2012 EDUCATIONAL BOOK - American Society of Clinical Oncology

Current Concepts in Brain Tumor Imaging
By Andrew D. Norden, MD, MPH, Whitney B. Pope, MD, PhD, and Susan M. Chang, MD
Overview: Magnetic resonance imaging (MRI) is the most
useful imaging tool in the evaluation of patients with brain
tumors. Most information is supplied by standard anatomic
images that were developed in the 1980s and 1990s. More
recently, functional imaging including diffusion and perfusion
MRI has been investigated as a way to generate predictive and
prognostic biomarkers for high-grade glioma evaluation, but
additional research is needed to establish the added benefits
of these indices to standard MRI. Response critieria for
high-grade gliomas have recently been updated by the Response
Assessment in Neuro-Oncology (RANO) working
THE FIRST published magnetic resonance image (MRI)
was from a paper in the journal Nature by Nobel Prize
Laureate Paul Lauterbur in 1973. 1 By 1981, magnetic resonance
had been used for imaging the brain, demonstrated
the pathologic appearance of glioblastoma (GBM), and
compared favorably to computed tomography (CT) as the
“posterior fossa was visualized with substantially less artifact.
...” 2 MRI was noted to detect tumors not seen on CT as
early as 1982, and this led quickly to an explosion of articles
evaluating MRI of brain tumors and other intracranial
pathology. T1- and T2-weighted images were quickly adopted
as standard imaging along with multiple planar scanning.
Gadolinium-based contrast agents were introduced
around 1984, 3 as were high-field strength superconducting
(1.5 Tesla) scanners. 4 Another advance in brain tumor
imaging occurred in the late 1990s with the introduction of
fluid-attenuated inversion recovery (FLAIR) sequences that
generated strongly T2-weighted images although signal associated
with cerebrospinal fluid (CSF) was suppressed. 5
Today, MRI remains the imaging modality of choice for
tumor diagnosis, characterization, and assessment of treatment
response.
Conventional MRI in Neuro-Oncology
MRI has traditionally been used to evaluate tumor location,
size and extent, mass effect, involvement of critical
structures such as adjacent blood vessels, and compromise of
the blood-brain barrier (which results in contrast enhancement).
The typical MR scan for a patient with glioma
includes sagittal T1, axial T1, T2, FLAIR and postcontrast
axial and coronal T1-weighted images. Recently pulse sequences
sensitive to physiology, rather than just anatomy,
are being more commonly used (see following). Changes in
enhancing tumor size based on bidimensional measurements
of postcontrast T1-weighted images are the basis for
both the Macdonald and later RANO criteria for evaluating
tumor response. 6 Conversely, nonenhancing tumor is assessed
qualitatively in RANO, but not at all in the Macdonald
criteria. Nonenhancing tumor is typified by areas of
increased T2 signal intensity associated with mass effect
and architectural distortion such as blurring of the graywhite
interface. 7 Edema and treatment effect including
gliosis also result in increased T2 signal, which can make
nonenhancing tumor difficult to quantify. FLAIR is more
sensitive to T2 signal abnormalities, as a result of the
nulling of CSF, thereby overcoming the limitation of partial
volume averaging in the cortical and periventricular regions
group. The new criteria account for nonenhancing tumor in
addition to the contrast-enhancing abnormalities on which
older criteria relied. This issue has recently come to the fore
with the introduction of the antiangiogenic agent bevacizumab
into standard treatment for recurrent glioblastoma. Because
of its potent antipermeability effect, contrast enhancement is
markedly reduced in patients who receive bevacizumab. The
RANO criteria also address the phenomenon of pseudoprogression,
in which there may be transient MRI worsening of a
glioblastoma following concurrent radiotherapy and temozolomide.
as can be seen in standard T2 images. However, FLAIR also
reduces gray-white differentiation in comparison to typical
T2-weighted images, which can diminish the image reader’s
ability to distinguish the T2 changes that are a result of
tumor compared with T2 changes that are the result of
edema and/or gliosis. Thus, T2 and FLAIR images can
provide complementary information, and both should be
acquired for evaluation of patients with brain tumors.
Although relying on changes in enhancing tumor previously
worked well for evaluating treatment response, the
widespread adoption of bevacizumab therapy for recurrent
GBM highlights the limitations of this approach. This limitation
stems largely from bevacizumab’s antipermeability
effect. GBMs are characterized by extensive abnormal vasculature
with a leaky blood-brain barrier. 8 As a result,
contrast material extravasates out of tumor vessels, leading
to increased signal on gadolinium-enhanced T1-weighted
images. Bevacizumab sequesters vascular endothelial
growth factor (VEGF), a potent permeability factor and
promoter of angiogenesis, and thereby acts to diminish
contrast enhancement. Therefore a reduction in contrast
enhancement following bevacizumab infusion may not necessarily
reflect a cytotoxic tumor effect. Relying on the
change in contrast enhancement alone can thus misrepresent
treatment response, a phenomenon known as “pseudoresponse.”
9,10
Although the RANO criteria include FLAIR or T2 hyperintensity
changes as potentially indicative of nonenhancing
tumor progression, no quantification of nonenhancing tumor
is performed. This is because of difficulties in determining
the borders of T2 abnormal regions as well as differentiating
gliosis and other treatment effects from tumor. This has
spurred interest in physiologic imaging as a way of obtaining
quantitative data on tumor burden, although to date, this
goal has not been fully realized.
From Dana-Farber Cancer Institute and Brigham and Women’s Hospital, Boston, MA;
David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA;
University of California, San Francisco, Department of Neurological Surgery, San Francisco,
CA.
Authors’ disclosures of potential conflicts of interest are found at the end of this article.
Address reprint requests to Susan M. Chang, MD, University of California, San
Francisco, Department of Neurological Surgery, 400 Parnassus Ave., A808, San Francisco,
CA 94143-0372; email: changs@neurosurg.ucsf.edu.
© 2012 by American Society of Clinical Oncology.
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