Arrhythmogenic cardiomyopathy (AC) is an inherited cardiac disease, clinically characterized by life-threatening ventricular arrhythmias and progressive cardiac dysfunction. Patient-specific computational models could help understand the disease progression and may help in clinical decision-making. We propose an inverse modelling approach using the CircAdapt model to estimate patient-specific regional abnormalities in tissue properties in AC subjects. However, the number of parameters ( n  = 110) and their complex interactions make personalized parameter estimation challenging. The goal of this study is to develop a framework for parameter reduction and estimation combining Morris screening, quasi-Monte Carlo (qMC) simulations and particle swarm optimization (PSO). This framework identifies the best subset of tissue properties based on clinical measurements allowing patient-specific identification of right ventricular tissue abnormalities. We applied this framework on 15 AC genotype-positive subjects with varying degrees of myocardial disease. Cohort studies have shown that atypical regional right ventricular (RV) deformation patterns reveal an early-stage AC disease. The CircAdapt model of cardiovascular mechanics and haemodynamics has already demonstrated its ability to capture typical deformation patterns of AC subjects. We, therefore, use clinically measured cardiac deformation patterns to estimate model parameters describing myocardial disease substrates underlying these AC-related RV deformation abnormalities. Morris screening reduced the subset to 48 parameters. qMC and PSO further reduced the subset to a final selection of 16 parameters, including regional tissue contractility, passive stiffness, activation delay and wall reference area. This article is part of the theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.

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Background Idiopathic ventricular fibrillation (IVF) is diagnosed in patients with ventricular fibrillation of which the origin is not identified after extensive evaluations. Recent studies suggest an association between mitral annulus disjunction (MAD), mitral valve prolapse (MVP), and ventricular arrhythmias. The prevalence of MAD and MVP in patients with IVF in this regard is not well established. We aimed to explore the prevalence of MAD and MVP in a consecutive cohort of patients with IVF compared with matched controls. Methods and Results In this retrospective, multicenter cohort study, cardiac magnetic resonance images from patients with IVF (ie, negative for ischemia, cardiomyopathy, and channelopathies) and age‐ and sex‐matched control subjects were analyzed for the presence of MAD (≥2 mm) and MVP (>2 mm). In total, 72 patients (mean age 39±14 years, 42% women) and 72 control subjects (mean age 41±11 years, 42% women) were included. MAD in the inferolateral wall was more prevalent in patients with IVF versus healthy controls (7 [11%] versus 1 [1%], P =0.024). MVP was only seen in patients with IVF and not in controls (5 [7%] versus 0 [0%], P =0.016). MAD was observed in both patients with (n=4) and without (n=3) MVP. Conclusions Inferolateral MAD and MVP were significantly more prevalent in patients with IVF compared with healthy controls. The authors advocate that evaluation of the mitral valve region deserves extra attention in the extensive screening of patients with unexplained cardiac arrest. These findings support further exploration of the pathophysiological mechanisms underlying a subset of IVF that associates with MAD and MVP.