Can rate of brain atrophy in multiple sclerosis be explained by clinical and MRI characteristics?

Mult Scler. 2009 Apr;15(4):465-71. doi: 10.1177/1352458508100505. Epub 2008 Dec 17.


Introduction: Multiple sclerosis (MS) is characterized, besides focal lesions, by brain atrophy. The determinants of atrophy rates in individual patients are poorly understood.

Aim: This study investigated the predictive value of clinical and magnetic resonance imaging (MRI) factors, including short-term changes thereof, for concurrent and future atrophy evolution using Spearman's rank correlations and stepwise multiple linear regression.

Methods: We retrospectively identified a group of 115 active, early relapsing-remitting (RR) patients relatively homogeneous in terms of disease course and MRI activity compared to a second group of 96 patients with broader spectrum of MS phenotypes and inactive scans. All patients had undergone three MRI investigations with interscan intervals of at least 12 and 24 months, respectively.

Results: In the RR patients, 23% of variance in concurrent atrophy rates (over the first interval) could be explained by the combination of baseline T2 lesion volume and change in EDSS score over the first interval, whereas only 6% in future atrophy rates (over the second interval) was explained. In the heterogeneous group, 20.2% of the variance in future atrophy rates could be explained, but slightly less in concurrent atrophy rates (16.2%).

Conclusion: We concluded that variance in brain atrophy rates can partially be explained by clinical and MRI measures of disease. Future atrophy rates in individual MS patients are difficult to predict even when including previous atrophy rates.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Atrophy
  • Brain / pathology*
  • Disease Progression
  • Female
  • Humans
  • Magnetic Resonance Imaging*
  • Male
  • Middle Aged
  • Multiple Sclerosis, Chronic Progressive / pathology*
  • Multiple Sclerosis, Relapsing-Remitting / pathology*
  • Multivariate Analysis
  • Predictive Value of Tests
  • Retrospective Studies