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Cardiovascular magnetic resonance parametric mapping in the risk stratification of patients affected by chronic myocarditis. | LitMetric

AI Article Synopsis

  • Chronic myocardial inflammation can lead to serious heart issues like arrhythmias and dilated cardiomyopathy, and cardiovascular magnetic resonance (CMR) is a key tool for detecting this inflammation non-invasively.* -
  • A retrospective study involving 88 patients suspected of chronic myocarditis indicated that certain CMR mapping parameters could help predict negative outcomes, with models showing good to very good predictive performance.* -
  • The findings suggest that analyzing the extent of myocardial damage through CMR parameters can enhance risk assessment in patients suffering from chronic myocarditis.*

Article Abstract

Objectives: Chronic myocardial inflammation is the substrate for arrhythmias and dilated cardiomyopathy onset, causing morbidity and mortality. Cardiovascular magnetic resonance (CMR) is the noninvasive gold standard for myocardial inflammation detection, due to the high sensitivity of the parametric mapping techniques. However, the potential prognostic capabilities of CMR mapping have not been studied in the setting of chronic myocarditis.

Methods: This is a retrospective study on consecutive patients undergoing CMR with suspicion of chronic myocarditis from September 2017 to November 2021. CMR was acquired according to 2018 Lake Louise Criteria recommendations. The outcome (chronic heart failure, recurrent chronic myocarditic chest pain, ICD/PM implantation, arrhythmias [Lown class ≥ 2]) was collected at follow-up. The extent and degree of native T1, T2, and extracellular volume fraction alterations were used to create multivariate binary logistic regression models for outcome prediction, with or without left ventricle ejection fraction; their AUCs were compared with DeLong test. Differences between other parameters were assessed using Chi-square test, Fisher's exact test, or Mann-Whitney U-test.

Results: The population included 88 patients (age 43 [32-52] yo), mostly male (53/88, 60%). After a median follow-up of 21 (17-34) months, 31/88 (35%) patients experienced the outcome. The model based on the extension of mapping alterations and LV dysfunction reached a good predictability (AUC 0.71). The model based on the intensity of mapping alterations and LV dysfunction had a very good performance (AUC 0.80).

Conclusion: The quantitative analysis of CMR mapping parameters indicative of myocardial damage severity may improve risk stratification in patients with chronic myocarditis.

Clinical Relevance Statement: The intensity of myocardial damage, assessed as the degree of native T1, T2, and ECV alteration, together with left ventricle dysfunction, improved patient risk stratification. Further prospective studies will be necessary for validation before clinical application.

Key Points: Risk stratification of patients affected by chronic myocarditis is an unmet clinical need. Cardiovascular MRI (CMR) can role in risk stratification thanks to its multiparametric capabilities of tissue characterization. A model based on CMR parametric mapping and left ventricle ejection fraction can predict arrhythmia, heart failure, and recurrent symptoms.

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Source
http://dx.doi.org/10.1007/s00330-024-10978-zDOI Listing

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