Eichhorn, Christian; Greulich, Simon; Bucciarelli-Ducci, Chiara; Sznitman, Raphael; Kwong, Raymond Y; Gräni, Christoph (2022). Multiparametric Cardiovascular Magnetic Resonance Approach in Diagnosing, Monitoring, and Prognostication of Myocarditis. JACC. Cardiovascular imaging, 15(7), pp. 1325-1338. Elsevier 10.1016/j.jcmg.2021.11.017
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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 will describe the evidence surrounding different CMR methods and image postprocessing methods and highlight their values for clinical decision making, monitoring, and risk stratification across stages of this condition.
Item Type: |
Journal Article (Review Article) |
|---|---|
Division/Institute: |
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - AI in Medical Imaging Laboratory 04 Faculty of Medicine > Department of Cardiovascular Disorders (DHGE) > Clinic of Cardiology |
UniBE Contributor: |
Sznitman, Raphael, Gräni, Christoph |
Subjects: |
600 Technology > 610 Medicine & health |
ISSN: |
1936-878X |
Publisher: |
Elsevier |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
23 May 2022 07:58 |
Last Modified: |
05 Dec 2022 16:20 |
Publisher DOI: |
10.1016/j.jcmg.2021.11.017 |
PubMed ID: |
35592889 |
Uncontrolled Keywords: |
CMR ECV LGE LLC Lake Louise criteria T1 mapping T2 mapping artificial intelligence feature-tracking magnetic resonance myocardial strain myocarditis postprocessing radiomics texture analysis |
BORIS DOI: |
10.48350/170153 |
URI: |
https://boris.unibe.ch/id/eprint/170153 |
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