Composite MRI scores improve correlation with EDSS in multiple sclerosis.

Area of Science:

• Neuroimaging
• Biomarkers
• Multiple Sclerosis Research

Background:

• Quantitative magnetic resonance imaging (MRI) measures are explored as non-invasive biomarkers for multiple sclerosis (MS).
• Individual MRI measures show limited correlation with the Expanded Disability Status Scale (EDSS), particularly in large cohorts.

Purpose of the Study:

• To enhance the correlation between MRI-derived measures and EDSS by developing composite MRI scores.
• To investigate if combining various MRI metrics provides a more accurate reflection of MS disability.

Main Methods:

• 126 relapsing-remitting MS patients' MRI scans were segmented into brain tissues and lesions (T2-hyperintense, gadolinium-enhancing, T1-hypointense/black holes).
• Volumes and average T2 values were calculated, converted to z-scores, and combined into composite z-scores.
• Individual and composite z-scores were correlated with EDSS scores.

Main Results:

• Composite MRI scores, incorporating relaxation times and volumetric data, demonstrated stronger correlations with EDSS than individual measures.
• The highest correlation achieved was r = 0.344 (p < 0.0001) with a composite score, surpassing the best single measure (black holes, r = 0.298, p < 0.001).

Conclusions:

• Z-transformation enables the creation of composite MRI scores using volumetric and T2-relaxation data.
• Integrating multiple MRI measures into composite scores provides a more comprehensive characterization of the MS disease process, leading to improved EDSS correlation.