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Differentiation of acute non-ST elevation myocardial infarction and acute infarct-like myocarditis by visual pattern analysis: a head-to-head comparison of different cardiac MR techniques

OBJECTIVES: Parametric cardiac magnetic resonance (CMR) techniques have improved the diagnosis of pathologies. However, the primary tool for differentiating non-ST elevation myocardial infarction (NSTEMI) from myocarditis is still a visual assessment of conventional signal-intensity-based images. Th...

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Detalles Bibliográficos
Autores principales: Jahnke, Charlotte, Sinn, Martin, Hot, Amra, Cavus, Ersin, Erley, Jennifer, Schneider, Jan, Chevalier, Celeste, Bohnen, Sebastian, Radunski, Ulf, Meyer, Mathias, Lund, Gunnar, Adam, Gerhard, Kirchhof, Paulus, Blankenberg, Stefan, Muellerleile, Kai, Tahir, Enver
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415415/
https://www.ncbi.nlm.nih.gov/pubmed/37438640
http://dx.doi.org/10.1007/s00330-023-09905-5
Descripción
Sumario:OBJECTIVES: Parametric cardiac magnetic resonance (CMR) techniques have improved the diagnosis of pathologies. However, the primary tool for differentiating non-ST elevation myocardial infarction (NSTEMI) from myocarditis is still a visual assessment of conventional signal-intensity-based images. This study aimed at analyzing the ability of parametric compared to conventional techniques to visually differentiate ischemic from non-ischemic myocardial injury patterns. METHODS: Twenty NSTEMI patients, twenty infarct-like myocarditis patients, and twenty controls were examined using cine, T2-weighted CMR (T2w) and late gadolinium enhancement (LGE) imaging and T1/T2 mapping on a 1.5 T scanner. CMR images were presented in random order to two experienced fully blinded observers, who had to assign them to three categories by a visual analysis: NSTEMI, myocarditis, or healthy. RESULTS: The conventional approach (cine, T2w and LGE combined) had the best diagnostic accuracy with 92% (95%CI: 81–97) for NSTEMI and 86% (95%CI: 71–94) for myocarditis. The diagnostic accuracies using T1 maps were 88% (95%CI: 74–95) and 80% (95%CI: 62–91), 84% (95%CI: 67–93) and 74% (95%CI: 54–87) for LGE, and 83% (95%CI: 66–92) and 73% (95%CI: 53–87) for T2w. The accuracies for cine (72% (95%CI: 52–86) and 60% (95%CI: 38–78)) and T2 maps (62% (95%CI: 40–79) and 47% (95%CI: 28–68)) were significantly lower compared to the conventional approach (p < 0.001 and p < 0.0001). CONCLUSIONS: The conventional approach provided a reliable visual discrimination between NSTEMI, myocarditis, and controls. The diagnostic accuracy of a visual pattern analysis of T1 maps was not significantly inferior, whereas the diagnostic accuracy of T2 maps was not sufficient in this context. CLINICAL RELEVANCE STATEMENT: The ability of parametric compared to conventional CMR techniques to visually differentiate ischemic from non-ischemic myocardial injury patterns can avoid potentially unnecessary invasive coronary angiography and help to shorten CMR protocols and to reduce the need of gadolinium contrast agents. KEY POINTS: • A visual differentiation of ischemic from non-ischemic patterns of myocardial injury is reliably achieved by a combination of conventional CMR techniques (cine, T2-weighted and LGE imaging). • There is no significant difference in accuracies between visual pattern analysis on native T1 maps without providing quantitative values and a conventional combined approach for differentiating non-ST elevation myocardial infarction, infarct-like myocarditis, and controls. • T2 maps do not provide a sufficient diagnostic accuracy for visual pattern analysis for differentiating non-ST elevation myocardial infarction, infarct-like myocarditis, and controls.