Tissue characterization of acute myocardial infarction and myocarditis by cardiac magnetic resonance

JACC Cardiovasc Imaging. 2008 Sep;1(5):652-62. doi: 10.1016/j.jcmg.2008.07.011.

Abstract

Electrocardiograms, biomarkers, and ventricular function studies are diagnostic tools that are currently used to assess patients with acute myocardial disease. These tools are limited in their diagnostic accuracy and scope. Thus, for informed therapeutic decision making, tissue characterization may serve as a very important source of information in these initially regional diseases. Cardiac magnetic resonance (CMR) is becoming an important tool for phenotyping cardiac patients in vivo. Recent advances of CMR hardware and software as well as protocols have allowed for accurately visualizing tissue changes in patients with acute myocardial diseases. This is of special interest for acute myocardial infarction and acute myocarditis, because these entities may have a very similar clinical presentation and require immediate therapeutic decision making. Several CMR approaches can be combined in a comprehensive CMR examination, which provides information not only on ventricular size, morphology, and function, but also on the stage, degree, and extent of reversible and irreversible myocardial injury. Streamlined protocols allow such a CMR examination to be a time- and cost-efficient diagnostic tool, even in patients with acute disease. Current CMR approaches for visualizing tissue pathology in vivo are reviewed, examples are presented, and the potential role of CMR tissue characterization in patients with acute myocardial disease is discussed. The specific role of imaging the extent and regional distribution of myocardial edema and necrosis is discussed.

Publication types

  • Review

MeSH terms

  • Acute Disease
  • Edema, Cardiac / pathology
  • Humans
  • Magnetic Resonance Imaging* / methods
  • Myocardial Infarction / pathology*
  • Myocarditis / pathology*
  • Myocardium / pathology*
  • Necrosis
  • Predictive Value of Tests
  • Reproducibility of Results
  • Severity of Illness Index