Related Experiment Video
Updated: Jul 9, 2026
Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla
Published on: February 19, 2021
Predicting short-term disability progression in early multiple sclerosis: added value of MRI parameters
A Minneboo1, B Jasperse, F Barkhof
1MS Center of the VU University Medical Center, Department of Radiology, VU University Medical Center, Amsterdam, The Netherlands. a.minneboo@vumc.nl
Objective:
Magnetic resonance imaging (MRI) and clinical parameters are associated with disease progression in multiple sclerosis (MS). The aim of this study was to investigate whether adding MRI parameters to a model with only clinical parameters could improve these associations.
Methods:
89 patients (55 women) with recently diagnosed MS had clinical and MRI evaluation at baseline (time of diagnosis) and at follow-up after 2.2 years. Detailed clinical data were available, including disease type (relapse-onset or progressive-onset) and disability, as measured by the Expanded Disability Status Scale (EDSS). MRI parameters included Normalised Brain Volume (NBV) at baseline, percentage brain volume change (PBVC/year), T2- and T1-lesion loads and spinal cord abnormalities. Progression of disability (increase in EDSS of at least 1 point at follow-up) was the main outcome measure. For a model containing only clinical parameters, the added value of MRI parameters was tested using logistic regression.
Results:
PBVC/year and lesion loads at follow-up were significantly higher in the group with progression. Adding PBVC/year to a clinical model improved the model, indicating that MRI parameters added independent information (p<0.001).
Conclusion:
The rate of cerebral atrophy conveys added information for the progression of disability in patients with early MS, suggesting that clinical disability is determined by neurodegenerative changes as depicted by MRI.
Insights
In early multiple sclerosis (MS), brain atrophy rate (percentage brain volume change per year) independently predicts disability progression. Adding MRI measures to clinical data improves prediction accuracy for MS disease worsening.
Area of Science:
- Neuroimaging
- Neurology
- Clinical Research
Background:
- Multiple sclerosis (MS) is a chronic neurological disease.
- Disease progression in MS is associated with both clinical and Magnetic Resonance Imaging (MRI) parameters.
- Predicting MS progression is crucial for effective management.
Purpose of the Study:
- To determine if incorporating MRI parameters into clinical models enhances the prediction of MS disease progression.
- To assess the added value of specific MRI metrics beyond clinical data.
Main Methods:
- A cohort of 89 recently diagnosed MS patients underwent baseline and 2.2-year follow-up evaluations.
- Clinical data included disease type and Expanded Disability Status Scale (EDSS).
- MRI parameters assessed were Normalised Brain Volume (NBV), percentage brain volume change (PBVC/year), lesion loads, and spinal cord abnormalities.
Main Results:
- Patients with disability progression showed significantly higher PBVC/year and lesion loads at follow-up.
- The inclusion of PBVC/year into a clinical model significantly improved predictive accuracy (p<0.001).
- MRI parameters provided independent information regarding MS progression.
Conclusions:
- The rate of cerebral atrophy (PBVC/year) is a valuable predictor of disability progression in early MS.
- Neurodegenerative changes, as visualized by MRI, are key determinants of clinical disability in MS.
- Integrating MRI metrics with clinical data offers a more comprehensive approach to monitoring MS progression.
Related Concept Videos
01:19Multiple Sclerosis l: Introduction
01:24Magnetic Resonance Imaging