title: Composite MRI scores improve correlation with EDSS in multiple sclerosis.
abstract: BACKGROUND
  Quantitative measures derived from magnetic resonance imaging (MRI) have been widely investigated as non-invasive biomarkers in multiple sclerosis (MS). However, the correlation of single measures with Expanded Disability Status Scale (EDSS) is poor, especially for studies with large population samples.
  
  
  OBJECTIVE
  To explore the correlation of MRI-derived measures with EDSS through composite MRI scores.
  
  
  METHODS
  Magnetic resonance images of 126 patients with relapsing-remitting MS were segmented into white and gray matter, cerebrospinal fluid, T2-hyperintense lesions, gadolinium contrast-enhancing lesions, T1-hypointense lesions ('black holes': BH). The volumes and average T2 values for each of these tissues and lesions were calculated and converted to a z-score (in units of standard deviation from the mean). These z-scores were combined to construct composite z-scores, and evaluated against individual z-scores for correlation with EDSS.
  
  
  RESULTS
  Composite scores including relaxation times of different tissues and/or volumetric measures generally correlated more strongly with EDSS than individual measures. The maximum observed correlation of a composite with EDSS was r = 0.344 (p < 0.0001), which is an improvement over the highest-performing single MRI measure (BH; r = 0.298, p < 0.001).
  
  
  CONCLUSIONS
  Z-transformation permits construction of composite scores including volumetric and T2-relaxation measures. Inclusion of multiple MRI measures in the composite can provide a broader characterization of the disease process, resulting in more robust correlations with EDSS.
authors.affiliation: Department of Diagnostic and Interventional Imaging, University of Texas Medical School at Houston, Houston TX, USA.
authors.forename: A H
authors.initials: AH
authors.lastname: Poonawalla
authors.forename: S
authors.initials: S
authors.lastname: Datta
authors.forename: V
authors.initials: V
authors.lastname: Juneja
authors.forename: F
authors.initials: F
authors.lastname: Nelson
authors.forename: J S
authors.initials: JS
authors.lastname: Wolinsky
authors.forename: G
authors.initials: G
authors.lastname: Cutter
authors.forename: P A
authors.initials: PA
authors.lastname: Narayana
mesh_terms: D000328:Adult; D003287:Contrast Media; D003430:Cross-Sectional Studies; D004185:Disability Evaluation; D005260:Female; D005682:Gadolinium; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D020529:Multiple Sclerosis, Relapsing-Remitting / Q000175:diagnosis* / Q000473:pathology; D011237:Predictive Value of Tests; D012720:Severity of Illness Index; D013781:Texas
chemical_list: D003287:Contrast Media; D005682:Gadolinium
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