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Related Experiment Video

Updated: Apr 4, 2026

Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI—Application in Premanifest Huntington's Disease
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Robust MR-based approaches to quantifying white matter structure and structure/function alterations in Huntington's

Jessica J Steventon1, Rebecca C Trueman2, Anne E Rosser3

  • 1Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Park Place, Cardiff CF10 3AT, UK; Brain Repair Group, Life Science Building, 3rd Floor, School of Biosciences, Cardiff University, Museum Avenue, Cardiff CF10 3AX, UK; Neuroscience and Mental Health Research Institute, Cardiff University, Hadyn Ellis Building, Cathays, Cardiff CF24 4HQ, UK.

Journal of Neuroscience Methods
|September 4, 2015
PubMed
Summary

This study introduces an optimized diffusion MRI analysis pipeline to improve white matter microstructure quantification in Huntington's disease (HD) patients. Enhanced methods reveal disease-specific changes and recommend Tissue Volume Fraction (TVF) for better clinical correlation.

Keywords:
Corpus callosumDTIDiffusion MRIDisease burdenHuntington's diseaseTractography

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Area of Science:

  • Neuroimaging
  • Diffusion MRI
  • White Matter Microstructure

Background:

  • Advances in diffusion MRI analysis for white matter microstructure are not yet widely applied in clinical research.
  • Specific confounds in diffusion MRI data are more pronounced in Huntington's disease (HD), impacting data quality and interpretability.
  • This study addresses these confounds in an HD patient cohort using an optimized analysis pipeline.

Purpose of the Study:

  • To present an optimized diffusion MRI analysis pipeline tailored for HD patients.
  • To address specific confounds that impede data quality and interpretability in HD.
  • To improve the quantification of white matter microstructure and detection of group differences in HD.

Main Methods:

  • 15 HD gene-positive and 13 matched controls underwent 3T MRI with two diffusion MRI sequences.
  • An optimized pipeline included motion, eddy current, and EPI correction, B matrix rotation, free water elimination (FWE), and crossing fiber tractography.
  • Corpus callosum analysis used region-of-interest and deterministic tractography with diffusion tensor imaging (DTI) and spherical deconvolution.

Main Results:

  • Correcting for CSF contamination significantly altered microstructural metrics and group difference detection.
  • Spherical deconvolution provided more complete corpus callosum reconstructions and greater sensitivity to group differences than DTI.
  • Tissue Volume Fraction (TVF) was reduced in HD participants and showed higher sensitivity to disease burden than DTI metrics.

Conclusions:

  • Addressing diffusion MRI confounds yields more valid, anatomically faithful white matter tract reconstructions with reduced variance.
  • TVF is recommended as a complementary metric for assessing HD, offering insights into clinical symptoms beyond conventional DTI.
  • The optimized pipeline enhances the reliability and interpretability of diffusion MRI data in HD research.