Characterisation of patients referred to a tertiary-level inherited cardiac condition clinic with suspected arrhythmogenic right ventricular cardiomyopathy (ARVC).

BACKGROUND: Arrhythmogenic right ventricular cardiomyopathy (ARVC) or arrhythmogenic cardiomyopathy is a rare inherited disease with incomplete penetrance and an environmental component. Although a rare disease, ARVC is a common cause of sudden cardiac death in young adults. Data on the different stages of ARVC remains scarce. The purpose of this study is to describe the initial presentation and cardiac phenotype of definite and non-definite ARVC for patients seen at a tertiary service. METHODS: This is a single centre, observational cohort study of patients with definite and non-definite ARVC seen at the Inherited Cardiac Conditions services at University Hospital Birmingham (UHB) in the period 2010-2021. Patients were identified by interrogation of digital health records, medical history, imaging and by examining 12-lead electrocardiograms (ECG). RESULT: The records of 1451 patients were reviewed; of those, 165 patients were at risk of ARVC (mean age 41 ± 17 years, 56% male). 60 patients fulfilled task force criteria for definite ARVC diagnosis (n = 40, 67% males), and 38 (72%) of them carried a known pathogenic variant. The remaining 105 patients (50% males) were non-definite, and of these 45 (62%) carried a known pathogenic variant. Patients in the definite group were more symptomatic, with palpitations (57% vs. 17%), syncope (35% vs. 6%) and shortness of breath (28% vs. 5%, p < 0.001). T-wave inversion in V1-V3 and epsilon waves were observed only in the definite group. Both PR interval and QRS duration were longer in the definite (170 ± 34 ms and 100 ± 19 ms, p < 0.001) compared to (149 ± 25 and 91 ± 14 ms, p = 0.005). Patients with definite ARVC had significantly larger RV end diastolic areas and significantly reduced biventricular function (RVEDA = 27 ± 10 cm2, RVFAC = 37 ± 11% and EF = 56 ± 12%) compared to the non-definite group (RVEDA = 18 ± 4 cm2, RVFAC 49 ± 6% and LVEF 64 ± 7%, p < 0.001). Sustained ventricular tachycardia (VT) occurred more frequently in the definite group compared to the non-definite group (27% vs. 2%, p < 0.001). Ventricular fibrillation was observed in the definite group only (8 of 60 patients, 13%). CONCLUSION: Our study showed differences between definite and non-definite ARVC patients in terms of clinical, electrophysiological and imaging features. Major adverse cardiac events occurred more commonly in the definite group, but also were observed in non-definite ARVC. This single centre observational cohort study forms a basis for further prospective multicentre interventional studies.

JavaCyte, a novel open-source tool for automated quantification of key hallmarks of cardiac structural remodeling.

Many cardiac pathologies involve changes in tissue structure. Conventional analysis of structural features is extremely time-consuming and subject to observer bias. The possibility to determine spatial interrelations between these features is often not fully exploited. We developed a staining protocol and an ImageJ-based tool (JavaCyte) for automated histological analysis of cardiac structure, including quantification of cardiomyocyte size, overall and endomysial fibrosis, spatial patterns of endomysial fibrosis, fibroblast density, capillary density and capillary size. This automated analysis was compared to manual quantification in several well-characterized goat models of atrial fibrillation (AF). In addition, we tested inter-observer variability in atrial biopsies from the CATCH-ME consortium atrial tissue bank, with patients stratified by their cardiovascular risk profile for structural remodeling. We were able to reproduce previous manually derived histological findings in goat models for AF and AV block (AVB) using JavaCyte. Furthermore, strong correlation was found between manual and automated observations for myocyte count (r = 0.94, p < 0.001), myocyte diameter (r = 0.97, p < 0.001), endomysial fibrosis (r = 0.98, p < 0.001) and capillary count (r = 0.95, p < 0.001) in human biopsies. No significant variation between observers was observed (ICC = 0.89, p < 0.001). We developed and validated an open-source tool for high-throughput, automated histological analysis of cardiac tissue properties. JavaCyte was as accurate as manual measurements, with less inter-observer variability and faster throughput.