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Hypertrophic cardiomyopathy or athlete's heart? A systematic review of novel cardiovascular magnetic resonance imaging parameters.

Constantinos BakogiannisDimitrios MouselimisAnastasios TsarouchasEfstathios PapatheodorouVassilios P VassilikosEmmanuel Androulakis
Published in: European journal of sport science (2021)
Hypertrophic cardiomyopathy (HCM) is a common cause of sudden cardiac death in athletes. Cardiac Magnetic Resonance (CMR) imaging is considered an excellent tool to differentiate between HCM and athlete's heart. The aim of this systematic review was to highlight the novel CMR-derived parameters with significant discriminative capacity between the two conditions. A systematic search in the MEDLINE, EMBASE and Cochrane Reviews databases was performed. Eligible studies were considered the ones comparing novel CMR-derived parameters on athletes and HCM patients. Therefore, studies that only examined Cine-derived volumetric parameters were excluded. Particular attention was given to binary classification results from multi-variate regression models and ROC curve analyses. Bias assessment was performed with the Quality Assessment on Diagnostic Accuracy Studies. Five (5) studies were included in the systematic review, with a total of 284 athletes and 373 HCM patients. Several novel indices displayed discriminatory potential, such as native T1 mapping and T2 values, LV global longitudinal strain, late gadolinium enhancement and whole-LV fractal dimension. Diffusion tensor imaging enabled quantification of the secondary eigenvalue angle and fractional anisotropy in one study, which also proved capable of reliably detecting HCM in a mixed athlete/patient sample. Several novel CMR-derived parameters, most of which are currently under development, show promising results in discerning between athlete's heart and HCM. Prospective studies examining the discriminatory capacity of all promising modalities side-by-side will yield definitive answers on their relative importance; diagnostic models can incorporate the best performing variables for optimal results.
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