Abstract
BACKGROUND: Deterioration of right ventricular (RV) function in repaired tetralogy of Fallot (rToF) is poorly understood. Cardiovascular magnetic resonance (CMR) is used for monitoring, but its analysis is user-dependent and time-consuming. We sought to automate the analysis of CMR using machine learning and to identify imaging traits associated with adverse RV remodeling in the natural history of rToF. METHODS: A longitudinal cohort of rToF patients underwent CMR at the Children's Hospital of Philadelphia. The nnU-Net method was used to train a machine learning model to segment the left ventricular (LV) blood pool, LV myocardium, and RV blood pool from two-dimensional short-axis CMR images. Conventional and novel measures were calculated and studied in association with remodeling rates using multivariable linear regression. Remodeling rates were calculated as ((Variable(scan2) - Variable(scan1))/years between scans) for the variables end-diastolic volume index (EDVi), end-systolic volume index (ESVi), stroke volume index (SVi), ejection fraction (EF), and peak systolic dV/dt. RESULTS: The cohort was comprised of 758 patients, of whom 152 had 2 analyzable scans. Thirty-six patients underwent pulmonic valve replacement (PVR) between scans. Compared to patients with no intervention (representing the natural history of rToF), patients with PVR had significantly lower remodeling rates for RVEDVi, RVESVi, RVSVi, and absolute peak systolic RV dV/dt, while RVEF and left-sided metrics did not differ between groups. In 116 patients without PVR between scans, RV remodeling rates were negatively associated with baseline LV mass index, LVEDVi, LVSVi, and absolute peak systolic LV dV/dt. CONCLUSION: We demonstrated that rToF patients with two CMR scans and PVR have significant differences in and opposite directions of RV remodeling rates compared to those with no intervention. We also showed that several left-sided measures of structure and function were associated with RV remodeling rates, indicating the importance of baseline LV measurements in characterizing future risk of adverse RV remodeling.