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Abstract #2804

Automatic Segmentation of Diffusely Abnormal White Matter in MS Using Deep Neural Network

Refaat E Gabr1 and Ponnada A Narayana1
1Diagnostic and Interventional Imaging, University of Texas Health Science Center at Houston, Houston, TX, United States

Deep neural network was used to automatically segment diffusely abnormal white matter (DAWM) in 100 relapsing remitting multiple sclerosis patients (RRMS). Our calculated DAWM prevalence of 32% is comparable to ~ 25% reported elsewhere. Based on our studies, only 13% of T2 lesions at baseline converted into DAWM by 60 months. Of the DAWM detected at baseline, only 15% converted to lesions, 45% persisted, and 40% resolved (converted to NAWM). These initial results suggest that DAWM may present a significant disease burden by itself.

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