Diffusion basis spectrum imaging for identifying pathologies in MS subtypes

Afsaneh Shirani, Peng Sun, Kathryn Trinkaus, Dana C. Perantie, Ajit George, Robert T. Naismith, Robert E. Schmidt, Sheng Kwei Song, Anne H. Cross

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


Diffusion basis spectrum imaging (DBSI) combines discrete anisotropic diffusion tensors and the spectrum of isotropic diffusion tensors to model the underlying multiple sclerosis (MS) pathologies. We used clinical MS subtypes as a surrogate of underlying pathologies to assess DBSI as a biomarker of pathology in 55 individuals with MS. Restricted isotropic fraction (reflecting cellularity) and fiber fraction (representing apparent axonal density) were the most important DBSI metrics to classify MS using brain white matter lesions. These DBSI metrics outperformed lesion volume. When analyzing the normal-appearing corpus callosum, the most significant DBSI metrics were fiber fraction, radial diffusivity (reflecting myelination), and nonrestricted isotropic fraction (representing edema). This study provides preliminary evidence supporting the ability of DBSI as a potential noninvasive biomarker of MS neuropathology.

Original languageEnglish (US)
Pages (from-to)2323-2327
Number of pages5
JournalAnnals of Clinical and Translational Neurology
Issue number11
StatePublished - Nov 1 2019

ASJC Scopus subject areas

  • General Neuroscience
  • Clinical Neurology


Dive into the research topics of 'Diffusion basis spectrum imaging for identifying pathologies in MS subtypes'. Together they form a unique fingerprint.

Cite this