Predictors of Long-term Disability in Multiple Sclerosis Patients Using Routine Magnetic Resonance Imaging Data: A 15-year Retrospective Study

Overview

Journal Neuroradiol J

Publisher Sage Publications

Specialties Neurology
Radiology

Date 2023 Feb 6

PMID 36745094

Authors

Amjad Altokhis

Abdulmajeed Alotaibi

Paul Morgan

Radu Tanasescu

Nikos Evangelou

Affiliations

Soon will be listed here.

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.

Citing Articles

Neuroimaging markers and disability scales in multiple sclerosis: A systematic review and meta-analysis.

Mirmosayyeb O, Yazdan Panah M, Mokary Y, Mohammadi M, Moases Ghaffary E, Shaygannejad V PLoS One. 2024; 19(12):e0312421.

PMID: 39637162 PMC: 11620670. DOI: 10.1371/journal.pone.0312421.

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