Journal of Magnetic Resonance Imaging · 2018 · 18 citations · 24 references
MedicineNeurologyNeuroscienceCognitive NeurologyDiagnostic ImagingVolume VisualizationBrain ImagingDisability AssessmentDisability EvaluationMultiple SclerosisNeurological AssessmentVolume Status AssessmentDisability Severity AssessmentDisability Severity MeasurementDisability Status AnalysisDisability Status DeterminationNeurological Outcome PredictionNeurological Status AssessmentOutcome MeasuresSymbol Digit Modalities Test
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: -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.
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R: A Language and Environment for Statistical Computing
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Diagnostic criteria for multiple sclerosis: 2010 Revisions to the McDonald criteria
Chris H. Polman, Stephen C. Reingold, Brenda Banwell et al. · Annals of Neurology · 2011 · 9.8K citations · Full text
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Elizabeth Fisher, Jar‐Chi Lee, Kunio Nakamura et al. · Annals of Neurology · 2008 · 673 citations