AUTHORS: Lu PJ, Barakovic M, Weigel M, Rahmanzadeh R, Galbusera R, Schiavi S, Daducc A, La Rosa F, Bach Cuadra M, Sandkühler R, Kuhle J, Kappos L, Cattin P, Granziera C
Proceedings of the 29th ISMRM & SMRT Annual Meeting, : , Online, May 2021
ABSTRACT
We applied an attention-based convolutional neural network to select discriminating diffusion measures derived from mathematical models of multi-shell diffusion data in the classification of multiple sclerosis lesions. Further, we correlated the selected measures or their combinations with the Expanded Disability Status Scale (EDSS) and the serum level of neurofilament light chain (sNfL). Our results show that the combinations have stronger correlations with EDSS and sNfL than the individual measures. The proposed method might be useful for selecting the microstructural measures most discriminative of focal tissue damage and identifying the combination most related to clinical disability and neuroaxonal damage.
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Module: SP
