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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