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Diffusion-weighted echo planar imaging in patients with recent myocardial infarction

Jean-François Deux1, Mezri Maatouk, Alexandre Vignaud

  • 1Radiology Department, H. Mondor Hospital, Assistance Publique-Hôpitaux de Paris, University Paris 12, Créteil, France. jean-francois.deux@hmn.aphp.fr

European Radiology
|August 4, 2010
PubMed
Abstract

Insights

Diffusion-weighted (DW) black blood magnetic resonance (MR) sequences effectively detect myocardial signal abnormalities in recent myocardial infarction (MI) patients, offering a viable alternative to standard T2-weighted sequences.

Area of Science:

  • Cardiovascular Imaging
  • Magnetic Resonance Imaging
  • Myocardial Infarction Research

Background:

  • Assessing myocardial signal abnormalities is crucial for diagnosing recent myocardial infarction (MI).
  • Standard T2-weighted sequences may not always accurately detect these abnormalities.
  • Diffusion-weighted (DW) black blood magnetic resonance (MR) imaging offers potential for improved detection.

Purpose of the Study:

  • To evaluate the efficacy of a DW black blood MR sequence in identifying myocardial signal abnormalities in patients with recent MI.
  • To compare the performance of DW black blood MR sequences against standard T2-weighted sequences.

Main Methods:

  • A 1.5 T DW black blood EPI sequence was used in 12 recent MI patients.
  • Standard STIR T2-weighted sequences were acquired for comparison.
  • Myocardial viability was assessed using delayed-enhancement sequences; images were analyzed qualitatively and quantitatively.

Main Results:

  • DW EPI sequences demonstrated superior blood suppression compared to STIR T2-weighted sequences (P=0.01).
  • Myocardial high signal areas were detected in 100% of patients using DW EPI versus 67% with STIR T2-weighted imaging.
  • DW EPI correctly identified abnormalities in four patients with false-negative STIR T2 findings.

Conclusions:

  • DW EPI sequences are a feasible and effective alternative for detecting myocardial signal abnormalities in recent MI.
  • This technique shows promise for improving the diagnostic accuracy of MI assessment.

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