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Abstract #2746

T2 Relaxometry in the Prediction of Progression-Free Survival in Patients with Primary Glioblastoma: Whole Brain and Deep Learning Approach

Aaron Rulseh1 and Josef Vymazal1
1Dept. of Radiology, Na Homolce Hospital, Prague, Czech Republic


Glioblastoma (GBM) is the most common and aggressive primary brain tumor. Any methods that may improve confirmation or early detection of progression are highly desirable. T2 relaxometry shows great promise in the monitoring of GBM patients following complex therapy. We found WB metrics, such as median 1/T2, correlated with PFS and were able to distinguish progression from pseudo-progression. A deep neural network trained on automatically segmented 1/T2 data achieved an F1 accuracy of 85% in classifying progression with a threshold of 18 months.

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