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Abstract #0187

MRI-PET Guided Surgical Targeting & Generation of Parametric Maps Reflecting Cellular Proliferation & Microvascular Permeability in High Grade Gliomas

Mohan Pauliah1, Philip H. Gutin2, Heiko Schoder2, Cameron Brennan2, Michelle S. Bradbury3, 4

1Radiology, Memorial Sloan Kettering Cancer Center, New York , United States; 2Neurosurgery, Memorial Sloan Kettering Cancer Center, New York, United States; 3Radiology, Memorial Sloan Kettering Cancer Center, New York, United States; 4Molecular Imaging, Memorial Sloan Kettering Cancer Center, New York, United States

By integrating functional and metabolic imaging technologies, increasingly more sensitive and specific read-outs reflecting the biological status of tumors may be obtained which, in turn, may improve characterization and direct targeted biopsy efforts. The purposes of our study are three-fold: (1) investigate the feasibility of deriving voxel-wise parameter estimates reflecting tumor cell proliferation, metabolic flux, and microvascular permeability in high grade glial tumors from precisely co-registered dynamic 18F-FLT PET and DCE-MRI with histologic correlation and (2) to investigate relationships among voxel-based determinations of PET- and MRI-based kinetic parameters during the first-pass and equilibrium phases of the study. In addition, targeted biopsy specimens were acquired using frameless stereotactic surgery and intraoperative MRI to determine whether parametric images are predictive of regional histologic assays of tumor cell proliferation and microvascular density. Quantitative accuracy of parametric images is also being evaluated through comparison of histologic determinations and gene expression differences, obtained at different biopsy locations, with the PET-MRI imaging features at those same locations. Given the high degree of heterogeneity of glial tumors, the molecular characteristics and functional imaging correlation on the same tumor areas may facilitate the development of novel therapies and yield increasingly more accurate prognostic information on the basis of key biomarkers.