Diffusion-based structural connectivity patterns of multiple sclerosis phenotypes.

Eloy Martinez-HerasElisabeth SolanaFrancesc VivóElisabet Lopez-SoleyAlberto CalviSalut Alba-ArbalatMenno Michiel Schoonheim Eva M M StrijbisHugo VrenkenFrederik BarkhofMaria Assunta Rocca Massimo FilippiElisabetta PaganiSergiu Groppa Vinzenz Fleischer Robert A DineenBarbara BellenbergCarsten LukasDeborah ParetoÀlex Rovira Jaume Sastre-Garriga Collorone SaraFerran PradosAhmed ToosyOlga CiccarelliAlbert SaizYolanda BlancoSara Llufriu

Published in: Journal of neurology, neurosurgery, and psychiatry (2023)

In conclusion, brain connectivity is disrupted in MS and has differential patterns according to the phenotype. Secondary progressive is associated with more widespread changes in connectivity. Additionally, classification tasks can distinguish between MS types, with subcortical connections being the most important factor.

Keyphrases

multiple sclerosis
white matter
resting state
functional connectivity
machine learning
deep learning
mass spectrometry
ms ms
working memory