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White Matter Bundle Reconstruction From Single-Shell Diffusion Magnetic Resonance Imaging: Test-Retest Reliability

Amelie Rauland1,2, Steven L Meisler3,4,5, Aaron F Alexander-Bloch4,5,6

  • 1Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Jülich, Jülich, Germany.

Human Brain Mapping
|December 11, 2025
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Summary
This summary is machine-generated.

This study shows that white matter (WM) bundles can be reliably reconstructed from lower-resolution, single-shell diffusion MRI (dMRI) data, enabling broader clinical applications. The single-shell three-tissue CSD method demonstrated the best performance for reconstructing these WM bundles.

Keywords:
bundlescognitiondiffusion MRIreliabilitytest–retestwhite matter

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Area of Science:

  • Neuroimaging
  • Diffusion MRI
  • White Matter Anatomy

Background:

  • White matter (WM) bundle derivation typically requires high-resolution, multi-shell diffusion MRI (dMRI) acquisitions, limiting its use to research settings due to cost and time.
  • Existing legacy dMRI datasets, often single-shelled with lower angular resolution, represent a vast resource for broader clinical applications and population studies.
  • The reliability of WM bundles reconstructed from these legacy datasets is currently unclear.

Purpose of the Study:

  • To evaluate the test-retest reliability of WM bundle reconstruction from lower-resolution, single-shell dMRI data.
  • To compare the performance of three orientation distribution function (ODF) reconstruction methods: generalized q-sampling imaging (GQI), constrained spherical deconvolution (CSD), and single-shell three-tissue CSD (SS3T).
  • To assess the potential of reconstructed WM bundles for predicting cognitive function.

Main Methods:

  • Leveraged a large research dataset with 64-direction dMRI scans acquired as two independent 32-direction runs per subject.
  • Reconstructed WM bundles using GQI, CSD, and SS3T methods from the 32-direction scans.
  • Assessed bundle reliability using Dice coefficients and evaluated predictive performance for complex reasoning using extracted bundle features.

Main Results:

  • The majority of WM bundles were reliably extracted from 32-direction, single-shell dMRI data across all tested ODF methods.
  • Within-subject Dice coefficients were consistently higher than between-subject coefficients, indicating preserved individual anatomy.
  • Stable prediction accuracies (r: 0.15-0.36) for complex reasoning were observed across test-retest data.
  • SS3T demonstrated a favorable balance of sensitivity and specificity, high intra-class correlation, plausible bundles, and strong predictive performance compared to GQI and CSD.

Conclusions:

  • Bundle-specific reconstruction methods can achieve robust performance even with lower angular resolution, single-shell dMRI data.
  • ODF methods optimized for single-shell data, like SS3T, offer particular advantages for reconstructing WM bundles from legacy datasets.
  • This work highlights the significant potential of utilizing existing dMRI data from healthcare and research settings to advance WM research and clinical applications.