Cardiac magnetic resonance imaging: A non-invasive approach for the detection of myocardial inflammation — Potentials and limitations

  • Matthias Gutberlet
Part of the Progress in Inflammation Research book series (PIR)


Cardiac magnetic resonance imaging (CMR) has evolved to the imaging modality of choice for the volumetric and functional evaluation of the heart in different cardiac diseases. Furthermore, it is capable of tissue characterization using T1- and T2-weighted images with and without the use of contrast agents. Therefore, it is the ideal imaging modality in cardiomyopathies or ischemic heart disease. Currently, the most commonly used CMR technique is the so-called delayed enhancement technique using T1-weighted inversion recovery sequences 10–15 min after the intravenous administration of a contrast agent, usually Gd-DTPA. With this technique viable myocardium can be distinguished from non-viable myocardium in ischemic heart disease, cardiomyopathies or myocarditis. Therefore, delayed myocardial enhancement is not specific for myocarditis, but a typical subepicardial or diffuse appearance allows for the differentiation between ischemic versus inflammatory heart disease. However, delayed myocardial enhancement represents more the irreversibly injured myocardium than inflammation itself. T2-weighted sequences and early myocardial enhancement using published ratios (edema ratio) or the global relative enhancement are best used for the detection of inflammation in comparison to results from endomyocardial biopsies, especially if used in combination. Simple evaluation of reduced global or regional ventricular function by magnetic resonance imaging is helpful for follow-up examinations but not very sensitive or specific for the diagnosis of myocarditis.


Cardiovascular Magnetic Resonance Cardiac Magnetic Resonance Cardiac Magnetic Resonance Imaging Endomyocardial Biopsy Myocardial Edema 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Basel 2010

Authors and Affiliations

  • Matthias Gutberlet
    • 1
  1. 1.Department of Diagnostic and Interventional RadiologyUniversity Leipzig/ Leipzig Heart CenterLeipzigGermany

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