Corpus callosum atrophy correlates with gray matter atrophy in patients with multiple sclerosis

J Neuroimaging. 2015 Jan-Feb;25(1):62-7. doi: 10.1111/jon.12124. Epub 2014 May 9.

Abstract

Objective: Atrophy of the corpus callosum is a recognized characteristic of multiple sclerosis (MS). We describe a new reliable method for measuring corpus callosum atrophy and correlate this with global cerebral atrophy measures.

Methods: Whole brain 3T MRI was performed in 38 relapsing-remitting MS subjects and 21 healthy controls (HC). Brain global gray and white matter volumes were segmented with SPM8. The contour of the corpus callosum was outlined on the midline of 3-D T1-weighted images by a semiautomated edge-detection technique to determine the corpus callosum area (CCA). Normalized CCA was correlated with other brain atrophy measures in MS subjects.

Results: CCA was disproportionately lower in MS subjects vs. HC (20.1% mean decrease; P < .001), with a large effect size (d = .62) when compared with global atrophy measures. In MS subjects, CCA correlated with brain parenchymal fraction (r = .55; P < .001) and gray matter fraction (r = .45; P = .005) but not white matter fraction (r = .18; P = .29). An inverse correlation with FLAIR hyperintense lesion volume (r = -.40; P = .01) was detected for CCA.

Conclusion: Measurement of atrophy of the corpus callosum can have sensitivity as a useful imaging biomarker in patients with MS, even in patients with low disability levels. Both gray and white matter involvement in MS contribute to corpus callosum atrophy.

Keywords: Multiple sclerosis; atrophy; corpus callosum.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Agenesis of Corpus Callosum / complications*
  • Agenesis of Corpus Callosum / pathology*
  • Female
  • Gray Matter / pathology*
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods
  • Magnetic Resonance Imaging / methods*
  • Male
  • Multiple Sclerosis / complications*
  • Multiple Sclerosis / pathology*
  • Pattern Recognition, Automated / methods
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Statistics as Topic
  • White Matter / pathology