Eloy Martinez-Heras
Diffusion-based structural connectivity patterns of multiple sclerosis phenotypes
Martinez-Heras, Eloy; Solana, Elisabeth; Vivó, Francesc; Lopez-Soley, Elisabet; Calvi, Alberto; Alba-Arbalat, Salut; Schoonheim, Menno M; Strijbis, Eva M; Vrenken, Hugo; Barkhof, Frederik; Rocca, Maria A; Filippi, Massimo; Pagani, Elisabetta; Groppa, Sergiu; Fleischer, Vincenz; Dineen, Robert A; Ballenberg, Barbara; Lukas, Carsten; Pareto, Deborah; Rovira, Alex; Sastre-Garriga, Jaume; Collorone, Sara; Prados, Ferran; Toosy, Ahmed; Ciccarelli, Olga; Saiz, Albert; Blanco, Yolanda; Llufriu, Sara
Authors
Elisabeth Solana
Francesc Vivó
Elisabet Lopez-Soley
Alberto Calvi
Salut Alba-Arbalat
Menno M Schoonheim
Eva M Strijbis
Hugo Vrenken
Frederik Barkhof
Maria A Rocca
Massimo Filippi
Elisabetta Pagani
Sergiu Groppa
Vincenz Fleischer
ROBERT DINEEN rob.dineen@nottingham.ac.uk
Professor of Neuroradiology
Barbara Ballenberg
Carsten Lukas
Deborah Pareto
Alex Rovira
Jaume Sastre-Garriga
Sara Collorone
Ferran Prados
Ahmed Toosy
Olga Ciccarelli
Albert Saiz
Yolanda Blanco
Sara Llufriu
Abstract
Background: We aimed to describe the severity of the changes in brain diffusion-based connectivity as multiple sclerosis (MS) progresses and the microstructural characteristics of these networks that are associated with distinct MS phenotypes.
Methods: Clinical information and brain MRIs were collected from 221 healthy individuals and 823 people with MS at 8 MAGNIMS centres. The patients were divided into four clinical phenotypes: clinically isolated syndrome, relapsing-remitting, secondary progressive and primary progressive. Advanced tractography methods were used to obtain connectivity matrices. Then, differences in whole-brain and nodal graph-derived measures, and in the fractional anisotropy of connections between groups were analysed. Support vector machine algorithms were used to classify groups.
Results: Clinically isolated syndrome and relapsing-remitting patients shared similar network changes relative to controls. However, most global and local network properties differed in secondary progressive patients compared with the other groups, with lower fractional anisotropy in most connections. Primary progressive participants had fewer differences in global and local graph measures compared with clinically isolated syndrome and relapsing-remitting patients, and reductions in fractional anisotropy were only evident for a few connections. The accuracy of support vector machine to discriminate patients from healthy controls based on connection was 81%, and ranged between 64% and 74% in distinguishing among the clinical phenotypes.
Conclusions: 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.
Citation
Martinez-Heras, E., Solana, E., Vivó, F., Lopez-Soley, E., Calvi, A., Alba-Arbalat, S., …Llufriu, S. (2023). Diffusion-based structural connectivity patterns of multiple sclerosis phenotypes. Journal of Neurology, Neurosurgery and Psychiatry, 94(11), 916-923. https://doi.org/10.1136/jnnp-2023-331531
Journal Article Type | Article |
---|---|
Acceptance Date | May 30, 2023 |
Online Publication Date | Jun 15, 2023 |
Publication Date | 2023-11 |
Deposit Date | Jun 16, 2023 |
Publicly Available Date | Jun 16, 2023 |
Journal | Journal of Neurology, Neurosurgery and Psychiatry |
Print ISSN | 0022-3050 |
Electronic ISSN | 1468-330X |
Publisher | BMJ Publishing Group |
Peer Reviewed | Peer Reviewed |
Volume | 94 |
Issue | 11 |
Pages | 916-923 |
DOI | https://doi.org/10.1136/jnnp-2023-331531 |
Public URL | https://nottingham-repository.worktribe.com/output/19010097 |
Publisher URL | https://jnnp.bmj.com/content/94/11/916 |
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