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Abstract #3860

Assessment of metabolic heterogeneity in glioblastoma multiforme (GBM) through histogram analysis of whole-brain echo planar spectroscopic imaging

Gaurav Verma1, Sanjeev Chawla2, Suyash Mohan2, Sumei Wang2, Rebecca Emily Feldman1, MacLean Nasrallah3, Steven Brem4, Donald O'Rourke4, Harish Poptani5, and Priti Balchandani1

1Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States, 2Neuroradiology, Hospital of the University of Pennsylvania, Philadelphia, PA, United States, 3Pathology, Hospital of the University of Pennsylvania, Philadelphia, PA, United States, 4Neurosurgery, Hospital of the University of Pennsylvania, Philadelphia, PA, United States, 5Cellular and Molecular Physiology, University of Liverpool, Liverpool, United Kingdom

Glioblastoma multiforme (GBM) is an infiltrating and heterogeneous disease with low median survival and over 70% recurrence rates, though 20-30% of progressive enhancing lesions seen in GBM post-treatment exhibit pseudoprogression rather than true recurrent tumor. Differentiating these could improve speed and accuracy of treatment. A statistical and histogram analysis of segmented high-resolution echo-planar spectroscopic imaging data goes beyond mean metabolite ratios to show distribution of Cho/NAA and Cho/Cr ratios in contrast enhancing regions and the surrounding tissue. Cho/NAA distribution in enhancing region showed greater kurtosis than Cho/Cr, suggesting reduction in NAA may be a driving factor in observed Cho/NAA increases.

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