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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
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Fast diffusion imaging with high angular resolution.

Tzu-Cheng Chao1,2, Jr-Yuan George Chiou3, Stephan E Maier3,4

  • 1Department of Computer Science and Information Engineering, National Cheng-Kung University, Tainan, Taiwan.

Magnetic Resonance in Medicine
|February 23, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a fast imaging method combining accelerated multishot diffusion imaging (AMDI), multiplexed sensitivity encoding (MUSE), and crossing fiber angular resolution of intravoxel structure (CFARI) to reduce scan times and distortions in high angular resolution diffusion imaging (HARDI). The new approach achieves over 85% similarity with fully sampled data in under 5 minutes, facilitating clinical HARDI integration.

Keywords:
accelerated imagingcompressed sensinghigh angular resolution diffusion imagingparallel imaging

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Area of Science:

  • Neuroimaging
  • Diffusion MRI
  • Medical Physics

Background:

  • High angular resolution diffusion imaging (HARDI) reveals nerve bundle architecture but faces limitations due to long scan times and geometric distortions from echo planar imaging (EPI).
  • Clinical integration of HARDI is hindered by these challenges, necessitating faster and more accurate imaging techniques.

Purpose of the Study:

  • To develop and evaluate a novel, accelerated imaging method for high angular resolution diffusion imaging (HARDI).
  • To significantly reduce scan duration and minimize geometric distortions in HARDI acquisitions.

Main Methods:

  • The proposed method combines accelerated multishot diffusion imaging (AMDI), multiplexed sensitivity encoding (MUSE), and crossing fiber angular resolution of intravoxel structure (CFARI).
  • A multishot EPI sequence was employed for improved geometrical fidelity, alongside k-space and diffusion sampling acceleration.
  • The technique incorporates regularization and self-navigation for motion correction, with whole-brain acquisitions performed on seven volunteers.

Main Results:

  • Achieved average similarity of microstructural orientations above 85% between undersampled and fully sampled datasets.
  • Reduced scan times to below 5 minutes for whole-brain HARDI acquisitions.
  • Demonstrated up to 2.7-fold scan time acceleration and four-fold reduction in spatial distortions.

Conclusions:

  • The developed imaging strategy effectively generates HARDI results with good geometrical fidelity and reduced scan duration.
  • This approach shows promise in transitioning HARDI from a research tool to a practical clinical application.
  • The method facilitates the integration of advanced diffusion imaging techniques into routine clinical practice.