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Tract-based morphometry.

Lauren J O'Donnell1, Carl-Fredrik Westin, Alexandra J Golby

  • 1Golby Surgical Brain Mapping Laboratory, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston MA, USA. odonnell@bwh.harvard.edu

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|November 30, 2007
PubMed
Summary

This study introduces tract-based morphometry (TBM) for analyzing diffusion MRI data, moving beyond mean fractional anisotropy (FA) values. TBM reveals spatial variations in white matter tracts, enhancing group comparison and detecting subtle differences.

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Area of Science:

  • Neuroimaging
  • Diffusion MRI
  • White Matter Analysis

Background:

  • Traditional diffusion tensor imaging (DTI) analysis often uses mean fractional anisotropy (FA) values.
  • This approach overlooks spatial variations in FA along white matter tracts.
  • A more detailed analysis is needed to capture tract-specific morphometric differences.

Purpose of the Study:

  • To introduce tract-based morphometry (TBM) for statistical analysis of diffusion MRI data.
  • To develop an automated method for generating white matter tract arc length parameterizations.
  • To enable the detection of group differences in white matter structure using an anatomical tract-based coordinate system.

Main Methods:

  • Developed an automated method for white matter tract arc length parameterization.

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  • Created an anatomical tract-based coordinate system for statistical analysis.
  • Applied TBM to analyze interhemispheric differences in fractional anisotropy (FA).

    • Main Results:

    • Demonstrated the capability of TBM to perform statistical analyses along the entire length of white matter tracts.
    • Successfully generated tract-based coordinate systems from multi-subject tractography data.
    • Presented example TBM results highlighting interhemispheric differences in FA.

    Conclusions:

    • Tract-based morphometry (TBM) offers a more comprehensive approach to analyzing white matter structure compared to traditional methods.
    • The automated tract parameterization and coordinate system facilitate robust group comparisons.
    • TBM is effective in detecting subtle white matter differences, such as interhemispheric FA variations.