Comparison between prospective and retrospective triggering for mouse cardiac MRI

Edwin Heijman, Wolter de Graaf, Petra Niessen, Arno Nauerth, Guillaume van Eys, Larry de Graaf, Klaas Nicolaij, Gustav J Strijkers

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High-resolution magnetic resonance imaging (MRI) has evolved into one of the major non-invasive tools to study the healthy and diseased mouse heart. This study presents a Cartesian CINE MRI protocol based on a fast low-angle shot sequence with a navigator echo to generate cardiac triggering and respiratory gating signals retrospectively, making the use of ECG leads and respiratory motion sensors obsolete. MRI of the in vivo mouse heart using this sequence resulted in CINE images with no detectable cardiac and respiratory motion artefacts. The retrospective method allows for steady-state imaging of the mouse heart, which is essential for quantitative contrast-enhanced MRI studies. A comparison was made between prospective and retrospective methods in terms of the signal-to-noise ratio and the contrast-to-noise ratio between blood and myocardial wall, as well as global cardiac functional indices: end-diastolic volume, end-systolic volume, stroke volume and ejection fraction. The retrospective method resulted in almost constant left-ventricle wall signal intensity throughout the cardiac cycle, at the expense of a decrease in the signal-to-noise ratio and the contrast-to-noise ratio between blood and myocardial wall as compared with the prospective method. Prospective and retrospective sequences yielded comparable global cardiac functional indices. The largest mean relative difference found was 8% for the end-systolic volume.

Original languageEnglish
Pages (from-to)439-447
Number of pages9
JournalNMR in Biomedicine
Issue number4
Publication statusPublished - Jun 2007



  • Algorithms
  • Animals
  • Artifacts
  • Echo-Planar Imaging
  • Heart
  • Image Enhancement
  • Image Interpretation, Computer-Assisted
  • Magnetic Resonance Imaging, Cine
  • Mice
  • Phantoms, Imaging
  • Reproducibility of Results
  • Sensitivity and Specificity

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