| Literature DB >> 35592889 |
Christian Eichhorn1, Simon Greulich2, Chiara Bucciarelli-Ducci3, Raphael Sznitman4, Raymond Y Kwong5, Christoph Gräni6.
Abstract
Myocarditis represents the entity of an inflamed myocardium and is a diagnostic challenge caused by its heterogeneous presentation. Contemporary noninvasive evaluation of patients with clinically suspected myocarditis using cardiac magnetic resonance (CMR) includes dimensions and function of the heart chambers, conventional T2-weighted imaging, late gadolinium enhancement, novel T1 and T2 mapping, and extracellular volume fraction calculation. CMR feature-tracking, texture analysis, and artificial intelligence emerge as potential modern techniques to further improve diagnosis and prognostication in this clinical setting. This review describes the evidence surrounding different CMR methods and image postprocessing methods and highlights their values for clinical decision making, monitoring, and risk stratification across stages of this condition.Entities:
Keywords: ECV; LGE; Lake Louise criteria (LLC); T1 mapping; T2 mapping; artificial intelligence; cardiac magnetic resonance (CMR); feature-tracking; myocardial strain; myocarditis; postprocessing; radiomics; texture analysis
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Year: 2022 PMID: 35592889 DOI: 10.1016/j.jcmg.2021.11.017
Source DB: PubMed Journal: JACC Cardiovasc Imaging ISSN: 1876-7591