The Relationship Between Brain MR Spectroscopy and Disability in Multiple Sclerosis: 20-Year Data from the U.S. Glatiramer Acetate Extension Study. Academic Article uri icon

abstract

  • Conventional MRI techniques do not necessarily provide information about multiple sclerosis (MS) disease pathology or progression. Nonconventional MRI techniques, including proton magnetic resonance spectroscopy ((1) H-MRS), are increasingly used to improve the qualitative and quantitative specificity of MR images. This study explores potential correlations between MRI measures of disease and disability progression as measured by the Expanded Disability Status Scale (EDSS), Functional Systems (FS), and ambulation index scores in a unique cohort of MS patients treated with glatiramer acetate that has been closely monitored for over 20 years.This was a multicenter, open-label, cross-sectional MRI substudy among participants in the GA-9004 open-label extension of the 36-month, double-blind GA-9001 study, timed to coincide with the prospectively planned 20-year clinical exam.Of 64 patients who participated in the MRI substudy, results are presented for the 39 patients (61%) who had a (1) H-MRS assessment at 20 years of treatment. Both total N-acetylaspartate relative to total creatinine (tNAA/tCr) concentration ratio and T1 lesion volume were found to be robustly associated with disability levels with different statistical approaches. Gray matter (GM) volume was found to be a more consistent parameter than white matter (WM) volume for disability allocation. The elastic net algorithm showed a trade-off between WM and GM volumes for disability estimation when different disability definitions were used.Among patients with MS receiving long-term glatiramer acetate therapy, consistent effects on disability levels indicated by EDSS and pyramidal FS score thresholds were found for tNAA/tCr concentration ratio and T1 lesion volume.© 2016 The Authors. Journal of Neuroimaging published by Wiley Periodicals, Inc. on behalf of American Society of Neuroimaging.

publication date

  • May 2016