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Segmented simultaneous multi-slice diffusion weighted imaging with generalized trajectories.

Michael Herbst1,2, Weiran Deng1, Thomas Ernst1

  • 1Department of Medicine, John A. Burns School of Medicine, University of Hawaii, Honolulu, Hawaii, USA.

Magnetic Resonance in Medicine
|November 27, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a new framework for rapid and robust simultaneous multislice (SMS) diffusion weighted imaging (DWI) at 3 Tesla. The Multiplexed Sensitivity Encoding (MUSE) technique successfully reduces artifacts for both Cartesian and non-Cartesian trajectories.

Keywords:
diffusion weighted imagingsimultaneous multislice imaging

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Diffusion Weighted Imaging (DWI)
  • Simultaneous Multislice (SMS) imaging

Background:

  • Simultaneous multislice (SMS) imaging accelerates MRI acquisition by acquiring multiple slices concurrently.
  • Diffusion weighted imaging (DWI) is crucial for assessing microstructural changes in tissues, particularly in the brain.
  • Artifacts can degrade the quality of SMS-DWI, limiting its clinical utility.

Purpose of the Study:

  • To develop and evaluate a unified framework for rapid and robust SMS-DWI at 3 Tesla.
  • To enable the use of both Cartesian and non-Cartesian segmented trajectories within a single SMS framework.
  • To improve the quality and efficiency of DWI acquisition.

Main Methods:

  • A generalized SMS approach utilizing Multiplexed Sensitivity Encoding (MUSE) with intrinsic phase navigation was developed.
  • Segmented blipped-controlled aliasing in parallel imaging echo planar imaging (EPI) and z-gradient modulated spiral trajectories were investigated.
  • SMS-DWI scans were performed at 3T using a 32-channel head coil.

Main Results:

  • The generalized SMS MUSE reconstruction framework effectively reduced artifacts across all tested trajectories.
  • A high-resolution DWI brain volume (1.5-mm isotropic resolution) was acquired.
  • The entire DWI acquisition, including 90 diffusion weightings, was completed in a scan time of 6 minutes.

Conclusions:

  • The MUSE technique is versatile and can be generalized for the reconstruction of both Cartesian and non-Cartesian segmented trajectories.
  • This framework offers a promising solution for rapid and artifact-reduced SMS-DWI.
  • The findings support the potential of MUSE for advanced DWI applications in clinical settings.