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Abstract #2150

Multiparametric metabolic and physiologic MR-Imaging models for differentiating tumor from treatment effects in patients suspected of recurrent glioblastoma

Julia Cluceru1, Sarah Nelson1, Annette Molinaro1, Joanna Phillips1, Marram Olson1, Marisa LaFontaine1, Angela Jakary1, Devika Nair1, Soonmee Cha1, Susan Chang1, and Janine Lupo1

1Department of Radiology and Biomedical Imaging, UCSF, San Francisco, CA, United States

Despite previous research on physiological and metabolic MR imaging techniques with standard clinical anatomical MRI of patients with recurrent glioma, there is still no one parameter that can differentiate recurrent glioblastoma (rGBM) from treatment-induced effects (TxE) with high enough accuracy to be used clinically. We assessed the value of incorporating anatomical, perfusion-weighted, diffusion-weighted, and spectroscopic imaging parameters to identify TxE in patients suspected of rGBM. nPH from DSC perfusion-weighted imaging and Choline-to-NAA Index from MR spectroscopic imaging were found to be the most related to pathological markers of tumor and TxE.

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