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The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool
Published on: June 30, 2014
Single MRI-Based Volumetric Assessment in Clinical Practice Is Associated With MS-Related Disability
Marie B D'hooghe1,2, Jeroen Gielen1,2, Ann Van Remoortel1
1National MS Center, Neurology, Melsbroek, Belgium.
Background:
The added value of brain volume measurements in the clinical practice of multiple sclerosis (MS) has been questioned.
Purpose:
To investigate the contribution of volume measures obtained with magnetic resonance scans performed as part of regular care to predict measures of cognitive and physical MS disability in a real-world setting.
Study Type:
Retrospective.
Subjects:
In all, 470 adults with diagnosed MS.
Field Strength/Sequence:
3D fluid attenuation inversion recovery (FLAIR) and 3D T1 -weighted MR images at 3.0T MR.
Assessment:
Lesion and brain volume were measured by an automated method, MSmetrix, developed by icometrix.
Statistical Tests:
We used stepwise linear regression models to assess the added value of a single volumetric assessment in predicting Expanded Disability Status Scale (EDSS) and Symbol Digit Modalities Test (SDMT). Brain volumes categorized into quartiles were used as predictive variables in a time-to-event analysis and Cox proportional hazard regression with time to worsening from baseline as outcome measures.
Results:
Brain and lesion volume in relapsing onset MS strongly contributed to the best models, with a substantial role for age in the EDSS model and a modest role for education in the SDMT model. Adding MR volumetric information increased the explained variance from 17% to 28% in the best model for EDSS and from 9% to 25% in the best model for SDMT. A significantly reduced hazard (P < 0.05) of SDMT worsening was found in the highest normalized brain volume quartiles (1375-1608 ml), compared with the lowest quartile (1201-1374 ml) in the total study population.
Data Conclusion:
Our findings indicate that a single brain volumetric assessment contributes to the prediction of MS-related disability, with distinct patterns for EDSS as a measure of physical disability, and SDMT as a measure of cognitive disability. A threshold effect for the lowest brain volumes with regard to SDMT worsening over time was found.
Level Of Evidence:
3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1312-1321.
Insights
Brain volume measurements using MRI scans can predict multiple sclerosis (MS) disability. Higher brain volumes are associated with a reduced risk of cognitive decline, as measured by the Symbol Digit Modalities Test (SDMT).
Area of Science:
- Neuroimaging
- Neurology
- Radiology
Background:
- The clinical utility of brain volume measurements in multiple sclerosis (MS) management remains debated.
- Standard clinical care often involves magnetic resonance imaging (MRI) for MS patients.
Purpose of the Study:
- To evaluate the predictive value of MRI-derived brain volume measures for cognitive and physical disability in a real-world MS cohort.
- To determine if routine MRI volumetric data can enhance disability prediction models.
Main Methods:
- Retrospective analysis of 470 adult MS patients.
- Utilized 3D FLAIR and 3D T1-weighted MRI scans at 3.0T.
- Automated brain and lesion volume quantification using MSmetrix software.
- Stepwise linear regression and Cox proportional hazard models were employed.
Main Results:
- Brain and lesion volumes were significant predictors of disability in relapsing-onset MS.
- Incorporating volumetric data improved variance explained for physical (EDSS) and cognitive (SDMT) disability prediction.
- Higher normalized brain volume quartiles showed a significantly reduced hazard of SDMT worsening over time.
Conclusions:
- A single brain volumetric assessment using MRI provides valuable predictive information for MS-related physical and cognitive disability.
- Distinct predictive patterns exist for physical (EDSS) versus cognitive (SDMT) outcomes.
- A threshold effect was observed, where lower brain volumes are associated with increased risk of cognitive decline.
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