Comparison of self-gated cine MRI retrospective cardiac synchronization algorithms

Grace M. Nijm, Alan V. Sahakian, Steven Swiryn, James C. Carr, John J. Sheehan, Andrew C. Larson

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Purpose: To determine whether improved self-gating (SG) algorithms can provide superior synchronization accuracy for retrospectively gated cine MRI. Materials and Methods: First difference, template matching, and polynomial fitting algorithms were implemented to improve the synchronization of MRI data using cardiac SG signals. Cine datasets were acquired during short-axis, two-, three-, and four-chamber cardiac MRI scans. The root-mean-square (RMS) error of SG synchronization positions compared to detected R-wave positions were calculated along with the mean square error (MSE) and peak signal-to-noise ratio (PSNR) comparing SG to electrocardiogram (ECG)-gated images. Overall image quality was also compared by two expert reviewers. Results: RMS errors were highest for the first difference method for all orientations. Improvements for both template matching and cubic polynomial fitting methods were significant for two-, three-, and four-chamber scans. MSE values were lower and PSNR were significantly higher for the cubic method compared to the first difference method for all orientations. Reviewers scored the images to be of comparable quality. Conclusion: Template matching and polynomial fitting improved the accuracy of cardiac cycle synchronization for two-, three-, and four-chamber scans; improvements in SG synchronization accuracy were reflected in improvements In analytical image quality. Implementation of robust post-processing algorithms may bring SG approaches closer to clinical utilization.

Original languageEnglish (US)
Pages (from-to)767-772
Number of pages6
JournalJournal of Magnetic Resonance Imaging
Volume28
Issue number3
DOIs
StatePublished - Sep 2008

Keywords

  • Cardiac MRI
  • Retrospective gating
  • Self-gating

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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