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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
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Voxel-based analysis of the diffusion tensor.

Osamu Abe1, Hidemasa Takao, Wataru Gonoi

  • 1Department of Radiology, Graduate School of Medicine, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan. abediag-tky@umin.ac.jp

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Gradient nonlinearity correction in diffusion tensor imaging (DTI) affects fractional anisotropy (FA) maps differently depending on the statistical analysis method used. Tract-based spatial statistics (TBSS) showed no significant differences.

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Area of Science:

  • Neuroimaging
  • Neuroscience
  • Medical Physics

Background:

  • Diffusion Tensor Imaging (DTI) is crucial for understanding brain development, aging, and diseases.
  • Voxelwise analysis of DTI data requires robust acquisition, preprocessing, and statistical methods.
  • Statistical Parametric Mapping (SPM) and Tract-Based Spatial Statistics (TBSS) are common DTI analysis techniques.

Purpose of the Study:

  • To review current protocols for DTI acquisition, preprocessing, and statistical analysis.
  • To evaluate the impact of gradient nonlinearity distortion correction on DTI analysis using SPM and TBSS.
  • To compare the performance of SPM-based (coregistration, FA template) and TBSS methods in handling corrected and uncorrected DTI data.

Main Methods:

  • Tested distortion correction effects on fractional anisotropy (FA) maps and FA skeletons.
  • Utilized two SPM-based methods (coregistration and FA template) and one TBSS-based method.
  • Compared results from corrected and uncorrected DTI data across the different analytical approaches.

Main Results:

  • SPM-based methods showed discrepancies: FA elevation in anterior white matter (uncorrected) and cerebellar peduncles (corrected).
  • Significant differences in FA were observed in internal capsules/corona radiata between corrected and uncorrected images with SPM methods.
  • TBSS-based method revealed no significant difference in FA skeletons between corrected and uncorrected DTI data.

Conclusions:

  • Discrepancies in SPM results may stem from misregistration and smoothing.
  • TBSS's insensitivity to FA changes outside white matter bundle centers might explain its lack of significant findings.
  • The choice of DTI analysis method impacts the interpretation of gradient nonlinearity correction effects.