0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessIn 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.
Massimo Filippi, Paolo Preziosa, Douglas L. Arnold, Frederik Barkhof, Daniel M. Harrison, Pietro Maggi, Caterina Mainero, Xavier Montalbán, Elia Sechi, Brian G. Weinshenker, Maria A. Rocca (2022). Present and future of the diagnostic work-up of multiple sclerosis: the imaging perspective. , 270(3), DOI: https://doi.org/10.1007/s00415-022-11488-y.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2022
Authors
11
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1007/s00415-022-11488-y
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access