心肌炎
医学
磁共振成像
危险分层
心脏病学
心脏磁共振
放射科
特征跟踪
急性心肌炎
人工智能
模式识别(心理学)
计算机科学
作者
Christian Eichhorn,Simon Greulich,Chiara Bucciarelli‐Ducci,Raphael Sznitman,Raymond Y. Kwong,Christoph Gräni
标识
DOI:10.1016/j.jcmg.2021.11.017
摘要
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.
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