Towards elimination of the dark-rim artifact in first-pass myocardial perfusion MRI: removing Gibbs ringing effects

Behzad Sharif1, Rohan Dharmakumar, Troy LaBounty

  • 1Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA.

Abstract

Insights

Optimized radial MRI acquisition significantly reduces dark-rim artifacts (DRAs) in first-pass perfusion (FPP) imaging. This new method improves diagnostic accuracy for detecting myocardial ischemia by eliminating Gibbs ringing effects.

Area of Science:

  • Cardiovascular Magnetic Resonance Imaging
  • Medical Imaging Physics

Background:

  • Subendocardial dark-rim artifacts (DRAs) are a significant challenge in first-pass perfusion (FPP) myocardial MRI.
  • These artifacts, often caused by Gibbs ringing, can reduce the accuracy of ischemia detection.

Purpose of the Study:

  • To propose and evaluate an optimized radial acquisition strategy for FPP MRI.
  • The goal is to eliminate Gibbs ringing-induced DRAs and improve diagnostic performance.

Main Methods:

  • Investigated the point spread function (PSF) to develop an optimized radial sampling and reconstruction method.
  • Evaluated the technique using MRI phantom experiments and in vivo studies on 12 healthy humans, comparing it to conventional Cartesian imaging.

Main Results:

  • Simulations and phantom experiments confirmed the theoretical predictions.
  • In vivo studies demonstrated a significant reduction in DRAs during the early myocardial enhancement phase with the optimized radial method.
  • The proposed method maintained comparable image resolution and quality to conventional Cartesian imaging.

Conclusions:

  • The developed optimized radial imaging technique effectively reduces the prevalence and spatial extent of DRAs in FPP MRI.
  • This approach offers a significant improvement over conventional Cartesian techniques for reducing artifacts in myocardial perfusion imaging.