Maximal LVWT to LVEDV ratio differentiated early HCM from athlete's heart with AUC 0.977, sensitivity 91.7%, specificity 92.6%, and multivariate model AUC 0.987.
Do cardiac magnetic resonance imaging parameters differentiate physiological exercise-induced cardiac remodelling from early-stage genotype-positive hypertrophic cardiomyopathy?
CMR-derived maximal LVWT to LVEDV ratio strongly differentiates physiological exercise-induced cardiac remodeling in athletes from early-stage hypertrophic cardiomyopathy.
Absolute Event Rate: 0% vs 0%
Abstract Background Increased left ventricular (LV) wall thickness (LVWT) can be a hallmark of both an athlete’s heart and early HCM, making it challenging to distinguish exercise-induced cardiac remodelling (EICR) from early-stage HCM. Navigating this ‘grey zone’ remains a key challenge in sports cardiology. Purpose To determine cardiac magnetic resonance imaging (CMR) parameters differentiating physiological EICR from early-stage genotype positive HCM. Methods We conducted a cross-sectional analysis of genotype-positive borderline HCM patients (LVWT: women 9-16mm, men 11-16mm), and matched elite athletes in a 1:1 ratio. Elite athletes were propensity score distance matched to HCM patients based on sex, length and LVWT. Athlete were selected from ELITE, a prospective elite athlete cohorts which collects data from standardized cardiovascular screenings (16 years, 10h/week training, competing at national or Olympic levels) in the Netherlands, including CMR (Siemens Avanto Fit 1.5T). HCM patients were selected from the Cardiogenetic Biobank of Amsterdam UMC, which systematically collects data from index HCM patients and those identified via cascade screening. Primary metrics of interest were segmented LVWT, cardiac volume/function parameters and ratios. Differences in LV hypertrophy (LVH) distribution were assessed with MANOVA and principal component (PC) analysis (PCA). LVWT risk score (sum(segment i loading x segment i LVWT (mm)) based on the loadings of the PCs. Multivariate backwards logistic regression was used to determine discriminating factors. Receiver operating characteristic (ROC) curves were plotted and areas under the curves (AUC) were calculated to evaluate sensitivity (Sens) and specificity (Spec). Results We included a total of 30 athletes and 30 HCM patients. Sex (female 32% vs 50%, p = .277), length (180 cm ± 10 vs 170 cm ± 13, p = .124) and LVWT (12 mm ± 1.6 vs 13 mm ± 2.0, p = .070) were comparable between groups. HCM patients were older than elite athletes (29 years ± 10 vs 47 years ± 16, p .001). Differences in cardiac volume, function and ratios are shown in Table 1. MANOVA showed a difference in LVWT distribution across the 16 AHA segments between HCM patients and elite athletes (Pillai’s trace = .823, F(16,41) = 11.912, p .001). The maximal LVWT to LV end-diastolic volume (LVEDV) ratio was highly differentiating as singular variable (AUC = .977; Sens = 91.7%; Spec = 92.6%). A multivariate logistic regression model including LVM/LVEDV ratio and the LVWT risk score also performed well (AUC = .987, Sens = 96.4%, Spec = 93.1%). Conclusion Athletes exhibit a distinct LVH pattern with increased LVWT and concomitantly higher LVEDV. The LVWT/LVEDV ratio strongly differentiates physiological adaptation from HCM. Moreover, LVH distribution across the 16 segments differs between athletes and HCM patients, and a multivariate model including the LVM/LVEDV ratio and LVWT risk score performed well to distinguish EICR from HCM.Population Characteristics Scatter Plots and ROC curves
Daems et al. (Sat,) reported a other. Maximal LVWT to LVEDV ratio differentiated early HCM from athlete's heart with AUC 0.977, sensitivity 91.7%, specificity 92.6%, and multivariate model AUC 0.987.