TRADITIONAL POSTER - ismrm

Poster Sessions
1661. Characterization of White Matter Fasciculi with T1 Quantification: A Feasibility Study at High Field
Nico Dario Papinutto 1 , Jorge Jovicich 1
1 Center for Mind/Brain Sciences, University of Trento, Mattarello, Trento, Italy
Diffusion tensor imaging (DTI) of in-vivo human brains is a technique that is becoming widely used to get insight into normal and abnormal white matter
anatomical connectivity. Characterization of pathologies with fractional anisotropy (FA) losses have been done, both at voxel level and along tracts. A
promising method to further improve the characterization of main streamlines consists on adding relaxation times measurements. We present a simple
method for T1 quantification of white matter tracts using sequences available in most commercial scanners.
1662. Gradual Variation of Anatomical Connectivity in the Macaque Insula Revealed by Probabilistic
Tractography
Leonardo Cerliani 1 , Helen D'Arceuil 2 , Rajat M. Thomas 3 , Saad Jbabdi 4 , Christian M. Keysers 1
1 Neuroscience, University Medical Center Groningen, Neuroimaging Center, Groningen, Netherlands; 2 Dept. of Radiology, Athinoula
A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, United States; 3 Kapteyn Astronomical Institute,
University of Groningen, Netherlands; 4 FMRIB Centre, Univ. of Oxford, John Radcliffe Hospital, United Kingdom
The connectivity of the macaque insula was analyzed by means of probabilistic tractography on diffusion-weighted images. The main aim was to detect and
analyze trajectories of connectivity variation in this brain region, and to test the consistency of the results with the available anatomical evidence from
animal literature. The employed method of laplacian eigenmaps was able to recover the expected gradual change in connectivity, and to discriminate this
with the sharp transition in connectivity featured by the medial motor cortex
1663. Assessment of the Reproducibility of HARDI Tractography Based Cortical Connectivity Measures
Suitable for Clinical Populations Using a Bootstrap Approach
Kerstin Pannek 1,2 , Jane Mathias 3 , James Taylor 4 , Parnesh Raniga 5 , Olivier Salvado 5 , Stephen Rose 1,2
1 Centre for Magnetic Resonance, University of Queensland, Brisbane, Queensland, Australia; 2 UQ Centre for Clinical Research,
University of Queensland, Brisbane, Queensland, Australia; 3 School of Psychology, University of Adelaide, Adelaide, South
Australia, Australia; 4 Magnetic Resonance Imaging Unit, Royal Adelaide Hospital, Adelaide, South Australia, Australia; 5 The
Australian E-Health Research Centre, CSIRO, Brisbane, Queensland, Australia
Structural connectivity of the brain using MR diffusion tractography has gained significant interest. A connectivity matrix of cortical connectivity may
provide unique insight into brain organisation. We aimed to develop a method to determine the number of seeds required to obtain stable and reproducible
connectivity, and to assess reproducibility over time. We employ a bootstrap approach for estimation of these parameters. While connectivity measures of
some regions are highly reproducible over time, other connections show poor reproducibility. This study highlights the relationship between seed number
and reproducibility of connectivity.
1664. Validation of in Vivo Mouse Brain Fiber Tracking with Correlative Axonal Tracing in Wild-Type and
Reeler Animals
Laura-Adela Harsan 1 , Csaba David 2 , Marco Reisert 1 , Susanne Schnell 1 , Jürgen Hennig 1 , Dominik von
Elverfeldt 1 , Jochen F. Staiger 2
1 Department of Diagnostic Radiology, Medical Physics, University Hospital, Freiburg, Germany; 2 Department of Neuroanatomy,
Institute for Anatomy and Cell Biology, Freiburg, Germany
The present study validates an in-vivo DT-MRI and FT protocol capable of identifying and characterizing the subtle connection pathways in the living
mouse brain. The reconstructions of the thalamocortical projections derived from in-vivo DT-MRI were co-registered and correlated with 3D reconstructions
of the fibers labeled with Phaseolus vulgaris-leucoagglutinin histological tracer, injected in the thalamus of the same animal. Good agreement between the
deterministic and probabilistic tractography and the histological tracing was obtained in wild type and reeler mutant brains
1665. Challenges of Cortical Connectivity Measurements Using MR Tractography
Ann Sunah Choe 1,2 , Yurui Gao 1,3 , Iwona Stepniewska 4 , Xia Li 5 , Zhaohua Ding 5 , Adam W. Anderson 1,3
1 Biomedical Engineering, Vanderbilt University, Nashville, TN, United States; 2 Vanderbilt University Institute of Imaging Science,
Vanderbilt University, Nashville, TN, United States; 3 Vanderbilt University Institute of Imaging Science , Vanderbilt University,
Nashville, TN, United States; 4 Department of Psychology, Vanderbilt University, Nashville, TN, United States; 5 Vanderbilt University
Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States
Study of anatomical connections often involves tracing fiber bundles to and from cortical areas of interest. The fiber tracking involved in such studies
presents some unique problems. One of the challenges is the low diffusion anisotropy in gray matter, and the high directional uncertainty this causes. This
problem is often circumvented by placing seed regions within the subcortical white matter, below the target regions of cortex. This approach risks tracking
erroneous fibers due to limited spatial resolution and the complex interface between white and gray matter. In this abstract, the risk of such approaches is
demonstrated by comparing DTI fiber pathways to histological sections of the corresponding regions.
1666. Piconmat.com Version 2.0: A Web-Based Probabilistic Tractography Data Service
Chris James Rose 1,2 , David Morris 1,2 , Hamied Haroon 1,2 , Karl Embleton, 2,3 , Nikos Logothetis 1,4 , Matthew
Lambon Ralph 3 , Geoffrey J. Parker 1,2
1 Imaging Science and Biomedical Engineering, The University of Manchester, Manchester, United Kingdom; 2 The University of
Manchester Biomedical Imaging Institute, Manchester, United Kingdom; 3 School of Psychological Sciences, The University of
Manchester, Manchester, United Kingdom; 4 Max Planck Institute for Biological Cybernetics, Tübingen, Germany
We present version 2.0 of piconmat.com, a freely-available web-based system for exploring connectivity strengths between cortical and subcortical regions
in a database of individuals. Connectivity strength is computed using diffusion MRI and probabilistic tractography. Version 2.0 is a significant update:
connectivity strengths are presented in an interactive connectivity matrix and controls allow the user to study connectivity in individuals who meet certain