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Gap cycling for SWIFT.

Curtis A Corum1, Djaudat Idiyatullin, Carl J Snyder

  • 1Center for Magnetic Resonance Research, Department of Radiology, Medical School, University of Minnesota, Minneapolis, Minnesota, USA.

Magnetic Resonance in Medicine
|March 8, 2014
PubMed
Summary
This summary is machine-generated.

Gap cycling effectively eliminates bulls-eye artifacts in SWeep Imaging with Fourier Transformation (SWIFT) MRI scans. This novel technique addresses crosstalk in SWIFT data, improving image quality.

Keywords:
bull's-eye artifactgap cyclingsweep imagingultra-short T2 imaging

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Medical Imaging Technology
  • Signal Processing in MRI

Background:

  • SWeep Imaging with Fourier Transformation (SWIFT) is a non-Cartesian MRI technique.
  • SWIFT involves simultaneous radiofrequency (RF) excitation and reception, leading to interband crosstalk.
  • This crosstalk manifests as a characteristic "bulls-eye" artifact in SWIFT images.

Purpose of the Study:

  • To introduce and evaluate a novel method called "gap cycling" for artifact reduction in SWIFT MRI.
  • To address and eliminate the interband crosstalk artifact in SWIFT imaging.
  • To improve the quality of SWIFT MRI images.

Main Methods:

  • Theoretical analysis of the SWIFT signal chain and artifact generation.
  • Computer simulations to model and understand crosstalk mechanisms.
  • Experimental validation using phantoms and in vivo subjects to demonstrate artifact elimination.

Main Results:

  • Theoretical analysis elucidated the mechanism by which gap cycling cancels interband crosstalk.
  • Simulations confirmed the effectiveness of the proposed method.
  • Phantom and in vivo experiments yielded SWIFT images free of the bulls-eye artifact.

Conclusions:

  • Gap cycling is a highly effective strategy for removing bulls-eye artifacts in SWIFT MRI.
  • The method successfully mitigates artifacts caused by interband crosstalk.
  • This technique enhances the diagnostic utility of SWIFT imaging.