Neural Regeneration Research ›› 2019, Vol. 14 ›› Issue (1): 114-123.doi: 10.4103/1673-5374.243716

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Detecting white matter alterations in multiple sclerosis using advanced diffusion magnetic resonance imaging

Sourajit M. Mustafi1, Jaroslaw Harezlak2, Chandana Kodiweera3, Jennifer S. Randolph4, James C. Ford4, Heather A. Wishart4, Yu-Chien Wu1, 3   

  1. 1 Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
    2 Department of Epidemiology and Biostatistics, School of Public Health, Indiana University, Bloomington, IN, USA
    3 Department of Psychological and Brain Sciences and Dartmouth Brain Imaging Center, Dartmouth College, Hanover, NH, USA
    4 Department of Psychiatry, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
  • Online:2019-01-15 Published:2019-01-15
  • Contact: Yu-Chien Wu, PhD, DABMP, yucwu@iu.edu.
  • Supported by:

    This work was supported by Indiana University-Purdue University Indianapolis Imaging Technology Development Program (IUPUI ITDP), National Institutes of Health (NIH) grant R21 NS075791, and R01 AG053993.

Abstract:

Multiple sclerosis is a neurodegenerative and inflammatory disease, a hallmark of which is demyelinating lesions in the white matter. We hypothesized that alterations in white matter microstructures can be non-invasively characterized by advanced diffusion magnetic resonance imaging. Seven diffusion metrics were extracted from hybrid diffusion imaging acquisitions via classic diffusion tensor imaging, neurite orientation dispersion and density imaging, and q-space imaging. We investigated the sensitivity of the diffusion metrics in 36 sets of regions of interest in the brain white matter of six female patients (age 52.8 ± 4.3 years) with multiple sclerosis. Each region of interest set included a conventional T2-defined lesion, a matched perilesion area, and normal-appearing white matter (NAWM). Six patients with multiple sclerosis (n = 5) or clinically isolated syndrome (n = 1) at a mild to moderate disability level were recruited. The patients exhibited microstructural alterations from NAWM transitioning to perilesion areas and lesions, consistent with decreased tissue restriction, decreased axonal density, and increased classic diffusion tensor imaging diffusivity. The findings suggest that diffusion compartment modeling and q-space analysis appeared to be sensitive for detecting subtle microstructural alterations between perilesion areas and NAWM.

Key words: multiple sclerosis, hybrid diffusion imaging, NODDI, diffusion tensor imaging, q-space imaging