Patterns of white matter damage are non-random and associated with cognitive function in secondary progressive multiple sclerosis

K. A. Meijer, M. Cercignani, N. Muhlert, V. Sethi, D. Chard, J. J. G. Geurts, O. Ciccarelli

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13 Citations (Scopus)


In multiple sclerosis (MS), white matter damage is thought to contribute to cognitive dysfunction, which is especially prominent in secondary progressive MS (SPMS). While studies in healthy subjects have revealed patterns of correlated fractional anisotropy (FA) across white matter tracts, little is known about the underlying patterns of white matter damage in MS. In the present study, we aimed to map the SPMS-related covariance patterns of microstructural white matter changes, and investigated whether or not these patterns were associated with cognitive dysfunction. Diffusion MRI was acquired from 30 SPMS patients and 32 healthy controls (HC). A tensor model was fitted and FA maps were processed using tract-based spatial statistics (TBSS) in order to obtain a skeletonised map for each subject. The skeletonised FA maps of patients only were decomposed into 18 spatially independent components (ICs) using independent component analysis. Comprehensive cognitive assessment was conducted to evaluate five cognitive domains. Correlations between cognitive performance and (1) severity of FA abnormalities of the extracted ICs (i.e. z-scores relative to FA values of HC) and (2) IC load (i.e. FA covariance of a particular IC) were examined. SPMS patients showed lower FA values of all examined patterns of correlated FA (i.e. spatially independent components) than HC (p 
Original languageEnglish
Pages (from-to)123-131
Number of pages9
JournalNeuroImage: Clinical
Publication statusPublished - 2016


  • Cognition
  • Diffusion tensor imaging
  • Independent component analysis
  • MRI
  • Secondary progressive multiple sclerosis
  • Tract-based spatial statistics

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