Age-related degeneration of corpus callosum measured with diffusion tensor imaging

Neuroimage. 2006 Jul 15;31(4):1445-52. doi: 10.1016/j.neuroimage.2006.02.008. Epub 2006 Mar 24.

Abstract

The corpus callosum is the major commissure connecting the cerebral hemispheres, and there is evidence of its change with aging. The sub-regions of the corpus callosum (genu, rostral body, anterior midbody, posterior midbody, isthmus, splenium) respectively comprise fibers connecting heteromodal- and unimodal-associated cortical regions, and it is known that abnormalities of the corpus callosum are correlated with abnormalities in cognition and behavior. Yet, little is known about changes in the tissue characteristics of its sub-regions. We assessed age-related changes in fractional anisotropy and mean diffusivity in the sub-regions of the corpus callosum using diffusion tensor imaging. We studied 42 healthy right-handed individuals aged 21-73 years. There were no significant interactions of sex x region. Age has significant negative correlation with fractional anisotropy in the genu (P < 0.001), rostral body (P < 0.001), and isthmus (P = 0.005). Fractional anisotropy of the anterior midbody was correlated negatively with age at a trend level (P = 0.022). Age was significantly positively correlated with mean diffusivity in the genu (P = 0.001), rostral body (P = 0.002), anterior midbody (P = 0.001), and isthmus (P = 0.001). Age-related changes were detected in the sub-regions where their projection areas are thought to be vulnerable to normal aging. This suggested that fractional anisotropy and mean diffusivity values of the corpus callosum sub-regions could serve as markers of disturbance across the respective projection areas.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aging / physiology*
  • Anisotropy
  • Cognition / physiology
  • Corpus Callosum / anatomy & histology
  • Corpus Callosum / physiology*
  • Diffusion Magnetic Resonance Imaging
  • Female
  • Humans
  • Image Processing, Computer-Assisted
  • Male
  • Middle Aged
  • Sex Characteristics