Tractography-guided statistics (TGIS) in diffusion tensor imaging for the detection of gender difference of fiber integrity in the midsagittal and parasagittal corpora callosa

Neuroimage. 2007 Jul 1;36(3):606-16. doi: 10.1016/j.neuroimage.2007.03.020. Epub 2007 Mar 28.


Parasagittal or off-midsagittal structures of the interhemispheric fiber tracts, i.e., the corpus callosum (CC), have a tendency to form structures which diverge from the midsagittal CC (mCC). This has led to mild inconsistencies in terms of defining parasagittal structures as region of interest for diffusion tensor imaging (DTI) analysis. Moreover, it is a labor-intensive work with potential inconsistencies and inaccuracies to define the parasagittal structure slice by slice using currently available methods. In the present study, to better cope with these problems, a new method was developed to construct the extended parasagittal structure of the CC using diffusion tensor tractography-guided (TGI) parameterization methods based on tract-length-based and parasagittal plane-based extensions. Using extended ROIs, fractional anisotropy (FA) values, as the indicators of fiber integrity in DTI, were compared between normal 14 male (25.7+/-4.7 years) and 17 female (25.9+/-4.6 years) groups for investigating the gender difference. Both TGI parameterization methods showed that men have significantly higher regional FA values than women for global CC structure areas in parasagittal and midsagittal space. In contrast, women showed significantly higher FA values in the partial areas of the rostrum, genu and splenium. Our findings based on TGI statistics (TGIS) of fiber integrity could serve as a frame of reference for assessing the group differences of the CCs in finer scale and in more extended space or parasagittal space.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Brain Mapping
  • Corpus Callosum / cytology*
  • Data Interpretation, Statistical
  • Diffusion Magnetic Resonance Imaging / statistics & numerical data*
  • Female
  • Humans
  • Image Processing, Computer-Assisted
  • Male
  • Models, Neurological
  • Models, Statistical
  • Nerve Fibers / physiology*
  • Sex Characteristics