Titre
Present and future of the diagnostic work-up of multiple sclerosis: the imaging perspective.
Type
article
Institution
UNIL/CHUV/Unisanté + institutions partenaires
Périodique
Auteur(s)
Filippi, M.
Auteure/Auteur
Preziosa, P.
Auteure/Auteur
Arnold, D.L.
Auteure/Auteur
Barkhof, F.
Auteure/Auteur
Harrison, D.M.
Auteure/Auteur
Maggi, P.
Auteure/Auteur
Mainero, C.
Auteure/Auteur
Montalban, X.
Auteure/Auteur
Sechi, E.
Auteure/Auteur
Weinshenker, B.G.
Auteure/Auteur
Rocca, M.A.
Auteure/Auteur
Liens vers les unités
ISSN
1432-1459
Statut éditorial
Publié
Date de publication
2023-03
Volume
270
Numéro
3
Première page
1286
Dernière page/numéro d’article
1299
Peer-reviewed
Oui
Langue
anglais
Notes
Publication types: Journal Article ; Review
Publication Status: ppublish
Publication Status: ppublish
Résumé
In recent years, the use of magnetic resonance imaging (MRI) for the diagnostic work-up of multiple sclerosis (MS) has evolved considerably. The 2017 McDonald criteria show high sensitivity and accuracy in predicting a second clinical attack in patients with a typical clinically isolated syndrome and allow an earlier diagnosis of MS. They have been validated, are evidence-based, simplify the clinical use of MRI criteria and improve MS patients' management. However, to limit the risk of misdiagnosis, they should be applied by expert clinicians only after the careful exclusion of alternative diagnoses. Recently, new MRI markers have been proposed to improve diagnostic specificity for MS and reduce the risk of misdiagnosis. The central vein sign and chronic active lesions (i.e., paramagnetic rim lesions) may increase the specificity of MS diagnostic criteria, but further effort is necessary to validate and standardize their assessment before implementing them in the clinical setting. The feasibility of subpial demyelination assessment and the clinical relevance of leptomeningeal enhancement evaluation in the diagnostic work-up of MS appear more limited. Artificial intelligence tools may capture MRI attributes that are beyond the human perception, and, in the future, artificial intelligence may complement human assessment to further ameliorate the diagnostic work-up and patients' classification. However, guidelines that ensure reliability, interpretability, and validity of findings obtained from artificial intelligence approaches are still needed to implement them in the clinical scenario. This review provides a summary of the most recent updates regarding the application of MRI for the diagnosis of MS.
PID Serval
serval:BIB_91B926104148
PMID
Open Access
Oui
Date de création
2022-12-06T13:01:58.251Z
Date de création dans IRIS
2025-05-20T22:03:17Z
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Nom
36427168_BIB_91B926104148.pdf
Version du manuscrit
published
Licence
https://creativecommons.org/licenses/by/4.0
Taille
1.07 MB
Format
Adobe PDF
PID Serval
serval:BIB_91B926104148.P001
URN
urn:nbn:ch:serval-BIB_91B9261041484
Somme de contrôle
(MD5):7a4e91f908e3e3bf0918947651818890