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Abstract #2910

Detection of Tumor Progression in Patients with Glioblastoma using Multiparametric MRI

Sumei Wang1, Sanjeev Chawla1, Tianyu Yin1, Chakri Madla1, Ruyun Jin2, MacLean P Nasrallah3, Arati Desai4, Steven Brem5, Ronald Wolf1, Suyash Mohan1, and Harish Poptani6

1Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States, 2Medical Data Research Center, Providence Health & Services, Portland, OR, United States, 3Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States, 4Hematology-Oncology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States, 5Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States, 6Cellular and Molecular Physiology, University of Liverpool, Liverpool, United Kingdom

The study was performed to determine whether progression probabilities (PP) from DTI and DSC parameters can aid in differentiating glioblastomas with true-progression (TP) from pseudo-progression (PsP). MRI data from thirty-nine patients were included. All patients underwent at least two MR scans before pathological confirmation. TP patients tended to have high baseline PP values compared with PsP patients. An increase of PP of more than 25% at follow-up scans was noted in 12/15 TP patients, whereas stable or decreased PP were observed in 21/24 PsP patients. These results indicate that monitoring changes in PP values may aid in identifying TP.

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