non-obligate’ precursor
to breast cancer. But Ms. Jansen’s results provide the
first direct support for this hypothesis. This is an important
finding that will influence clinical treatment of
DCIS, and drive the development of new MRI methods
that can distinguish between DCIS that is likely to
progress to invasive cancer and DCIS that will not
progress and requires less aggressive treatment or
‘watchful waiting’.
Top image shows H & E stained mouse mammary duct containing
DCIS. Bottom image shows the X-ray fluorescence
image of the same duct following I.V. injection of Omniscan.
The green color shows a high concentration of Gadolinium in
the duct. This Gadolinium produces strong contrast in
MR images.
MRI Studies of Pre-cancerous Conditions in Mouse
Prostate
Sean Foxley used echo-planar spectroscopic MR imaging
(EPSI) to evaluate prostate cancer and pre-cancerous conditions
in a transgenic mouse line compared with conventional
non-spectroscopic imaging techniques. Simian
virus large T antigen transgenic male mice (n = 7, age =
34 ± 3.7 weeks) were imaged using EPSI, gradient echo,
and spin echo pulse sequences. Water peak-height (PH)
images produced from high spectral and spatial resolution
(HiSS) datasets showed twice the mean signal-tonoise
ratios (p < 0.001) and two to three times the contrast-to-noise
ratio (p < 0.03) than conventional images
over the segmented prostate. PH images showed greater
morphological detail in the prostate by a surface area texture
metric. Data suggests that texture was inversely correlated
with age, and size was directly correlated with
age. Small structures that were evident in HiSS images
were similar in appearance to the hyperplasia/prostatic
intraepithelial neoplasms (PIN), a precursor to prostate
adenocarcinoma, that were evident on histology. The
results (published in Magnetic Resonance in Medicine)
suggest that very high resolution MRI can be used to
study the development of prostate cancer in mice and the
response of early prostate cancer and pre-cancer to therapy.
Mr. Foxley was awarded a 2008 RSNA research
trainee prize for his work.
20

MR Imaging of Colitis and Colitis-Associated Early
Cancers in Mice
Drs. Devkumar Mustafi, Marc Bissonnette, Greg
Karczmar and their colleagues have used high-resolution
MRI to detect early colorectal tumors in mice and
differentiation of early cancer from colitis. Ulcerative
colitis is characterized by persistent or recurrent inflammation
that can lead to colon cancer. Animal models
have been widely used to study the pathogenesis and
potential therapies for these types of colitis. However,
non-invasive imaging methods that can differentiate
colitis and early colorectal cancers in murine models as
well as assess response to therapy are not available.
These investigators explored the feasibility of imaging
pre-malignant chronic colitis and distinguishing it from
early colorectal tumors in mice. Figure 12 illustrates spin
echo MR images of a control, tumor, and colitis-to-early
colorectal tumor-bearing mice. The results from
DCEMRI show that the contrast uptake in tumors is significantly
different from that of colitis or normal colon
(and muscle) following injection of Gd-DTPA as shown
in the figure. The two-compartment model was used to
analyze dynamic data over the tumor, colitis, and muscle
tissues. Based on studies with control mice, mice
with colitis, colorectal tumors, and mice with colitis
transitioning to early colorectal cancer, they have
demonstrated for the first time that functional MRI techniques
in mice offer the potential to discriminate chronic
colitis from neoplastic transformation of early colitisassociated
colorectal cancers, thus making it possible to
detect very early cancer non-invasively. The pre-clinical
research led by Dr. Mustafi parallels clinical research led
by Dr. Aytekin Oto to improve clinical MRI of colitis and
colorectal cancer.
Clinical and Pre-clinical Spectral Spatial Imaging of
Breast Cancer
Graduate Students Sean Foxley and Abbie Wood, working
with Gregary Karczmar, PhD, have found that detection
of tumor vasculature by MRI is a critical component
of cancer screening. In clinical practice DCEMRI is used
to detect dense tumor blood vessels. However, DCEMRI
produces noisy data because of the need to image rapidly
before contrast media washes out of tumors. In addition,
DCEMRI may not be appropriate for all patients, particularly
in the context of screening exams. Therefore, as part
of SPORE funded research, the researchers are developing
high spectral and spatial resolution imaging methods
that can be used to detect tumor blood vessels without
the need to inject contrast agents, based on the local magnetic
susceptibility gradients produced by deoxyhemoglobin
in deoxygenated tumor blood vessels
(see Figure 13).
Mr. Foxley did his research using rodent models of cancer,
and his work is ‘in press’ in Magnetic Resonance in
Medicine. Figure 14 is an excerpt from the paper demonstrating
agreement between detection of tumor microvasculature
on HiSS images and DCEMRI detection of tumor
vasculature.
Ms. Wood has developed methods for analyzing HiSS
data from patients with breast cancer to detect dense
tumor vasculature. Figure 14 demonstrates the analysis of
water signal lineshape in each voxel to produce images of
vasculature in a breast tumor.
Figure 12
Figure 13
a) Image of a tumor implanted in rodent hind limb; this is a
water peak height image calculated from spectral/spatial data;
b) water peak height image with a blue overlay showing areas of
dense vasculature identified from DCEMRI (blue scale -dark
blue means sparse vessels, light blue means dense vessels) overlaid:
c) water peak height image with superimposed image
showing estimates of vascular density calculated from water
spectral lineshape (red scale - dark to light red is lower to higher
vascular density; d) images with pixels where DCEMRI and
water lineshape analysis agree shown in green.
21

Figure 17
Figure 14
a) Image of ductal carcinoma in situ (DCIS) of the human
breast; this is a water peak height image calculated from spectral/spatial
data; b) water peak height image with a yellow-red
overlay showing areas of dense vasculature identified from
lineshape analysis (yellow means sparse vessels, red means
dense vessels); c) DCEMRI subtraction image from minute 2
post-injection. Areas with white pixel values indicate significantly-enhancing
regions with dense vasculature.
Very High Spectral and Spatial Resolution Imaging
Milica Medved, PhD, Gillian Newstead, MD, Greg
Karczmar, PhD, and Funmi Olopade, MD, have developed
very high spatial and spectral resolution (HiSS)
imaging, and are testing it as a tool for evaluation of
indeterminate breast lesions. They have achieved submillimeter
spatial resolution in 1mm think slices, with
enough spectral information to preserve the dynamic
range and superior fat saturation associated with HiSS
MRI. The resulting images (Figures 15, 16, 17) below
show clearly delineated parenchyma and lesions, with
high signal-to-noise.
A sagittal HiSS image of a
highrisk volunteer, with
spatial resolution of 0.5 x 0.5
mm, slice thickness 1 mm, and
spectral resolution of 5 Hz. Four
slices were acquired in 8 min. The
arrow points to a blood vessel.
Sagittal HiSS images showing parenchyma of three ‘high-risk’
volunteers are shown. The spatial resolution was 0.75 x 0.75
mm, with slice thickness of 1 mm, and spectral resolution of 18
Hz. Twelve slices were acquired in 8 minutes, for each patient.
Improved Analysis of Dynamic Contrast Enhanced
MRI Data
Xiaobin Fan, PhD, and Gregory Karczmar, PhD, are
studying Dynamic Contrast Enhanced MRI which
involves measurement and analysis of contrast media
uptake and
Figure 15
Figure 16
(Left) A sagittal HiSS image of a patient with infiltrating
ductal carcinoma (grade III; arrow), with spatial resolution of
0.5 x 0.75 mm, and spectral resolution of 5 Hz. Four slices
were acquired in 8 minutes; (Right) A maximum intensity
projection image of four 1mm-thick sliced centered around the
lesion (arrow) is shown.
Figure 18
a) The contrast concentration curve for rodent prostate tumor
(open circle) and fitted with the TCM (red line) and the convolution
fit (AIF_IRF) (blue line); b) the corresponding IRF for
tumor.
washout following bolus injection. These studies are critical
for, among other things, detecting and evaluating
tumor vasculature and changes in tumor vasculature during
therapy. However, there is no accepted method for
analyzing contrast media uptake and washout. The widely
used two compartment approach is not a good model
for tumors because tumors are very heterogeneous on a
microscopic level. Therefore, Dr. Fan and his
22

collaborators have developed a new approach to analysis
of DCEMRI based on calculation of the impulse
response function of the tumor. They developed a novel
numerical procedure to deconvolute arterial input function
(AIF) from contrast concentration vs. time curves
and to obtain the impulse response function (IRF) for
dynamic contrast enhanced MRI. A general simple
mathematical model of the IRF was developed and the
physiological meaning of the model parameters was
determined by comparing them with the widely accepted
two compartment model (TCM). The results demonstrate
that the deconvolution procedure is a simple,
robust, and useful technique. In addition, the IRF analysis
leads to the derivation of novel parameters relating
to tumor interstitial pressure and tumor vascular architecture,
which may have clinical utility in diagnosis of
cancers.
Functional MRI and Human Brain Mapping
Figure 19
a) Functional magnetic resonance image (in color) overlaid on
an anatomical image (in grey) in one subject depicts the active
areas after glucose ingestion; b): The signal time course of the
hypothalamus after glucose ingestion. Time t = 0 min corresponds
to the onset of drinking and the blue bar indicates the
approximate duration of drinking.
stimulation; (3) MRI measurements of the current density
distribution in a body when an external current source is
applied; (4) mapping of brain activation in the actions of
glucose and alcohol; (5) development of diffusion tensor
imaging as a biomarker for the study of brain trauma
injury. The neuroimaging techniques developed in BRIC
will greatly improve understating of the nature of normal
brain function and help in the treatment of neurological
disorders as well.
Spin Resonance Imaging
Graduate students Dan Xia, Emil Sidky, PhD, and
Xiaochuan Pan, PhD, are conducting spin-resonancebased
imaging. Nuclear magnetic resonance imaging
(MRI) has become one of the dominant clinical and
research imaging techniques. They have been investigating,
developing, and evaluating a variety of efficient and
accurate sampling schemes such as the spiral sampling
schemes for fast spatial-spectral MRI. The researchers are
also developing algorithms for optimal suppression of
data noise and other artifacts that are likely to be contained
in rapidly acquired data. Unlike MRI that is based
upon nuclear spin resonances, which are generally in
high abundance in biological samples, electron paramagnetic
resonance imaging (EPRI) detects spin resonances of
unpaired electrons of free radicals in samples and determines
the spatial distributions of parameters of physiologic
significance. Of particular interest is estimating
oxygen concentration within tumors because such information
is of paramount importance for detection, assessment,
and monitoring of cancer status. In collaborating
with Dr. Howard Halpern of the Department of Radiation
and Cellular Oncology, they are investigating innovative
sampling schemes for efficient and complete acquisition
of EPRI data and also seek to develop algorithms for optimally
processing the acquired data and for accurately
reconstructing EPRI images.
MRI Imaging of Pancreas and Heart
Jia-Hong Gao, PhD, Co-Director of the Brain Research
Imaging Center (BRIC), is developing a functional MRI
(fMRI) and human brain mapping research program at
the University of Chicago. The mission of the BRIC is
the development and synergistic application of MRI
techniques to neuroscience as well as a broad range of
other medical research disciplines. In late 2008, a
research-dedicated and the state-of-the-art 3T Philips
MRI scanner will be installed in BRIC. This new scanner
will be used to support all cutting-edge NIH funded
imaging projects at our campus. Presently, Dr. Gao’s
research activities are focused on several areas: (1) development
of a novel fMRI technique, termed neuronal current
MRI, that allows for substantial enhancement in the
detection of brain activity in terms of both spatial and
temporal resolution; (2) study of the biophysical mechanism
of the homodynamic-based fMRI signal, and
exploring the relationship between cerebral blood flow
Brian Roman, PhD, has continued the work in the pancreas
and heart as well as developing new projects and
collaborations with university investigators. One such
recent collaboration is with Dr. Kathleen Millen in the
department of Genetics. Dr.
Millen’s investigates the genetics
of brain formation and is
interested in measuring brain
volume of several mutant
mice. Muhammad Haque,
PhD, in the laboratory has
been developing MRI protocols
in order to measure the
volume of the cerebellum in
control and mutant mice.
Figure 20 illustrates a typical
image from the 9.4T scanner
which highlights the cerebellum
and oxygen metabolism during neuronal at 64 micron in plane resolution. Figure 20
23

Manganese Enhanced Magnetic Resonance Imaging
(MEMRI) of Pancreatic Islet Function
Diabetes is a metabolic disorder cause by inadequate
supply or utilization of insulin, secreted by the pancreatic
ß-cells located in the islets. Presently pancreatic ß-cell
function is assessed via insulin release or indirectly via
serum glucose levels. The lack of understanding about
pancreatic physiology and ß-cell mass is a major hurdle
in therapy development. Knowing the functional efficiency
of the pancreas would certainly be beneficial in
the development of novel therapies aimed at maintaining
or increasing ß-cell function. Thus, development of
non-invasive imaging modalities to evaluate ß-cell function
is needed.
ß-cells are stimulated as a result of increased blood glucose
levels which results in calcium (Ca+2) uptake
through voltage-gated channels followed by insulin
release. Manganese ions (Mn+2) are a Ca+2 analog and a
T1 relaxation agent. Therefore ß-cells activated by
increased glucose in the presence of Mn+2 will demonstrate
a change in MR signal intensity compared to nonactivated
cells. Muhammad Haque, PhD, in the laboratory
acquired the first in-vivo functional imaging of rodent
pancreas via Mn enhanced MRI (MEMRI) in response to
glucose stimulation (see Figure 21).
Figure 21
In vivo functional imaging of the pancreas. Top panel - axial
view of the rodent pancreas highlighted in red; bottom panel -
In-vivo rat pancreas activation images (color code) at baseline
with Mn contrast and following glucose stimulation.
MR Imaging of Transplanted Pancreatic Islets
Lara Leoni, PhD, and Muhammad Haque, PhD, have
applied high resolution MEMRI to investigate the functionality
of transplanted pancreatic islets (see Figure 22).
Islets were transplanted into the kidney of nude mice
previously rendered diabetic via streptozotocin injection.
Mice that reverted to normal blood glucose were imaged
at baseline and after injection of Mn and glucose
stimulation. Initial studies suggest an increase in SNR
following glucose stimulation. Further studies are ongoing
in order to precisely quantify in-vivo SNR, T1 and T2
values of the transplanted islets.
Figure 22
a) In-vivo T1 weighted spin echo image of transplanted rat
islets in mouse kidney; 117 micron in plane resolution;
b) in-vitro spin echo image of transplanted rat pancreatic islets
in mouse kidneys.
MRI Detection of Gene Expression
Brian Roman, PhD, and his lab members have been
developing techniques to use MR to detect gene expression
in the heart. Their recent work has been investigating
calcium handling in the heart and on how this is
influenced by expression of the gene creatine kinase
(CK). They are using transgenic mouse models which are
deficient in CK. These hearts are imaged under baseline,
increased workloads and hypertrophic conditions using
manganese enhanced cardiac MRI (MEMRI). In wild-type
mice, the MR signal increased following Mn infusion by
15–20% while it increased by 20–35% following dobutamine
challenge. In addition to the signal enhancement,
the wall thickness increased by 30% while it did not
change for the CK deficient or hypertrophic mice. The
signal enhancement was less for the hypertrophic wildtype
and CK-M mice and there was no change in signal
intensity for the treated CK deficient mice. This agreed
with the group’s hemodynamic data where significant
changes in contractility (dP/dt) due to Db, were only
found in wild-type mice (see Figures 23 and 24).
To pursue the mechanism for this altered contrast
enhancement, Dr. Roman and his team implemented
gene array and RT-PCR analyses of these hearts that
revealed CK deficient (CK-) mice exhibit altered calcium
handling gene expression compared to control mice. The
role creatine kinase plays in maintaining calcium homeostasis
suggests that the altered MRI contrast is likely
due to changes in genes regulating or binding calcium.
Microarray analysis indicated a large upregulation in the
expression of Guanylate Nucleotide binding protein
1(GBP1) and S100A9. The increases in expression were
24

confirmed using qRT-PCR analysis as indicated above in
single (MCKO) and double (DBKO) creatine kinase deficient
strains. These studies are aimed at elucidating
changes in calcium handling to refine applications of
Manganese-enhanced MRI. Additionally, differences in
MRI data have been noted in mouse strains such as 129
and C57/129 hybrids harboring elevated expression of
GBP1. The increased expression of GBP1 and S100A9
have also been confirmed in 129 and C57/129 hybrid
animals (see Figures 25 and 26).
Figure 23
Wild-type mice pre (left) and post (right) Mn infusion. The
increase in contrast is due to active calcium pumping and
therefore Mn uptake particularly in the septum and left ventricular
free wall of the heart.
Figure 26
Quantitative RT-PCR results from wild-type (C57) and CK
deficient mice. These data confirm the gene array results indicating
that both cell signaling cascade pathways and calcium
handling mechanisms are perturbed in the heart of CK deficient
mice and is likely the source of both image contrast and functional
differences.
Figure 24
Creatine kinase deficient mice pre (left) and post (right) Mn
infusion. Unlike wild-type mouse hearts, CK deficient hearts
do not demonstrate an increase in image contrast following
Mn administration. This indicates an altered mechanism for
calcium handling.
Figure 25
Results of gene array comparing CK deficient to wild-type
hearts. These data indicate a dramatic increase in specific cell
signaling and calcium handling genes.
Tomosynthesis
Optimization of Reconstruction Algorithms for
Computerized Detection of Microcalcifications in
Tomosynthesis
Ingrid Reiser, PhD, Beverly A. Lau, BS, and Robert M.
Nishikawa, PhD, are developing an automated scheme
for microcalcification detection in breast tomosynthesis
volume images. Several reconstruction methods have
been applied to tomosynthesis, which include iterative
reconstruction, as well as filtered back projection. The
appeal of the latter method is that it is computationally
faster. This allows an increased resolution of the image
volume, which may improve MC conspicuity. The purpose
of this work was to compare detection performance
of a CAD scheme, on breast images reconstructed with
maximum-likelihood expectation maximization (ML-EM),
or with filtered back projection (FBP). Figure 27 shows a
subtle MC cluster in both reconstructions. For the ML-EM
reconstructed images, at least 3 microcalcifications were
detected for all cases. For the FBP reconstructed
25

images, at least 3 microcalcifications were detected for
21 out of 22 cases, and 2 microcalcifications were detected
in one case. They noted that ML-EM reconstruction
was less sensitive to image artifacts such as insufficient
dead pixel correction, or underexposure in individual
projections. Algorithm performance showed a slight
advantage for the ML-EM reconstruction; however this
may be because the ML-EM algorithm results in images
that are less noisy, since ML-EM reconstruction involves
implicit image smoothing by use of unmatched projector-back
projector pairs. This result was contrary to previous
study that showed ML-EM was superior to FBP
for breast masses.
Microcalcification Detectability in Tomosynthesis:
Effect of Scan Parameters
Beverly A. Lau, BS, Ingrid Reiser, PhD, and Robert M.
Nishikawa, PhD, are investigating the detectability of
microcalcifications in breast tomosynthesis images. In
this study, they examined the effect of acquisition geometry
(the number of projection views and the total angle
covered by those projections) and position of the microcalcification
with respect to the center of the detector.
Using computer simulation, they determined that when
the projection is at a large angle the detectability
depends on the position of the microcalcification with
higher detectability when calcification is near the edge
that is closest to the x-ray tube and lowest when near the
opposite edge. The difference was 22% at 45 degrees.
This is due to the difference in the x-ray path length
when the x-ray tube is at large angles. When the tube is
at 0 degrees there is no position dependence. Further
they found that the detectability decreased when the
angular range scanned by the x-ray tube increased and
they found no dependence of detectability on the number
of projection views. In the future, they will determine
if these results apply when x-ray quantum noise
and breast structure noise are considered in the
simulation.
Figure 27
Subtle MC cluster – (Left) - maximum likelihood expectation
maximization reconstruction; (Right) - filtered back
projection reconstruction.
Novel Imaging Techniques
Innovative Imaging Techniques
Samuel La Roque, PhD, Emil Sidky, PhD, and Xiaochuan
Pan, PhD, are investigating innovative imaging techniques
such as diffraction tomography (DT), reflectivity
tomography, and other wave imaging. In recent years,
innovative imaging techniques have become increasingly
important for studying physiological processes as well as
anatomic structures in small animals. They have made
considerable impact on the algorithm development for
these imaging techniques. For example, they have shown
that reflectivity tomography can be related to the emerging
imaging techniques such as optacoustic tomography,
thus allowing the direct application of algorithms developed
for the former to the latter. They have proposed
short-scan and half-time imaging strategies in these
unconventional imaging modalities for reduction of scanning
time and image artifacts. In recent years, much
effort has been devoted to developing imaging techniques
that rely upon contrast mechanisms other than
absorption. Phase-contrast imaging is one such technique
that exploits differences in the real part of the refractive
index distribution of an object to form an image using
spatially coherent source. The researchers are developing
algorithms to reconstruct and process phase-contrast
images from the acquired data by use of the third-generation
synchrotron at Advance Photon Source at Argonne
National Laboratory. Recent research results seem to suggest
that tomosynthesis breast imaging may yield more
detailed information than does the mammography. In
collaborating with Dr. Robert Nishikawa, the group is
investigating and evaluating algorithms for image reconstruction
in tomosythesis breast imaging. Such an investigation
constitutes an important component of the foundation
for the development of CAD-based tomosythesis
breast imaging.
Developing Molecular Imaging Agents and Image
Reconstruction Strategies for Optoacoustic Tomography
Patrick La Riviere, PhD, and graduate student Dimple
Modgil are working with James Norris, PhD, of
Chemistry and Anthony Green, graduate student in
Chemistry, to develop imaging agents and imaging systems
that allow for visualization of protease activity in
vivo by stimulation and detection of optoacoustic signals.
Proteases are overexpressed in a number of pathologies,
including cancers and vascular disease. In optoacoustic
imaging, the tissue of interest is exposed to pulsed nearinfrared
laser light, as in optical imaging, but the image
is formed by measuring the acoustic signal engendered
by the absorption of optical energy in the tissue or by a
molecular probe. This optoacoustic approach will offer
advantages in terms of resolution, sensitivity, and depth
penetration over the purely optical approaches to protease
imaging that have been developed previously.
26

The molecular probe has been designed to shift its
absorption spectrum when cleaved by specific proteases.
This would allow the cleaved and uncleaved probes to
be distinguished by the optoacoustic signal at different
wavelengths. The imaging system will comprise a conventional
ultrasonic transducer with a coupled optical
fiber to deliver the stimulating near-infrared pulse. This
will enable interlaced anatomical and molecular images
to be acquired and superimposed.
X-ray Fluorescence Imaging of Pancreatic Islets
Research Associate Lara Leoni, PhD, Brian Roman, PhD,
and Patrick La Riviere, PhD have continued using the
scanning x-ray fluorescence microprobe at Sector 2 of
the Advanced Photon Source to image the spatial distribution
of exogeneous manganese that has been introduced
into islets of Langerhans as a contrast agent for
magnetic resonance imaging (MRI). The islets of
Langerhans comprise the hormone-secreting cells in the
pancreas, including the insulin-secreting beta cells
whose dysfunction is a major cause of diabetes. The ability
to assess the function of beta cells through in-vivo
imaging would aid in assessing the progression and
severity of diabetes as well as the success of therapies
based on islet transplantation. Recently, Dr. Roman and
his collaborators have shown that manganese can be
employed as an MRI contrast agent for islet imaging
since it is taken up through the calcium channels of
functional, glucose-stimulated beta cells. However, the
ability to draw quantitative conclusions about beta-cell
Left): Mn uptake in MIN-6
cells treated with 50 µm
MnCl 2 , 16 mM glucose and
30 mM KCl; Above):
intracellular Mn uptake
in MIN-6 cells
Figure 28
functionality from manganese-enhanced MRI is limited
by a lack of knowledge of how the manganese is actually
distributed in the islets: how much of it is actually taken
up by beta cells versus how much remains in the extracellular
space. X-ray fluorescence imaging is an ideal tool for
producing a map of exogenous manganese, as well as
endogenous elements such as calcium and zinc, in isolated,
intact islets.
New Image Acquisition Strategies in X-Ray Fluorescence
Computed Tomography (XFCT)
XFCT is an emerging imaging modality that allows for
the reconstruction of the distribution of nonradioactive
elements within a sample from measurements of fluorescence
x-rays produced by irradiation of the sample with
synchrotron radiation. The ability to map elemental distributions
within a sample has many potential biomedical
applications, including mapping of iodine distributions in
the thyroid, detection of heavy metals in the bones, and
mapping of cisplatin distribution in cancer cells. This
year, Patrick La Riviere, PhD, in collaboration with Ling-
Jian Meng, PhD, of the University of Illinois Urbana-
Champaign and scientists at the Advanced Photon
Source, have explored a new image acquisition strategy
based on the use of imaging detectors and multiple pinhole
collimators. It promises order-of-magnitude faster
imaging times and simpler data processing. See Figure 29.
Figure 29
Volume rendering of a 3D
x-ray fluorescence image of
three 0.75 mm tubes containing
three different elements:
zinc (blue),
bromine (green), and iron
(red). The 3D image was
acquired by illuminating
one slice at a time through
the object with monochromatic
x-rays and imaging
the stimulated characteristic
x-rays with an imaging
detector and multi-pinhole
collimator.
Quantitative Optical Imaging
Research Professional Lynnette Gerhold, PhD, Jeffrey
Souris, PhD, Patrick La Riviere, PhD, and Chin-Tu Chen,
PhD, have been collaborating with Rosie Xing, PhD, in
the Departments of Pathology and Radiation & Cellular
Oncology to develop evaluation, calibration, and correction
strategies for making the bioluminescence and fluorescence
imaging methods as more of quantitative imaging
approaches. They are investigating systematically the
physical factors that affect the accuracy and precision of
the quantitative measurements in using these optical
imaging techniques, develop novel strategies and methods
for correction of these physical effects in order to
make quantitative measurements feasible or improved,
27

and design and implement validation or evaluation
methodologies for characterization of these physical
effects, correction strategies, as well as resulting quantitative
accuracies. Dr. Souris has also developed a novel
approach to implant flexible and transparent materials
as window to view optical signals from tissues and
organs inside the animal models that previously can not
be viewed because of the lack of signals transmitted
through tissues and skins. This technique is now being
applied to several applications in animal imaging studies
for further validation and development.
Multi-Modality Imaging Probes
Jeffrey Souris, PhD, and Chin-Tu Chen, PhD, have been
collaborating with Liaohai Chen, PhD, in the Biological
Sciences Division of the Argonne National Laboratory to
utilize phage and micelle as nanoplatforms to develop
novel imaging probes, contrast agents, and tracers that
share the same shell vehicle which can “carry” a variety
of different agents for various imaging modalities,
including CT, PET, SPECT, optical imaging, ultrasound,
etc. These nanoparticles can also incorporate targeting
devices at their surface to home-in onto specific sites of
the cells or tissues that are to be traced, images, and
probed in order to increase substantially the uptake
ratio. In collaboration with Kurt M. Lin, PhD, and
Leuwei Lo, PhD, of the Medical Engineering Research
Division of the National Health Research Institute in
Taiwan, they are also using other tracer methodologies
and nanotechnology to design and build innovative
multi-modality imaging probes, which have been utilized
in a variety of applications such as imaging of
breast cancer. The theme of this line of research is to
design and develop novel imaging probes that can be
used for multiple imaging modalities in order to assess a
variety of structural or functional information of the
same tissues or organs.
Image Analysis In Chest
Imaging
Computerized Detection of Lung Nodules in Thin-
Section CT Images by use of Selective Enhancement
Filters and an Automated Rule-Based Classifier
Qiang Li, PhD, Feng Li, MD, PhD, and Kunio Doi, PhD,
have been developing a CAD scheme for lung nodule
detection in order to assist radiologists in the detection
of lung cancer in thin-section CT images. Our database
consisted of 117 thin-section CT scans with 153 nodules,
obtained from a lung cancer screening program at a
Japanese university (85 scans, 91 nodules) and from clinical
work at an American university (32 scans, 62 nodules).
The database included nodules of different sizes
(4-28 mm, mean 10.2 mm), shapes, and patterns (solid
and ground-glass opacity (GGO)). Our CAD scheme consisted
of modules for lung segmentation, selective nodule
enhancement, initial nodule detection, feature extraction,
and classification. The selective nodule enhancement filter
was a key technique for significant enhancement of
nodules and suppression of normal anatomic structures
such as blood vessels, which are the main sources of false
positives. Use of an automated rule-based classifier for
reduction of false positives was another key technique; it
resulted in a minimized overtraining effect and an
improved classification performance. They used a casebased
four-fold cross-validation testing method for evaluation
of the performance levels of the computerized
detection scheme. Their CAD scheme achieved an overall
sensitivity of 86% (small: 76%, medium-sized: 94%, large:
95%; solid: 86%, mixed GGO: 89%, pure GGO: 81%) with
6.6 false positives per scan; an overall sensitivity of 81%
(small: 69%, medium-sized: 91%, large: 91%, solid: 79%,
missed GGO: 88%, pure GGO: 81%) with 3.3. false positives
per scan; and an overall sensitivity of 75% (small:
60%, medium-sized: 88%, large: 87%; solid: 70%, mixed
GGO: 87%, pure GGO: 81%) with 1.6 false positives per
scan. In conclusion, the experimental results indicate that
their CAD scheme with its two key techniques can
achieve a relatively high performance for nodules presenting
large variations in size, shape, and pattern.
Lung Cancers Missed on Chest Radiographs: Results
Obtained with a Commercial Computer-Aided Detection
Program
Feng Li, MD, PhD, Roger E. Engelmann, MS, Charles E.
Metz, PhD, Kunio Doi, PhD, and Heber MacMahon, MD,
conducted the study to retrospectively determine the sensitivity
of and number of false-positive marks made by a
commercially available computer-aided detection (CAD)
system for identifying lung cancers previously missed on
chest radiographs by radiologists, with histopathologic
results as the reference standard. A CAD nodule detection
program was applied to 34 posteroanterior digital
chest radiographs obtained in 34 patients (21 men, 13
women; mean age, 69 years). All 34 radiographs showed
a nodular lung cancer that was apparent in retrospect but
had not been mentioned in the report. Two radiologists
identified these radiologist-missed cancers on the chest
radiographs and graded them for visibility, location, subtlety
(extremely subtle to extremely obvious on a 10-
point scale), and actionability (actionable or not actionable
according to whether the radiologists probably
would have recommended follow-up if the nodule had
been detected). The CAD results were analyzed to determine
the numbers of cancers and false-positive nodules
marked and to correlate the CAD results with the nodule
grades for subtlety and actionability. The x2 test or Fisher
exact test for independence was used to compare CAD
sensitivity between the very subtle (grade 1-3) and relatively
obvious (grade >3) cancers and between the actionable
and not actionable cancers. The CAD program had
28

an overall sensitivity of 35% (12 of 34 cancers), identifying
seven (30%) of 23 very subtle and five (45%) of 11
relatively obvious radiologist missed cancers (p = .21)
and detecting two (25%) of eight missed not actionable
and ten (38%) of 26 missed actionable cancers (p=.33).
The CAD program made an average of 5.9 false-positive
marks per radiograph. In conclusion, the described CAD
system can mark a substantial proportion of visually
subtle lung cancers that are likely to be missed by radiologists.
An Investigation of Radiologists’ Perception of Lesion
Similarity: Observations with Paired Breast Masses on
Mammograms and Paired Lung Nodules on CT Images
Seiji Kumazawa, PhD, Chisako Muramatsu, PhD, Qiang
Li, PhD, Feng Li, PhD, Junji Shiraishi, PhD, Philip
Caligiuri, MD, Robert A. Schmidt, MD, Heber
MacMahon, MD, and Kunio Doi, PhD, conducted an
observer study to investigate whether radiologists can
judge similarities in pairs of breast masses and lung
nodules consistently and reproducibly. They used eight
pairs of breast masses on mammograms and eight pairs
of lung nodules on computed tomographic images, for
which subjective similarity ratings ranging from 0 to 1
were determined in their previous studies. From these,
four sets of image pairs were created (i.e., a set of eight
mass pairs, a set of eight nodule pairs, and two mixed
sets of four mass and four nodule pairs). Eight radiologists,
including four breast radiologists and four chest
radiologists, compared all combinations of the eight
pairs in each set using a two-alternative forced-choice
(2AFC) method to determine the similarity ranking
scores by identifying which pair was more similar than
the other pair based on the overall impression for diagnosis.
In the mass set and nodule set, the relationship
between the average subjective similarity ratings and the
average similarity ranking scores by 2AFC indicated
very high correlations (r = 0.91 and 0.88). Moreover, in
the two mixed sets, the correlations between the average
subjective similarity ratings and the average similarity
ranking scores were also very high (r = 0.90 and 0.98).
Thus, radiologists were able to compare the similarities
for pairs of lesions consistently, even in the unusual
comparison of pairs of completely different types of
lesions. In conclusion, subjective similarity of a pair of
lesions in medical images can be quantified consistently
by a group of radiologists. The concept of similarity of
lesions in medical images can be subjected to rigorous
scientific research and investigation in the future.
Improved Detection of Small Lung Cancers with Dual
Energy Subtraction Chest Radiography
The objective of this study by Feng Li, MD, PhD, Roger
Engelmann, MS, Kunio Doi, PhD, & Heber MacMahon,
MD, was to retrospectively evaluate whether the use of
dual-energy subtraction chest radiographs can improve
radiologists’ performance for the detection of small
previously missed lung cancers. Dual-energy
subtraction chest radiographs of 19 patients with previously
missed nodular cancers, in which the radiology
report did not mention a nodule that was visible in retrospect,
were selected. Dual-energy subtraction radiographs
of 19 patients with cancer and 16 patients without cancer
were used for an observer study. Six radiologists indicated
their confidence level regarding the presence of a lung
cancer and, if they thought a cancer was present, also
marked the most likely position for each lung, first using
standard posteroanterior and lateral chest radiographs
and then using both soft-tissue and bone dual-energy
subtraction images along with standard radiographs.
Receiver operating characteristic (ROC) curves were used
to evaluate the observers’ performance. The indicated
locations of cancers and false-positive were also analyzed.
The average area under the ROC curve (AUC) value for
the six radiologists was improved from 0.718 to 0.816, a
statistically significant amount (p = 0.004), and the average
sensitivity (correct localizations) for 19 previously
missed cancers was also significantly improved from 40%
to 59% (p = 0.008) with the aid of dual-energy subtraction
images. The average number of false-positive (incorrect)
localizations on 70 lungs was 10 without and nine with
dual-energy subtraction images (p=0.785). In conclusion,
dual-energy subtraction chest radiography has the potential
to improve radiologists’ performance for the detection
of small missed lung cancers.
Enhanced Digital Chest Radiography: Temporal
Subtraction Combined with “Virtual Dual-Energy”
Technology for Improved Conspicuity of Growing
Cancers and Other Pathologic Changes
Kenji Suzuki, PhD, Samuel G. Armato, III, PhD, Heber
MacMahon, MD, and their colleagues are developing a
novel temporal-subtraction (TS) technique combined with
“virtual dual-energy” technology for improved conspicuity
of growing cancers and other pathologic
changes in digital chest radiography (CXR). Digital CXR
makes use of advanced image-processing techniques in
the radiology viewing environment. A TS technique provides
enhanced visualization of tumor growth and subtle
pathologic changes between previous and current CXRs
from the same patient. The researchers purpose was to
develop a new TS technique incorporating “virtual dualenergy”
technology to improve its enhancement quality.
Our TS technique consisted of ribcage edge detection,
rigid body transformation based on a global alignment
criterion, image warping based on local spatial displacement
vectors under the maximum cross-correlation criterion,
and subtraction between the registered previous and
current images. A major problem with TS was obscuring
of abnormalities by rib artifacts due to misregistration. To
reduce the rib artifacts, the team developed a massivetraining
artificial neural network (MTANN) for separation
of ribs from soft tissue. The MTANN was trained
with input CXRs and the corresponding “teaching” softtissue
CXRs obtained with dual-energy radiography.
Once trained, the MTANNs
29

Figure 30
Comparison of rib-suppressed novel temporal subtraction
images with conventional TS images: a) Previous chest radiographs;
b) Current chest radiographs of the same patient;
c) Rib-suppressed TS images with fewer rib artifacts;
d) Conventional TS images.
did not require a dual-energy system and provided softtissue
images in which ribs were substantially suppressed
(thus the term “virtual dual-energy” technology).
The database consisted of 100 sequential pairs of
digital CXR studies from 53 patients. To assess the registration
accuracy and clinical utility, a chest radiologist
subjectively rated original TS and rib-suppressed TS
images on a 5-point scale. By use of “virtual dual-energy”
technology, the contrast of ribs in the original CXRs
was reduced to 8% while maintaining that of soft tissue;
thus, rib artifacts in the TS images were reduced substantially.
The registration accuracy and clinical utility
ratings for TS rib-suppressed images (3.7; 3.9) were significantly
better than those for the original TS images
(3.5; 3.6) (p

statistical significance. Average sensitivity in the detection
of lesions improved from 59.8% to 69.3% for vertebral
fractures and from 64.9% to 67.6% for nodules.
Therefore, in the detection of vertebral fractures and
lung nodules on chest images, diagnostic accuracy
among radiologists improves with the use of CAD.
Reference Image Database to Evaluate Response to
Therapy in Lung Cancer
Samuel G. Armato III, PhD, is the local Principal
Investigator of the NCI-sponsored Reference Image
Database to Evaluate Response (RIDER) project, which
is investigating the role of imaging in the evaluation of
tumor response to therapy in lung cancer. Critical to the
clinical evaluation of effective novel therapies for lung
cancer is the early and accurate determination of tumor
response, which requires an understanding of the
sources of uncertainty in tumor measurements and subsequent
attempts to minimize their impact on the assessment
of the therapeutic agent. The RIDER project seeks
to develop a consensus approach to the optimization
and benchmarking of software tools for the assessment
of tumor response to therapy and to provide a publicly
available database of serial images acquired during lung
cancer drug and radiation therapy trials. Images of
phantoms and patient images acquired under situations
in which tumor size or biology are known to be
unchanged also will be provided. The RIDER project
will create standardized methods for benchmarking software
tools to reduce sources of uncertainty in vital clinical
assessments such as whether a specific tumor is
responding to therapy. One recurring and very significant
issue in the evaluation of new therapies, such as for
non-surgically treated lung cancer, is the assessment of
response to therapy. Establishing therapy safety and
effectiveness is essential for therapy regulatory approval
and for third-party payors to approve payments for that
therapy. The current approval metric, however, is based
on patient survival compared against a “best therapy”
standard in a randomized controlled study. Such studies
are expensive in terms of both time and money.
Moreover, since such studies may require large numbers
of subjects, the commencement of one study means that
other promising therapeutic agents are never tested.
Such an approach therefore denies the general population
access to many potentially useful agents. The
RIDER project is an important step in replacing this old
paradigm with a consensus-based process of developing
well-defined image-based metrics to measure tumorspecific
response as the primary outcome. This will
allow many more therapeutic agents to be tested more
rapidly, either singly or in combination, with large cost
savings and without detriment to subject safety. A final
randomized controlled study with patient survival as
the end point may still be needed for final regulatory
approval, but such a study then may be performed with
knowledge that the best available therapy has been chosen
for evaluation.
Image Analysis
In Body Imaging
Computer-Aided Diagnosis for the Classification of
Focal Liver Lesions by Use of Contrast-Enhanced
Ultrasonography
Junji Shiraishi, PhD, Katsutoshi Sugimoto, MD, Fuminori
Moriyasu, MD, and Kunio Doi, PhD, developed a CAD
scheme for classifying focal liver lesions (FLLs) as liver
metastasis, hemangioma, and three histologic differentiation
types of hepatocellular carcinoma (HCC), by use of
microflow imaging (MFI) of contrast-enhanced ultrasonography.
One hundred and three FLLs obtained from
97 cases used in this study consisted of 26 metastases (15
hyper- and 11 hypovascularity types), 16 hemangiomas
(five hyper- and 11 hypovascularity types) and 61 HCCs:
24 well differentiated (w-HCC), 28 moderately differentiated
(m-HCC), and nine poorly differentiated (p-HCC).
Pathologies of all cases were determined based on biopsy
or surgical specimens. Locations and contours of FLLs on
contrast-enhanced images were determined manually by
an experienced physician. MFI was obtained with contrast-enhanced
low-mechanical-index (MI) pulse subtraction
imaging at a fixed plane which included a distinctive
cross-section of the FLL. In MFI, the inflow high signals
in the plane, which were due to the vascular patterns and
the contrast agent, were accumulated following flash
scanning with a high-MI ultrasound exposure. In the initial
step of our computerized scheme, a series of the MFI
images was extracted from the original cine clip (AVI format).
We applied a smoothing filter and time-sequential
running average techniques in order to reduce signal
noise on the single MFI image and cyclic noise on the
sequential MFI images, respectively. A kidney, vessels,
and a liver parenchyma region were segmented automatically
by use of the last image of a series of MFI images.
The authors estimated time-intensity curves for an FLL
by use of a series of MFI images, in order to determine
temporal features such as estimated replenishment times
at early and delayed phases, flow rates, and peak times.
In addition, they extracted morphologic and gray-level
image features which were determined based on the
physician’s knowledge of the diagnosis of the FLL, such
as the size of lesion, vascular patterns, and the presence
of hypoechoic regions. They employed a cascade of six
independent artificial neural networks (ANNs) by use of
extracted temporal and image features for classifying five
types of liver diseases. A total of 16 temporal and image
features, which were selected from 43 initially extracted
features, were used for six different ANNs for making
decisions at each decision in the cascade. The ANNs were
trained and tested with a leave-one-lesion-out test
method. The classification accuracies for the 103 FLLs
31

were 88.5% for metastasis, 93.8% for hemangioma, and
86.9% for all HCCs. In addition, the classification accuracies
for histologic differentiation types of HCCs were
79.2% for w-HCC, 50.0% for m-HCC, and 77.8% for p-
HCC. The CAD scheme for classifying FLLs by use of
the MFI on contrast-enhanced ultrasonography has the
potential to improve the diagnostic accuracy in the histologic
diagnosis of HCCs and the other liver diseases.
Automated CT Liver Volumetry by Use of
Three-Dimensional Fast-Marching and Level-Set
Segmentation
Kenji Suzuki, PhD, Masatoshi Hori, MD, PhD, Aytekin
Oto, MD, Richard Baron, MD, and their colleagues are
developing an automated scheme for segmenting and
calculating liver volume in hepatic CT by means of 3D
fast-marching and level-set segmentation algorithms.
Automatic liver segmentation on hepatic CT images is
challenging because the liver often abuts other organs of
similar density. The researchers purpose was to develop
an automated liver segmentation scheme based on a 3D
level-set algorithm for measuring liver volumes. Hepatic
CT scans of eighteen prospective liver donors were
obtained under a liver transplant protocol. Scans were
acquired with a multi-detector CT system with a 16-, 40-,
or 64-channel detector scanner (Brilliance, Philips
Medical Systems, Netherlands). They developed an
automated liver segmentation scheme for volumetry of
the liver in CT, consisting of five steps. First, a 3D
anisotropic diffusion smoothing filter was applied to CT
images for removing noise while preserving the structures
in the liver, followed by a gradient magnitude filter
for enhancing liver edges. A nonlinear gray-scale
enhancement filter was applied to the gradient magnitude
image for further enhancing the boundary of the
liver. By use of the enhanced gradient magnitude image
as a speed function, a 3D fast-marching algorithm generated
an initial surface that roughly estimated the shape
of the liver. A 3D level-set segmentation algorithm
refined the initial surface so as to fit the liver boundary
more accurately (see Figure 31 for a segmentation
result). The liver volume was calculated based on the
refined liver surface. Automated volumes were
compared to manually determined liver volumes. The
mean liver volume obtained with our scheme was 1598
cc (range: 1002-2415 cc), whereas the mean manual volume
was 1,535 cc (range: 1,007-2,435 cc). The mean
absolute difference between automated and manual volumes
was 128 (9.5%) ± 119 (9.4%) cc. The two volumetrics
reached excellent agreement (the intra-class correlation
coefficient was 0.89) with no statistically significant
difference (p=0.13). The processing time by the automated
method was 2-5 min. per case (Intel, Xeon, 2.7 GHz),
whereas that by manual segmentation was approximately
50-60 min. per case. CT liver volumetrics based on an
automated scheme agreed excellently with manual volumetrics
and required substantially less completion time.
Thus, the automated scheme provides an efficient and
accurate way of measuring liver volumes in CT.
A CAD Utilizing 3D Massive-Training ANNs for
Detection of Flat Lesions in CT Colonography in a Large
Multicenter Clinical Trial
Kenji Suzuki, PhD, Abraham H. Dachman, MD, and their
colleagues are developing a computer-aided diagnostic
(CAD) scheme for detection of flat lesions (also called flat
polyps or depressed polyps) in CT colonography (CTC)
in a large multicenter clinical trial in collaboration with
Don C. Rockey, MD, at the Southwest Medical Center of
the University of Texas. Flat lesions in the colon are a
major source of false-negative interpretations in CTC. A
major challenge in CAD schemes is the detection
Figure 32
Figure 31
Illustration of automated liver segmentation: a) Original CT
liver image; b) Segmented liver obtained with our automated
liver segmentation method (Red curve).
Illustrations of flat lesions that exhibit uncommon flat morphology.
a) A flat lesion on a fold (10 mm; adenoma) in the cecum was
detected correctly by the MTANN CAD scheme (indicated by an
arrow). b) A small flat lesion (6 mm; adenoma) in the cecum was
detected correctly by the MTANN CAD scheme.
32

of flat lesions, because existing CAD schemes are
designed for detecting the common bulbous polyp
shape. The goal was to develop a CAD scheme for
detection of flat lesions in CTC. The researchers developed
a CAD scheme consisting of colon segmentation
based on histogram and morphologic analysis, detection
of polyp candidates based on intensity-based and morphologic
feature analysis, and linear discriminant analysis
for classification of the candidates as polyps or nonpolyps.
To detect flat lesions, the group developed a
“tolerant” morphologic analysis method in the polyp
detection step for accommodating the analysis to
include a flat shape. For reduction of false-positive (FP)
detections, a 3D massive-training artificial neural networks
(MTANNs) was designed to differentiate flat
lesions from various types of non-polyps. An independent
database consisting of CTC scans of 25 patients
obtained from a multicenter clinical trial in which 15
institutions participated nationwide was utilized. Each
patient was scanned in the supine and prone positions
with collimations of 1.0-2.5 mm and reconstruction intervals
of 1.0-2.5 mm. All patients underwent “referencestandard”
optical colonoscopy. Flat lesions were determined
under either “height” (< 3 mm high) or “ratio”
(height < 1/2 long axis) criteria. Twenty-eight flat
lesions were identified. Among them, 11 (39%) were
false negatives in CTC. Lesion sizes ranged from 6-18
mm, with an average of 9 mm. The MTANN CAD
scheme detected 68% (19/28) of flat lesions, including
six lesions “missed” by reporting radiologists in the
original clinical trial, with 10 (249/25) FPs per patient.
Figure 32 shows examples of flat lesions, which are very
small or on a fold (these are major causes of human
misses). Some flat lesions are known to be histologically
aggressive; therefore, detection of such lesions is critical
clinically, but they are difficult to detect because of their
uncommon morphology. It should be noted that these
two cases were “missed” by reporting radiologists in the
original trial; thus, detection of these lesions may be
considered “very difficult.” This scheme would be useful
for detecting flat lesions which are a major source of
false negatives, thus potentially improving radiologists’
sensitivity in their detection of polyps in CTC.
Image Analysis
In Breast Imaging
Comparison of CAD on Digitized Screen-Film
Mammograms and Full-Field Digital Mammograms
As part of her doctoral dissertation, Laura Yarusso, PhD,
working in conjunction with Robert Nishikawa, PhD,
Alexandra Edwards, MA, and John Papaioannou, MS,
has compared the performance of different components
of a computer-aided detection (CADe) scheme for clustered
calcifications on mammograms. The goals of this
research were to measure and compare image quality
between full-field digital mammography (FFDM) and
digitized screen-film mammography (dSFM), and to
investigate the effect of image quality differences on the
multiple components of our CADe scheme for the detection
of clustered microcalcifications. The main hypothesis
tested was that the superior image quality of FFDM relative
to dSFM would result in improvements to multiple
aspects of CADe performance.
Previously the group showed using test objects that
FFDM was able to depict small objects on the size of calcifications
with higher accuracy and precision than for
dSFM. Recently, using bone chips and cadaver breasts,
they found that with this higher accuracy and precision,
the feature analysis component of the CADe scheme was
improved for seven of eight features analyzed. This
resulted in higher performance for the CADe algorithm
when analyzing FFDM images compared to analyzing
dSFM images. This is an important result as FFDM systems
replace SFM systems.
Evaluation of Computer-Aided Diagnosis on a Large
Clinical Full-Field Digital Mammographic Dataset
Hui Li, PhD, Maryellen L Giger, PhD, Yading Yuan, BS,
Weijie Chen, PhD, Karla Horsch, PhD, Li Lan, MS,
Andrew R Jamieson, BS, Charlene A Sennett, MD, and
Sanaz A Jansen, MS converted and optimized their previously
developed computerized analysis methods for use
with images from full-field digital mammography
(FFDM) for breast mass classification in order to aid in
the diagnosis of breast cancer. Seven hundred and thirtynine
full-field digital mammographic images, which contained
287 biopsy-proven breast mass lesions, of which
148 lesions were malignant and 139 lesions were benign,
were retrospectively collected. Lesion margins were
delineated by an expert breast radiologist and were used
as the truth for lesion-segmentation evaluation. The computerized
image analysis method consisted of several
steps: 1) identified lesions were automatically extracted
from the parenchymal background using computerized
segmentation methods; 2) a set of image characteristics
(mathematical descriptors) were automatically extracted
from image data of the lesions and surrounding tissues;
and 3) selected features were merged into an estimate of
the probability of malignancy using a Bayesian artificial
neural network classifier. Performance of the analyses
was evaluated at various stages of the conversion using
receiver operating characteristic (ROC) analysis. An AUC
value of 0.81 was obtained in the task of distinguishing
between malignant and benign mass lesions in a roundrobin
by case evaluation on the entire FFDM dataset.
They failed to show a statistically significant difference
(p value=0.83) as compared with results from their previous
study in which the computerized classification was
performed on digitized screen-film
33

mammograms (DSFM). Thus, in conclusion, their computerized
analysis methods developed on digitized
screen-film mammography can be converted for use
with FFDM. Results show that the computerized analysis
methods for the diagnosis of breast mass lesions on
FFDM are promising, and can potentially be used to aid
clinicians in the diagnostic interpretation of FFDM.
Determination of Subjective Similarity for Pairs of
Masses and Pairs of Clustered Microcalcifications on
Mammograms: Comparison of Similarity Ranking
Scores and Absolute Similarity Ratings
The presentation of images that are similar to that of an
unknown lesion seen on a mammogram may be helpful
for radiologists to correctly diagnose that lesion. For
similar images to be useful, they must be quite similar
from the radiologists’ point of view. Chisako
Muramatsu, PhD, Qiang Li, PhD, Robert A. Schmidt,
MD, Junji Shiraishi, PhD, Kenji Suzuki, PhD, Gillian M.
Newstead, MD, and Kunio Doi, PhD, have been trying
to quantify the radiologists’ impression of similarity for
pairs of lesions and to establish a “gold standard” for
development and evaluation of a computerized scheme
for selecting such similar images. However, it is considered
difficult to reliably and accurately determine similarity
ratings, because they are subjective. In this study,
we compared the subjective similarities obtained by two
different methods, an absolute rating method and a 2-
alternative forced-choice (2AFC) method, to demonstrate
that reliable similarity ratings can be determined by the
responses of a group of radiologists. The absolute similarity
ratings were previously obtained for pairs of masses
and pairs of microcalcifications from five and nine
radiologists, respectively. In this study, similarity ranking
scores for eight pairs of masses and eight pairs of
microcalcifications were determined by use of the 2AFC
method. In the first session, the eight pairs of masses
and eight pairs of microcalcifications were grouped and
compared separately for determining the similarity
ranking scores. In the second session, another similarity
ranking score was determined by use of mixed pairs, i.e.,
by comparison of the similarity of a mass pair with that
of a calcification pair. Four pairs of masses and four
pairs of microcalcifications were grouped together to
create two sets of eight pairs. The average absolute similarity
ratings and the average similarity ranking scores
showed very good correlations in the first study
(Pearson’s correlation coefficients: 0.94 and 0.98 for
masses and microcalcifications, respectively). Moreover,
in the second study, the correlations between the
absolute ratings and the ranking scores were also very
high (0.92 and 0.96), which implies that the observers
were able to compare the similarity of a mass pair with
that of a calcification pair consistently. These results provide
evidence that the concept of similarity for pairs of
images is robust, even across different lesion types, and
that radiologists are able to reliably determine subjective
similarity for pairs of breast lesions.
Automated Method for Improving System Performance
of Computer-Aided Diagnosis in Breast Ultrasound
Karen Drukker, PhD, Charlene A Sennett, MD, and
Maryellen L Giger, PhD, demonstrated the feasibility of
their computerized auto-assessment method in which a
computer-aided diagnosis (CADx) system itself provides
a level of confidence for its estimate for the probability of
malignancy for each radiologist-identified lesion. The
computer performance was assessed within a leave-onecase-out
protocol using a database of sonographic images
from 542 patients (19% cancer prevalence). They investigated
the potential of computer-derived confidence levels
both 1) as an output aid to radiologists and 2) as an
automated method to improve the computer classification
performance in the task of differentiating between
cancerous and benign lesions for the entire database. For
the former, the CADx classification performance was
assessed within ranges of confidence levels. For the latter,
the computer-derived confidence levels were used in the
determination of the computer-estimated probability of
malignancy for each actual lesion based on probabilities
obtained from different views. The use of this autoassessment
method resulted in the modest but statistically
significant increase in the area under the ROC curve
(AUC value) of 0.01 with respect to the performance
obtained using the ‘traditional’ CADx approach, increasing
the AUC value from 0.89 to 0.90 (p-value 0.03). They
believe that computer-provided confidence levels may be
helpful to radiologists who are using CADx output in
diagnostic image interpretation as well as for automated
improvement of the CADx classification for cancer.
Breast Ultrasound Computer-Aided Diagnosis:
Performance on a Large Clinical Diagnostic Population
Karen Drukker, PhD, Nicholas Gruszauskas, PhD,
Charlene A. Sennett, MD, and Maryellen L. Giger, PhD,
evaluated the performance of their computer-aided diagnosis
(CADx) workstation in the task of classifying cancer
in a realistic dataset representative of a clinical diagnostic
breast ultrasound practice. The database consisted
of consecutive diagnostic breast ultrasound examinations
acquired with a Philips HDI5000 scanner, collected with
informed consent under an approved IRB and HIPAA
compliant protocol. Images from 695 patients were collected
for this study and images from all patients presenting
with at least one sonographically visible lesion
were used (508 patients with a total of 1046 distinct
abnormalities); 101 patients had breast cancer. They presented
results both for patients for whom lesion pathology
was proven by either biopsy or aspiration (183
patients), and for all patients irrespective of biopsy-status
(508 patients). The ability of the CADx workstation to
distinguish malignancies from benign lesions was evaluated
with a leave-one-out-by-case analysis. The clinical
specificity of the radiologists for this dataset was determined
by the biopsy rate and outcome. In the task of distinguishing
cancer from all other lesions sent to biopsy,
the CADx workstation obtained an area under the ROC
34

curve (AUC value) of 0.88, obtaining 100% sensitivity at
26% specificity (157 cancers and 362 lesions total). The
radiologists’ specificity at 100% sensitivity for this set
was zero. When analyzing all lesions irrespective of
biopsy-status, more representative of actual clinical
practice, the CADx scheme obtained an AUC of 0.90 and
100% sensitivity at 30% specificity (157 cancers and 1046
lesions total). The radiologists’ specificity at 100% sensitivity
for this set equaled 77%. In conclusion, current
levels of computer performance warrant a clinical evaluation
of the potential of sonographic CADx to aid radiologists
in lesion work-up recommendations.
Robustness of a Breast Ultrasound Computer-Aided
Diagnosis System across Different Patient Populations
Nicholas P. Gruszauskas, PhD, Karen Drukker, PhD, and
Maryellen L. Giger, PhD, in a collaboration with Ruey-
Feng Chang, PhD, from the Department of Computer
Science and Information Engineering, National Taiwan
University, Taipai, Tawain investigated the robustness of
the University of Chicago breast ultrasound computeraided
diagnosis system (CADx) when it is used across
different patient populations. A sonographic database
consisting of 433 lesions (127 malignant, 306 benign)
from patients in the United States was used in the training
of the breast ultrasound CADx system. A second
sonographic database consisting of 456 lesions (145
malignant, 311 benign) was obtained from a separate
patient population from Asia and used to test the
trained classifier. Four sonographic features were
extracted from each lesion (shape, margin sharpness,
posterior acoustic behavior, and texture). These features
were used to train a Bayesian neural network classifier.
Both round-robin and independent testing were used to
evaluate the classifier with the two databases.
Performance was assessed by calculating the area under
the ROC curve (AUC) for each test. The AUC of the
independent test was 0.80 while the AUCs for the
round-robin tests were 0.87 and 0.88 for the Asian and
American databases, respectively. The difference
between the independent test AUC and the round-robin
AUC for the Asian database was statistically significant
(p-value=0.02). This work indicates that the University
of Chicago breast ultrasound CADx system is moderately
robust across different patient populations. The statistically
significant difference between the AUCs of the
Asian database along with the similarity of the roundrobin
AUCs indicate that while the sonographic features
used by the system are useful in both databases, their
relative importance differs. This motivates the future
exploration of optimal feature sets to improve the overall
performance of the CADx system.
Performance of Breast Ultrasound Computer-Aided
Diagnosis: Dependence on Image Selection
The automated classification of sonographic breast
lesions is generally accomplished by extracting and
quantifying various features from the lesions.
The selection of images to be analyzed, however, is usually
left to the radiologist. Nicholas P. Gruszauskas, PhD,
Karen Drukker, PhD, Maryellen L. Giger, PhD, Charlene
A. Sennett, MD, and Lorenzo L. Pesce, PhD, presented an
analysis of the effect that image selection can have on the
performance of a breast ultrasound computer-aided diagnosis
system. A database of 344 different sonographic
lesions was analyzed for this study (219 cysts/benign
processes, 125 malignant lesions). Three different image
selection protocols were used in the automated classification
of each lesion: all images, first image only, and randomly
selected images. After image selection, two different
protocols were used to classify the lesions: a) the
average feature values were input to the classifier, or b)
the classifier outputs were averaged together. Both protocols
generated an estimated probability of malignancy.
Round-robin analysis was performed using a Bayesian
neural network-based classifier. Receiver operating characteristic
analysis was used to evaluate the performance
of each protocol. Significance testing of the performance
differences was performed via 95% confidence intervals
and non-inferiority tests. The differences in the area
under the ROC curves were never more than 0.02 for the
primary protocols. Non-inferiority was demonstrated
between these protocols with respect to standard input
techniques (all images selected and feature averaging). In
conclusion, they showed that their automated lesion classification
scheme is robust and can perform well when
subjected to variations in user input.
Reader Study for the Evaluation of Radiologists’
Interpretation of Breast MRI using a CAD Breast
MRI Workstation
Akiko Shimauchi, MD, Maryellen Giger, PhD, Neha
Bhooshan, Li Lian, MS, Weijie Chen, PhD, and Gillian
Newstead, MD, evaluated and compared the radiologists’
use of the University of Chicago laboratory-developed
CAD workstation for contrast-enhanced breast MRI to the
current clinical method of interpreting breast MRI, which
is an MRI viewing workstation with commercially-available
dynamic analysis software (CAD stream). In this
IRB-approved study, five observers (all breast imaging
radiologists) evaluated 60 breast lesions with known
biopsy outcomes. T2WI, two series (early and delayed
phases) from dynamic contrast-enhanced exams, and the
corresponding subtraction images of the two series were
available on a GE viewing workstation, along with
Confirma color-coded images and dynamic curves.
BIRADS score assessment, probability of malignancy, and
patient management decisions were documented upon
completion of interpretation. Immediately after, observers
consulted the UC MRI CAD workstation output and were
able to modify their interpretation. The UC MRI CAD
workstation automatically segments lesions in 3D and
extracts both kinetic data and morphological lesion features,
and then generates an estimate of the probability of
malignancy from a merging of the extracted features by a
trained neural network based on an independent
35

database of biopsied lesions. Use of the UC CAD workstation
resulted in an improvement of the performance
of the all observers, as measured by means of a statistically
significant increase in average Az value (0.80 to
0.85; p=0.0015) and partial Az value (0.11 to 0.25;
p=0.0032), and sensitivity (0.82 to 0.87; p=0.0046) and
positive predictive value (PPV) (0.66 to 0.69, p=0.047)
calculated by patient biopsy management decision, as
well as sensitivity (0.77 to 0.81; p=0.034) as calculated by
BIRADS score assessment. Although all increased after
the use of CAD, they failed to show statistically significant
differences in specificity as calculated by management
(0.49 to 0.53; p=0.11) and BIRADS assessment (0.45
to 0.47, p=0.30), and PPV as calculated by BIRADS
assessment (0.60 to 0.61; p=0.20). In conclusion, use of
the UC MRI CAD workstation improved the performance
of radiologists in the task of differentiating malignant
and benign lesions at breast MRI. Thus the UC MR
CAD workstation can be used as an aid to breast imaging
radiologists in the interpretation of breast MRI (See
Figure 33).
Figure 33
Interface of the Breast MRI CADx workstation illustrating
output on a malignant case. The workstation automatically
segments the tumor in 3D, determine the most enhancing
voxels within the tumor along with the corresponding kinetic
curve, calculates various morphological and kinetics features,
and outputs an estimate of the probability of malignancy.
Pre-Clinical Evaluation of a Computerized System
for Lesion Characterization in Breast DCE-MRI:
Robustness Study and Correlation with BI-RADS
Assessments
Weijie Chen, PhD, Maryellen Giger, PhD, Ken Chiang,
Sanaz Jansen, and Gillian Newstead, MD, investigated
their automatic and efficient computerized system for
DCE-MRI breast lesion analysis, which includes assessment
of tumor extent, extraction of lesion characteristics,
and classification of the lesion in terms of an estimate of
the probability of malignancy. The analysis involved two
breast MR databases totaling 302 biopsy-proven lesions.
T1-weighted SPGR sequence was used to acquire one
precontrast series and 5 postcontrast series with a 1 min
temporal resolution. The first database (77 malignant and
44 benign) was obtained with a 1.5T Siemens scanner.
The second database (97 malignant and 84 benign) was
from a 1.5T GE scanner. In the computerized lesion characterization,
the identified breast lesions initially undergo
automatic 3D segmentation by the computer. Then, characteristic
kinetic curves are automatically identified.
Image features are then automatically extracted to characterize
the lesions as benign or malignant. Characteristic
features include (1) kinetic features that quantify the
uptake and washout characteristics of the contrast agent;
(2) 3D texture features that quantify the uptake inhomogeneity
within the lesion; and (3) 3D shape descriptors
that quantify the irregularity of the tumor. A point biserial
correlation method was used to investigate the correlation
of computerized features with ACR BI-RADS assessments
for breast MRI. A neural network model was used
to merge multiple features into an estimate of the likelihood
of malignancy. Statistical significant correlations
(P

model, they studied how changes in the prevalence of
cancer in the diagnostic breast population affect their
computer classifiers’ optimal operating points, as
defined by maximizing the expected utility. They found
that prevalence scaling affects the threshold at which a
particular TPF and FPF pair is achieved. They showed
that histograms of PMs scaled to reflect clinically-relevant
prevalence values differ greatly from histograms of
laboratory-designed PMs. The optimal pair of TPF and
FPF of their lower performing mammographic classifier
was found to be more sensitive to changes in clinical
prevalence than is that of their higher performing sonographic
classifier. In conclusion, prevalence scaling can
be used to change computer PM output to reflect clinically
more appropriate prevalence. Relatively small
changes in clinical prevalence can have large effects on
the computer classifier’s optimal operating point.
Volumetric Texture Analysis of Breast Lesions on
Contrast-Enhanced Magnetic Resonance Images
Automated image analysis aims to extract relevant information
from contrast-enhanced magnetic resonance
images (CE-MRI) of the breast and improve the accuracy
and consistency of image interpretation. Weijie Chen,
PhD, Maryellen L. Giger, PhD, Hui Li, PhD, Ulrich Bick,
MD, and Gillian M. Newstead, MD, extended traditional
2D gray-level co-occurrence matrix (GLCM) method to
investigate a volumetric texture analysis approach and
apply it for the characterization of breast MR lesions.
Their database of breast MR images was obtained using
a T1-weighted 3D spoiled gradient echo sequence and
consists of 121 biopsy-proven lesions (77 malignant and
44 benign). A fuzzy c-means clustering (FCM) based
method was employed to automatically segment 3D
breast lesions on CE-MR images. For each 3D lesion, a
nondirectional GLCM was then computed on the first
post-contrast frame by summing 13 directional GLCMs.
Texture features were extracted from the nondirectional
GLCMs and the performance of each texture feature in
the task of distinguishing between malignant and
benign breast lesions was assessed by receiver operating
characteristics (ROC) analysis. Their results show that
the classification performance of volumetric texture features
is significantly better than that based on 2D analysis.
Their investigations of the effects of various parameters
on the diagnostic accuracy provided means for the
optimal use of the approach.
Power Spectral Analysis of Mammographic
Parenchymal Patterns for Breast Cancer Risk
Assessment
Hui Li, PhD, Maryellen L. Giger, PhD, Olufunmilayo I.
Olopade, MD, and Michael R. Chinander, PhD, evaluated
the usefulness of power law spectral analysis on
mammographic parenchymal patterns in breast cancer
risk assessment. Mammograms from 172 subjects (30
women with the BRCA1/BRCA2 gene mutation and 142
low-risk women) were retrospectively collected and
digitized. Because age is a very important risk factor, 60
low-risk women were randomly selected from the 142
low-risk subjects and were age matched to the 30 gene
mutation carriers. Regions of interest were manually
selected from the central breast region behind the nipple
of these digitized mammograms and subsequently used
in power spectral analysis. The power law spectrum
analysis was evaluated for the mammographic patterns.
The performance of exponent beta as a decision variable
for differentiating between gene mutation carriers and
low-risk women was assessed using receiver operating
characteristic analysis for both the entire database and the
age-matched subset. Power spectral analysis of mammograms
demonstrated a statistically significant difference
between the 30 BRCA1/BRCA2 gene mutation carriers
and the 142 low risk women with average beta values of
2.92 (±0.28) and 2.47(±0.20), respectively. An AUC value
of 0.90 was achieved in distinguishing between gene
mutation carriers and low-risk women in the entire database,
with an Az value of 0.89 being achieved on the agematched
subset. The BRCA1/BRCA2 gene mutation carriers
and low-risk women have different mammographic
parenchymal patterns. It is expected that women identified
as high risk by computerized feature analyses might
potentially be more aggressively screened for breast
cancer.
Image Analysis
In Skeletal Imaging
Radiographic Texture Analysis in the Characterization of
Trabecular Patterns in Periprosthetic Osteolysis
Periprosthetic osteolysis is a disease attributed to the
body’s reaction to fine polyethylene wear debris shed
from total hip replacements. Joel R. Wilkie, PhD,
Maryellen L. Giger, PhD, Charles A. Engh Sr., MD, Robert
H. Hopper Jr., PhD, and John M. Martell, MD, investigated
the ability of radiographic texture analysis (RTA) to
characterize the trabecular texture patterns on pelvic
images for osteolysis and normal total hip arthroplasty
(THA) cases. Fourier-based and fractal-based texture features
were calculated for a database of digitized radiographs
from 202 THA cases, 70 of which developed osteolysis.
The features were calculated from regions of interest
selected at two time points: less than 1 month after
surgery, and at the first clinical indication of osteolysis (or
randomly selected follow-up time for normal cases).
Receiver operating characteristic (ROC) analysis was
used to compare feature performance at baseline and follow-up
for osteolysis and normal cases. Separation
between the RTA features for osteolysis and normal cases
was negligible at baseline and increased substantially for
37

the follow-up images. The directional Fourier-based feature
provided the best separation with an AUC value
from ROC analysis of 0.75 for the follow-up images, in
the task of distinguishing between normal and osteolytic
cases. The results from this preliminary analysis indicate
that qualitative changes in trabecular patterns from
immediately after surgery to the eventual detection of
osteolysis correspond to quantitative changes in RTA
features. It therefore appears that RTA provides information
that could potentially be useful to aid in the detection
of this disease.
Temporal Radiographic Texture Analysis in the
Detection of Periprosthetic Osteolysis
Periprosthetic osteolysis is one of the most serious longterm
problems in total hip arthroplasty. It has been primarily
attributed to the body’s inflammatory response to
submicron polyethylene particles worn from the hip
implant, and it leads to bone loss and structural deterioration
in the surrounding bone. It was previously
demonstrated that radiographic texture analysis has the
ability to distinguish between osteolysis and normal
cases at the time of clinical detection of the disease; however,
that analysis did not take into account the changes
in texture over time. Thus, Joel R. Wilkie, PhD,
Maryellen L. Giger, PhD, Michael R. Chinander, PhD,
Charles A. Engh, Sr., Robert H. Hopper, Jr., and John M.
Martell assessed the ability of temporal radiographic
texture analysis, tRTA, to distinguish between patients
who develop osteolysis and normal cases. Two tRTA
methods were used in the study: the RTA feature change
from baseline at various follow-up intervals and the
slope of the best-fit line to the RTA data series. These
tRTA methods included Fourier-based and fractal-based
features calculated from digitized images of 202 total hip
replacement cases, including 70 that developed osteolysis.
Results show that separation between the osteolysis
and normal groups increased over time for the feature
difference method, as the disease progressed, with area
under the curve values from receiver operating characteristic
analysis of 0.65 to 0.72 at 15 years postsurgery.
Separation for the slope method was also evident, with
AUC values ranging from 0.65 to 0.76 for the task of distinguishing
between osteolysis and normal cases. The
results suggest that tRTA methods have the ability to
measure changes in trabecular structure, and may be
useful in the early detection of periprosthetic osteolysis.
Image Analysis
In Cardiac Imaging
Feature-Based Characterization of Motion-Contaminated
Calcified Plaques in Cardiac Multidetector CT
In coronary calcium scoring, motion artifacts affecting
calcified plaques are commonly characterized using
descriptive terms, which incorporate an element of subjectivity
in their interpretations. Quantitative indices may
improve the objective characterization of these motion
artifacts. Thus, Martin King, PhD, Maryellen L. Giger,
PhD, Kenji Suzuki, PhD, and Xiaochuan Pan, PhD, developed
an automated method for generating 12 quantitative
indices, i.e., features that characterize the motion
artifacts affecting calcified plaques. This method consists
of using the rapid phase-correlated region-of-interest
tracking algorithm for reconstructing ROI images of calcified
plaques automatically from the projection data
obtained during a cardiac scan, and applying methods
for extracting features from these images. The 12 features
include two dynamic, six morphological, and four intensity-based
features. The two dynamic features are threedimensional
velocity and 3D acceleration. The six morphological
features include edge-based volume, threshold-based
volume, sphericity, irregularity, average margin
gradient, and variance of margin gradient. The four
intensity-based features are maximum intensity, mean
intensity, minimum intensity, and standard deviation of
intensity. The 12 features were extracted from 54 reconstructed
sets of simulated four-dimensional images from
the dynamic NCAT phantom involving six calcified
plaques under nine heart rate/multi-sector gating combinations.
In order to determine how well the 12 features
correlated with a plaque motion index, which was
derived from the trajectory of the plaque, partial correlation
coefficients adjusted for heart rate, number of gated
sectors, and mean feature values of the six plaques were
calculated for all 12 features. Features exhibiting stronger
correlations with the motion index were 3D velocity,
maximum intensity, and standard deviation of intensity.
Features demonstrating stronger correlations with other
features mostly involved intensity-based features. Edgebased
volume/irregularity and average margin gradient/variance
of margin gradient were the only two feature
pairs out of 12 with stronger correlations that did not
involve intensity-based features. Automatically extracted
features of the motion artifacts affecting calcified plaques
in cardiac computed tomography images potentially can
be used to develop models for predicting image assessability
with respect to motion artifacts.
Computerized Assessment of Motion-Contaminated
Calcified Plaques in Cardiac Multidetector CT
Martin King, PhD, Maryellen L. Giger, PhD, Kenji
Suzuki, PhD, Dianna ME Bardo, MD, Brent Greenberg,
MD, Li Lan, MS, and Xiaochuan Pan, PhD, presented an
automatic method for assessing the image quality of calcified
plaques with respect to motion artifacts in noncontrast-enhanced
cardiac computed tomography images.
This method involves using linear regression (LR) and
artificial neural network (ANN) regression models for
predicting two patient-specific, region-of-interest-specific,
reconstruction-specific and temporal phase-specific
image
38

quality indices. The first is a plaque motion index, which
is derived from the actual trajectory of the calcified
plaque and is represented on a continuous scale. The
second is an assessability index, which reflects the
degree to which a calcified plaque is affected by motion
artifacts, and is represented on an ordinal five-point
scale. Two sets of assessability indices were provided
independently by two radiologists experienced in evaluating
cardiac CT images. Inputs for the regression models
were selected from 12 features characterizing the
dynamic, morphological, and intensity-based properties
of the calcified plaques. Whereas LR-velocity (LR-V)
used only a single feature (three-dimensional velocity),
the LR-multiple (LR-M) and ANN regression models
used the same subset of these 12 features selected
through stepwise regression. The regression models
were parameterized and evaluated using a database of
simulated calcified plaque images from the dynamic
NCAT phantom involving nine heart rate/multi-sector
gating combinations and 40 cardiac phases covering two
cardiac cycles. Six calcified plaques were used for the
plaque motion indices and three calcified plaques were
used for both sets of assessability indices. In one configuration,
images from the second cardiac cycle were used
for feature selection and regression model parameterization,
whereas images from the first cardiac cycle were
used for testing. With this configuration, repeated measures
concordance correlation coefficients (CCCs) and
associated 95% confidence intervals for the LR-V, LR-M,
and ANN were 0.817 (0.785, 0.848), 0.894 (0.869, 0.916),
and 0.917 (0.892, 0.936) for the plaque motion indices.
For the two sets of assessability indices, CCC values for
the ANN model were 0.843 (0.791, 0.877) and 0.793
(0.747, 0.828). These two CCC values were statistically
greater than the CCC value of 0.689 (0.648, 0.727), which
was obtained by comparing the two sets of assessability
indices with each other. These preliminary results suggest
that the variabilities of assessability indices provided
by regression models can lie within the variabilities
of the indices assigned by independent observers. Thus,
the potential exists for using regression models and
assessability indices for determining optimal phases for
cardiac CT image interpretation.
Computerized Assessment of Coronary Calcified
Plaques in CT Images of a Dynamic Cardiac Phantom
Motion artifacts in cardiac CT are an obstacle to obtaining
diagnostically usable images. Although phase-specific
reconstruction can produce images with improved
assessability (image quality), this requires that the radiologist
spend time and effort evaluating multiple image
sets from reconstructions at different phases. Thus,
Zachary B. Rodgers, Martin King, PhD, Maryellen L.
Giger, PhD, Michael Vannier, MD, Dianna ME Bardo,
MD, Kenji Suzuki, PhD, and Li Lan, MS, used ordinal
logistic regression (OLR) and artificial neural network
(ANN) models to automatically assign assessability to
images of coronary calcified plaques obtained using a
physical, dynamic cardiac phantom. 350 plaque images
of 7 plaques from five data sets (heart rates 60, 60, 70, 80,
90) and ten phases of reconstruction were obtained using
standard cardiac CT scanning parameters on a Phillips
Brilliance 64-channel clinical CT scanner. Six features of
the plaques (velocity, acceleration, edge-based volume,
threshold-based volume, sphericity, and standard deviation
of intensity) as well as mean feature values and heart
rate were used for training the OLR and ANN in a roundrobin
re-sampling scheme based on training and testing
groups with independent plaques. For each image, an
ordinal assessability index rating on a 1-5 scale was
assigned by a cardiac radiologist for use as a “truth” in
training the OLR and ANN. The mean difference between
the assessability index truth and model-predicted assessability
index values was +0.111 with SD=0.942 for the
OLR and +0.143 with SD=0.916 for the ANN. Comparing
images from the repeat 60 bpm scans gave concordance
correlation coefficients (CCCs) of 0.794 [0.743, 0.837]
(value, 95% CI) for the radiologist assigned values, 0.894
[0.856, 0.922] for the OLR, and 0.861 [0.818, 0.895] for the
ANN. Thus, the variability of the OLR and ANN assessability
index values appear to lie within the variability of
the radiologist assigned values.
Image Analysis In
Histological Images
Development of Computer-Aided Detection of Prostate
Cancer in Histology Images
Graduate student Yahui Peng and Yulei Jiang, PhD, collaborating
with clinical pathologists at Northwestern
University and the University of Chicago, have been
developing computer-aided diagnosis (CAD) methods for
prostate cancer in histology images. While most work in
the development of CAD has been aimed at helping radiologists
diagnose cancers more accurately, their work
aims at helping pathologists diagnose prostate cancer
more accurately. They have developed a computer technique
to recognize adenocarcinoma of the prostate in histology
sections processed with an immunohistochemistry
staining technique known as a triple antibody cocktail
(AMACR/p63/34_E12). This staining technique labels
malignant prostate epithelial cells red, and benign basal
cells brown, making it easier for pathologists to identify
the presence of malignant epithelial cells and the presence
of benign basal cells crucial for the diagnosis of
prostate adenocarcinoma. The computer technique further
simplifies this detection task and automatically recognizes
the presence of red and brown colors corresponding
to these diagnostic features. In a blinded study of
more than 300 images, they report sensitivity of the computer
technique between 85% and 88%, and specificity
between 89% and 97%, depending on the diagnostic subcategories
of the cases. Further development of the
39

technique is expected to improve its performance and
further testing with routine clinical cases is planned.
They are currently also working on techniques to analyze
the standard H&E image based on the color and
morphology information with the goal of automatically
identifying prostate cancer in histology images.
Image & Technology
Evaluation
ACritical Analysis of the Clinical Studies Measuring
the Effectiveness of Computer-Aided Detection in
Screening Mammography
There have been ten clinical studies on CADe used in
screening mammography. The results have been mixed.
Robert M. Nishikawa, PhD, and Lorenzo Pesce, PhD,
have critically evaluated the studies to determine why
discrepancies exist. They examined the different
methodologies used in the eight studies to identify
sources of bias. Two different methods were used to
measure the effectiveness of CADe. One was to compare
the cancer detection rate between two time periods
before and after CADe was implemented. The second
was for a given radiologist determine how many extra
cancers are detected because CADe was used. The two
different methods can lead to different results, with the
differences due in part to differences in biases. There are
three large sources of variation that makes it difficult to
measure the effectiveness of CADe. The first is intrareader
variability; the second inter-reader variability;
and the third is the variation in the number of women
presenting with cancer at screening. In spite of these
sources of variability, using the six studies without significant
biases, CADe can decrease the missed cancer
rate by 9.7% with an increase in the recall rate of 13%.
Measuring the clinical effectiveness of CADe in screening
is difficult with a number of subtleties that are often
overlooked by investigators. While each individual
study is small (statistically speaking), the aggregate of
the studies indicate that the performance of CADe is
comparable to double reading by two radiologists. The
researchers are now preparing a meta-analysis of CADe
in screening mammography. While there are contradictory
results from the different clinical study, most differences
are result of methodological shortcomings and
reader and patient variability. Since radiologists are most
often the ones designing and conducting the studies, it is
important for them to understand how to perform the
studies properly.
Potential Effect of Different Radiologist Reporting
Methods on Studies Showing Benefit of CAD
Karla Horsch, PhD, Maryellen Giger, PhD, and Charles
E. Metz, PhD investigated the effect of different reporting
methods and performance measures on the assessment of
the benefit of computer-aided diagnosis (CAD) in characterizing
malignant and benign breast lesions on mammography
and sonography. In a previous study, ten
observers provided three types of reporting data (probability
of malignancy [PM] estimates, Breast Imaging
Reporting and Data System [BI-RADS] ratings, and biopsy
decisions), both without and with CAD. The current
study compares alternative performance measures computed
from the three types of reporting data. The area
under the receiver operating characteristic curve (AUC)
was computed from both the PM estimates and the BI-
RADS ratings, whereas sensitivity and specificity were
computed from all three data types. Sensitivity and specificity
values calculated from either the PM estimates or
the BI-RADS ratings were determined by setting both
constant and user-dependent thresholds. Student’s t-tests
were used to evaluate the statistical significance of the
differences in the performance measures without and
with CAD. The average AUC values of the ten observers
calculated from either PM estimates or BI-RADS ratings
demonstrated statistically significant improvements in
performance with CAD, increasing from 0.87 to 0.92 or
0.93, respectively. However, the statistical significance of
improvements in sensitivity or specificity depended on
the type of reporting data used. Use of different types of
reporting data in the computation of sensitivity and
specificity may result in different conclusions concerning
the benefit of CAD. Meaningful determination of sensitivity
and specificity from PM estimates require the use
of user-dependent thresholds.
Quality Assurance for Expert-Defined “Truth” in CT
Nodule Detection
Samuel G. Armato III, PhD, and Heber MacMahon, MD,
are the local Principal Investigators of the NCI-sponsored
Lung Image Database Consortium (LIDC), which is
developing a public database of thoracic computed
tomography (CT) scans as a medical imaging research
resource. A key aspect of this database is the annotations
assigned by LIDC radiologists to indicate lung nodules in
the scans. Computer-aided diagnostic (CAD) systems
fundamentally require the opinions of expert human
observers to establish “truth” for algorithm development,
training, and testing. The integrity of this “truth,” however,
must be established before investigators commit to
this “gold standard” as the basis for their research. The
purpose of this study was to develop a quality assurance
(QA) model as an integral component of the “truth” collection
process concerning the location and spatial extent
of lung nodules observed on CT in the LIDC public database.
One hundred CT scans were interpreted by four
radiologists through a two-phase process. For the first of
these reads (the “blinded read phase”), radiologists independently
identified and annotated lesions, assigning
each to one of three categories: “nodule > 3mm,” “nodule
< 3mm,” or “non-nodule > 3mm.”
40

For the second read (the “unblinded read phase”), the
same radiologists independently evaluated the same CT
scans but with all of the annotations from the previously
performed blinded reads presented; each radiologist
could add marks, edit or delete their own marks, change
the lesion category of their own marks, or leave their
marks unchanged. The post-unblinded-read set of marks
was grouped into discrete nodules and subjected to the
QA process, which consisted of (1) identification of
potential errors introduced during the complete image
annotation process (such as two marks on what appears
to be a single lesion or an incomplete nodule contour)
and (2) correction of those errors. Seven categories of
potential error were defined; any nodule with a mark
that satisfied the criterion for one of these categories was
referred to the radiologist who assigned that mark for
either correction or confirmation that the mark was
intentional. A total of 105 QA issues were identified
across 45 (45.0%) of the 100 CT scans. Radiologist review
resulted in modifications to 101 (96.2%) of these potential
errors. Twenty-one lesions erroneously marked as
lung nodules after the unblinded reads had this designation
removed through the QA process (See Figure 34).
Figure 34
A lesion marked as a “nodule
> 3 mm” by three radiologists
with no mark at all
assigned by the fourth radiologist
(category 6 error).
As a result of the QA
process, the fourth radiologist
indicated that an error
had been made and also
marked this lesion as a
“nodule > 3 mm.”
Evaluation of Lesion Boundary and Area Definitions
Samuel G. Armato III, PhD, and colleagues have been
investigating the potential impact of inconsistent
approaches to lesion size quantification. Measurement of
the size of anatomic regions of interest in medical
images is used to diagnose disease, track growth, and
evaluate response to therapy. The discrete nature of
medical images allows for both continuous and discrete
definitions of region boundary. These definitions may, in
turn, support several methods of area calculation that
give substantially different quantitative values. This
study investigated the possible impact of applying
inconsistent definitions of region boundary and area to
medical images for the purpose of computerized patient
analysis by evaluating several boundary definitions
(e.g., continuous polygon, internal discrete, and external
discrete) and area calculation methods (pixel counting
and Green’s Theorem). Region boundary definitions and
area calculation methods were categorized as native to
discrete space or native to continuous space.
These methods were applied to two separate databases:
the Lung Image Database Consortium database of lung
nodules (with region boundaries confined to discrete
pixel space) and a database of adrenal gland outlines
(with region boundaries defined in continuous space).
Average percent differences in area on the order of 20%
were found among the different methods applied. These
results support the idea that inconsistent application of
region boundary definition and area calculation may substantially
impact measurement accuracy. Further, these
differences also support the importance of reporting
boundary definition and area calculation methods in
written protocols and published manuscripts.
Effect of Normal Breast Structure on Cancer Detection –
Preliminary study
Robert M. Nishikawa, PhD, and Ingrid Reiser, PhD, are
studying the effects of appearance of normal breast anatomy
on the detection of breast cancer. It is well known by
radiologists that the superposition of normal breast tissue
can obscure cancers (leading to a false negative) and can
cause what appears as a cancer but in fact it is not (false
positive). This is a fundamental limitation of mammography:
the 3D breast is projected on to a 2D image. Breast
tomosynthesis is an emerging technique that can produce
a stack of 2D slices through the breast reducing the
amount of tissue superposition. However, unlike CT,
tomosynthesis scans the breast over only a small arc and
not 360 degrees. As a result, there is still some residual
tissue overlap. They conducted a study to quantify how
much the breast structure is reduced in a tomosynthesis
reconstructed slice compared to a conventional mammogram.
There are two parameters that characterize the
appearance of the breast structure. The beta parameter is
a measure of the texture – the higher the beta the more
pronounced the texture, which increases the chances of a
false negative or false positive interpretation. The other
parameter is the magnitude of the texture – higher magnitude
the more likely the radiologist will make an error.
Compared to mammography, beta is reduced from 3.06 to
2.87 (p

efficiently. However, fundamental differences in methodology
and interpretation between the two methods warrant
careful analysis of both. Their work has shown that
when applied under equal conditions and under identical
assumptions, the Bayesian method generates similar
results as the MLE in producing ROC curve fits.
Modifying the prior assumptions used in the Bayesian
method causes modifications in the ROC curve fits. In
particular, a specific prior assumption that may be considered
more reasonable than the corresponding
assumption of the MLE results in small differences in
most ROC curve fits compared with the MLE, but produces
apparently more reasonable curve fits in "degenerate"
ROC curves that the MLE produces mathematically
perfect but not necessarily plausible fits because the data
do not contain enough information to discern the height
of the ROC curve under the method of MLE. More work
on the analysis and application of Bayesian ROC analysis
will continue.
Reliable and Computationally Efficient Maximum-
Likelihood Estimation of “Proper” Binormal ROC
Curves
Estimation of ROC curves and their associated indices
from experimental data can be problematic, especially in
multireader, multicase (MRMC) observer studies.
Wilcoxon estimates of area under the curve (AUC) can
be strongly biased with categorical data, whereas the
conventional binormal ROC curve-fitting model may
produce unrealistic fits. The “proper” binormal model
(PBM) was introduced by Metz and Pan to provide
acceptable fits for both sturdy and problematic datasets,
but other investigators found that its first software
implementation was numerically unstable in some situations.
Therefore, Lorenzo Pesce, PhD, and Charles Metz,
PhD, developed an entirely new algorithm to implement
the PBM and tested it extensively on a broad variety of
simulated and real datasets. The new algorithm never
failed to converge and produced good fits for all of the
several million datasets on which it was tested. For all
but the most problematic datasets, the algorithm
also produced very good estimates of AUC standard
error. The AUC estimates compared well with Wilcoxon
estimates for continuously distributed data and are
expected to be superior for categorical data. Windows,
Linux, and Apple Macintosh OS X versions of the new
algorithm are available online at http://xray.bsd.uchicago.edu/krl/.
Generalization of ROC Analysis to Classification Tasks
that Involve More than Two Classes
Areceiver operating characteristic (ROC) curve gives a
complete description of an observer's performance in a
two-class classification task. When the observer must distinguish
among three classes, his/her/its performance
must, in general, be described by a five-dimensional surface
in a six-dimensional ROC space. Because of this
increase in complexity, many researchers have proposed
restricted observer models whose performance can be
described with two-dimensional surfaces in three-dimensional
ROC spaces. Darrin Edwards, PhD, and Charles
Metz, PhD, analyzed four such restricted models and
showed that the observer which achieves optimal performance
with respect to the chosen three-dimensional
ROC space is in fact a restricted form of the so-called
ideal observer. The ideal observer is the observer that
obtains optimal performance in a general (unrestricted)
classification task. There are two well-known methods
for showing that the ideal observer is optimal: the
Neyman-Pearson criterion and maximization of expected
utility. During Drs. Edwards' and Metz's consideration of
the four restricted cases just mentioned, they discovered
that these two methods do not merely yield the same
observer, but are in fact completely equivalent in a mathematical
sense. This result has allowed them to prove
that, for a wide variety of observers which achieve optimal
performance with respect to a restricted ROC surface,
the two-dimensional surface in three-dimensional
ROC space that is determined by either method provides
a complete description of observer performance in those
restricted three-class classification tasks.
Paul C. Hodges Alumni Society
The Hodges Society had a solid, productive and effective
year. Our talented departmental alumni continue to
impress us with their skills and reach. The newest members
of the Society were inducted informally along with
other residents, fellows and staff at the annual June
departmental celebration. The organization continues to
provide funding for both for research efforts and for
educational materials, and is also adding new ideas to
achieve the department’s mission highlighted on our
department’s updated website. Efforts continue to largely
focus on training those who will provide not only excellence
in patient care, but contribute to education and
research.
42

Our alums remain in contact though our successful quarterly
newsletters that are disseminated electronically. The
newsletters have been expanded in size and number of
features, increasing the number of images. Society contact
lists continue to be improved and “lost” alums are
popping up as more information becomes available. Our
vision of an interactive and alum controlled website
where messaging can be shared through secure channels
moved closer this year as the larger departmental website
become more of a reality.
New initiatives in the year are Alumni funding supporting
the preparation and travel expenses incurred by
those in training. Monies were set aside to again make
research and conference presentation of our departmental
efforts as easy as possible. The board was enlarged by
five members and we are pleased to have introduced
new leadership which augments our reach nationally and
internationally.
The Society continues to support incoming new housestaff
with a gift of a basic radiology text, one that forms
the backbone of a six month course that covers fundamental
core knowledge on film interpretation and techniques
on presentation. The required physics texts are
also provided (loaned) to facilitate our residents having
the best materials available. We can report our residents
continue to score among the highest in the country. A
new book fund was approved to obtain pertinent texts
for the Medical Physics program to function in a similar
fashion to this program.
Research funding remains a backbone activity in the
form of internal grants which are decided in the fall prior
to the annual RSNA meeting. The grants were increased
to $5000 (from $4000) and these seed grants have been
helpful in initiating research that has been not only been
presented and published, but has also fostered an evolution
to larger projects downstream.
This retrospective study included ten consecutive patients
who had both carotid CTA and brain MRI. The carotid
calcium volume on CTA was measured using a regionbased
thresholding method (See Figures 35 and 36). The
intraobserver variability was evaluated. The mean ADC
value of cerebral white matter on MRI was computed
(See Figure 37).
Five patients had at least one visible carotid calcium
plaque on CTA and concurrent small vessel ischemic disease
on MRI. Among the five patients with no carotid
plaque, two had small vessel ischemic disease, and the
remaining three had normal-appearing white matter. The
mean carotid calcium volume ranged from 0.035 to 0.212
cm. The mean intraobserver variability of the calcium
volume measurement was 4.2% for an individual plaque
and 2.9% for the plaques combined. The mean ADC value
of white matter tended to increase in patients with small
vessel ischemic disease.
With this preliminary study, the algorithms of the measurements
of the ADC value of white matter and the volume
of the carotid calcium have been established. Future
investigation will explore associations between the ADC
values and the calcium volume and the risk
Axial MIP carotid CT
angiogram shows contouring
of a calcium plaque (yellow
color) in the right internal
carotid artery with a regionbased
thresholding method.
Figure 35
The Hodges Society presented two Paul C. Hodges
Research Awards in 2007, in which one was a full recipient
and another was shared. Respectively, the winners
were Shadi Othman, PhD, working with mentor Brian
Roman, PhD, and Cheng Hong, MD, PhD, and Fang Zhu,
MD, PhD, both fellows in the Neuroradiology section
advised by Dr. Jordan Rosenblum. Dr. Hong has summarized
the latter project below.
Relationship between Carotid Artery Calcification on
CT and Small Vessel Ischemic Disease on Diffusion-
Weighted MRI: A Quantitative Analysis
The relationship of presence of carotid artery calcification
to future stroke is unknown. Severity of white matter
ischemic change has been correlated with future stroke.
The objective of this research was to determine whether
the carotid calcium quantity could be a predictor of
stroke by examining the correlation between carotid
artery calcification and small vessel ischemic disease.
Figure 36
Histogram showing distribution of CT attenuation of the
calcium plaque voxels.
43

factors upon an increase in sample size to achieve a statistical
power. The ultimate clinical significance of this
research could be very great. Upon the success of this
research, the data could be helpful in future clinical trials
and strategies for prevention of stroke. Information
gained from this research would also reinforce the need
for imaging in the risk assessment and reflect a further
evolution to global risk assessment strategy for systemic
diseases.
A special thanks to the Paul C. Hodges Alumni Society
for its generosity and interest in funding this project,
which has provided great support and encouragement
for both my colleagues and me.
Society Members: Please remember to send any address or
email changes to Thelma Wright, University of Chicago,
Department of Radiology, 5841 S. Maryland Avenue,
MC2026, Chicago, IL 60637.
You may also send changes via fax to 773-702-2523 or email
at pchodges@radiology.bsd.uchicago.edu. Society business
questions may be directed to Dr. Christopher Straus at the
address listed above, or via email tot cstraus@uchicago.edu.
Donations may be made using the enclosed envelope.
Figure 37
ADC map (Left): A total of 6 ROIs were symmetrically placed on
the periventricular white matter to compute the ADC values;
Diffusion weighted image (Right): an acute stroke in the right
posterior parietal lobe.
Educational Programs
Fellowship Programs
Abdominal Imaging
The Abdominal Imaging Fellowship is a one-year comprehensive
fellowship comprising clinical, teaching, and
research activity in all aspects of abdominal imaging
using all available modalities, including dedicated MRI
rotations. The clinical experience combines a regional
population of patients providing a strong base of emergency
and primary presentation exams with a strong outpatient
and inpatient tertiary referral center providing a
high volume of oncology, surgery, gastroenterology,
transplantation and emergency referrals. CT focuses on
problem solving, detailed and tailored examinations,
such as multiphase hepatic CT, renal and adrenal mass
characterization and negative contrast luminal examinations.
Fellows will learn to perform and interpret 3D CT
angiography, CT enterography, CT urography, CT
colonography and other cutting-edge diagnostic studies.
The MRI experience includes dedicated liver, pancreas,
adrenal, renal and pelvic imaging including MR
angiography, cholangiography, prostate MRI, MR
enterography and fetal MRI. This rotation also affords
the fellow the opportunity to participate in non-abdominal
applications if desired.
Ultrasound offers the gamut of abdominal studies, small
parts ultrasound, and percutaneous biopsies, as well as
color and spectral Doppler vascular and transplant studies.
Fellows have the opportunity to gain additional
expertise in vascular ultrasound and ob-gyn ultrasound
as needed. Fellows can participate in a wide gamut of
gastrointestinal and genitourinary examinations.
Our cutting edge equipment includes six superconducting
magnets, with a second 3.0T magnet to be installed
this year, six multislice helical CT scanners, including 64
slice capability (and a 256 slice scanner to be installed
this year), an all Acuson/Siemens ultrasound area and
digital fluoroscopy.
Fellows participate in resident teaching and are encouraged
to participate in research and publication by either
joining ongoing projects or initiating a new project with a
faculty mentor and dedicated academic time.
44

Musculoskeletal Fellowship
The Musculoskeletal Fellowship is a one year program
that began July 1, 1999; thus far, seven individuals have
completed the program since inception. Prerequisites for
the program include completion of a residency in
Radiology as well as selective criteria, such as an interest
in both clinical and academic MSK radiology. Good letters
of reference from the residency program director
and other faculty members are essential. Finally a personal
interview day with the candidate is mandatory.
The section has successfully recruited top residents from
our own radiology residency programs as well as from
other nationally recognized programs such as Standford,
the Brigham, and Emory University.
The goal of the program is to train a radiologist in all
aspects of clinical MSK radiology as well as to promote
academic radiology interest. Each fellow participates in
case reading sessions four days a week with the fifth
day for academic interest. Participation is expected in
the weekly orthopedic oncology and weekly rheumatology
conferences. Formal conferences in musculoskeletal
are offered every week and there is a weekly case conference
in the section. Fellows are expected to prepare
conferences for residents, and to have projects leading to
publications. The fellow is also expected to perform procedures
including biopsies, arthrograms, and RFAs, as
well as supervise and train radiology residents.
Vascular and Interventional Radiology Fellowship
The Vascular and Interventional Radiology Fellowship is
a one-year comprehensive program, the goal of which is
to provide in-depth clinical, teaching and research experience
in all aspects of both adult and pediatric angiography
and interventional procedures. Fellows perform
Interventional Radiology procedures and provide clinical
care of patients under the daily supervision of full-time
faculty members. In addition to reading CT and MR
angiographic studies, fellows perform vascular and nonvascular
procedures using sonographic, fluoroscopic and
CT guidance. Education of fellows is performed through
a combination of clinical experience in the Interventional
Radiology suites, didactic teaching during film interpretation
procedure review sessions, attendance at multidisciplinary
conferences, attendance of monthly meetings
with review of morbidity and mortality cases, and attendance
of lectures provided by the faculty.
Essential to their educational development, the Vascular
and Interventional Radiology fellows are central components
in the day-to-day clinical management of the VIR
section at the University of Chicago. The VIR section is
unique in the Radiology department in that it is entirely
a clinical service, performing patient consultations, history
taking, physical examinations, inpatient rounds,
patient consents, physician consultations, procedures,
post-procedure care and patient follow-up. The fellows
are not just trainees, but represent an integral part of this
clinical management, communicating with referring
physicians, coordinating patients through the section,
overseeing patient care, and performing clinical rounds
and follow-up. The fellows are expected to participate
actively in ongoing scholarly projects under the supervision
of the faculty members. This work should result in
publication in refereed or educational journals and presentation
at institutional, regional or national scientific
meetings in accordance with ACGME recommendations.
In addition to these clinical responsibilities, the fellows
obtain in-depth teaching and research experience by
preparing and providing resident conferences and directly
participating in quality assurance, educational, and
research projects ongoing within the section.
The program is accredited by the ACGME for three positions
per year and, depending on the year, offers either
two or three of these positions in the annual match. The
section has hired two fellows for 2008-9 and two fellows
for 2009-10.
Diagnostic Radiology
Residency
The Department of Radiology’s mission is to provide outstanding
training in diagnostic radiology which will prepare
residents for future careers in academic radiology or
full-time clinical practice
Our basic four-year residency training program, supported
by clinical and research-oriented fellowships, is well
balanced and offers excellent preparation for a broad
variety of career pathways including academic careers,
general radiology and subspecialty practice in both academic
and private practice.
The residency program has increased in size for each of
the past three years and will reach our new full complement
of 28 residents for the 2007-2008 academic year. The
increase has allowed us to provide additional rotations in
cardiac imaging, mammography and PET imaging
among others. It will also allow us the flexibility to offer
new programs for incoming residents with research interest.
This past year has been very successful with numerous
resident publications and honors:
45

Presentations
Buckle, CE, Castillo, M:Use of DWI to Evaluate the
Initial Response of Progressive Multifocal
Leukoencephalopathy to Highly Active Antiretroviral
Therapy: Early Experience Presented at ASNR 06/2008
Langerman A, Comstock R, Konda S, Abramovich A,
Kasza K, Vokes E, Stenson K. “Neck dissection planning
based on post-chemoradiation computed tomography in
head and neck cancer patients” American Head and
Neck Society 7th International Conference on Head and
Neck Cancer, July 2008, San Francisco, CA (Poster,
Submitted for publication)
Awards
R. Evan Nichols, MD
Weiss Hospital Award (Outstanding Clinical Work at
Weiss Hospital), 2008
Christopher Buckle, MD
Neuroradiology Award (Outstanding Performance in
Neuroradiology), 2008
Danny Cheng, MD
Chien Tai Lu Award (Outstanding Clinical Work in
Vascular Interventional Radiology), 2008
Golden Tip Award (Outstanding Performance in
Gastrointestinal Radiology), 2008
Nicholas Krause, MD
Golden Tip Award (Outstanding Performance in
Gastrointestinal Radiology), 2008
In January 2008, Gregory Henkle and Sheela Konda
were chosen as co-chief residents and will serve until
January 2009.
Incoming Residents
We are pleased to welcome eight new residents for the
2008-2009 academic year in the hope that they will discover
the unique program of study that our department
has to offer. We are confident that they will make excellent
residents.
These residents began their training on July 1, 2008:
Parag Amin, MD, completed his medical education at
the University of Virginia and his PGY1 at Cornell
University;
Colin Brown, MD, completed his medical education at
the University of Iowa and his PGY1 at Carraway
Methodist Medical Center;
Andrew Hall, MD, completed his medical education at
the University of Pittsburgh and his PGY1 at the
University of Chicago;
Rony Kampalath, MD, completed his medical education
at the University of Texas and his PGY1 at the University
of Chicago;
Aswin Krishnamoorthy, MD, completed his medical education
at the University of Illinois and his PGY1 at Weiss
Hospital;
Avnit Kapur, MD, completed his medical education at the
University of Illinois and his PGY1 at the University of
Chicago;
Valeria Potigailo, MD, completed her medical education
at Johns Hopkins and her PGY1 at West Suburban
Medical Center;
Joseph Yacoub, MD, completed his medical education at
Wake Forest University and his PGY1 at the University of
Chicago.
Departing Residents
The residency program has had yet another successful
year. Seven residents graduated, with seven pursing
fellowships and three continuing at the University of
Chicago:
Joseph Carabetta, MD will begin a Gastrointestinal /
Genitourinary (GI/GU) MRI fellowship at Northwestern
University;
Rodney Corby, MD will begin an MSK fellowship at
University of Michigan;
Philip Kurzman, MD will begin an Interventional
Vascular fellowship at Yale University;
Rajshri Shah, MD will remain at the University of
Chicago to become an Instructor in Breast Imaging and
MSK;
Steven Thiel, MD will remain at the University of
Chicago to become an Instructor in Breast Imaging and
MSK;
Carl Valentin, MD will begin a Body fellowship at Johns
Hopkins in Baltimore;
Ivica Vucic, MD will remain at the University of Chicago
to begin an Interventional Vascular fellowship.
46

Medical Student
Education
Graduate Programs in
Medical Physics
Medical student education has undergone some significant
changes recently. Building on the momentum of the
changes in the Human morphology course made last
year their involvement in the first two years of medical
school increases again. A large improvement has been
noted, including in medical student boards part I scores.
The program will now begin to include key imaging in
the spring neuro anatomy course and make measured
progress in incorporating imaging into the key MS II
course Clinical Pathophysiology and Treatment. This
will mean that nearly every course the student takes in
their first two years will have radiology imaging as part
of the content, much of it taught by radiologists; students
will also have access and exposure to radiology
staff throughout this time.
We continue to provide outreach in the form of small
research grants which involve students through the
Radiology Research and Opportunity Program (RROP).
This makes smaller funds available for projects which
involve students on a short turn around basis (usually
two days) and with a short simple one page application.
This was developed to ensure that money was available
for equipment as the need arose and not allow the shorter
windows of opportunity most students allow to close
when an interest is expressed.
We have since restructured our senior elective and have
received positive feedback from not only our medical
students but also students from other institutions. Our
faculty has created dedicated lectures which are specific
to the student’s needs and interests. Students will spend
time each week in a different subspecialties observing
and learning. Residents are now playing a larger role by
serving as mentors that assist the student with a case
study which they will present.
As the year ended the discussion and next major change
was discussed and adopted. This includes the restructuring
of the senior elective to one which has equivalent
flexibility but also provides more structure and role for
our senior students while on this elective tract. The
changes will include dedicated lectures for students,
computer access and teaching files and a focus that will
stress the importance of radiology imaging in overall
patient care. These new changes will be in development
over the following summer and implemented towards
the start of the new year. These major changes continue
to demonstrate the need and augment the core experiences
which help motivate many who choose our specialty
as a career but also supplement our mission of
additionally steering many into academics and leaving
others who choose other fields of study to understand
and use our resources effectively.
The Graduate Programs in Medical Physics are under the
Committee on Medical Physics at the University of
Chicago and offers research training at three levels that
lead to the Master of Science degree and to the Doctor of
Philosophy degree, and provide postdoctoral training.
Faculty on the Committee come from the Departments of
Radiology and Radiation & Cellular Oncology. Maryellen
Giger, PhD, is Chair of the Committee and represents its
faculty within the BSD Basic Science Chairs. Primary
areas of research interest by the program faculty include
the Physics of Diagnostic Radiology, Physics of Nuclear
Medicine/Molecular Imaging, Physics of Magnetic
Resonance Imaging, and Physics of Radiation Therapy.
Unique features of this CAMPEP-Accredited program are
the faculty’s focused effort on research in medical imaging
and on the training of high-level medical physicists.
We have 30 pre-doctoral students and six post-doctoral
trainees. A continuing NIH training grant funds four predoctoral
students and two post-doctoral fellows in the
training of medical physics. Additional funding has been
obtained from the U.S. Army, the BSD, the UCCRC and
the Lawrence Lanzl Fund. Currently 10 of our 30 students
have been awarded US Army Pre-doctoral fellowships for
their dissertation research.
Current post doctoral fellows are:
• Hee Jong Kim, PhD, from Yonsei University, who is
working under the supervision of Chien-Min Kao, PhD,
and conducting research on the early digitization of the
PET signal and its greater advantages than the typical
PET signal processing method. The multi-threshold
method is one of the ways to achieve this goal by
applying the different threshold to the signal from the
photo detector. With the guidance of Dr. Kao, they are
developing the multi-threshold discriminator board in
47

collaboration with the Physics department's electronics
group to implement the idea. The various tests on the
board show promise and the efficient readout scheme
for the digitized signal is being investigated in collaboration
with Fermi lab and Physics Department.
Silicon Photomultiplier (SiPM) is a promising photodetector
as a substitute to the long lasting
Photomultiplier Tube (PMT) in PET detector in terms
of compactness and low operation voltage. SiPM's
insensitivity to magnetic fields is also an attractive
characteristics for a PET/MRI development. A PET
detector design using the SiPM as a photo-device is
under study.
• Ji Li, PhD, from Renseselaer Polytechnic is working
under the supervision of Bulent Aydogan, PhD, conducting
research on developing a novel CT contrast
agent. This field of research has drawn great attention
in recent years. Successful completion of this project
could potentially change the landmarks of medical
imaging. This is a joint research project between the
University of Chicago and the Argonne National
Laboratory. Our ANL User Proposal was accepted by
the ANL review committee in September 2008 with an
“Excellent Rating”. Several preliminary experiments
have been conducted with promising results.
Current post doctoral scholars are:
• Michael Chinander, PhD, from the University of
Chicago is working under the supervision of
Maryellen Giger, PhD, conducting research on noninvasive
measurement of the temporal wear of total
hip arthoplasty components from radiographic
images. He also investigates the assessment of bone
quality and osteoporosis using radiographic texture
analysis of heel bone densitometry images. Mike is
also conducting research in the radiographic risk
assessment of slipped capital femoral epiphysis
(SCFE) using mechanical analysis of hip joint force
components.
• Lara Leoni, PhD, from the University of Illinois at
Chicago, works under the supervision of Brian
Roman, PhD, conducting research on functional magnetic
resonance imaging of pancreatic islets. Human
pancreatic islet transplantation is currently being performed
around the world to cure diabetes. Lara has
demonstrated that MRI can be used to image pancreatic
islets which have been activated by glucose stimulation
and can be detected on a T1-weighed MR
image. She has applied this approach to rodent and
human islets in-vitro and is currently applying this
technique in in-vivo rodent models of transplanted
islets.
• Margo Levine, PhD, from Northwestern University, is
working under the supervision of Xiaochuan Pan,
PhD, conducting research on addressing the issue of
data redundancy in image reconstruction algorithms
through the derivation and implementation of consistency
conditions for CT data.
• Guihua Zhai, PhD, from the University of North
Carolina at Chapel Hill, is working under the supervision
of Jia-Hong Gao, PhD, conducting research on
understanding the physiological mechanism of the
brain function in the actions of glucose and alcohol.
Cerebral blood flow based brain maps will be generated
using functional MRI and the results will be compared
with the neuronal activities in the hypothalamic
region and other parts of the brain.
Current pre-doctoral students are:
Michael Altman (Advisor: Pelizzari), Sanaz Arkani-
Jansen (Advisors: Karczmar and Newstead), Neha
Bhooshan (Advisor: Giger), Junguo Bian (Advisor: Pan),
Jonathan Bryant (Advisor: Halpern), Seungryong Cho
(Advisors: Pan and Pelizzari), Neal Corson (Advisor:
Armato), Anita Dhyani (Advisor: Roman), Sean Foxley
(Advisor: Karczmar), Xiao Han (Advisor: Pan), Elizabeth
Hipp (Advisor: Karczmar), Andrew Jamieson (Advisor:
Giger ), Zacariah Labby (Advisor: Aydogan), Beverly Lau
(Advisor: Nishikawa), Qingfei Luo (Advisor: Gao),
Dimple Modgil (Advisor: LaRiviere), Erik Pearson
(Advisors: Pan and Pelizzari), Yahui Peng (Advisor:
Jiang), Payam Seifi (Advisor: Halpern), William
Sensakovic (Advisor: Armato), Robert Tomek (Advisor:
Giger), Philip Vargas (Advisor: LaRiviere), Abbie Wood
(Advisor: Karczmar), Dan Xia (Advisor: Pan), Yading
Yuan (Advisor: Giger ), Richard Zur (Advisor: Jiang).
We expect four new pre-doctoral students to join us in
the autumn of 2008. They are Martin Andrews
(University of Illinois at Chicago), Xia Jiang (Washington
State University), Kevin Little (Taylor University), and
Federico Pindeda (Carnegie-Mellon University).
2007-2008 Graduates
Five students received their PhD’s during the academic
year. They were:
Michalis Aristophanous (Charles Pelizzari, PhD, Advisor)
“Definition of tumor volume from positron emission
tomography for radiation treatment of patients with nonsmall
cell lung cancer.”
Joshua Haslam (John Roeske, PhD, Advisor) “Analysis of
geometric uncertainties in women treated with intensity
modulated whole pelvic radiation therapy for gynecologic
malignancies.”
Martin King (Maryellen Giger, PhD, Advisor) “Featurebased
characterization and image quality optimization of
48

motion-contaminated coronary structures in cardiac CT
images.”
Chisako Muramatsu (Kunio Doi, PhD, Advisor)
“Investigation of similarity measures for selection of
similar images in computer-aided diagnosis of breast
lesions on mammograms.”
Laura Yarusso (Robert Nishikawa, PhD, Advisor) “The
effect of image quality on computer-aided diagnosis in
digitized screen-film and full-field digital mammography.”
Awards received within the past year by current predoctoral
students:
Michael Altman:
• Army Predoctoral Prostate Cancer Research Award,
Department of Defense (2008).
Sanaz (Sunny) Arkani Jansen:
• Radiological Society of North America (RSNA) Trainee
Research Prize for the RSNA Annual Meeting (2007).
Michalis Aristophanous:
• Student Travel Grant Award, SPIE Medical Imaging
Conference (2008).
Neha Bhooshan:
• Young Investigator’s Symposium Finalist, AAPM
(2008).
• Radiological Society of North America (RSNA) Trainee
Research Prize for the RSNA Annual Meeting (2008).
Junguo Bian:
• Army Predoctoral Breast Cancer Research Award,
Department of Defense (2008).
• Student Trainee Award, IEEE NSS-MIC (2008).
Seungryong Cho:
• Student Travel Grant Award, IEEE NSS-MIC (2007).
Sean Foxley:
• Radiological Society of North America (RSNA) Trainee
Research Prize for RSNA (2008).
• Educational Travel Stipend Sixteenth Scientific
Meeting and Exhibition of ISMRM (2008).
Xiao Han:
• Student Travel Grant Award, IEEE NSS-MIC (2007).
• Student Travel Grant Award, IEEE NSS-MIC (2008).
Andrew Jamieson:
• Army Predoctoral Breast Cancer Research Award,
Department of Defense (2008).
• Open Science Grid-International Summer School on
Grid Computing (2007).
Martin King:
• Radiological Society of North America (RSNA) Trainee
Research Prize for RSNA (2007).
Beverly Lau:
• Army Predoctoral Breast Cancer Research Award,
Department of Defense (2007).
• Student Travel Award, MIPS Conference (2007).
• Cum Laude Poster, SPIE (2008).
Dimple Modgil:
• Army Predoctoral Breast Cancer Research Award,
Department of Defense (2008).
Erik Pearson:
• Young Investigator’s Award, AAPM (2008).
Yahui Peng:
• Travel Grant Recipient from the University of Chicago
Women’s Board (2007).
William Sensakovic:
• IEEE Nuclear Sciences Symposium and Medical
Imaging Conference (2008).
• Doolittle-Harrison Fellowship, University of Chicago
(2008)
Abbie Wood:
• ISMRM New Entrant Stipend Award (2007).
Dan Xia:
• Student Travel Award, IEEE Medical Imaging
Conference (2008).
Yading Yuan:
• Women’s Board Travel Award in the Division of the
Biological Sciences, The University of Chicago (2008).
Peer-reviewed journal publications within the past year
by our pre-doctoral students:
M. Altman, B. Vesper, B. Smith, M. Stinauer, C. Pelizzari,
B. Aydogan, J. Radosevich, S. Chmura, J. Roeske:
Characterization and validation of a novel phantom for
three-dimensional in vitro experiments. Medical Physics
(under review) 2008.
M. Aristophanous, B. O’Brien-Penney, M. Martel, C.
Pelizzari: A gaussian mixture model of definition of lung
tumor volumes in positron emission tomography.
Medical Physics 34:4223-4235, 2007.
M. Aristophanous, B. O’ Brien-Penney, C. Pelizzari: The
development and testing of a digital PET phantom for the
evaluation of tumor volume segmentation techniques.
Medical Physics 2008.
49

S. Cho, J. Bian, C. Pelizzari, C-T. Chen, T-C. He, X. Pan:
Region-of-interest image reconstruction in circular conebeam
micro CT. Medical Physics 34:4923-4933, 2007.
S. Cho, D. Xia, C. Pelizzari, X. Pan: Exact reconstruction
of volumetric images in reverse helical cone-beam CT.
Medical Physics 35:3030-3040, 2008.
S. Cho, E. Pearson, X. Pan, C. Pelizzari: Region-of-interest
imaging with intensity-weighting in circular conebeam
CT for image-guided radiation therapy. Medical
Physics (under review) 2008.
S. Foxley, X. Fan, D. Mustafi, C. Haney, M. Zamora, E.
Markiewicz, M. Medved, A. Wood, G. Karczmar:
Sensitivity to tumor micro-vasculature without contrast
agents in high spectral and spatial resolution MR
images. Magnetic Resonance of Medicine (accepted for
publication) 2008.
S. Foxley, X. Fan, S. Jansen, M. Zamora, E. Markiewicz,
H. Al-Ahmadie, G. Karczmar: High spectral and spatial
resolution MRI of age-related changes in murine
prostate. Magnetic Resonance of Medicine 53(17) 4509-
22, 2008.
S. Foxley, X. Fan, D. Mustafi, C. Yang, M. Zamora, M.
Medved, G. Karczmar: Quantitative analysis of water
proton spectral line shape: A novel source of contrast in
MRI. Physics in Medicine and Biology 7:53(17):4509-22,
2008.
S. Jansen, S. Conzen, X. Fan, T. Krausz, M. Zamora, S.
Foxley, J. River, G. Newstead, G. Karczmar: Detection of
in situ mammary cancer in a transgenic mouse model: In
vitro and in vivo MRI studies demonstrate histopathologic
correlation. Physics in Medicine and Biology
7:53(19):5841-93, 2008.
X. Han, D. Xia, E. Sidky, X. Pan: Noise properties of the
discrete finite Hilbert transform (submitted 2008).
X. Han, H. Lui, D. McLean, H. Zeng: Near-infrared auto
fluorescence imaging of cutaneous melanins and human
skin in vivo. Journal of Biomedical Optics (submitted
and revising 2008).
S. Foxley, X. Fan, S. Jansen, M. Zamora, E. Markiewicz,
H. Al-Ahmadie, G. Karczmar: High spectral and spatial
resolution MRI of age-related changes in murine
prostate. Magnetic Resonance of Medicine 53(17) 4509-
22, 2008.
S. Jansen, X. Fan, G. Karczmar, H. Abe, R. Schmidt, G.
Newstead: Differentiation between benign and malignant
breast lesions detected by bilateral dynamic contrast-enhanced
MRI; A sensitivity and specificity study.
Magnetic Resonance of Medicine 59:747-54 2008.
S. Jansen, G. Newstead, H. Abe, A. Shimauchi, R.
Schmidt, G. Karczmar: Pure ductual carcinoma in situ:
Kinetic and morphologic MR characteristics compared
with mammographic appearance and nuclear grade.
Radiology 245:684-91 2008.
S. Jansen, X. Fan, G. Karczmar, H. Abe, R. Schmidt, M.
Giger, G. Newstead: DCEMRI of breast lesions: Is kinetic
analysis equally effective for both mass and non-masslike
enhancement? Medical Physics 35:3102-9 2008.
M. King, M. Giger, K. Suzuki, X. Pan: Feature-based
characterization of motion-contaminated calcified
plaques in cardiac multidetector CT. Medical Physics
34:4860-4875, 2007.
M. King, M. Giger, K. Suzuki, X. Pan: Computerized
assessment of motion-contaminated calcified plaques in
cardiac multidetector CT. Medical Physics 34 (12) 4876-
4889, 2007.
Q. Luo, H-L. Liu, B. Paris, H. Lu, D. Senseman, J-H Gao:
Modeling oxygen effects in tissue preparation neuronal
current MRI. Magnetic Resonance of Medicine 58(2):407-
412 2007.
M. Anatasio, J. Zhang, D. Modgil, P. LaRiviere:
Application of inverse source concepts to photoacoustic
tomography. Inverse Problems 23:S21-35, 2007.
R. Pereira, P. Azevedo-Marques, M. Honda, S. Kinoshita,
R. Engelmann, C. Muramatsu, K. Doi: Usefulness of
texture analysis for computerized classification of breast
lesions on mammograms. Journal of Digital Imaging
20:248-255, 2007.
C. Muramatsu, Q. Li, R. Schmidt, J. Shiraishi, K. Suzuki,
G. Newstead, K. Doi: Determination of subjective similarity
for pairs of masses and pairs of clustered microcalcifications
on mammograms: Comparison of similarity ranking
scores and absolute similarity ratings. Medical
Physics 34:2890-2895, 2007.
Y. Peng, Y. Jiang, S-T. Chuang, X. Yang: Automated
prostate cancer detection system using immunohistochemical
images of the prostate. Medical Physics (under
review).
W. Sensakovic, S. Armato, A. Starkey: Two-dimensional
extrapolation methods for texture analysis of CT scans.
Medical Physics 34 (9):3465-3472 2007.
S. Foxley, S. Mustafi, C. Haney, M. Zamora, E.
Markiewicz, M. Medved, A. Wood, G. Karczmar:
Sensitivity to tumor micro-vasculature without contrast
agents in high spectral and spatial resolution MR images.
Magnetic Resonance in Medicine (in press).
50

L. Yu, D. Xia, Y. Zou, E. Sidky, J. Bian, X. Pan: A
rebinned back projection-filtration algorithm for image
reconstruction in helical cone-beam CT. Physics in
Medicine and Biology 52:5497-5508, 2007.
D. Xia, L. Yu, E. Sidky, Y. Zou, N. Zou, X. Pan: Noise
properties of chord-image reconstruction. IEEE
Transition of Medical Imaging 26:1328-1344, 2007.
D. Xia, S. Cho, Y. Zou, E. Sidky, N. Zou, X. Pan: 3D ROI-
Image reconstruction from cone-beam data. Nuclear
Instruments and Methods in Physics Research Section A
580:866-875, 2007.
X. Pan, D. Xia, H. Halpern: Targeted-ROI imaging in
electron paramagnetic resonance imaging. Journal of
Magnetic Resonance 187:66-77, 2007.
Y. Yuan, M. Giger, H. Li, K. Suzuki, C. Sennett: A dualstage
method for lesion segmentation on digital mammograms.
Medical Physics 34:4180-4193, 2007.
H. Li, M. Giger, Y. Yuan, W. Chen, K. Horch, L. Lan, A.
Jamieson, C. Sennett, S. Jansen: Evaluation of computeraided
diagnosis on a large clinical full-field digital
mammographic dataset. Academic Radiology (in press)
2008.
Y. Yuan, M. Giger, H. Li, C. Sennett: Correlative feature
analysis on FFDM. Medical Physics (accepted 2008).
Proceeding papers within the past year by
our pre-doctoral students:
M. Aristophanous, C. Pelizzari: The evaluation of a
highly automated mixture model based technique for
PET tumor volume segmentation. Proceedings of SPIE,
6914M1, 2008.
J. Bian, X. Pan: 3D ROI imaging with a detector smaller
than the imaged object. Proceedings of IEEE Nuclear
Science Symposium and Medical Imaging Conference,
M19-283, 2007.
X. Zhao, J. Bian, E. Sidky, S. Cho, P. Zhang, X. Pan:
GPU-based 3D cone-beam CT image reconstruction:
Application to micro CT. Proceedings of IEEE Nuclear
Science Symposium and Medical Imaging Conference,
M19-287, 2007.
J. Bian, D. Xia, L. Yu, E. Y. Sidky, and X. Pan: A rebinned
BPF algorithm with a general source trajectory for ROI
imaging. Proceedings of SPIE 2008.
J. Bian, N. Packard, K. Yang, D. Xia, J. Boone, X. Pan:
Non-circular scans and image reconstruction for breast
CT. Proceedings of SPIE 2008.
J. Bian, D. Xia, E. Sidky, X. Pan: A Rebinned back projection-filtration
algorithm for saddle trajectories. IEEE
Nuclear Science Symposium and Medical Imaging
Conference 2008.
S. Cho, E. Sidky, C. Pelizzari, X. Pan: A preliminary investigation
of using prior information for potentially
improving image reconstruction in few-view CT.
Proceedings of SPIE Vol. 6913, 69132C, 2008.
S. Cho, E. Pearson, D. Xia, X. Han, C. Pelizzari, X. Pan: A
preliminary study of intensity-weighted ROI imaging in
cone-beam CT. Proceedings of SPIE, Vol. 6913, 691325,
2008.
S. Cho, D. Xia, C. Pelizzari, X. Pan: Cone-beam CT with a
modified reverse helical trajectory for long object problem.
IEEE Medical Imaging Conference, M18-282, 2007.
S. Jansen (Arkani), T. Paunesku, G. Woloschak, S. Vogt, S.
Conzen, E. Markiewicz, G. Newstead, G. Karczmar: Why
does ductual carcinoma in situ enhance on dynamic contrast
enhanced MR imaging of the breast? Proceedings for
RSNA 2008.
S. Jansen (Arkani), S. Conzen, G. Newstead, M. Zamora,
T. Krausz, G. Karczmar: Do all in situ cancers progress to
invasive disease? A first look at progression of mammary
cancer from in situ to invasive carcinoma in vivo.
Proceedings of Society of Magnetic Resonance in
Medicine 2008.
S. Jansen (Arkani), X. Fan, G. Karczmar, M. Giger, H.
Abe, G. Newstead: Are kinetic parameters diagnostically
useful for breast lesions exhibiting non mass-likeenhancement?
Proceedings of Society for Magnetic
Resonance in Medicine 2008.
M. King, X. Pan, M. Giger: Motion-compensated reconstructions
of calcified coronary plaques in cardiac CT.
Proceedings of SPIE 2007.
M. King, M. Giger, X. Pan: Computer-aided assessment
of cardiac computed tomography images. Proceedings of
SPIE 2007.
M. King, M. Giger, K. Suzuki, X. Pan: Image quality evaluation
of motion-contaminated calcified plaques in cardiac
CT. IEEE Nuclear Science Symposium Medical
Imaging Conference 4:2717-2720 2007.
Z. Rodgers, M. King, M. Giger, M. Vannier, D. Bardo, K.
Suzuki, L. Lan: Computerized assessment of coronary calcified
plaques in CT images of dynamic cardiac phantom.
Proceedings of SPIE 6915, 691521 2008.
M. King, D. Xia, X. Pan M. Vannier, T. Koehler, P. La
Riviere, E. Sidky, M. Giger: Chord-based image reconstruction
from clinical projection data sets. Proceedings of
SPIE 6193, 19387 2008.
B. Lau, I. Reiser, R. Nishikawa: Microcalfication
detectability in tomosynthesis. Proceedings of SPIE 2008.
51

D. Modgil, P. LaRiviere: Implementation and comparison
of reconstruction algorithms for 2D optoacoustic
tomography using linear array. Proceedings of SPIE
Volume 6856 2008.
C. Muramatsu, Q. Li, R. Schmidt, J. Shiraishi, K. Suzuki,
G. Newstead, K. Doi: Determination of subjective and
objective similarity for pairs of masses on mammograms
for selection of similar images. Proceedings of SPIE
Volume 6514, pp. 651411-651419 2007.
D. Xia, S. Cho, X. Pan: Back projection-filtration reconstruction
without invoking a spatially varying weighting
factor. IEEE Medical Image Conference Record, M11-4,
2008.
D. Xia, J. Bian, E. Sidky, C. Pelizzari, X. Pan:
Tomosynthesis with source positions distributed over a
surface, Proceedings of SPIE vol. 6913, pp. 69132A, 2008.
M. King, D. Xia, X. Pan, M. Vannier, T. Kohler, P. La
Riviere, E. Y. Sidky, M. Giger: Chord-based image reconstruction
from clinical projection data. Proceedings of
SPIE vol. 69134G, 2008.
M. Anastasio, D. Xia, X. Pan: Region-of-interest image
reconstruction in x-ray differential phase contrast
tomography. Proceedings of SPIE vol. 6913, pp. 691327,
2008.
D. Xia, S. Cho, X. Pan: Extended reconstructible volume
in reduced saddle scan. IEEE Medical Image Conference
Record, M04-5, 2007.
D. Xia, S. Cho, X. Pan: Image noise properties in circular
sinusoid cone-beam CT. IEEE Medical Image Conference
Record, M13-285, 2007.
D. Xia, S. Cho, X. Pan: Image reconstruction for a
reduced scan in circular sinusoid cone-beam CT.
Proceedings of the 9th International Conference on Fully
3D Image Reconstruction in Radiology and Nuclear
Medicine, 213-216, 2007.
D. Xia, L. Yu, Y. Zou and, X. Pan: An exact rebinningtype
reconstruction algorithm for helical cone beam CT.
Proceedings of SPIE Vol. 6510, pp. 57, 2007.
Y. Yuan, M. Giger, H. Li, C Sennett: Correlative feature
analysis of FFDM images. Proceedings of SPIE, 6915,
69151L, 2008.
Y. Yuan, M. Giger, H. Li, L. Lan, C. Sennett: Identifying
corresponding lesions from CC and MLO views via correlative
feature analysis. IWDM LNCS 5116:323-328,
2008.
H. Li, M. Giger, Y. Yuan, L. Lan, C. Sennett: Performance
of CADx on a large clinical database of FFDM Images.
IWDM LNCS 5116:510-514, 2008.
R. Zur, Y. Jiang, L. Pesce: Noise injection for training artificial
neural networks: A simulation-study comparison
with weight decay (submitted to IEEE Transactions on
Neural Networks, 2008).
Presentations and abstracts within the past year by our
pre-doctoral students
M. Altman, M. Stinaue, S. Chmura, B. Smith, B.
Aydogan, C. Pelizzari, J. Roeske: In vitro optimization
effects on cell survival for single fraction of radiation.
AAPM 2007.
M. Aristophanous, C. Pelizzari: A mixture model based
technique for PET tumor volume segmentation with minimal
user interaction. SPIE Medical Imaging 2008.
N. Bhooshan, M. Giger, W. Chen, S. Jansen, H. Li, L. Lan,
D. Edwards, G. Newstead: CAD on breast cancer subtypes
differentiation. AAPM 2008.
N. Bhooshan, M. Giger, W. Chen, S. Jansen, H. Li, L. Lan,
G. Newstead: Classification of breast carcinoma subtypes
using computer-extracted morphological and kinetic features
in DCE-MRI (abstract 2008).
J. Bian, X. Pan: Investigation of an innovative ROI imaging
approach and its potential to IGRT. AAPM 2007.
J. Bian, N. Packard, K. Yang, D. Xia, J. Boone, X. Pan:
Investigation of image reconstruction in a dedicated,
cone-beam breast CT scanner with innovative scanning
configurations. RSNA 2007.
J. Bian, K. Yang, N. Packard, E. Sidky, J. Boone, X. Pan:
Image reconstruction from sparse data in breast CT.
AAPM 2008.
S. Cho, E. Pearson, C. Pelizzari, X. Pan. Image artifacts
caused by the extra focal spot of an x-ray tube in conebeam
computed tomography. AAPM 2008.
S. Cho, D. Xia, C. Pelizzari, X. Pan. Reverse helical conebeam
CT and its application to image-guided radiation
therapy. RSNA 2007.
S. Foxley, X. Fan, D. Mustafi, C. Haney, M. Zamora, E
Markiewicz, G. Karczmar: Sensitivity to tumor microvasculature
without contrast agents in high spectral and
spatial resolution MR images. RSNA 2008.
S. Foxley, X. Fan, D. Mustafi, C. Haney, M. Zamora, E.
Markiewicz, G. Karczmar: Detection of tumor microvasculature
using high spectral and spatial resolution MR
imaging without the use of contrast agents. RSNA 2008.
C. Haney, C. Pelizzari, S. Foxley, M. Zamora, D. Mustafi,
M. Tretiakova, T-S. Li, X. Fan, G. Karczmar: Validation of
ESPI angiography by image co-registration. ISMRM 2007
52

X. Han, D. Xia, E. Sidky, X. Pan: A preliminary investigation
of the propagation of correlated data noise in the
finite Hilbert transform. SPIE Medical Imaging 2008.
X. Han, D. Xia, E. Sidky, X. Pan: Noise properties of the
discrete finite Hilbert transform. IEEE Medical Imaging
Conference 2008.
X. Han, D. Xia, E. Sidky, X. Pan: Noise properties of
Hilbert transforms. IEEE Medical Imaging Conference
2007.
X. Han, S. Cho, W-X. Song, T-C He, X. Pan: Micro-CT
imaging and quantitative characterization of bone morphogenetic
protein regulated differentiation of mesenchymal
stem cells. AAPM 2007.
E. Hipp, N. Bhooshan, M. Giger, S. Jansen, H. Li, G.
Newstead: Preliminary analysis of morphological features
from T1 and T2 MR images in the diagnosis of
breast cancer. AAPM 2008.
Jamieson, M. Giger, M. Wilde, L. Pesce. I. Foster: Gridcomputing
for optimization of CAD. AAPM 2008.
M. King, X.Pan, M. Giger: Motion-compensated reconstructions
of calcified coronary plaques in cardiac CT.
SPIE Medical Imaging 2007.
M. King, M. Giger, X. Pan: Computer-aided assessment
of cardiac computed tomography images. SPIE Medical
Imaging, 2007.
T. Wu, Z. Labby, K. Yenice: Commissioning and validation
of the brain lab Monte Carlo dose calculation algorithm.
AAPM 2008.
B. Lau, I. Reiser, R. Nishikawa: Microcalfication
detectability in tomosynthesis. SPIE Medical Imaging
2008.
B. Lau, I. Reiser, R. Nishikawa: The effect of variable
exposure distribution on microcalcification detectability
in tomosynthesis. AAPM 2008.
B. Lau, I. Reiser, R. Nishikawa: Microcalfication
detectability in tomosynthesis. NIBIB Training Grantees
Meeting 2008.
C. Muramatsu, Q. Li, R. Schmidt, J. Shiraishi, K. Suzuki,
G. Newstead, K. Doi: Investigation of similarity measures
for selection of similar images for breast lesions on
mammograms. AAPM 2007.
C. Muramatsu, R. Schmidt, Q. Li, J. Shiraishi, G.
Newstead, K. Doi: Determination of similarity measures
for pairs of masses by use of BI-RADS lexicons and
images features. RNSA 2007.
E. Pearson, S. Cho, X. Pan, C. Pelizzari: Region of interest
imaging in CBCT for radiation therapy. AAPM 2008
E. Pearson, S. Cho, X. Pan, C. Pelizzari: Dose reduction in
IBCT via intensity weighted region of interest imaging.
AAPM 2008.
E. Pearson, S. Cho, X. Pan, C. Pelizzari: Intensity weighted
region-of-interest imaging in cone-beam CT for radiation
therapy. NIBIB Training Grantees Meeting.
E. Pearson, S. Cho, X. Pan, C. Pelizzari: Region-of-interest
imaging for cone-beam CT in radiation therapy. Varian
Research Partners Symposium 2008.
P. Seifi, B. Epel, S. Sundramoorthy, C. Mailer, H. Halpern:
Multiple stepped magnetic field technique applied to
enhance the resolution of electron spin echo oxygen
imaging (ESEOI) at 250MHz. AAPM 2008.
P. Seifi, B. Epel, C. Mailer, H. Halpern: Simulation of time
domain EPR imaging at 250MHz and applications to high
resolution multiple B scheme in electron spin echo oxygen
imaging. Rocky Mountain Conference on Analytical
Chemistry 2008.
A. Wood, H. Al-Hallaq, J. Bian: Accounting for tissue heterogeneities
in head and neck IMRT plans increases planning
target volume and spinal cord doses. AAPM 2008.
A. Wood, M. Medved, S. Foxley, G. Karczmar: Detection
of tumor vasculature in pre-contrast high spectral resolution
images. NIBIB Training Grantees Meeting 2008.
Y. Yuan, M. Giger, H. Li, L. Lan, C. Sennett: Identifying
corresponding lesions from CC and MLO views via correlative
features analysis. International Workshops on
Digital Mammography 2008.
Y. Yuan, M. Giger, H. Li, L. Lan, C. Sennett: Comparison
of image segmentation methods on classification performance
of FFDM CAD. AAPM 2008.
W. Chen, M. Giger, G. Newstead, Y. Yuan: Computeraided
diagnosis of breast cancer using DCE-MRI. Preclinical
evaluation on two independent clinical data sets.
Department of Defense Breast Cancer Research Program
Meeting 2008.
Y. Yuan, M. Giger, H. Li, C. Sennett: Correlative feature
analysis of FFDM images. SPIE Medical Imaging
Conference 2008.
Y. Yuan, M. Giger, H. Li, C. Sennett: Correlative feature
analysis for multi-modality breast CAD: Identifying the
corresponding lesions from different mammographic
views. Department of Defense Breast Cancer Research
Meeting 2008.
53

Faculty Achievements
Honors & Awards
Paul Chang, MD
• Herbert M. Stauffer Award for Best Clinical Paper in
2007-2008. Presented to B Branstteter, M Morgan, C
Nesbit, J Phillips, D Lionetti, P Chang, and J Towers
for “Preliminary Reports in the Emergency
Department: Is a Subspecialist Radiologist More
Accurate than a Radiology Resident?” Association of
University Radiologists. Published in Academic
Radiology 2007; 14:201-206.
Abraham Dachman, MD
• Presiding Officer, Scientific Sessions, Radiological
Society of North American 93rd Scientific Assembly
and Annual Meeting, Chicago, IL, November 25 – 30,
2007.
• Radiology Editor’s Recognition Award.
Maryellen Giger, PhD
• Named Director, Imaging Research Institute,
University of Chicago, Chicago, Illinois.
Chien-Min Kao, PhD
• Senior Member, Institute of Electrical and Electronics
Engineers.
MG Knuttinen, T Van Ha, C Reilly, et al.
• Outstanding Scientific Presentation for “Unintended
Thermal Injuries from RFA: Organ Protection using an
Angioplasty Balloon Catheter in an Animal Model.
Society of Interventional Radiology, 33rd Annual
Meeting, Washington, DC, March 15, 2008.
Patrick La Rivière, PhD
• Kurt Rossmann Award for Excellence in Teaching,
Graduate Programs in Medical Physics, The
University of Chicago, October 2007.
Heber MacMahon, MD
• Elected President, Fleischner Society.
Robert Nishikawa, PhD
• Cum Laude Award. Presented to BA Lau, I Reiser, and
RM Nishikawa for the poster “Microcalcification
Detectability in Tomosynthesis.” Presented at SPIE
Medical Imaging Conference, San Diego, CA,
February 2008.
Aytekin Oto, MD
• Certificate of Merit Award. Presented to R Ernst, D
Hughes, A Oto, R Riascos, T Nishino, G Chaljub, et al.
for the Web based broadcast for the radiology noon
conference. Radiological Society of North America 93rd
Scientific Assembly and Annual Meeting, Chicago, IL,
November 25–30, 2007.
Xiaochuan Pan, PhD
• Fellow, American Institute of Medical and Biological
Engineering.
• Fellow, Optical Society of America.
David Paushter, MD
• Fellow, the American College of Radiology.
• Radiology Editor’s Recognition Award.
G. Scott Stacy, MD
• James W. Ryan Senior Class Teaching Award,
Department of Radiology, The University of Chicago,
Chicago, IL, 2007.
• Silver Medal Award. Presented to G. Scott Stacy, MD
and Rodney Corby, MD for the educational electronic
exhibit “Benign and Malignant Masses of High Signal
Intensity on T2-weighted Magnetic Resonance Imaging
Studies of the Knee: An Interactive Tutorial.” American
Roentgen Ray Society Annual Meeting, Washington,
DC, April 2008.
Christopher Straus, MD
• Selected by the Pritzker School of Medicine Class of
2008 as one of the top ten teachers.
Kenji Suzuki, PhD
• Listed in Marquis Who’s Who in Science and
Engineering.
• Listed in Marquis Who’s Who of Emerging Leaders.
Society Offices & Committees
American Association of Physicists in Medicine
Samuel Armato, PhD
Member, Journal Business Management Committee
Member, Education and Training of Medical Physicists
Committee
Member, Computer-Aided Detection in Diagnostic
Imaging (CAD) Subcommittee
Maryellen Giger, PhD
Elected, President-Elect of AAPM and Board Member
54

Robert Nishikawa, PhD
Chair, Research Subcommittee
Member, Physics Committee
Member, Science Council
Member, RSNA Education Coordination Subcommittee
Xiaochuan Pan, PhD
Symposium Chair, Annual Meeting
American Board of Radiology
Daniel Appelbaum, MD
Maintenance of Certification (MOC) Committee in
Nuclear Medicine
G. Scott Stacy, MD
Member, Subcommittee on Practice Guidelines and
Technical Standards for Radiography of Extremities in
Adults and Children
American College of Radiology
Abraham Dachman, MD
Media spokesperson
Member, Colorectal Cancer Committee
Member, Subcommittee on Colon Cancer Screening
Member, Subcommittee on CT Colonography Metrics
Member, Virtual Colonoscopy Screening Panel
Kate Feinstein, MD
Member, Commission on Pediatric Radiology
Member, Committee on Drugs and Contrast Media
Member, Committee on Economics (Commission on
Ultrasound)
Member, Continuing Profession Improvement, Expert
Panel on Pediatric Radiology
Brian Funaki, MD
Chairman, Appropriateness Committee Expert Panel on
Interventional Radiology
Jonathan Lorenz, MD
Member, Expert Panel on Interventional Radiology
Heber MacMahon, MD
Member, Appropriateness Standard Committee
David Paushter, MD
Member, CT Accreditation Committee
Member, Economics Committee, Abdominal Imaging
Ultrasound Credentialing Site Reviewer
American College of Radiology Imaging Network
(ACRIN)
Abraham Dachman, MD
Member, Publications Committee
Heber MacMahon, MD
Member, National Lung Screening Trial Computer Aided
Diagnosis Working Group
Robert Nishikawa, PhD
Member, Breast Committee
Member, Digital Mammography Screening Trial -
Executive Committee
Member, Informatics Committee
American Institute of Ultrasound in Medicine
David Paushter, MD
Chair, Clinical Standards Committee
American National Standards Institute Medical Devices
Standard Management Board
Paul Chang, MD
Representative (from RSNA)
American Roentgen Ray Society
Abraham Dachman, MD
Member, CME Evaluations Subcommittee
Brian Funaki, MD
Associate Chair, 2008 Program Committee
Chairman, 2008 Annual Meeting Instructional Course
Committee (Vascular and Interventional Radiology)
Co-Director, 2008 Annual Meeting Approach to
Diagnosis: Case Based Imaging Review Course
Member, Self Assessment Module Subcommittee
Jonathan Lorenz, MD
Coordinator, Moderator, and Lecturer, Abscess
Workshops, Annual Meeting
Judge, Electronic Exhibits, 2008 Annual Meeting
Member, Interventional Radiology Subcommittee
Gillian Newstead, MD
Member, Program Review Committee
Member, Scientific Education Subcommittee
Ibericoamerican Society of Interventionism
Mario Zaritzky, MD
Co-editor, Intervencionismo (Scientific Journal)
Illinois Radiological Society
Abraham Dachman, MD
Executive Committee
Kate Feinstein, MD
President
Institute of Electrical and Electronics Engineers
Chien-Min Kao, PhD
Member, Technical Committee, IEEE Nuclear Science
Symposium and Medical Imaging Conference
Xiaochuan Pan, PhD
Member, Scientific Program Committee, Symposium on
Medical Imaging and Augmented Reality
Member, Technical Program Committee, IEEE Medical
Imaging Conference
55

Institute of Electrical and Electronics Engineers in
Medicine and Biology
Chien-Min Kao, PhD
Associate Editor, Conference
Xiaochuan Pan, PhD
Theme Chair, Annual Meeting
Track Chair, Annual Meeting
Kenji Suzuki, PhD
Reviewing Panelist, Senior Member Application Review
Panel
International Conference on Machine Learning and
Applications
Kenji Suzuki, PhD
Member, Program Committee, Special Session on
Applications of Machine Learning in Radiotherapy
International Conference on Pattern Recognition
Kenji Suzuki, PhD
Member, Reviewing Committee
International Conference on Smart Homes and Health
Telematics
Kenji Suzuki, PhD
Member, Reviewing Committee
International Symposium on Computational
Intelligence and Industrial Applications
Kenji Suzuki, PhD
Member, Program Committee
MedBiquitous
Paul Chang, MD
Member, Standards Committee (from RSNA)
National Cancer Institute
Heber Macmahon, MD
Member and Investigator, Lung Image Database
Consortium
Organization for Human Brain Mapping
Jia-Hong Gao, PhD
Member, Organizing Committee Annual Meeting
Radiological Society of North America
Samuel Armato, PhD
Member, Physics Subcommittee of the Education
Exhibits Committee
Richard Baron, MD
Chair, Education Exhibits Committee
Paul Chang, MD
Informatics Architect, RADScope
Member, Education Exhibits Committee
Member, Public Information Advisors Network
Member, Radiology Informatics Committee
Abraham Dachman, MD
Member, Committee to Review Exhibits in Computed
Tomography for Radiographics
Member, Gastrointestinal Subcommittee of the Education
Exhibit Committee
Member, Local Committee on Scientific Exhibits
Jia-Hong Gao, PhD
Chair, Session on Image Quality/Reproducibility, Annual
Meeting
Aytekin Oto, MD
Member, Uroradiology Education Exhibits Committee
Xiaochuan Pan, PhD
Member, Physics Subcommittee of Scientific Program
Committee for the Annual Meeting
Session Chair, Annual Meeting
David Paushter, MD
Member, Quality Round Table
Kenji Suzuki, PhD
Session Chair, Annual Meeting
Society for Imaging Informatics in Medicine
Paul Chang, MD
Member, Annual Program Committee
Member, Board of the College of SIIM Fellows
Section Leader, SIIM University
Society of Directors of Academic Medical Physics
Programs
Samuel Armato, PhD
Member, Steering Committee
Society of Gastrointestinal Radiologists
Richard Baron, MD
President
Society of Interventional Radiology
Brian Funaki, MD
Course Director, Fellow’s Symposium
Society of Nuclear Medicine
Daniel Appelbaum, MD
Member, Committee on Education
Editorial Board Memberships
BrainMap DataBase Journal
Jia-Hong Gao, PhD
Editorial Board
Computerized Tomography Theory and Applications
Xiaochuan Pan, PhD
Advisory Board
56

eMedicine
Abraham Dachman, MD
Managing Editor, Radiology Book
European Radiology
Aytekin Oto, MD
Scientific Editorial Board
Human Brain Mapping
Jia-Hong Gao, PhD
Editorial Board
IEEE Transactions on Biomedical Engineering
Xiaochuan Pan, PhD
Associate Editor
IEEE Transactions on Medical Imaging
Xiaochuan Pan, PhD
Associate Editor
International Journal of Computer Aided Radiology
and Surgery
Michael Vannier, MD
Editor-in-Chief
International Journal of Magnetic Resonance Imaging
Jia-Hong Gao, PhD
Editorial Board
Journal of Cardiovascular Computed Tomography
Xiaochuan Pan, PhD
Editorial Board
Journal of Vascular and Interventional Radiology
Brian Funaki, MD
Editorial Board
Liver Transplantation
Richard Baron, MD
Associate Editor
Magnetic Resonance Imaging
Jia-Hong Gao, PhD
Editorial Board
Medical Physics
Samuel Armato, PhD
Associate Editor
Editorial Board
Patrick La Rivière, PhD
Guest Associate Editor
Xiaochuan Pan, PhD
Associate Editor
Kenji Suzuki, PhD
Guest Associate Editor
Neuroanatomy
Aytekin Oto, MD
Editorial Board
Open Artificial Intelligence Journal
Kenji Suzuki, PhD
Editorial Board
Open Biomedical Engineering Journal
Xiaochuan Pan, PhD
Editorial Board
Kenji Suzuki, PhD
Editorial Board
Radiology Case Reports
Brian Funaki, MD
Editorial Board
Seminars in Interventional Radiology
Brian Funaki, MD
Editor in Chief
Thuong Van Ha, MD
Editorial Board
Manuscript Reviewers
Academic Radiology
Samuel Armato, PhD
Charles Metz, PhD
Kenji Suzuki, PhD
American Board of Radiology
Daniel Appelbaum, MD (Self Assessment Modules in
Nuclear Medicine)
American Journal of Perinatology
Aytekin Oto, MD
American Journal of Roentgenology
Abraham Dachman, MD
Kate Feinstein, MD
Jonathan Lorenz, MD
Aytekin Oto, MD
David Paushter, MD
Thuong Van Ha, MD
Bioinformatics and Biology Insights
Kenji Suzuki, PhD
Cancer
Thuong Van Ha, MD
Cardiovascular and Interventional Radiology
Jonathan Lorenz, MD
57

Cerebral Cortex
Jia-Hong Gao, PhD
Clinical Medicine: Case Reports
Kenji Suzuki, PhD
Computer Vision and Image Understanding
Kenji Suzuki, PhD
Computerized Medical Imaging and Graphics
Kenji Suzuki, PhD
Diagnostic and Interventional Radiology
Aytekin Oto, MD
European Radiology
Aytekin Oto, MD
IEEE Nuclear Science Symposium and Medical
Imaging Conference Abstracts
Bill O’Brien-Penney, PhD
IEEE Transactions on Biomedical Engineering
Kenji Suzuki, PhD
IEEE Transactions on Image Processing
Kenji Suzuki, PhD
IEEE Transactions on Information Technology in
Biomedicine
Kenji Suzuki, PhD
IEEE Transactions on Medical Imaging
Samuel Armato, PhD
Chien-Min Kao, PhD
Patrick La Rivière, PhD
Xiaochuan Pan, PhD
Kenji Suzuki, PhD
IEEE Transactions on Neural Networks
Kenji Suzuki, PhD
IEEE Transactions on Nuclear Science
Chien-Min Kao, PhD
Patrick La Rivière, PhD
Human Brain Mapping
Jia-Hong Gao, PhD
International Conference on Pattern Recognition
Kenji Suzuki, PhD
International Conference on Smart Homes and Health
Telematics
Kenji Suzuki, PhD
International Journal of Computer-Assisted Radiology
and Surgery
Kenji Suzuki, PhD
Journal of Biomedical Informatics
Charles Metz, PhD
Journal of Computer Assisted Tomography
Abraham Dachman, MD
Aytekin Oto, MD
Journal of Magnetic Resonance
Jia-Hong Gao, PhD
Journal of Magnetic Resonance Imaging
Jia-Hong Gao, PhD
Journal of Nuclear Medicine
Daniel Appelbaum, MD
Patrick La Rivière, PhD
Yonglin Pu, MD
Journal of the American Medical Association
Jonathan Lorenz, MD
Journal of Vascular and Interventional Radiology
Brian Funaki, MD
Jonathan Lorenz, MD
Journal of Visual Communication and Image
Representation
Kenji Suzuki, PhD
Leukemia and Lymphoma
Daniel Appelbaum, MD
Liver Transplantation
Brian Funaki, MD
Jonathan Lorenz, MD
Aytekin Oto, MD
Yonglin Pu, MD
Thuong Van Ha, MD
Magnetic Resonance Imaging
Jia-Hong Gao, PhD
Magnetic Resonance in Medicine
Jia-Hong Gao, PhD
Medical Engineering & Physics
Kenji Suzuki, PhD
Medical Physics
Samuel Armato, PhD
Chien-Min Kao, PhD
Patrick La Rivière, PhD
Robert Nishikawa, PhD
Xiaochuan Pan, PhD
Kenji Suzuki, PhD
Neuroanatomy
Aytekin Oto, MD
58

Neuroimage
Jia-Hong Gao, PhD
New England Journal of Medicine
Jonathan Lorenz, MD
Open Artificial Intelligence Journal
Kenji Suzuki, PhD
Optical Engineering
Chien-Min Kao, PhD
Ophthalmic Plastic and Reconstructive Surgery
Yonglin Pu, MD
Pediatric Radiology
Kate Feinstein, MD
David Yousefzadeh, MD
Physics in Medicine and Biology
Chien-Min Kao, PhD
Patrick La Rivière, PhD
Robert Nishikawa, PhD
Xiaochuan Pan, PhD
Proceedings of the National Academy of Sciences
Jia-Hong Gao, PhD
Radiographics
Abraham Dachman, MD
Radiology
Samuel Armato, PhD
Abraham Dachman, MD
Kate Feinstein, MD
Charles Metz, PhD
Aytekin Oto, MD
Society of Nuclear Medicine Annual Meeting
Daniel Appelbaum, MD
Thyroid
Daniel Appelbaum, MD
Turkish Journal of Cardiovascular Surgery
Aytekin Oto, MD
Scientific Presentations
American Association of Physicists in Medicine
Minneapolis MN, July 22–26, 2007
Armato SG III, Pearson EA, Roberts RY, Sensakovic WF,
Caligiuri P: Assessment of Mesothelioma Tumor
Response: Correlation of Tumor Thickness and Tumor
Area.
Roberts RY, Armato SG III, Starkey A, Sensakovic WF,
Maitland M: Evolution of Adrenal Gland Perfusion with
Anti-angiogenic Therapy: A CT-based Study.
Sensakovic WF, Armato SG III, Starkey A: An External
Energy Field for Hemithoracic-cavity Segmentation using
Deformable Contours. (Poster presentation by WF
Sensakovic).
Shiraishi J, Appelbaum D, Pu Y, Doi K, Li Q, Englemann
R: Intelligent Workstation for Whole-Body Bone Scans:
Temporal and Contralateral Subtraction Techniques for
Identification of Interval Changes and Asymmetric
Subtle Lesions.
American Roentgen Ray Society Meeting
Washington DC, April 13-18, 2008
Jansen S, Fan X, Karczmar G, Abe H, Shimauchi A,
Newstead G: Non-mass vs. Mass-like Enhancement:
Which Kinetic Parameters Distinguish Benign and
Malignant Breast Lesions?
Jansen S, Shimauchi A, Abe H, Karczmar G, Newstead G:
The Kinetic and Morphologic Characteristics of
Mammographically Occult, MR Visible Breast Cancers:
How Different are the Extra Cancers Found at MR
Imaging?
Oto A, Ernst RD, Ghulmiyyah L, Riascos R, Saade G,
Hughes D, Chaljub G: Role of MRCP in Evaluation of
Pregnant Patients with Acute Pancreaticobiliary Disease.
Stacy G, Montag A: The Triple-signal Pattern: Not Just for
Synovial Sarcoma Anymore.
Wiginton C, Ernst R, Oto A, Chaljub G, Swischuk L:
Nephrogenic Systemic Fibrosis- a Summary and One
Institution's Experience.
Wood A, Medved M, Foxley S, Karczmar G, Newstead G,
Shimauchi A, Abe H: Fourier Components of the Water
Peak in High Spectral and Spatial Resolution Breast
Images may Indicate Tumor Blood Vessels.
Food and Drug Administration, Radiological Devices
Panel Advisory Committee Meeting
Gaithersburg MD, March 2008
Nishikawa RM: Clinical Studies of Computer-Aided
Detection for Screening Mammography.
Nishikawa RM: Evaluation of Computer-Aided
Detection.
IEEE International Symposium on Biomedical Imaging
Paris France, May 14-17, 2008
59

Suzuki K, Epstein ML, Sheu I, Kohlbrenner R, Rockey
DC, Dachman AH: Massive-training Artificial Neural
Networks for CAD for Detection of Polyps in CT
Colonography: False-negative Cases in a Large
Multicenter Clinical Trial.
Institute of Electrical and Electronics Engineers
Nuclear Science Symposium and Medical
Imaging Conference, Honolulu Hawaii,
October 27–November 3, 2007
Hu Z, Liu W, Dong Y, Zhang Z, Xie Q, Chen CT, Kao
CM: Semi-automatic Position Calibration for a Dualhead
Small Animal Scanner.
Kao CM: Windowed Image Reconstruction for TOF-PET.
Kao CM, Dong Y, and Xie Q: Evaluation of Fully 3D
Image Reconstruction Methods for a Dual-head Smallanimal
PET Scanner.
Kao CM, Xie Q, Dong Y, Wan L, and Chen CT:
Performance Characterization of a High-sensitivity
Small-animal PET Scanner.
Xie Q, Kao CM, Dong Y, Han X, and Chen CT: Potential
Advantages of Digitally Sampling Scintillation Pulses in
Timing Determination in PET.
Xie Q, Wagner R, Drake G, DeLurgio P, Dong Y, Chen
CT, and Kao CM: Performance Comparison of Multipixel
Photon Counters with Different Pixel Numbers for
PET Imaging.
International Symposium on Virtual Colonoscopy
Boston MA, October 15-17, 2007
Dachman AH, Bekeny KA, Zintsmaster M, Rana R,
Khankari S, Novak J, Ali A, Qalbani A, Fletcher JG:
Effectiveness of Standardized Training for Interpretation
of CT Colonography by Novice Readers.
Lostumbo A, Tsai J, Suzuki K, Dachman AH:
Comparison of 2D and 3D Views for Measurement and
Conspicuity of Flat Lesions in CT Colonography.
Suzuki K, Sheu I, Epstein ML, Verceles J, Rockey DC,
Dachman AH: Performance of CAD Based on MTANNs
for Detection of False-negative Polyps in a Multicenter
Clinical Trial.
Radiological Society of North America 93rd Scientific
Assembly and Annual Meeting
Chicago IL, November 25–30, 2007
Armato SG III, MacMahon H, Aberle DR, Kazerooni EA,
van Beek EJR, Yankelevitz DF, et al.: “Truth" and
Radiologist Performance in the Detection of Lung
Nodules.
Chen W, Giger M, Newstead G, Jansen SA, Chiang K, Lan
L, et al.: Breast Cancer Diagnosis Using DCE-MRI: Role of
Computer in Interpretation of 4D Data.
Ernst R, Hughes D, Oto A, Riascos R, Nishino T, Chaljub
G, et al.: Web-based Broadcast for the Radiology Noon
Conference.
Ichikawa K, Hasegawa M, Abe H, Shiraishi J, Doi K:
Development of Super-high Resolution LCDs with 16 and
9 Mega-pixels for Displaying High-resolution
Radiological Images.
Jansen SA, Fan X, Abe H, Schmidt RA, Newstead GM:
DCEMRI of Breast Lesions: Is Kinetic Analysis Equally
Effective for Both Mass and Non-mass-like Enhancement?
Jansen SA, Yang C, Abe H, Shimauchi A, Karczmar G,
Newstead GM: DCEMRI of Malignant Breast Lesions:
Should a Fixed Volume of Contrast be Injected, or a Fixed
Dose?
Jiang Y, Giger M, Nishikawa R, Schmidt R, Newstead G,
Chang P: A PACS Enabled Computer-aided Diagnosis
(CADx) Workstation for Breast Imaging Applications.
Nishikawa RM: A Critical Analysis of the Clinical Studies
Measuring the Effectiveness of Computer-aided Detection
in Screening Mammography.
Nishikawa RM, Engström E, Reiser E, Kopans DB, Moore
RH: Comparison of the Breast Tissue Power Spectrum for
Tomosynthesis Projection and Reconstructed Images.
Oto A, Hughes D, Ghulmiyyah L, Ernst R, Nishino T,
Chaljub G: MR Imaging in Triage of Pregnant Patients
with Acute Abdominal and Pelvic Pain.
Pu Y, Huang Y, Li Q, Chen C, Appelbaum DE: Interobserver
Variability between Measurements of the
Maximal Standardized Uptake Value on FDG PET/CT
and Measurements of the Tumor Size on Diagnostic CT in
Patients with Lymphoma.
Shimauchi A, Jansen SA, Abe H, Kulkarni, K, Schmidt
RA, Newstead GM: Cancers Not Detected at MR
Imaging: Review of False-Negative Lesions.
Shiraishi J, Abe H, Ichikawa K, Hasegawa M, Doi K:
Evaluation of Radiologists’ Performance in Detection of
Clustered Microcalcifications on Digital Mammograms by
use of Super-high Resolution Liquid Crystal Display
Monitors.
Suzuki K, Verceles J, Khankari S, Rockey DC, Dachman
AH: Performance of a CAD Scheme Incorporating a
Massive Training Artificial Neural Network (MTANN)
for Detection of Polyps in False-Negative CT
60

Colonography Cases in a Large Multicenter Clinical
Trial.
Thiel S, Shah R, Abe H, Jansen SA, Shimauchi A,
Newstead G: Evaluating the Extent of Disease with MRI
in the Setting of Breast Calcifications Suggestive of
DCIS.
San Antonio Breast Cancer Symposium
San Antonio TX, December 13-16, 2007
Fan X, Arkani S, Karczmar G, Abe H, Schmidt R,
Newstead G: Using Three-parameter Empirical
Mathematical Model to Analyze Breast DCEMRI Data;
Comparison with Conventional BI-RADS Classification.
Jansen SA, Abe H, Shimauchi A, Karczmar GS,
Newstead GM: How Does ER/PR and Her2/Neu Status
affect the MR Characteristics of Invasive Ductal
Carcinoma?
Jansen SA, Abe H, Shimauchi A, Karczmar GS, Olopade
O, Zak L, Newstead GM: Are the MRI Characteristics of
Malignant Breast Lesions Different for African American
Women?
Jansen SA, Conzen S, Zamora M, Krausz T, Newstead
GM, Karczmar GS: A New Approach to Studying the
Progression of Breast Cancer in Mice: High Resolution
MRI of Early Cancer and DCIS.
Kulkarni K, Newstead GM, Jansen SA, Abe H,
Shimauchi A, Schmidt RA, Jaskowiak N: Does MRI
Improve Chances of Obtaining Negative Surgical
Margins after Localized Excision? A Retrospective Study.
Kulkarni K, Newstead GM, Jansen SA, Abe H,
Shimauchi A, Schmidt RA, Sennett CA, Jaskowiak N:
Influence of DCEMRI on Obtaining Negative Surgical
Margins in Patients with Breast Cancer Undergoing
Localized Excision: A retrospective Study.
Medved M, Newstead GM, Abe H, Wood AM, Olopade
O, Shimauchi A, Fischer S, Karczmar GS: Pushing the
Limits: Very High Spatial Resolution Spectroscopic MR
Imaging of Human Breast.
Newstead GM, Abe H, Jansen SA, Shimauchi A, Sennett
CA, Schmidt RA, Zak L, Olopade O, Jaskowiak N: Effect
of Magnetic Resonance Imaging on the Clinical
Management of Women with Newly Diagnosed Breast
Cancer.
Society for Imaging Informatics in
Medicine Annual Meeting
Providence RI, June 2007
Morgan M, Branstetter B, Richardson J, Dexter D, Martin
W, Chang P: The Enterprise Imaging Support Dashboard:
Bringing IT All Together.
Society for Magnetic Resonance Imaging in Medicine
Toronto Ontario, May 3-9, 2008
Jansen SA, Fan X, Karczmar G, Giger M, Abe H,
Newstead GM: Are Kinetic Parameters Diagnostically
Useful for Breast Lesions Exhibiting Nonmass-like-
Enhancement?
Jansen SA, Karczmar G, Shimauchi A, Abe H, Newstead
GM: Are Kinetic Parameters Related to Prognostic
Indicators in

Symposium on Radiation Measurements and
Applications
Berkeley CA, June 2-5, 2008
Lin J, Biris O, Chen CT, Choong WS, Frisch H, Kao CM,
Moses WW, Tang F, Xie Q, and Zhou L: Electronics
Development for Fast-timing PET Detectors: The Multithreshold
Discriminator Time of Flight PET System.
Invited Presentations
Daniel Appelbaum, MD
Bone Scintigraphy Review. Society of Nuclear Medicine,
Nuclear Medicine Board Review course, New Orleans
LA, June 14, 2008.
Identifying Unknown Whole Body Scans. Chicago
Radiological Society meeting, Rush Presbyterian Medical
Center, Chicago IL, April 17, 2008.
Nuclear Medicine Breast Imaging Techniques: Breast PET,
PET/CT and Lymphoscintigraphy. The Chicago
International Breast Course, Chicago IL, October 6, 2007.
Overview of Oncologic Imaging: MR, CT, PET/CT and
other Molecular Imaging Techniques. Oncology Nursing
Society Advanced Practice Nursing Conference, Chicago
IL, October 8, 2007.
PET/CT Imaging: Overview and Update. Grand Rounds,
St. Mary’s Medical Center, Knoxville TN, February 7,
2008.
Paul Chang, MD
Delivering the Goods: Web Content for the 2.0 Era.
Digital Now: Association Leadership in the Digital Age,
Orlando FL, April 25, 2008. (Co-presenters: C Carr and S
Drew).
Leveraging Informatics to Enhance Radiology Relevance
and Value. President’s Address and Opening Session,
Radiological Society of North America, Chicago IL,
December 2007.
Re-engineering Radiology in an Electronic World:
Radiologist as Value Innovator. Illinois Radiology Society,
Chicago IL, March 15, 2008. Also presented in Grand
Rounds, Indiana University School of Medicine,
Methodist Hospital, Indianapolis IN, April 21, 2008.
Abraham Dachman, MD
Director, Free Paper Sessions; and Panelist: Plenary
Session #6: Practical Issues for Dissemination.
International Symposium on Virtual Colonoscopy, Boston
MA, October 15-17, 2007.
Faculty, Course on CT Colonography, Supervised Case
Review. American College of Radiology, Reston VA,
March 16-18, 2008.
Faculty, Course on CTC - Lectures: (1) Polyp Detection
and Characterization; (2) Flat Lesions and Common
Pitfalls; (3) Review of Cases. American
Gastroenterological Association, Washington DC, March
7, 2008.
Faculty, Hands-on CTC Course; and Workshop, joint with
P. Lefere: Virtual Colonoscopy Pitfalls of Interpretation.
Society of Gastrointestinal Radiologists, Palm Desert CA,
February 17-22, 2008.
Faculty, Virtual Colonoscopy: A Practice-Based Course.
Lectures: (1) Future Directions: CAD, Subtraction
Cathartic free CTC, Colon Unraveling; (2) Issues of
Current Implementation: Reimbursement, Training,
Accreditation; (3) Training Cases 1-10. American
Roentgen Ray Society Chicago IL. June 27-28, 2008.
Kate Feinstein, MD
Unusual Neonatal Fractures; Venous Thromboembolism
in Children with ALL; Gastroschisis with Bladder
Evisceration. Midwest Society for Pediatric Radiology,
Cincinnati OH, September 29, 2007.
Brian Funaki, MD
Avoidance and Treatment of Complications Related to
Percutaneous Lung Biopsy; also Case Based Review
Course -Arterial Diagnosis. American Roentgen Ray
Society Annual Meeting, Washington DC, April 13-18,
2008.
Case Based Reviews in Interventional Radiology -Non-
Vascular Interventions. Radiologic Society of North
America, Chicago IL, November 27, 2007.
Enteral Feeding. Society of Interventional Radiology
Fellow’s Spring Symposium, May 9, 2008.
Enteroscopy in the 21st Century. Obscure GI bleeding:
Use of Radiology in the DCE Era. American Society of
Gastrointestinal Endoscopy Masters Series Course. Oak
Brook IL, March 7-8, 2008.
Portal Interventions. Arterial Diagnosis. Society of
Interventional Radiology, Washington DC, March 15-20,
2008.
Vascular Physiology and Anatomic Variants. True
Confessions: What I Wish I Hadn’t Done. Metallic Stent
62

Design & Sheaths, Guides and Catheters Workshops.
Tibial Interventions. Advances in Endovascular
Intervention, Chicago IL, August 17-19, 2007.
Jia-Hong Gao, PhD
Current Status in Neuronal Current MRI. International
Society for Magnetic Resonance in Medicine, Berlin
Germany, 2007.
Developments in Neuronal Current MRI. Nanjing,
China, 2007.
Directly Measuring Neuronal Activity Using MRI.
Taiwan, 2008.
New Developments in fMRI. Chinese Society of
Magnetic Resonance in Medicine, Darlin China, 2007.
Patrick La Rivière, PhD
Development of Protease-sensitive Molecular Probes and
Acoustic Attenuation Correction Schemes for
Optoacoustic Tomography. National Taiwan University,
Taipei, Taiwan, 2007.
Novel Scanning Approaches for Synchrotron-based X-
ray Fluorescence Computed Tomography. National
Health Research Institute, Taiwan, 2007.
Penalized-likelihood Sinogram Preprocessing for Lowdose
and Non-contrast Computed Tomography.
Department of Biomedical Engineering, Purdue
University, 2008.
Sinogram Preprocessing for Low-dose Computed
Tomography. Chang Gung Memorial Hospital, Taiwan,
2007.
Jonathan Lorenz, MD
Abscess Meeting workshop. Society of Interventional
Radiology, Washington DC, March 2, 2007.
Meeting course. Abscess Drainage Course Director.
American Roentgen Ray Society, Washington DC, May
2008.
Heber MacMahon, MD
Cutting Edge Thoracic Radiology. American Thoracic
Society State of the Art Meeting, Chicago IL, February
2008.
Management of Pulmonary Nodules. I-ELCAP Annual
Conference on Screening for Lung Cancer, Rancho
Mirage CA, October 2007.
New Thoracic Imaging Technologies: 64-Slice
Multidetector CT, Postprocessing, PET/CT, and
Enhanced Radiography Methods. The State of
Computer-aided Diagnosis (CAD): Are you ready to
Move? Radiological Society of North America, Chicago
IL, 2007.
Robert Nishikawa, PhD
An Overview of Computer-aided Diagnosis and
Application to Digital Breast Tomosynthesis. XCounter
AB, Stockholm Sweden, September 2007.
Computer-Aided Diagnosis: Get Ready, It’s Coming to a
Workstation near You! Practical Course in Medical
Digital Imaging & Teleradiology, Toronto Canada, March
2008.
Aytekin Oto, MD
Evaluation of Pain in Pregnancy: US, CT and MR. Shared
workshop with Dr. Genevieve Bennett in Abdominal
Radiology Course, Rancho Mirage CA, February 17-22,
2008.
MRCP: Technique, Artefacts and Anatomical Variants.
Shared workshop with Dr. Giuseppe D'Ippolito.
European Society of Gastrointestinal and Abdominal
Radiologists, Istanbul Turkey, June 10-13, 2008.
MRI of Focal Liver Lesions; MRI of the Pancreas; MRI of
Maternal Diseases. The 3rd Congress of Turkish Society
of Magnetic Resonance, Ankara Turkey, May 22-24, 2008.
New Developments in Small Bowel Imaging and Board
Drills. Visiting professor at University of Texas Medical
Branch at Galveston TX, April 7, 2008.
Update on Imaging of the Inflammatory Bowel Diseases.
Illinois CCFA Annual Educational Conference, Chicago
IL, March 29, 2008.
Sidney Regalado, MD
Vascular and Interventional Radiology Unknown Cases.
Chicago Radiological Society Resident and Fellow
Section, Chicago IL, April 17, 2008.
Kenji Suzuki, PhD
Computer-aided Diagnosis Research at the University of
Chicago. School of Life System Science and Technology,
Chukyo University, Aichi Japan, 2007.
Computer-aided Diagnosis Research in the United States.
Graduate School of Information Science and Technology,
Aichi Prefectural University, Aichi Japan, 2007.
63

Machine Learning for Computer-aided Diagnosis. UCSD
Radiation Oncology Academic Seminar Series,
Department of Radiation Oncology, the Moores Cancer
Center, the University of California at San Diego, 2008.
Massive-training Artificial Neural Networks (MTANNs)
for Computer-aided Diagnosis in Digital X-rays. JPI,
Seoul South Korea, 2008.
Recent Progress in Computer-aided Diagnosis (CAD)
Research of the Chest and Abdomen at the University of
Chicago. Graduate School of Engineering, University of
Tokushima, Tokushima Japan, 2008.
Recent Progress in Development of Computer-aided
Diagnosis (CAD) at the University of Chicago: Massivetraining
Artificial Neural Networks (MTANNs). Konica
Minolta Medical & Graphic, Tokyo Japan, 2008.
Recent Progress in Computer-aided Diagnosis Research
at the Kenji Suzuki Lab at the University of Chicago.
Seminar, Faculty of Information Science and Technology,
Aichi Prefectural University, Aichi Japan, 2008.
Thuong Van Ha, MD
Abscess Drainages Management and Endocavitary
Abscess Drainages; also Regional Cancer Therapy:
Combined Transarterial Chemoembolization and
Radiofrequency Ablation for Cirrhosis Related
Hepatocellular Carcinoma; also How to Maximize
Günther Tulip IVC Filter Retrieval Rate. Society of
Interventional Radiology, Washington DC, March 15-20,
2008.
Chemoembolization: How and why I do it; also
Chemoembolization complications: Mistakes I made
when I started. Society of Interventional Radiology
Fellows Practicum, Oakbrook IL, May 10, 2008.
Michael Vannier, MD
Medical Imaging Workstations. FutureScape, College of
American Pathologists, Northbrook IL, June 2008.
Neuroimaging Visualization and Analysis. Royal Dental
College, Copenhagen DK, April 2008.
Neuroimaging Workshop. Mathematical Biosciences
Institute, Ohio State University, Columbus OH, June
2008.
President's Symposium on Imaging Biomarkers.
American Association of Physicists in Medicine, July
2007.
David Yousefzadeh, MD
Application of US and Doppler in Pediatric MSK
Disorders with Major Emphasis on Infectious Disorders.
Society for Pediatric Radiology, Scottsdale AZ, May 6-10,
2008.
Steve Zangan, MD
How to Avoid and Treat Complications of Percutaneous
Lung Biopsy. Arterial Interventions Case Based Imaging
Review Course. American Roentgen Ray Society,
Washington DC, April 2008.
Port Catheters: Insertion and Complications. Society of
Interventional Radiology Fellow Spring Practicum, Oak
Brook IL, May 9, 2008.
The Future of Radiology. Information Session AMA
Medical Showcase, Chicago IL, June 23, 2007.
Mario Zaritzky, MD
How to Improve your Pediatric Interventional Practice.
Curso Internacional Hands On en Cirugía Invasiva
Mínima y Radiología Intervencionista, Buenos Aires
Argentina, Oct. 25-27, 2007.
Role of the Radiologist in Esophageal Atresia. Latin
American Society of Pediatric Radiology, Viña de Mar
Chile, November 1-3, 2007.
Use of Magnets for Primary Esophageal Atresia Repair.
International Congress of Endoscopic Surgery, Puerto
Vallarta, Mexico, April 29-May 3, 2008.
Exhibits
American Roentgen Ray Society Meeting
Washington DC, 2008
Stacy G, Corby R: Benign and Malignant Masses of High
Signal Intensity on T2 Weighted MRI Studies of the Knee:
An Interactive Tutorial.
Radiological Society of North America 93rd Scientific
Assembly and Annual Meeting
Chicago IL, November 2007
Ferrari CM, Gatti M, Bertolotti JJ, Morín A, Zaritzky MF:
Ultrasonography in Congenital Hypothyroidism.
Jiang Y, Giger ML, Nishikawa RM, Newstead GM,
Schmidt RA, Chang PJ, et al.: A PACS-Enabled Computeraided
Diagnosis (CADx) Workstation for Breast Imaging
Applications.
64

Nishikawa RM, Pesce L: Physics Case of the Day.
Paushter DM, Oto A, Dachman AH, Vannier MW,
Funaki BS, Baron RL: Ultrasound of the Acute Scrotum:
Initial Presentation and Sequelae.
Reiser I, Nishikawa RM, Seifi P: Image Quality and
Artifact Conspicuity in Breast Tomosynthesis.
Suzuki K, Armato SG III, He L, Engelmann R, Caligiuri
P, MacMahon H: Usefulness of "Virtual Dual-energy
Radiography (VDER)" for Improving Conspicuity of
Nodules and Other Pathologic Changes by Means of Rib
Suppression in Standard and Temporally Subtracted
Chest Radiographs.
Suzuki K, Verceles J, Khankari S, Rockey DC, Dachman
AH: Advanced CAD System Incorporating a 3D
Massive-training Artificial Neural Network (MTANN)
for Detection of “Missed” Polyps in CT Colonography in
a Large Multicenter Clinical Trial.
Society of Vascular and Interventional Radiology
Washington DC, March 15, 2008
Knuttinen MG, Van Ha T, Reilly C, et al.: Unintended
Thermal Injuries from RFA: Organ Protection using an
Angioplasty Balloon Catheter in an Animal Model.
Reilly C, Knuttinen MG, Montag A, Straus C, Van Ha T:
How Far Do They Go? A Direct Comparison of Two
Spherical Embolic Agents in Porcine Kidneys.
SPIE Medical Imaging Conference
San Diego CA, February 2008.
Lau BA, Reiser I, Nishikawa RM: Microcalcification
Detectability in Tomosynthesis. (Awarded Cum Laude
Poster Award).
Yarusso LM, Nishikawa RM: Influence of Signal-to-noise
Ratio and Temporal Stability on Computer-aided
Detection of Mammographic Microcalcifications in
Digitized Screen-film and Full-field Digital
Mammography.
Patents
Shiraishi J, Doi K, Appelbaum D, Li Q: Computer-aided
Method for Detection of Interval Changes in Successive
Whole-Body Bone Scans and Related Computer Program
Product and System. WO 2007/062135 A2.
Suzuki K: Image Processor. Japanese Patent No.
3,953,569, issued May 2007. Suzuki K, Ikeda S, Horiba I:
Image Processor. Japanese Patent No. 39492129, issued
April 2007.
Zaritzky MF and Surti VC: Pediatric Esophageal Atresia
Magnets. US 7,282,057 B2, issued October 2007.
Peer-Reviewed Publications
Abe HA, Schmidt RA, Sennett CA, Newstead GM:
Ultrasound-guided 14G Core Needle Biopsy of
Suspicious Axillary Lymph Nodes in Patients with Breast
Cancer: Clinical Experience in 100 Patients. Radiology (in
press).
Abe HA, Schmidt RA, Sennett CA, Shimauchi A,
Newstead GM: Ultrasound-guided Core Needle Biopsy
of Axillary Lymph Nodes in Patients with Breast Cancer:
Why and How to Do It. Radiographics 27 Suppl 1:S91-9,
2007.
Al-Hallaq HA, Mell LK, Bradley J, Chen L, Ali A,
Hellman S, Weichelsbaum R, Newstead GM, Chmura S:
Magnetic Resonance Imaging Identifies Additional
Multifocal and Multicentric Disease in Breast Cancer
Patients Eligible for the NSABP B-39/RTOG 0413 Partial
Breast Irradiation PBI Trial. Cancer (in press).
Anastasio M and Pan X: Image Reconstruction in a
Region of Interest from Truncated Phase Contrast Data.
Optical Letters 32:3167-3169, 2007.
Anastasio M, Pan X, Shi D: Data Symmetries and Their
Use in Acoustic Diffraction Tomography. Acoustic Imaging
28:155-172, 2007.
Anastasio M, Zhang J, Modgil D, Pan X, La Riviere PJ: A
Fourier Shell Identity for Photoacoustic Tomography.
Inverse Problems 23:S21-S35, 2007.
Anastasio M, Zou Y, Sidky E, Pan X: Local Cone-beam
Tomography Image Reconstruction on Chords. Journal of
the Optical Society of America 24:1569-1579, 2007.
Aristophanous M, Penney B, LaRiviere P, Pelizzari C: The
Development of a Realistic Digital PET Lung Phantom
for the Evaluation of Tumor Volume Segmentation
Techniques. Medical Physics 34:2636, 2007.
Aristophanous M, Penney B, Martel M, Pelizzari C: A
Gaussian Mixture Model for Definition of Lung Tumor
Volumes in Positron Emission Tomography. Medical
Physics 34:4223-4235, 2007.
65

Armato SG III, McNitt-Gray MF, Reeves AP, Meyer CR,
McLennan G, Aberle DR, Kazerooni EA, MacMahon H,
van Beek EJR, Yankelevitz D, Hoffman EA, Henschke CI,
Roberts RY, Brown MS, Engelmann RM, Pais RC, Piker
CW, Qing D, Kocherginsky M, Croft BY, Clarke LP: The
Lung Image Database Consortium (LIDC): An
Evaluation of Radiologist Variability in the Identification
of Lung Nodules on CT Scans. Academic Radiology
14:1409-1421, 2007.
Armato SG III, Roberts RY, McNitt-Gray MF, Meyer CR,
Reeves AP, McLennan G, Engelmann RM, Bland PH,
Aberle DR, Kazerooni EA, MacMahon H, van Beek EJR,
Yankelevitz D, Croft BY, Clarke LP: The Lung Image
Database Consortium (LIDC): Ensuring the Integrity of
Expert-defined "Truth". Academic Radiology 14:1455-1463,
2007.
Bardo D, Oto A: MR Imaging for Evaluation of the Fetus
and the Placenta. American Journal of Perinatology
(in press).
Chao Y, He L, Suzuki K, Nakamura T, Shi Z, Itoh H: An
Improvement of Herbrand Theorem and its Application
to Model Generation Theorem Proving. Journal of
Computer Science and Technology 22: 541-553, 2007.
Chen W, Giger ML, Li H, Bick U, Newstead GM:
Volumetric Texture Analysis of Breast Lesions on
Contrast-enhanced Magnetic Resonance Images.
Magnetic Resonance in Medicine 58(3):562-71, 2007.
Cho S, Bian J, Pelizzari C, Chen CT, Pan X: Region-ofinterest
Image Reconstruction in Circular Cone-beam
MicroCT. Medical Physics 34:4923-4933, 2007.
Cho S, Xia D, Pelizzari CA, Pan X: Exact Reconstruction
of Volumetric Images in Reverse Helical Cone-beam CT.
Medical Physics 35:3030-3040, 2008.
Corby RR, Stacy GS, Peabody TD, Dixon LB:
Radiofrequency Ablation for the Treatment of Solitary
Eosinophilic Granuloma of Bone. American Journal of
Roentgenology 190:1492-1494, 2008.
Dachman AH, Bekeny KA, Zintsmaster M, Rana R,
Khankari S, Novak J, Ali A, Qalbani A, Fletcher JG:
Formative Evaluation of Standardized Training for CT
Colonography Interpretation by Novice Readers.
Radiology (in press).
Doshi T, Rusinak DJ, Halvorsen RA, Rockey DC,
Dachman AH: Retrospective Analysis of Sources of Error
in a Large CTC Clinical Trial. Radiology 244:165-173,
2007.
Drukker K, Gruszauskas N, Sennett CA, Giger ML:
Breast Ultrasound Computer-Aided Diagnosis:
Performance on a Large Clinical Diagnostic Population.
Radiology (in press).
Drukker K, Sennett CA, Giger ML: Automated Method
for Improving System Performance of Computer-aided
Diagnosis in Breast Ultrasound. IEEE Transactions in
Medical Imaging (in press).
Edwards DC, Metz CE: Optimization of Restricted ROC
Surfaces in Three-class Classification Tasks. IEEE
Transactions on Medical Imaging 26:1345-1356, 2007.
Flicker MS, Tsoukas AT, Hazra A, Dachman AH:
Extracolonic Findings at CT Colonography. Journal of
Computer Assisted Tomography (in press for July/August
2008 issue).
Gruszauskas N, Drukker K, Giger ML, Sennett CA, Pesce
LL: Performance of Breast Ultrasound Computer-aided
Diagnosis: Dependence on Image Selection. Academic
Radiology (in press).
Hammes M, Funaki B, Coe FL: Cephalic Arch Stenosis in
Patients with Fistula Access for Hemodialysis:
Relationship to Diabetes and Thrombosis. Hemodialysis
International 12:85-89, 2008.
Hansell DM, Bankier AA, MacMahon H, McLoud TC,
Muller NL, and Remy J: Fleischner Society: Glossary of
Terms for Thoracic Imaging. Radiology 246:697-722, 2008.
Harish MG, Konda SD, MacMahon H, and Newstead
GM: Breast Lesions Incidentally Detected with CT: What
the General Radiologist Needs to Know. RadioGraphics 27:
S37-S51, 2007.
He L, Chao Y, Suzuki K: A Run-based Two-scan Labeling
Algorithm. IEEE Transactions on Image Processing 17:749-
756, 2008.
He L, Chao Y, Suzuki K, Nakamura T, Itoh H: An Efficient
Two-scan Connected-component Labeling Algorithm.
Transactions of IEICE J91-D:1016-1024, 2008.
He L, Chao Y, Suzuki K, Shi Z, Itoh H: An Improvement
on Sub-Herbrand Universe Computation. The Open
Artificial Intelligence Journal 1:12-18, 2007.
Hillis SL, Berbaum KS, Metz CE: Recent Developments in
the Dorfman-Berbaum-Metz Procedure for Multireader
ROC Study Analysis. Academic Radiology 15:647-661, 2008.
Horsch KJ, Giger ML, Metz CE: Potential Effect of
Different Radiologist Reporting Methods on Studies
Showing Benefit of CAD. Academic Radiology 15:139-152,
2008.
66

Horsch KJ, Giger ML, Metz CE: Prevalence Scaling:
Applications to an Intelligent Workstation for the
Diagnosis of Breast Cancer Academic Radiology.
Academic Radiology (in press).
Jansen SA, Conzen S, Krausz T, Zamora M, Foxley M,
Fan X, Newstead G, Karczmar G: Detection of in situ
Mammary Cancer in a Transgenic Mouse Model: In vitro
and in vivo MRI Studies Demonstrate Histopathologic
Correlation. Biology and Medicine (in press).
Jansen SA, Fan X, Karczmar GS, Abe H, Schmidt RA,
Giger M, Newstead GM: DCEMRI of Breast Lesions: Is
Kinetic Analysis Equally Effective for Both Mass and
Non-mass-like Enhancement?” Medical physics (in press).
Jansen SA, Fan X, Karczmar GS, Abe H, Schmidt RA,
Newstead GM: Differentiation between Benign and
Malignant Breast Lesions Detected by Bilateral Dynamic
Contrast Enhanced MRI: A Sensitivity and Specificity
Study. Magnetic Resonance in Medicine 59(4):747-54, 2008.
Jansen SA, Newstead GM, Abe H, Shimauchi A, Schmidt
RA Karczmar GS: MR Imaging of Pure Ductal
Carcinoma in situ: Kinetics, Morphology and
Correlation with Mammographic Presentation and
Nuclear Grade. Radiology 245(3):684-91, 2007.
Johnson CD, Chen MH, Toledano AY, Heiken JP,
Limbrug PH, Dachman A, Kuo MD, Menias C, Fidler JL,
Cheema JI, Coakley K, Iyer RB, Horton KM, Siewert B,
Obregon RG, Zimmerman P, Hara AK, Halvorsen RA Jr,
Yee J, Casola G, Herman BA, Burgart LJ: The National
CT Colonography Trial: Multicenter Assessment of
Accuracy for Detection of Large Adenomas and Cancers.
New England Journal of Medicine (accepted for publication).
Kao CM: Windowed Image Reconstruction for Time-offlight
Positron Emission Tomography. Physics in Medicine
and Biology 53:3431–3445, 2008.
Kao CM, Zou Y, Cho S, Pan X: An Exact Analytic
Approach to 3D PET Image Reconstruction. International
Journal of Image and Graphics 7:35-54, 2007.
Kasai S, Li F, Shiraishi J, Doi K: Usefulness of Computeraided
Detection Schemes for Vertebral Fractures and
Lung Nodules in Chest Radiographs: Observer
Performance Study by use of ROC Analysis without and
with Localization. American Journal of Roentgenology
191:260-265, 2008.
King M, Giger ML, Suzuki K, Bardo D, Greenberg B, Lan
L, Pan X: Computerized Assessment of Motion-contaminated
Calcified Plaques in Cardiac Multidetector CT.
Medical Physics 34:4876-4889, 2007.
Kuban K, Adler I, Allred EN, Batton D, Bezinque S, Betz
BW, Cavenagh E, Durfee S, Ecklund K, Feinstein K,
Fordham LA, Hampf F, Junewick J, Lorenzo R, McCauley
R, Miller C, Seibert J, Specter B, Wellman J, Westra S,
Leviton A: Observer Variability Assessing US Scans of
the Preterm Brain: The ELGAN Study. Pediatric Radiology
37:1202-1208, 2007.
Kumazawa S, Muramatsu C, Li Q, Li F, Shiraishi J,
Caligiuri P, Schmidt RA, MacMahon H, Doi K: An
Investigation of Radiologists’ Perception of Lesion
Similarity: Observations with Paired Breast Masses on
Mammograms and Paired Lung Nodules on CT images.
Academic Radiology 15:887-894, 2008.
La Rivière PJ and Vargas PA: Correction for Resolution
Non-uniformities Caused by Anode Angulation in
Computed Tomography. IEEE Transactions on Medical
Imaging (accepted for publication).
LaRoque S, Sidky E, Pan X: Accurate Image
Reconstruction in Few-view Diffraction Tomography.
Journal of the Optical Society of America 2008.
Lee T, Leung A, Fox P, Gao JH, Chan C: Age-related
Differences in Neural Activities during Risk Taking as
Revealed by Functional MRI. Social Cognitive and Affective
Neuroscience 3:7-15, 2008.
Lefere P, Dachman AH, Gryspeerdt S: Computed
Tomographic Colonography: Clinical Value. Abdominal
Imaging 32:541-551, 2007.
Li F, Engelmann R, Doi K, MacMahon H: Improved
Detection of Small Lung Cancers with Dual-Energy
Subtraction Chest Radiography. American Journal of
Roentgenology 190:886-891, 2008.
Li F, Engelmann R, Metz CE, Doi K, MacMahon H:
Results Obtained by a Commercial Computer-aided
Detection (CAD) Program with Missed Lung Cancers on
Chest Radiographs. Radiology 246:273-280, 2008.
Li H, Giger ML, Olopade OI, Chinander MR: Power
Spectral Analysis of Mammographic Parenchymal
Patterns of Digitized Mammograms. Journal of Digital
Imaging 21:145-152, 2008.
Li H, Giger ML, Yuan Y, Chen W, Lan L, Jamieson A,
Sennett CA, Arkani S, Horsch K: Evaluation of
Computerized Diagnosis Scheme on a Large Clinical
Full-Field Digital Mammographic Dataset. Academic
Radiology (in press).
Li Q, Li F, Doi K: Computerized Detection of Lung
Nodules in Thin-section CT by Use of Selective
Enhancement Filters and Automated Rule-based
Classifier. Academic Radiology 15:165-175, 2008.
67

Lin A, Fox P, Yang Y, Lu H, Tan L, Gao JH: Evaluation of
MRI Models in the Measurement of CMRO2 and its
Relationship with CBF. Magnetic Resonance in Medicine
60:380-389.
Luo Q, Liu H, Parris B, Lu H, Senseman D, Gao JH:
Modeling Oxygen Effects in Tissue Preparation
Neuronal Current MRI. Magnetic Resonance in Medicine
58:407-412.
MacMahon H: Advanced Image Processing and
Computer-aided Diagnosis: Are We There Yet?
(Editorial) Journal of Thoracic Imaging 23(2):75.
MacMahon H, Li F, Engelmann R, Roberts R, Armato S:
Dual Energy and Temporal Subtraction Chest
Radiography. Journal of Thoracic Imaging 23(2):77.
Mates J, Branstetter B, Morgan M, Lionetti D, Chang P:
“Wet Reads” in the Age of PACS: Technical and
Workflow Considerations for a Preliminary Report
System. Journal of Digital Imaging 20:296-306, 2007.
Matsuo K, Glahn D, Peluso M, Hatch J, Monkul E, Najt
P, Sanches M, Zamarripa F, Li J, Lancaster J, Fox P, Gao
JH, Soares J: Perfrontal Hyperactivation During Working
Memory Task in Untreated Individuals with Major
Depressive Disorder. Molecular Psychiatry 12:158-166,
2007.
McNitt-Gray MF, Armato SG III, Meyer CR, Reeves AP,
McLennan G, Pais R, Freymann J, Brown MS,
Engelmann RM, Bland PH, Laderach GE, Piker C, Guo J,
Towfic Z, Qing DP, Yankelevitz DF, Aberle DR, van Beek
EJR, MacMahon H, Kazerooni EA, Croft BY, Clarke LP:
The Lung Image Database Consortium (LIDC) Data
Collection Process for Nodule Detection and Annotation.
Academic Radiology 14:1464-1474, 2007.
Mitchell MT, Gasparaitis AE, Alverdy JC: Imaging
Findings in Roux-en-Y and Other Misconstructions: Rare
but Serious Complications of Roux-en-Y Gastric Bypass
Surgery. American Journal of Radiology 190:367-373, 2008.
Molvar C, Funaki B: Hypothenar Hammer Syndrome.
American Journal of Roentgenology Integrative Imaging
(accepted for publication).
Morgan M, Branstetter B, Lionetti D, Richardson J,
Chang P: The Radiology Digital Dashboard:
Effect on Report Turnaround Time. Journal of Digital
Imaging 21:50-58, 2008.
Muramatsu C, Li Q, Schmidt RA, Shiraishi J, Suzuki K,
Newstead GM, Doi K: Determination of Subjective
Similarity for Pairs of Masses and Pairs of Clustered
Microcalcifications on Mammograms: Comparison of
Similarity Ranking Scores and Absolute Similarity
Ratings. Medical Physics 34:2890-2895, 2007.
Nishikawa RM, Schmidt RA, and Metz CE: Computeraided
Screening Mammography (Letter to the Editor).
New England Journal of Medicine 357:83-85, 2007.
Oto A, Ernst RD, Ghulmiyyah L, Nishino T, Hughes D,
Riascos-Castaneda R, Chaljub G, Saade G: MR Imaging in
the Triage of Pregnant Patients with Acute Abdominal
and Pelvic Pain. Abdominal Imaging (in-press).
Oto A, Ernst R, Ghulmiyyah L, Saade G, Hughes D,
Chaljub G: The Role of MR Cholangiopancreatography in
the Evaluation of Pregnant Patients with Acute
Pancreaticobiliary Disease. British Journal of Radiology
(in press).
Pan X, Siewerdsen J, La Riviere PJ, Kalender W:
Development of X-ray Computed Tomography: The Role
of Medical Physics and AAPM from the 1970s to Present.
Medical Physics (accepted for publication).
Pan X, Xia D, Halpern H: Targetted ROI-imaging in
Electron Paramagnetic Resonance Imaging. Journal of
Magnetic Resonance 187:66-77, 2007.
Pan X, Zhang J, Anastasio M: Data Redundancies in
Reflectivity Tomography Using Offset Sources and
Receivers. Acoustic Imaging 28:231-246, 2007.
Pesce LL, Metz CE: Reliable and Computationally
Efficient Maximum-likelihood Estimation of “Proper”
Binormal ROC Curves. Academic Radiology 14:814–829,
2007.
Pu Y, Li QF, Zeng CM, Garg A, Corby R, Pu S, Gao JH: A
Positive Correlation Between Alpha Glutamate and
Glutamine on Brain 1H-MRS and Neonatal Seizures in
Moderate and Severe Hypoxic-Ischemic Encephalopathy.
American Journal of Neuroradiology 29(2):216, 2008.
Pu Y, Mahankali S, Hou J, Fox PT, Appelbaum D, Gao JH:
“True” Prevalence of Pineal Cysts in Normal Adults
Demonstrated By High-Resolution MR Imaging. American
Journal of Neuroradiology 28:1706-1706.
Pu Y, Mahankali S, Hou J, Li J, Lancaster JL, Gao JH,
Appelbaum DE, Fox PT: High Prevalence of Pineal Cysts
in Healthy Adults Demonstrated by High-resolution,
Noncontrast Brain MR Imaging. American Journal of
Neuroradiology 28:1706-1709, 2007.
Reeves AP, Biancardi AM, Apanasovich TV, Meyer CR,
MacMahon H, van Beek EJR, Kazerooni EA, Yankelevitz
DF, McNitt-Gray MF, McLennan G, Armato SG III,
Henschke CI, Aberle DR, Croft BY, Clarke LP: The Lung
Image Database Consortium (LIDC): A Comparison of
Different Size Metrics for Pulmonary Nodule
Measurements. Academic Radiology 14:1475-1485, 2007.
68

Regalado SP, Funaki B: Radiological Reasoning: Post-
Operative Hemorrhage After Open Cholecystectomy
and Common Bile Duct Exploration. American Journal of
Roentgenology 190(6):S69-S74, 2008.
Reiser I, Nishikawa RM, Edwards AV, Schmidt RA,
Papaioannou J, E, Moore R, Kopans, DB: Automated
Detection of Microcalcification Clusters for Digital Breast
Tomosynthesis Using Projection Data Only: A
Preliminary Study. Medical Physics 35:1486-1493, 2008.
Runyon MK, Johnson-Kerner BL, Kastrup CJ, Van Ha T,
Imagilov RF: Propagation of Blood Clotting in the
Complex Biochemical Network of Hemostasis is
Described by a Simple Mechanism. Journal of the
American Chemical Society 129:7014-7015, 2007.
Runyon MK, Kastrup CJ, Johnson-Kerner BL, Van Ha
TG, Ismagilov RF: The Effects of Shear Rate on
Propagation of Blood Clotting Determined by Using
Microfluidics and Numerical Simulations. Journal of the
American Chemical Society 130:3458-3464, 2008.
Sakai S, Yabuuchi H, Matsuo Y, Okafuji T, Kamitani T,
Honda H, Yamamoto K, Fujiwara K, Sugiyama N, Doi K:
Integration of Temporal Subtraction and Nodule
Detection System for Digital Chest Radiographs into
PACS: Four-year Experience. Journal of Digital Imaging
21:91-98, 2008.
Sensakovic WF, Armato SG III, Starkey A: Two-dimensional
Extrapolation Methods for Texture Analysis on CT
Scans. Medical Physics 34:3465-3472, 2007.
Sheran J, Dachman AH: Quality of CT Colonography
Related Web Sites for Consumers. Journal of the American
College of Radiology 5:593-597, 2008.
Shi Z, Chao Y, He L, Suzuki K, Nakamura T, Itoh H:
Object Location and Track in Image Sequences by Means
of Neural Networks. International Journal of
Computational Science 2:274-285, 2008.
Shiraishi J, Appelbaum D, Pu Y, Li Q, Pesce L, Doi K:
Usefulness of Temporal Subtraction Images for
Identification of Interval Changes in Successive Whole-
Body Bone Scans: JAFROC Analysis of Radiologists’
Performance. Academic Radiology 14(8):959-966, 2007.
Stacy GS, Nair LD: Magnetic Resonance Imaging
Features of Extremity Sarcomas of Uncertain
Differentiation. Clinical Radiology 62:950-958, 2007.
Suzuki K, Yoshida H, Nappi J, Armato III SG, Dachman
AH: Mixture of Expert 3D Massive-training ANNs for
Reduction of Multiple Types of False Positives in CAD
for Detection of Polyps in CT Colonography. Medical
Physics 35:694-703, 2008.
Tannus J, Dagoglu G, Oto A: MR Imaging of the Maternal
Diseases of the Abdomen and Pelvis in the Pregnant
Patient. American Journal of Perinatology (in press).
Towbin A, Paterson B, Chang P: A Computer-based
Radiology Simulator as a Learning Tool to Help Prepare
First-year Residents for Being on Call. Academic Radiology
14:1271-1283, 2007.
Towbin A, Paterson B, Chang P: Computer-based
Simulator for Radiology: An Educational Tool.
Radiographics 28:309-316, 2008.
Van Ha T, Chien A, Funaki B, Lorenz J, Rosenblum J, Leef
J, Shen M: Use of Retrievable Inferior Vena Cava Filters:
Single Institution Experience. CVIR October 23, 2007.
Vokes TJ, Pham A, Wilkie J, Kocherginsky M, Ma SL,
Chinander M, Karrison T, Bris O, Giger ML:
Reproducibility and Sources of Variability in
Radiographic Texture Analysis of Densitometric
Calcaneal Images. Journal of Clinical Densitometry (in
press).
Wiggington C, Brent B, Oto A, Ernst RD, Jessie M,
Chaljub G, Swischuk L: Gadolinium-based Contrast
Exposure, Nephrogenic Systemic Fibrosis and
Gadolinium Detection in Tissue. American Journal of
Roentgenology 190:1060-8, 2008.
Wilkie J, Giger ML, Chinander MR, Engh CA, Hopper
RH, Martell JM: Temporal Radiographic Texture Analysis
in the Detection of Periprosthetic Osteolysis. Medical
Physics 35:377-387, 2008.
Wilkie J, Giger ML, Engh CA, Hopper RH, Martell JM:
Radiographic Texture Analysis in the Characterization of
Trabecular Patterns in Periprothetic Osteolysis. Academic
Radiology 15:176-185.
Xia D, Cho S, Bian J, Zou Y, Sidky E, Zuo N, Pan X: 3D
ROI-image Reconstruction from Cone-beam Data. Nuclear
Instruments and Methods in Physics Research 580:866-975,
2007.
Xia D, Yu L, Sidky E, Zou Y, Zuo N, Pan X: Investigation
on Noise Properties of Chord-based Image
Reconstruction. IEEE Transactions on Medical Imaging
26:1328-1344, 2007.
Yousefzadeh DK, Doerger K, Sullivan C: The Blood
Supply of Early, Late, and Nonossifying Cartilage:
Preliminary Gray-scale and Doppler Assessment and
their Implications. Pediatric Radiology 38:146-158, 2008.
Yu L, Xia D, Sidky E, Bian J, Pan X: A Rebinned
Backprojection-filtration Algorithm for Image
Reconstruction in Helical Cone-beam CT. Physics in
Medicine and Biology 52:5497-5508.
69

Yuan Y, Giger ML, Li H, Suzuki K, Sennett C: A Dualstage
Method for Lesion Segmentation on Digital
Mammograms. Medical Physics 34:4180-4193, 2007.
Zangan SM, Funaki B, Van Ha TG: Spontaneous
Antepartum Hemorrhage While Awaiting Preoperative
Balloon Occlusion for Placenta Percreta. European Journal
of Radiology 65:21-23, 2008.
Zangan SM, Van Ha TG: Percutaneous Placement of a
Constrained Stent for the Treatment of Dialysis
Associated Arteriovenous Graft Steal Syndrome. The
Journal of Vascular Access 8:228-230, 2007.
Zeng L, Chen H, Luo Q, Yao D, Gao JH: Quantitative
Analysis of Asymmetrical Cortical Activity in Motor
Areas During Sequential Finger Movement. Magnetic
Resonance Imaging 25:1370-1375, 2007.
Zhao X, Li G, Glahn D, Fox PT, Gao JH: Derivative
Temporal Clustering Analysis: Detecting Prolonged
Neuronal Activity. Magnetic Resonance Imaging
25:183-187, 2007.
Zuo N, Xia D, Jiang T, Zou Y, Pan X: Exact Image
Reconstruction Based on General Circle-line Trajectory.
ACTA Electronica Sinica 35:1382-1386, 2007.
Invited Publications
Backer M, Zangan S: Delayed Presentation of Rupture
after Venous Angioplasty. Seminars in Interventional
Radiology 24:324-326, 2007.
Dachman AH: Is Meta-analysis a Suitable Tool for
Assessing the Diagnostic Accuracy of CT colonography?
Nature Clinical Practice Gastroenterology & Hepatology
5(1):10-11, 2008.
Dachman AH: Training for Interpretation of CTC: Some
Get It, but Some Don’t. AGA Perspectives December
2007/January 2008; 3(6):5-7.
Dachman AH, Lefere P, Gryspeerdt S, Morrin M. Virtual
Colonography: Visualization Methods and Pitfalls. The
Radiologic Clinics of North America 45(2):347-359, 2007.
DeMonte T, Gao JH, Wang D, Ma W, Joy M:
Measurement of Current Density Vectors in a Live Pig
for the Study of Human Electro-muscular Incapacitation
Devices. IEEE Engineering in Medicine and Biology 2008.
Funaki B: ALS and Pop Music. Seminars in Interventional
Radiology 24:139-140, 2007.
Funaki B: Carbon Dioxide Angiography. Seminars in
Interventional Radiology 25:065-070, 2008.
Funaki B: Diagnostic Radiology for Interventional
Radiologists. Seminars in Interventional Radiology 25:001-
002, 2008.
Funaki B: Embolization of Pulmonary Arteriovenous
Malformations. Seminars in Interventional Radiology 24:350-
355, 2007.
Funaki B: Filter Migration to the Right Heart. Seminars in
Interventional Radiology 24:356-360, 2007.
Funaki B: Iatrogenic Post-catheterization
Pseudoaneurysm. Seminars in Interventional Radiology
25:071-074, 2008.
Funaki B: JACHO and Me. Seminars in Interventional
Radiology 24:277-278, 2007.
Funaki B: Minimizing Occupational Exposure to
Biohazards. Seminars in Interventional Radiology 24:430-
432, 2007.
Funaki B: Percutaneous Biliary Drainage. Seminars in
Interventional Radiology 24:268-271, 2007.
Funaki B: Pneumothorax Treated by Small Bore Chest
tube. Seminars in Interventional Radiology 24:272-276, 2007.
Funaki B: The Customer is Always Right. Seminars in
Interventional Radiology 24:361-362, 2007.
Funaki B, Doshi T: Pulseless Electrical Activity after SVC
Dilation. Seminars in Interventional Radiology 24:433-436,
2007.
He L, Chao Y, Suzuki K, Nakamura T, Itoh H: A Fast Twoscan
Connected-component Labeling Algorithm for
Binary Images. ImageLab 2008.
Lefere P, Dachman AH: Coloscopie Virtuelle: état Actuel
et Nouveaux Développements. Journées Françaises de
Radiologie. CME Course Syllabus. Paris, October 20-24,
2007.
Metz CE: ROC Analysis in Medical Imaging: A Tutorial
Review of the Literature. Radiological Physics & Technology
1:2-12, 2008.
Molvar C, Funaki B: Hypothenar Hammer Syndrome.
AJR Integrative Imaging (Accepted for publication).
Newstead GM: How Reliable is the Negative Predictive
Value of Magnetic Resonance Mammography (MRM)?
European Radiology Supplement October 2007.
70

Newstead GM, Meinel LA: Computer-aided
Visualization and Analysis (CAVA) for Breast Cancer
Detection and Diagnosis. Medico Mundi July 2008.
Qalbani A, Paushter D, Dachman AH: Multidetector CT
of Small Bowel Obstruction. The Radiologic Clinics of
North America 45(3):499-512, 2007.
Radvany M, Funaki B: Non-invasive Vascular Self
Assessment Module. American Roentgen Ray Society
(In press).
Regalado S, Funaki B: Novel Wound Closure for
Interventional Radiology. Seminars in interventional
Radiology 25:058-064, 2008.
Singh AS, Breitkopf DM, Oto A, Roncal OA, Kathuria
MK, Ozkan O: Imaging of Female Infertility.
Contemporary Diagnostic Radiology 31:1-6, 2008.
Suzuki K: Applications of Computer-aided Diagnosis by
Means of Massive-training Artificial Neural Networks
(MTANN) to Diagnosis of the Thorax. Medical 39:1202-
1209, 2007.
Van Ha T: Use of the Interlock Fibered IDC Occlusion
System in Clinical Practice. Seminars in Interventional
Radiology 25:3-10, 2008.
Abstracts & Proceedings
Armato SG III, MacMahon H, Aberle DR, Kazerooni EA,
van Beek EJR, Yankelevitz DF, et al.: "Truth" and
Radiologist Performance in the Detection of Lung
Nodules. Radiology 245(P): 418-419, 2007.
Armato SG III, Pearson EA, Roberts RY, Sensakovic WF,
Caligiuri P: Assessment of Mesothelioma Tumor
Response: Correlation of Tumor Thickness and Tumor
Area. Medical Physics 34:2554, 2007.
Armato SG III, Roberts RY, McLennan G, McNitt-Gray
MF, Yankelevitz D, Kazerooni EA, van Beek EJR,
MacMahon H, Aberle DR, Meyer CR, Reeves AP,
Henschke CI, Hoffman EA, Croft BY, Clarke LP: The
Lung Image Database Consortium (LIDC): A Quality
Assurance Model for the Collection of Expert-defined
"Truth" in Lung-nodule-based Image Analysis Studies.
Proceedings SPIE 6514: 651429-1-651429-7, 2007.
Biancardi AM, Apanasovich TV, Meyer CR, MacMahon
H, van Beek EJR, Kazerooni EA, Yankelevitz D, McNitt-
Gray MF, McLennan G, Armato SG III, Aberle DR,
Henschke CI, Hoffman EA, Croft BY, Clarke LP: The
Lung Image Database Consortium (LIDC): Pulmonary
Nodule Measurements, the Variation and the Difference
between Different Size Metrics. Proceedings SPIE 6514:
65140J-1–65140J-8, 2007.
Chen W, Metz CE, Giger ML: Hybrid Linear Classifier for
Jointly Normal Data: Theory. Proceedings SPIE Medical
Imaging Conference, 2008.
Drukker K, Giger ML: Computerized Self-assessment of
Automated Lesion Segmentation in Breast Ultrasound:
Implication for CADx Applied to Findings in the Axilla.
Proceedings SPIE Medical Imaging Conference, 2008.
Edwards DC, Metz CE. A Utility-based Performance
Metric for ROC Analysis of N-class Classification Tasks.
Proceedings SPIE 6515:65150301-65150310, 2007.
Fredenberg E, Cederström B, Lundqvist M, Ribbing C,
Åslund M, Diekmann F, Nishikawa RM, Danielsson M:
Contrast-enhanced Dual-energy Subtraction Imaging
using Electronic Spectrum-splitting and Multi-prism X-
ray Lenses. Proceeding SPIE 6913:691310.1-691310.12,
2008.
Guo X, Gao JH, Penn R: Brain Tissue Water Content
Measured by MRI: Pre vs. Postshunt Chronic
Hydrocephalus. ISMRM, 2007.
Guo X, Somayaji M, Linninger A, Gao JH, Penn R:
Turboprop Diffusion Tensor Imaging for Computational
Design of Drug Transport in Brain. ISMRM, 2008.
He L, Chao Y, Suzuki K: A Fast Two-scan Labeling
Algorithm. Proceedings IEEE International Conference on
Image Processing, V:241-244, San Antonio, TX, September
2007.
He L, Chao Y, Suzuki K: A Run-based Two-scan Labeling
Algorithm. Lecture Notes in Computer Science, Image
Analysis and Recognition 4633:131–142 (Springer-Verlag,
Berlin), Montreal, Canada, August 2007.
Hu Z, Liu W, Dong Y, Zhang Z, Xie Q, Chen CT, Kao CM:
Semi-automatic Position Calibration for a Dual-head
Small Animal Scanner. IEEE Nuclear Science Symposium
and Medical Imaging Conference 2007, pp. 1618-1621.
Itai Y, Hyoungseop K, Ishikawa S, Katsuragawa S, Doi K:
A New Registration Method with Voxel Matching
Technique for Temporal Subtraction Image. Proceedings
SPIE 6915:69153I1-8, 2008.
Januszyk MP, Armato SG III, Engelmann R, MacMahon
H: Automated Detection of Interval Change in
Temporally Subtracted Chest Radiographs. Radiology
245(P):406, 2007.
71

Kao CM, Dong Y, Xie Q: Evaluation of Fully 3D Image
Reconstruction Methods for a Dual-head Small-animal
PET Scanner. IEEE Nuclear Science Symposium and
Medical Imaging Conference 2007, pp. 3046-3050.
Kao CM, Xie Q, Dong Y, Wan L, Chen CT: Performance
Characterization of a High-sensitivity Small-animal PET
Scanner. IEEE Nuclear Science Symposium and Medical
Imaging Conference 2007, pp. 4176-4180.
King M, Giger ML, Suzuki K, Bardo DM, Greenberg BM,
Pan X, et al.: Computerized Assessment of Calcified
Plaques in Cardiac CT Images. Program of Scientific
Assembly and Annual Meeting of Radiological Society of
North America, p. 405, 2007.
King M, Giger ML, Suzuki K, Pan X: Computer-aided
Assessment of Cardiac Computed Tomography Images.
Proceedings SPIE Medical Imaging 6514:65141B-1-6, 2007.
King M, Pan X, Giger ML, Suzuki K: Motion
Compensated Reconstructions of Calcified Coronary
Plaques in Cardiac CT. Proceedings SPIE Medical Imaging
6510:651012-1-6, 2007.
King M, Xia D, Pan X, Vannier M, Kohler T, La Riviere P,
Sidky E, Giger ML: Chord-based Image Reconstruction
from Clinical Projection Data. Proceedings SPIE Medical
Imaging Conference, 2008.
La Rivière PJ and Vargas P: Optimal Sampling and
Interpolation Schemes for 3D X-ray Fluorescence
Computed Tomography. Proceedings of the Ninth
International Meeting on Fully Three-Dimensional Image
Reconstruction in Radiology and Nuclear Medicine, 2007.
La Rivière PJ and Vargas P: Potential Equivalence of
Sinogram and Image-domain Penalized Likelihood
Methods. IEEE Nuclear Science Symposium Conference
Record, 2007, pp. 4169-4173.
La Rivière PJ, Vargas PA, Newville M, Sutton S:
Reduced-scan Schemes for X-ray Fluorescence
Computed Tomography. IEEE Nuclear Science Symposium
Conference Record, 2007, pp. 2991-2995.
Lau BA, Reiser I, Nishikawa RM: Microcalcification
Detectability in Tomosynthesis. Proceedings SPIE
6913:6913L1-6913L7 2008.
Li F, Engelmann R, Doi K, MacMahon HM: Small
Nodular Lung Cancers on Chest Radiographs:
Obscuration by Bones and Mean Size at the Time of
Detection. Radiological Society of North America Annual
Meeting, 2007.
Lin A, Fox P, Gao JH: Frequency-dependent Changes in
Lactate Concentration During Activation of Human
Visual Cortex. ISMRM 2257, 2007. Also NeuroImage 36
(S1):381, 2007.
Lin A, Fox P, Gao JH: Time-related Flow-metabolism
Relationship in Activated Human Visual Cortex: fMRI vs.
PET. ISMRM 615, 2007. Also NeuroImage 36(S1):382, 2007.
Lostumbo A, Tsai J, Suzuki K, Dachman AH: Comparison
of 2D and 3D Views for Measurement and Conspicuity of
Flat Lesions in CT Colonography. Proceedings International
Symposium on Virtual Colonoscopy, pp. 120-121, October
2007.
McNitt-Gray MF, Armato SG III, Meyer CR, Reeves AP,
McLennan G, Pais R, Freymann J, Brown MS, Engelmann
RM, Bland PH, Laderach GE, Piker C, Guo J, Qing DP,
Yankelevitz D, Aberle DR, van Beek EJR, MacMahon H,
Kazerooni EA, Croft BY, Clarke LP: The Lung Image
Database Consortium (LIDC) Data Collection Process for
Nodule Detection and Annotation. Proceedings SPIE
6514:65140K-1-65140K-8, 2007.
Modgil D and La Rivière PJ: Implementation and
Comparison of Reconstruction Algorithms for 2D
Optoacoustic Tomography Using a Linear Array.
Proceedings SPIE 6856:68571Dff, 2008.
Muramatsu C, Li Q, Schmidt RA, Shiraishi J, Suzuki K,
Newstead GM, Doi K: Determination of Subjective and
Objective Similarity for Pairs of Masses on Mammograms
for Selection of Similar Images. Proceedings SPIE Medical
Imaging 6514:65141I-1-9, 2007.
Oda S, Awai K, Suzuki K, He L, MacMahon H, Yamashita
Y: Detection of Pulmonary Nodules on Chest
Radiographs: Effect of Rib Suppression by Means of
Massive Training Artificial Neural Network (MTANN) on
Performance of Radiologists. Program of Scientific Assembly
and Annual Meeting of Radiological Society of North America,
p. 419, 2007.
Pereira RR, Shiraishi J, Li F, Li Q, Doi K: Computerized
Scheme for Detection of Diffuse Lung Diseases on CR
Chest Images. Proceedings SPIE 6915:69151A1-12, 2008.
Raicu DS, Varutbangkul E, Cisneros JG, Furst JD,
Channin DS, Armato SG III: Semantics and Image
Content Integration for Pulmonary Nodule Interpretation
in Thoracic Computed Tomography. Proceedings SPIE
6512:65120S-1-65120S-12, 2007.
Reeves AP, Biancardi AM, Apanasovich TV, Meyer CR,
MacMahon H, van Beek EJR, Kazerooni EA, Yankelevitz
D, McNitt-Gray MF, McLennan G, Armato SG III, Aberle
DR, Henschke CI, Hoffman EA, Croft BY, Clarke LP: The
Lung Image Database Consortium (LIDC): Pulmonary
Nodule Measurements, the Variation and the Difference
Between Different Size Metrics. Proceedings SPIE
6514:65140J-1-65140J-8, 2007.
72

Reiser I, Lau BA, Nishikawa RM: Effect of Scan Angle
and Reconstruction Algorithm on Model Observer
Performance in Tomosynthesis. Digital Mammography.
Lecture Notes in Computer Science Vol 5116. Krupinski,
EA, Ed. (Springer-Verlag, Berlin) 2008.
Roberts RY, Armato SG III, Starkey A, Sensakovic WF,
Maitland M: Evolution of Adrenal Gland Perfusion with
Anti-angiogenic Therapy: A CT-based Study. Medical
Physics 34:2338-2339, 2007.
Rodgers ZB, King MT, Giger ML, Bardo D, Vannier MW,
Lan L, Suzuki K: Computerized Assessment of Coronary
Calcified Plaques in CT Images of a Dynamic Cardiac
Phantom. Proceedings SPIE Medical Imaging 6915:69150M-
1-6.
Sensakovic WF, Armato SG III, Starkey A: An External
Energy Field for Hemithoracic-cavity Segmentation
Using Deformable Contours. Medical Physics 34:2338,
2007.
Sensakovic WF, Armato SG III, Starkey A: Extrapolation
Techniques for Textural Characterization of Tissue in
Medical Images. Proceedings SPIE 6514:65143G-1-65143G-
5, 2007.
Shiraishi J, Sugimoto K, Kamiyama N, Moriyasu F, Doi
K: Computer-aided Diagnosis for Classification of Focal
Liver Lesions on Contrast-enhanced Ultrasonography:
Image Feature Extraction and Characterization of
Vascularity Patterns. Proceedings SPIE 6915:6515321-11,
2008.
Sidky EY, Reiser I, Nishikawa RM, Pan XC, Chartrand R,
Kopans DB, Moore RH: Practical Iterative
Reconstruction in Digital Breast Tomosynthesis by Nonconvex
TpV Optimization. Proceedings SPIE
6913:691328.1-691328.6, 2008.
Suzuki K, Armato SG, He L, Engelmann R, Caliguiri P,
MacMahon HM: Usefulness of “Virtual Dual-energy
Radiography (VDER)” for Improving Conspicuity of
Nodules and Other Pathologic Changes by Means of Rib
Suppression in Standard and Temporally Subtracted
Chest Radiographs. Program of Scientific Assembly and
Annual Meeting of Radiological Society of North America, p.
979, 2007.
Suzuki K, Epstein ML, Sheu I, Kohlbrenner R, Rockey
DC, Dachman AH: Massive-training Artificial Neural
Networks for CAD for Detection of Polyps in CT
Colonography: False-negative Cases in a Large
Multicenter Clinical Trial. Proceedings IEEE International
Symposium on Biomedical Imaging, pp. 684-687, Paris,
France, May 2008.
Suzuki K, He L, Khankari S, Ge L, Verceles J, Dachman
AH: Mixture of Expert Artificial Neural Networks with
Ensemble Training for Reduction of Various Sources of
False Positives in CAD. Proceedings SPIE Medical Imaging,
6514:651401-1-6, 2007.
Suzuki K, Sheu I, Epstein ML, Kohlbrenner R, Lostumbo
A, Rockey DC, Dachman AH: An MTANN CAD for
Detection of Polyps in False-negative CT Colonography
Cases in a Large Multicenter Clinical Trial: Preliminary
Results. Proceedings SPIE Medical Imaging,
6915: 69150F-1-7, 2008.
Suzuki K, Sheu I, Epstein M L, Verceles J, Rockey DC,
and Dachman AH: Performance of CAD Based on
MTANNs for Detection of False-negative Polyps in a
Multicenter Clinical Trial. Proceedings International
Symposium on Virtual Colonoscopy, pp. 93-94, October
2007.
Suzuki K, Verceles J, Khankari S, Lostumbo A, Rockey
DC, Dachman AH: Advanced CAD System Incorporating
a 3D Massive-training Artificial Neural Network
(MTANN) for Detection of “Missed” Polyps in CT
Colonography in a Large Multicenter Clinical Trial.
Program of Scientific Assembly and Annual Meeting of
Radiological Society of North America, p. 778, 2007.
Suzuki K, Verceles J, Khankari S, Lostumbo A, Rockey
DC, Dachman AH: Performance of a CAD Scheme
Incorporating a Massive-training Artificial Neural
Network (MTANN) for Detection of Polyps in False-negative
CT Colonography Cases in a Large Multicenter
Clinical Trial. Program of Scientific Assembly and Annual
Meeting of Radiological Society of North America, p. 595,
2007.
Wang J, Li Q, Hirai T, Katsuragawa S, Li F, Doi, K: An
Accurate Segmentation Method for Volumetry of Brain
Tumor in 3D MRI. Proceedings SPIE 6914:6915H1-8, 2008.
Xie Q, Kao CM, Wang X, Guo N, Zhu C, Frisch H, Moses
WW, Chen CT: Potential Advantages of Digitally
Sampling Scintillation Pulses in Timing Determination in
PET. IEEE Nuclear Science Symposium and Medical Imaging
Conference 2007, pp. 4271-4274.
Xie Q, Wagner R, Drake G, DeLurgio P, Dong Y, Chen CT,
Kao CM: Performance Comparison of Multi-pixel Photon
Counters with Different Pixel Numbers for PET Imaging.
IEEE Nuclear Science Symposium and Medical Imaging
Conference 2007, pp. 969–974.
Xie Q, Zhu J, Wang X, Zhang B, Zhu C, Guo N, Zhang Z,
Chen CT, Wah YW, Bogdan M, Kao CM: An Investigation
of Digital Signal Processing for Shaped Pulses for Alldigital
PET. Proceedings SPIE 6913, 2008 (in press).
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Yarusso LM, Nishikawa RM: Influence of Signal-to-noise
Ratio and Temporal Stability on Computer-aided
Detection of Mammographic Microcalcifications in
Digitized Screen-film and Full-field Digital
Mammography. Proceedings SPIE 6915:6915X1-6915X8,
2008.
Chapters, Books, &
Review Articles
Feinstein KA: Renal Neoplasms (The Abdomen, Pelvis,
and Retroperitoneum). In Slovis TL (ed): Caffey’s
Pediatric Diagnostic Imaging (Eleventh Edition).
Philadelphia: Mosby, Elsevier Inc., 2281-2289, 2008.
Fernbach SK, Feinstein KA: Normal Renal Anatomy,
Variants, and Congenital Anomalies (The Abdomen,
Pelvis, and Retroperitoneum). In Slovis TL (ed): Caffey’s
Pediatric Diagnostic Imaging (Eleventh Edition).
Philadelphia: Mosby, Elsevier Inc., 2234-2262, 2008.
Giger ML: Computer-aided Detection/Computer-aided
Diagnosis (Chapter 10). In Wolbarst AB, Mossman KL,
Hendee WR (eds): Advances in Medical Physics 2008.
Madison, Wisconsin: Medical Physics Publishing.
Giger ML, Karssemeijer N. Editors SPIE Volume 6514:
Medical Imaging 2007: Computer-aided Diagnosis, 2007.
Giger ML, Suzuki K: Computer-aided Diagnosis (Chapter
16). In Feng (ed): Biomedical Information Technology,
p.359, 2007.
Kao CM, Sidky EY, La Rivière PJ, Pan, X: Some Recent
Developments in Reconstruction Algorithms for
Tomographic Imaging. In Dhawan AP, Huang HK, and
Kim DS (eds.): Principles and Advanced Methods in
Medical Imaging and Image Analysis. World Scientific
Publishing Company, New Jersey, pp. 361-393, 2008.
La Rivière PJ, Zhang J, Anastasio M: Image
Reconstruction in Optoacoustic Tomography Accounting
for Frequency-dependent Attenuation. To appear in Wang
L (ed): Photoacoustic Imaging and Spectroscopy. CRC
Press, 2008.
Oto A, Dachman A, Gasparaitis A: Benign Small Bowel
Wall Thickening and Neoplasms. In Dushyant Sahani
(eds): Abdominal Imaging (in-press).
Grants & Contracts
(ACTIVE JULY 1, 2007- JUNE 30, 2008)
Primary Investigators
Samuel Armato, PhD
Title:
Computerized Analysis of
Mesothelioma on CT Scans
Agency: National Cancer Institute
Project Period: 6/1/2006-5/31/2010
DC/IDC/Total: $943,978/$488,019/$1,431,997
Title:
Medical Informatics Experiences in
Undergraduate Research
Agency: National Science Foundation
Project Period: 2/1/2008-1/31/2011
DC/IDC/Total: $59,404/$6,182/$65,586
Title:
Standard Database for CT Lung Images
Agency: National Cancer Institute
Project Period: 8/20/2001-7/31/2007
DC/IDC/Total: $1,079,391/$532,950/$1,612,341
Chin-Tu Chen, PhD
Title:
AFIP-UC Collaborative Research
Agreement
Agency: AFIP
Project Period: 5/2/2007-5/1/2009
DC/IDC/Total: $335,000/$0/$335,000
Title:
Biomedical Imaging Research
Agency: National Health Research Institute
Project Period: 3/1/2007-2/28/2009
DC/IDC/Total: $153,500/$12,280/$165,780
Title:
Hybrid Microspect/MicroCT for
Quantitative Imaging
Agency: National Institutes of Health
Project Period: 3/1/2008-2/28/2009
DC/IDC/Total: $500,000/$0/$500,000
74

Abraham Dachman, MD
Title:
Comparison of Linear Dimensions and
Polyp Volumes in CTC
Agency: Philips Medical System
Project Period: 1/1/2007-11/30/2007
DC/IDC/Total: $10,225/$4,090/$14,315
Title:
National CT Colonography Trial
Agency: National Cancer Institute
Project Period: 1/1/2004-12/31/2007
DC/IDC/Total: $104,918/$55,082/$160,000
Kunio Doi, PhD
Title:
CAD for CT Nodules in Lung Cancer
Detection
Agency: National Cancer Institute
Project Period: 9/19/2003-8/31/2008
DC/IDC/Total: $884,771/$446,668/$1,331,439
Title:
Evaluation & Analysis of CAD Scheme
for Detection of Nodules
Agency: Riverain
Project Period: 4/1/2005-9/30/2008
DC/IDC/Total: $120,000/$48,000/$168,000
Title:
Psychophysical Measures for Selection
of Similar Images
Agency: Department of Defense/Army
Research Office
Project Period: 3/15/2005-4/14/2008
DC/IDC/Total: $83,777/$6,223/$90,000
Title:
Toshiba Research Agreement
Agency: Toshiba
Project Period: 6/1/2001-5/31/2009
DC/IDC/Total: $120,000/$48,000/$168,000
Jia-Hong Gao, PhD
Title:
3t MRI Scanner for High Resolution
MRI/MRS Research
Agency: National Institutes of Health
Project Period: 6/1/2007-5/31/2009
DC/IDC/Total: $2,000,000/$0/$2,000,000
Title:
Development & Optimization of
Magnetic Source MRI
Agency: National Institute of Biomedical
Imaging & Bioengineering
Project Period: 9/1/2004-8/31/2008
DC/IDC/Total: $257,418/$128,498/$385,916
Title:
MRI of Current Density and Current
Pathways Study
Agency: Department of Defense/Office of Navy
Research
Project Period: 1/1/2007-3/31/2008
DC/IDC/Total: $195,440/$104,560/$300,000
Title:
Support MRI of Current Density and
Current Pathways Study
Agency: Department of Defense/Office of Navy
Research
Project Period: 4/28/2008-5/28/2008
DC/IDC/Total: $14,930/$7,987/$22,917
Maryellen Giger, PhD
Title:
Computerized Radiographic Analysis
of Bone Structure
Agency: National Institute of Arthritis and
Musculoskeletal and Skin Diseases
Project Period: 4/1/2006-3/31/2010
DC/IDC/Total: $849,025/$454,229/$1,303,254
Title:
Correlative Feature Analysis for
Multimodality Breast CAD
Agency: Department of Defense/Army
Research Office
Project Period: 12/1/2006-11/30/2009
DC/IDC/Total: $90,000/$7,200/$97,200
Title:
Optimization of CAD Output in Breast
Imaging
Agency: National Cancer Institute
Project Period: 6/15/2006-5/31/2008
DC/IDC/Total: $1,022,636/$544,553/$1,567,189
Title:
Agency:
Research Training in Medical Physics
National Institute of Biomedical
Imaging & Bioengineering
Project Period: 5/1/2005-4/30/2010
DC/IDC/Total: $1,536,221/$95,913/$1,632,134
Title:
SPORE in Breast Cancer
Agency: National Cancer Institute
Project Period: 9/27/2006-7/31/2011
Total: $1,734,824
Yulei Jiang, PhD
Title:
Computer-Aided Analysis of
Histopathology Images of Prostate
Agency:
National Institute of Biomedical
Imaging & Bioengineering
Project Period: 6/15/2007-5/31/2009
DC/IDC/Total: $312,892/$117,214/$430,106
Title:
Computer-Aided Diagnosis of Breast
Lesions in Mammograms
Agency: National Cancer Institute
Project Period: 4/1/2002-6/30/2009
DC/IDC/Total: $986,616/$527,839/$1,514,455
Chien-Min Kao, PhD
Title:
Development and Evaluation of an
IGRT Technology for Prostate Cancer
Agency: American Cancer Society
Project Period: 1/1/2006-12/31/2008
DC/IDC/Total: $20,000/$0/$20,000
75

Gregory Karczmar, PhD
Title:
Detection & Evaluation of Early Breast
Cancer via MRI
Agency: Department of Defense/Army
Research Office
Project Period: 2/6/2006-3/5/2009
DC/IDC/Total: $83,333/$6,667/$90,000
Title:
Dynamic Spatial and Spectral Contrast
Enhanced MRI of Breast
Agency: National Cancer Institute
Project Period: 7/1/2005-6/30/2008
DC/IDC/Total: $254,969/$135,118/$390,087
Title:
Fast Spectroscopic MR Imaging of
Breast Cancer
Agency: National Cancer Institute
Project Period: 9/1/1999-2/28/2009
DC/IDC/Total: $652,478/$342,550/$995,028
Title:
High Spectral/Spatial Resolution
Imaging Breast Cancer
Agency: National Institute of Biomedical
Imaging & Bioengineering
Project Period: 9/15/2003-7/31/2008
DC/IDC/Total: $805,241/$422,753/$1,227,994
Title:
Implementation of Improved Spectral,
Temporal & Spatial Sampling Methods
Agency: Philips Medical System
Project Period: 4/1/2006-3/31/2008
DC/IDC/Total: $144,862/$57,945/$202,807
Title:
Microvessel Density with High
Spectral/Spatial MRI
Agency: National Cancer Institute
Project Period: 9/20/2007-8/31/2010
DC/IDC/Total: $877,942/$441,203/$1,319,145
Title:
SPORE in Breast Cancer
Agency: National Cancer Institute
Project Period: 9/27/2006-7/31/2011
Total: $1,522,490
Patrick La Rivière, PhD
Title:
Molecular Probes & System
Development for Optoacoustic
Imaging of Proteases in Breast Cancer
Agency: National Cancer Institute
Project Period: 9/27/2006-7/31/2011
DC/IDC/Total: $25,000/$13,375/$38,375
Title:
Molecular Probes & Techniques for
Optoacoustic Imaging
Agency: American Cancer Society
Project Period: 7/1/2008-6/30/2012
DC/IDC/Total: $90,000/$7,200/$97,200
Title:
Penalized Livelihood Sinogram
Smoothing & Restoration
Agency: Schweppe
Project Period: 4/1/2005-3/31/2008
DC/IDC/Total: $100,000/$0/$100,000
Title:
System Design, Algorithm
Development and Verification
Agency: Department of Defense/Army
Research Office
Project Period: 5/1/2008-5/31/2011
DC/IDC/Total: $90,000/$7,200/$97,200
Charles Metz, PhD
Title:
Improved DBM ROC Methods for
Diagnostic Radiology
Agency: National Institute of Biomedical
Imaging & Bioengineering
Project Period: 4/1/2007-3/31/2008
DC/IDC/Total: $279,919/$149,757/$429,676
Title:
Receiver Operating Characteristic (Roc)
Analysis
Agency: National Institute of Diabetes and
Digestive and Kidney Diseases
Project Period: 9/29/2007-9/28/2008
DC/IDC/Total: $232,979/$124,645/$357,624
Gillian Newstead, MD
Title:
Computer-Aided Diagnosis (CADx)
Systems for Breast MR
Agency: Philips Medical System
Project Period: 6/1/2006-5/31/2009
DC/IDC/Total: $93,000/$37,200/$130,200
Title:
New Approaches to Sampling &
Analyzing Contrast Media
Agency: National Cancer Institute
Project Period: 7/8/2005-6/30/2008
DC/IDC/Total: $233,469/$123,831/$357,300
Robert Nishikawa, PhD
Title:
A Novel Method for Determining
Image Similarity
Agency: National Institute of Biomedical
Imaging & Bioengineering
Project Period: 9/1/2005-8/31/2007
DC/IDC/Total: $100,382/$52,701/$153,083
Title:
Advanced High-Resolution Two-
Dimensional X-Ray Detector
Agency: National Institute of Biomedical
Imaging & Bioengineering
Project Period: 2/1/2008-11/30/2008
DC/IDC/Total: $44,081/$23,583/$67,664
76

Title:
Comparison of Computer-Aided
Detection on Digital & Film
Agency: Illinois Department of Public Health
Project Period: 7/1/2007-6/30/2008
DC/IDC/Total: $75,000/$0/$75,000
Title:
Computerized Lesion Detection in
Breast Tomosynthesis
Agency: National Cancer Institute
Project Period: 9/22/2006-8/31/2009
DC/IDC/Total: $604,458/$300,060/$904,518
Title:
High-Performance Computer Cluster
for Image Analysis
Agency: National Institutes of Health
Project Period: 4/1/2007-3/31/2009
DC/IDC/Total: $229,551/$0/$229,551
Title:
Optimization of Breast Tomosynthesis
Imaging Systems
Agency: Department of Defense/Army
Research Office
Project Period: 5/1/2008-5/31/2011
DC/IDC/Total: $90,000/$7,200/$97,200
Title:
Mammography Computer Aided
Detection (CAD)
Agency: Kodak
Project Period: 8/1/2006-7/31/2007
DC/IDC/Total: $40,000/$10,000/$50,000
Title:
Using CAD as a Surrogate Reader in
Observer Studies
Agency: National Institute of Biomedical
Imaging & Bioengineering
Project Period: 9/30/2005-8/31/2007
DC/IDC/Total: $275,682/$145,192/$420,874
Xiaochuan Pan, PhD
Title:
Development of Innovative MRI
Methods To
Improve Early Breast Cancer Detection
Agency: Illinois Department of Public Health
Project Period: 1/1/2008-6/30/2009
DC/IDC/Total: $100,000/$0/$100,000
Title:
Optimization of Tomosynthesis
Imaging for Improved Mass
Agency: Department of Defense/Army
Research Office
Project Period: 3/15/2006-4/14/2009
DC/IDC/Total: $83,754/$6,243/$89,997
Title:
Optimized Cone-Beam CT for Image-
Guided Radiation Therapy
Agency: National Cancer Institute
Project Period: 7/27/2007-5/31/2012
DC/IDC/Total: $1,250,000/$617,390/$1,867,390
Title:
Phase-Enhancement Micro-Computed
Tomography
Agency: Department of Energy
Project Period: 10/1/2006-9/30/2008
DC/IDC/Total: $41,000/$0/$1,000
Title:
Targeted Imaging in Helical Cone Beam
CT
Agency: National Institute of Biomedical
Imaging & Bioengineering
Project Period: 7/1/2000-8/31/2008
DC/IDC/Total: $940,101/$456,508/$1,396,609
Brian Roman, PhD
Title:
Imaging Pancreatic B-Cell Function by
Magnetic Resonance
Agency: National Institute of Biomedical
Imaging & Bioengineering
Project Period: 9/30/2003-7/31/2009
DC/IDC/Total: $981,170/$442,041/$1,423,211
Title:
NMR Detection of Gene Expression
Agency: National Heart, Lung, & Blood Institute
Project Period: 8/1/2003-7/31/2009
DC/IDC/Total: $765,440/$323,537/$1,088,977
Robert Schmidt, MD
Title:
Pilot Study: Comparison Of Konica
Minolta Regius Pure
Agency: Konica
Project Period: 3/1/2006-12/31/2007
DC/IDC/Total: $48,226/$12,057/$60,283
Emil Sidky, PhD
Title:
Helical CT Reconstruction and Lung
Cancer Screening
Agency:
National Institute of Biomedical
Imaging & Bioengineering
Project Period: 8/1/2004-7/31/2008
DC/IDC/Total: $311,803/$24,944/$336,747
Suzuki, Kenji
Title:
3D Massive Training ANN for CAD for
Colon Cancer in CT Colonography
National Cancer Institute
Agency:
Project Period: 9/26/2007-7/31/2011
DC/IDC/Total: $760,000/$406,600/$1,166,600
Title:
Advanced Computer-Aided Detection
of Colon Cancer in CT Colonography
Agency: American Cancer Society - Illinois
Division
Project Period: 4/1/2007-3/31/2009
DC/IDC/Total: $100,000/$0/$100,000
77

Title:
Analysis of Computer-Aided Detection
of Lung Nodules in Chest Radiology
Agency: Riverain
Project Period: 10/1/2006-9/30/2008
DC/IDC/Total: $60,714/$24,286/$85,000
Title:
Agency:
Development of Advanced CAD
System for Early Detection of
Colorectal Cancer in CT Colonography
Cancer Research Foundation, Young
Investigator Awards
Project Period: 1/1/2006-12/31/2007
DC/IDC/Total: $50,000/$0/$50,000
Title:
Agency:
Development & Evaluation of
Computer-Aided Detection of
Polyps in CT Colonography on False
Negative Cases in
Large Multicenter Clinical Trail
Radiological Society of North America
Research & Education Fund
Project Period: 7/1/2006-6/30/2008
DC/IDC/Total: $30,000/$0/$30,000
Hodges Alumni Reception, November 26, 2007 at Rhapsody.
78

The Annual Faculty Holiday Party,
December 8, 2007 at The Art Institute of Chicago.
79

The Staff Holiday Party, December 21, 2007 at Ida Noyes Hall.
Graduation Party for the Residents,
June 7, 2008 at N9NE Steakhouse.
80

Department Administration
RICHARD L. BARON, MD
Chairman
DAVID M. PAUSHTER, MD
Executive Vice Chair, Clinical Operations
MARYELLEN L. GIGER, PHD
Vice Chair for Basic Science Research
MICHAEL VANNIER, MD
Vice Chair for Clinical Research
MONICA GEYER, MBA
Interim Executive Administrator
Assistant Director, Specialty Imaging
DIANE BERNAHL, MHA, CPC
Assistant Director, Practice Operations & Faculty Affairs
THOMAS COLLINS, CBET
Assistant Director, Radiology Engineering
MILTON GRIFFIN
Assistant Director, General Imaging
ANISSHA WARNER, MBA
Assistant Director, Finance
GILLIAN NEWSTEAD, MD
BREAST IMAGING
DAVID PAUSHTER, MD
ABDOMINAL IMAGING
JORDAN ROSENBLUM, MD
NEURORADIOLOGY
G. SCOTT STACY, MD
MUSCULOSKELETAL IMAGING
EDUCATION DIRECTORS
MARYELLEN GIGER, PHD
DIRECTOR, GRADUATE PROGRAMS IN
MEDICAL PHYSICS
JORDAN ROSENBLUM, MD
DIRECTOR, RESIDENCY PROGRAM
CHRISTOPHER STRAUS, MD
DIRECTOR, MEDICAL STUDENT EDUCATION
LARRY DIXON, MD
ASSOCIATE DIRECTOR, RESIDENCY PROGRAM
SECTION CHIEFS
DANIEL APPELBAUM, MD
NUCLEAR MEDICINE
KATE FEINSTEIN, MD
PEDIATRIC IMAGING
BRIAN FUNAKI, MD
VASCULAR AND INTERVENTIONAL RADIOLOGY
MARYELLEN GIGER, PHD
RADIOLOGICAL SCIENCES
JEFFREY LEEF, MD
WEISS HOSPITAL IMAGING
HEBER MACMAHON, MD
THORACIC IMAGING
FELLOWSHIP DIRECTORS
DELILAH BURROWES, MD
DIRECTOR, NEURORADIOLOGY
FELLOWSHIP PROGRAM
ABRAHAM DACHMAN, MD
DIRECTOR, ABDOMINAL FELLOWSHIP PROGRAM
LARRY DIXON, MD
DIRECTOR, MUSCULOSKELETAL
FELLOWSHIP PROGRAM
JONATHAN LORENZ, MD
DIRECTOR, INTERVENTIONAL RADIOLOGY
FELLOWSHIP PROGRAM
GILLIAN NEWSTEAD, MD
DIRECTOR, BREAST IMAGING FELLOWSHIP
PROGRAM
81

Faculty, Clinical Fellows,
Residents & Researchers
Clinical Faculty
Hiroyuki Abe, MD
Daniel Appelbaum, MD
Richard Baron, MD
Delilah Burrowes, MD
Paul Chang, MD
Abraham Dachman, MD
Larry Dixon, MD
Kate Feinstein, MD
Brian Funaki, MD
Arunas Gasparaitis, MD
Jeffrey Leef, MD
Jonathan Lorenz, MD
Heber MacMahon, MD
Saeid Mojtahedi, MD
Steven Montner, MD
Gillian Newstead, MD
Aytekin Oto, MD
David Paushter, MD
Yonglin Pu, MD
Sidney Regalado, MD
Jordan Rosenblum, MD
Robert Schmidt, MD,
Vivek Sehgal, MD
Charlene Sennett, MD
Gregory Scott Stacy, MD
Christopher Straus, MD
Thuong VanHa, MD
Michael Vannier, MD
David Yousefzadeh, MD
Steve Zangan, MD
Mario Zaritzky, MD
Science Faculty
Samuel Armato III, PhD
Chin Tu Chen, PhD
Kunio Doi, PhD
Jia Hong Gao, PhD
Maryellen Giger, PhD
Yulei Jiang, PhD
Chien-Min Kao, PhD
Greg Karczmar, PhD
Patrick LaRiviere, PhD
Charles Metz, PhD
Robert Nishikawa, PhD
Bill O’Brien-Penney, PhD
Xiaochuan Pan, PhD
Brian Roman, PhD
Kenju Suzuki, PhD
Clinical Associates
Gabriel Angres, MD
Alexandra Funaki, DO
Brent Greenberg, MD
Stephanie Rosania, MD
Clinical Professors
Peter Doris, MD
Clinical Fellows
Rashid Alsukaiti, MD
Kirti Kulkarni, MD
Shital Makim, MD
Saad Naseer, MD
Scott Santeler, MD
Susan Sung, MD
Residents
(First Year)
Christopher Buckle, MD
Danny Cheng, MD
Jack Collins, MD
Nicholas Krause, MD
Jay Patel, MD
Sarah Ronan, MD
William Whetsell, MD
(Second Year)
Anna Abramovitch, MD
Michael Hutchinson, MD
Vicky Lin, MD
Hao Lo, MD
Evan Nichols, MD
Michael Noud, MD
David Schacht, MD
(Third Year)
Samantha Fienberg, MD
Monica Harish, MD
Gregory Henkle, MD
Sheela Konda, MD
Albert Li, MD
Michael Lester, MD
Christopher Molvar, MD
(Fourth Year)
Joseph Carabetta, MD
Rodney Corby, MD
Phil Kurzman, MD
Rajshri Shah, MD
Steven Thiel, MD
Carl Valentin, MD
Ivica Vucic, MD
Research Associates with Rank
Karen Drukker, PhD
Darrin Edwards, PhD
Xiaobing Fan, PhD
Chad Haney PhD
Feng Li, PhD
Hui Li, PhD
Milica Medved, PhD
Ingrid Reiser, PhD
Junji Shiraishi, PhD
Emil Sidky, PhD
Ming Chi Shih, PhD
Jeffrey Souris, PhD
Post Doctoral Scholars
Michael Chinander, PhD
Lara Leoni, PhD
Guihua Zhai, PhD
Post Doctoral Fellows
Hee-Jong Kim, PhD
Ji Li, PhD
Visiting Appointments
Ryohei Nakayama, PhD
Katsutoshi Sugimoto, PhD
Emeritus
John Fennessy, MD
Martin Lipton, MD
Chien-Tai Lu, MD
Secondary Appointments
in Radiology
Jonathan Silverstein, MD
Kim Williams, MD
82

Department Of Radiology University Chicago 2008

THE UNIVERSITY OF CHICAGO
DIVISION OF BIOLOGICAL SCIENCES
DEPARTMENT OF RADIOLOGY
5841 SOUTH MARYLAND AVENUE
CHICAGO, IL 60637
WWW.RADIOLOGY.UCHICAGO.EDU