Why the study?
CMR is useful in evaluating clinically suspected acute myocarditis, but the diagnosis remains challenging.
Does data-driven texture analysis of CMR images (including CINE imaging) distinguish between patients with and without CMR-verified acute myocarditis?
Does data-driven texture analysis of CMR images (including CINE imaging) distinguish between patients with and without CMR-verified acute myocarditis?
Data-driven texture analysis of CMR, particularly using CINE imaging, shows promise as a novel, non-contrast-based technique for tissue characterization in diagnosing acute myocarditis.
Texture analysis of CMR may aid non-contrast myocarditis diagnosis; hypothesis-generating and requires prospective validation before clinical use.
Cardiac magnetic resonance (CMR) has emerged as a useful tool in the diagnostic work-up of patients with clinically suspected acute myocarditis (AM), yet the diagnosis remains challenging. The purpose of this proof-of-concept study was to evaluate if data-driven texture analysis has the feasibility to automatically distinguish between patients with and without CMR-verified AM using T2-weighted, late gadolinium enhancement, and CINE imaging. In particular, the present study investigated if functional CINE imaging could be used as a novel tissue characterization technique. Twenty patients with clinically suspected AM, separated into CMR-verified (n = 10) and non CMR-verified (n = 10) AM according to the Lake Louise criteria, were retrospectively included. Texture features were extracted from the images, compared on a group level, and correlated to the diagnostic outcome (CMR-verified versus non CMR-verified AM). Several features showed good to excellent reproducibility with very large differences between the groups, and moderate to strong correlation with the diagnostic outcome, suggesting that CMR texture analysis is a promising diagnostic tool for patients with clinically suspected AM. Furthermore, findings indicate that CINE imaging, which is currently used for the evaluation of cardiac function, might be a useful non-contrast-based technique for tissue characterization in patients with clinically suspected AM.
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Papalini et al. (2022) studied this question.
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