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Abstract #0185

Probabilistic Functional Diffusion Maps (FDMs) in Human Glioblastoma

Benjamin M. Ellingson1, Timothy F. Cloughesy2, Albert Lai2, Phioanh L. Nghiemphu2, Whitney B. Pope1

1Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States; 2Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States

Functional diffusion mapping (fDM) uses the voxel-wise changes in apparent diffusion coefficient (ADC) measured in the same patient over time as a biomarker for cancer response to therapy. FDMS have been shown to be predictive of response and survival in glioblastoma under a variety of treatment paradigms. The current study develops a probabilistic approach to fDM quantification, where finite translational and rotational perturbations are performed after initial registration of ADC maps. These probabilistic fDMs were applied to newly diagnosed glioblastoma patients treated with standard radiochemotherapy (n = 143). Results suggest probabilistic fDMs have higher clinical sensitivity compared with traditional fDMs.