Bi-exponential diffusion signal decay in normal appearing white matter of multiple sclerosis

Magn Reson Imaging. 2013 Feb;31(2):286-95. doi: 10.1016/j.mri.2012.07.007. Epub 2012 Aug 16.

Abstract

Purpose: Our aim was to characterize bi-exponential diffusion signal changes in normal appearing white matter of multiple sclerosis (MS) patients.

Methods: Diffusion parameters were measured using mono-exponential (0-1000 s/mm(2)) and bi-exponential (0-5000 s/mm(2)) approaches from 14 relapsing-remitting subtype of MS patients and 14 age- and sex-matched controls after acquiring diffusion-weighted images on a 3T MRI system. The results were analyzed using parametric or nonparametric tests and multiple linear regression models.

Results: Mono-exponential apparent diffusion coefficient (ADC) slightly increased in controls (P=.09), but decreased significantly in MS as a function of age, nonetheless an elevated ADC was observed with increasing lesion number in patients. Bi-exponential analyses showed that the increased ADC is the result of decreased relative volume fraction of slow diffusing component (f(s)). However, the fast and slow diffusion components (ADC(f), ADC(s)) did not change as a function of either age in controls or lesion number and age in MS patients.

Conclusions: These data demonstrated that the myelin content of the white matter affects diffusion in relapsing-remitting subtype of multiple sclerosis that is possibly a consequence of the shift between different water fractions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Brain / pathology*
  • Case-Control Studies
  • Cerebrum / pathology
  • Diffusion Magnetic Resonance Imaging / methods
  • Female
  • Humans
  • Magnetic Resonance Imaging / methods
  • Male
  • Middle Aged
  • Models, Statistical
  • Multiple Sclerosis / diagnosis*
  • Multiple Sclerosis / pathology*
  • Myelin Sheath / pathology
  • Nerve Fibers, Myelinated / pathology*
  • Regression Analysis
  • Signal Processing, Computer-Assisted
  • Young Adult