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Case 28 - Low-grade oligodendroglioma

Published online by Cambridge University Press:  18 December 2013

Nafi Aygun
Affiliation:
The Johns Hopkins University
Gaurang Shah
Affiliation:
University of Michigan Health System
Dheeraj Gandhi
Affiliation:
University of Maryland Medical Center
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Summary

Imaging description

Relative cerebral blood volume (rCBV) measurement derived from perfusion-weighted imaging (PWI) is shown to predict the grade of gliomas [1,2]. WHO grade II gliomas show lower rCBV than WHO grade III and IV gliomas. This is based on rCBV’s ability to accurately predict microvascular density (MVD) within a tumor. MVD is a measure of angiogenesis and is associated with various cytogenetic and molecular features including vascular endothelial growth factor (VEGF) and epidermal growth factor receptor (EGFR) expression/overexpression. Although demonstration of high rCBV within a brain tumor appears to be a good predictor of aggressive behavior and higher grade, limitations do exist, presumably because of the heterogeneity present between various types of tumors and their cytogenetic features.

One such limitation is apparent in the evaluation of oligodendrogliomas (ODGs) [3]. Certain low-grade ODGs show increased rCBV (Figs. 28.1, 28.2). The most common cytogenetic aberrations in ODGs are losses on chromosomes 1p (60%), 19q (60–70%), and 10q (25%). In particular, combined allelic loss (loss of heterozygosity, LOH) on chromosomes 1p and 19q is associated with both chemosensitivity and longer survival after chemotherapy. Recently, it has been shown that WHO grade II ODGs that have 1p and 19q LOH (which is associated with better outcome) demonstrate higher rCBV values on PWI MRI as compared to ODGs that have intact 1p and 19q (which is associated with worse outcome), in stark contrast to astrocytomas, in which increased rCBV predicts higher grade [4].

Type
Chapter
Information
Pearls and Pitfalls in Head and Neck and Neuroimaging
Variants and Other Difficult Diagnoses
, pp. 114 - 115
Publisher: Cambridge University Press
Print publication year: 2013

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References

Law, M, Yang, S, Wang, H, et al. Glioma grading: sensitivity, specificity, and predictive values of perfusion MR imaging and proton MR spectroscopic imaging compared with conventional MR imaging. AJNR Am J Neuroradiol 2003; 24: 1989–98.Google ScholarPubMed
Preul, C, Kuhn, B, Lang, EW, et al. Differentiation of cerebral tumors using multi-section echo planar MR perfusion imaging. Eur J Radiol 2003; 48: 244–51.CrossRefGoogle ScholarPubMed
Whitmore, RG, Krejza, J, Kapoor, GS, et al. Prediction of oligodendroglial tumor subtype and grade using perfusion weighted magnetic resonance imaging. 2007 J Neurosurg 107: 600–9.CrossRefGoogle ScholarPubMed
Kapoor, GS, Gocke, TA, Chawla, S, et al. Magnetic resonance perfusion-weighted imaging defines angiogenic subtypes of oligodendroglioma according to 1p19q and EGFR status. J Neurooncol 2009; 92: 373–86.CrossRefGoogle ScholarPubMed

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