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Predictors of long-term disability in multiple sclerosis patients using routine magnetic resonance imaging data: A 15-year retrospective study
- Source :
- The Neuroradiology Journal. :197140092211508
- Publication Year :
- 2023
- Publisher :
- SAGE Publications, 2023.
-
Abstract
- Introduction Early identification of patients at high risk of progression could help with a personalised treatment strategy. Magnetic resonance imaging (MRI) measures have been proposed to predict long-term disability in multiple sclerosis (MS), but a reliable predictor that can be easily implemented clinically is still needed. Aim Assess MRI measures during the first 5 years of the MS disease course for the ability to predict progression at 10+ years. Methods Eighty-two MS patients (53 females), with ≥10 years of clinical follow-up and having two MRI scans, were included. Clinical data were obtained at baseline, follow-up and at ≥10 years. White matter lesion (WML) counts and volumes, and four linear brain sizes were measured on T2/FLAIR ‘Fluid-Attenuated-Inversion-Recovery’ and T1-weighted images. Results Baseline and follow-up inter-caudate diameter (ICD) and third ventricular width (TVW) measures correlated positively with Expanded Disability Status Scale, ≥10 or more of WMLs showed a high sensitivity in predicting progression, at ≥10 years. A steeper rate of lesion volume increase was observed in subjects converting to secondary progressive MS. The sensitivity and specificity of both ICD and TVW, to predict disability at ≥10 years were 60% and 64%, respectively. Conclusion Despite advances in brain imaging and computerised volumetric analysis, ICD and TVW remain relevant as they are simple, fast and have the potential in predicting long-term disability. However, in this study, despite the statistical significance of these measures, the clinical utility is still not reliable.
- Subjects :
- Radiology, Nuclear Medicine and imaging
Neurology (clinical)
General Medicine
Subjects
Details
- ISSN :
- 23851996 and 19714009
- Database :
- OpenAIRE
- Journal :
- The Neuroradiology Journal
- Accession number :
- edsair.doi...........2a8a9623c45d297685ed4a8115b0cf47
- Full Text :
- https://doi.org/10.1177/19714009221150853