Electroanatomical voltage mapping with contact force sensing for diagnosis of arrhythmogenic right ventricular cardiomyopathy

Background Three-dimensional electroanatomical mapping (EAM) can be helpful to diagnose arrhythmogenic right ventricular cardiomyopathy (ARVC). Yet, previous studies utilizing EAM have not systematically used contact-force sensing catheters (CFSC) to characterize the substrate in ARVC, which is the current gold standard to assure adequate tissue contact. Objective To investigate reference values for endocardial right ventricular (RV) EAM as well as substrate characterization in patients with ARVC by using CFSC. Methods Endocardial RV EAM during sinus rhythm was performed with CFSC in 12 patients with definite ARVC and 5 matched controls without structural heart disease. A subanalysis for the RV outflow tract (RVOT), septum, free-wall, subtricuspid region, and apex was performed. Endocardial bipolar and unipolar voltage amplitudes (BVA, UVA), signal characteristics and duration as well as the impact of catheter orientation on endocardial signals were also investigated. Results ARVC patients showed lower BVA vs. controls (p = 0.018), particularly in the subtricuspid region (1.4, IQR:0.5–3.1 vs. 3.8, IQR:2.5-5 mV, p = 0.037) and RV apex (2.5, IQR:1.5–4 vs. 4.3,IQR:2.9–6.1 mV, p = 0.019). BVA in all RV regions yielded a high sensitivity and specificity for ARVC diagnosis (AUC 59–78%, p < 0.05 for all), with the highest performance for the subtricuspid region (AUC 78%, 95% CI:0.75–0.81, p < 0.001, negative predictive value 100%). A positive correlation between BVA and an orthogonal catheter orientation (46°-90°:r = 0.106, p < 0.001), and a negative correlation between BVA and EGM duration (r = −0.370, p < 0.001) was found. Conclusions EAM using CFSC validates previous bipolar cut-off values for normal endocardial RV voltage amplitudes. RV voltages are generally lower in ARVC as compared to controls, with the subtricuspid area being commonly affected and having the highest discriminatory power to differentiate between ARVC and healthy controls. Therefore, EAM using CFSC c