Present and future of the diagnostic work-up of multiple sclerosis: the imaging perspective
Journal of Neurology, ISSN: 1432-1459, Vol: 270, Issue: 3, Page: 1286-1299
2023
- 32Citations
- 147Captures
- 1Mentions
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Metrics Details
- Citations32
- Citation Indexes32
- 32
- CrossRef1
- Captures147
- Readers147
- 147
- Mentions1
- News Mentions1
- News1
Most Recent News
Institute for Cancer Research and Treatment (IRCCS) San Raffaele Scientific Institute Reports Findings in Artificial Intelligence (Present and future of the diagnostic work-up of multiple sclerosis: the imaging perspective)
2022 DEC 06 (NewsRx) -- By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News -- New research on Artificial
Review Description
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.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85142476316&origin=inward; http://dx.doi.org/10.1007/s00415-022-11488-y; http://www.ncbi.nlm.nih.gov/pubmed/36427168; https://link.springer.com/10.1007/s00415-022-11488-y; https://dx.doi.org/10.1007/s00415-022-11488-y; https://link.springer.com/article/10.1007/s00415-022-11488-y
Springer Science and Business Media LLC
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