Longitudinal, region-specific course of diffusion tensor imaging measures in mild cognitive impairment and Alzheimer's disease

Milap A. Nowrangi, Constantine G. Lyketsos, Jeannie Marie S. Leoutsakos, Kenichi Oishi, Marilyn Albert, Susumu Mori, Michelle M. Mielke

Research output: Contribution to journalArticlepeer-review

77 Scopus citations


Background: Diffusion tensor imaging (DTI) is a promising method for identifying significant cross-sectional differences of white-matter tracts in normal controls (NC) and those with mild cognitive impairment (MCI) or Alzheimer's disease (AD). There have not been many studies establishing its longitudinal utility. Methods: Seventy-five participants (25 NC, 25 amnestic MCI, and 25 AD) had 3-Tesla MRI scans and clinical evaluations at baseline and 3, 6, and 12 months. Fractional anisotropy (FA) and mean diffusivity (MD) were analyzed at each time-point and longitudinally in eight a priori-selected areas taken from four regions of interest (ROIs). Results: Cross-sectionally, MD values were higher, and FA values lower in the fornix and splenium of the AD group compared with either MCI or NC (P <.01). Within-group change was more evident in MD than in FA over 12 months: MD increased in the inferior, anterior cingulum, and fornix in both the MCI and AD groups (P <.01). Conclusions: There were stable, cross-sectional, region-specific differences between the NC and AD groups in both FA and MD at each time-point over 12 months. Longitudinally, MD was a better indicator of change than FA. Significant increases of fornix MD in the MCI group suggest this is an early indicator of progression.

Original languageEnglish (US)
Pages (from-to)519-528
Number of pages10
JournalAlzheimer's and Dementia
Issue number5
StatePublished - Sep 2013


  • Alzheimer's disease
  • Anisotropy
  • DTI
  • Diffusivity
  • Longitudinal

ASJC Scopus subject areas

  • Epidemiology
  • Health Policy
  • Developmental Neuroscience
  • Clinical Neurology
  • Geriatrics and Gerontology
  • Psychiatry and Mental health
  • Cellular and Molecular Neuroscience


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