Differentiation between physiological sport adaptation and hypertrophic cardiomyopathy in highly trained athletes using cardiac magnetic resonance. (25th November 2020) - Czimbalmos, C; Nardocci, C; Deetjen, E; Szabo, L; Dohy, Z; Toth, A; Suhai, F.I; Csecs, I; Horvath, V; Kiss, O; Sydo, N; Merkely, B; et al.
Abstract: : Differentiation between hypertrophic cardiomyopathy (HCM) patients and healthy athletes (HA) is a common clinical conundrum. We aimed to analyze cardiac magnetic resonance (CMR) characteristics of HA, sedentary HCM and athletic HCM patients and to determine CMR parameters which can help to diagnose HCM in athletes. Male sedentary HCM patients with slightly elevated maximal end-diastolic wall thickness (EDWT 13–18 mm, n=40, 47.6±14.7y) and HA (n=30, 27.5±5.6y) were consecutively enrolled. Additionally, athletes with HCM were enrolled (n=16, 29.6±13.4 y), where a comprehensive investigation confirmed the diagnosis of HCM. We determined conventional CMR parameters (left ventricular (LV) ejection fraction (EF), end-diastolic (EDVi) and end-systolic volume index, mass index (Mi)), derived parameters such as EDWT/LVEDVi, LVM/LVEDV ratio and strain parameters such as global longitudinal (GLS), radial (GRS) and circumferential strain (GCS), SD of peak LS and CS using feature tracking. Presence of late gadolinium enhancement (LGE) was also determined. CMR parameters representing LV hypertrophy pattern or LV function were analyzed using a logistic regression to detect the best CMR parameters to predict HCM in athletes. To differentiate between HA and athletes with HCM optimal cut-off values for CMR parameters were calculated using receiver operating curve analysis. Comparing the three groups significant differences were found regarding conventional and derived CMR parameters and strain values. None of the HA showed LGE, 75% of athletic HCM and 82% of sedentary HCM patients showed LGE. The univariate regression model showed that LVEF, EDWT, EDWT/LVMi, LVM/LVEDV, GCS, GRS, SD of peak LS and CS are determinants of the diagnosis of HCM among athletes. Multivariate regression revealed that EDWT/LVMi and GCS are independent disease predictors in athletes (p<0.05). Cut-off value for GCS ≤−32.5 and for EDWT/LVEDVi >0.126 discriminate athletic HCM from HA with a sensitivity of 81.3 and 87.5% (AUC 0.93), and a specificity of 96.7 and 83.3% (AUC 0.95), respectively (Figure 1). CMR characteristics of sedentary and athletic HCM may differ, therefore establishing diagnostic parameters based on comparison between athletic HCM and HA is essential. CMR based strain and derived parameters may help to differentiate between physiological and pathological left ventricular hypertrophy in athletes. Funding Acknowledgement: Type of funding source: Public grant(s) – National budget only. Main funding source(s): National Research, Development and Innovation Office of Hungary (NKFIA) and National Research, Development and Innovation Office (NFKIH) of Hungary.