Electromechanical Substrate Characterization in ARVC | 65 simulations were optimized using the stochastic multi-swarm particle swarm optimization (MSPSO).20,21 MSPSO is an evolutionary algorithm, where a population of candidate solutions moves through the input space driven by their history and the history of a changing subpopulation. Eventually, this parameter estimation protocol results in a virtual patient, from which regional tissue properties can be extracted. Local tissue properties RVfw contractility, compliance, and activation delay were extracted from the resulting virtual patient simulations and the heterogeneity of these tissue properties was investigated. Due to the nonlinearity, non-monotonicity, and non-additivity of the lumped system, the individual estimated parameters were not interpreted directly, but local tissue properties were derived from the simulated time signals of myofibre stress and strain. As the RVfw is typically most affected in desmosomal mutation carriers1, we focus on the heterogeneity in regional RVfw tissue properties. To limit the degrees of freedom in the model, parameters in the LV and IVS were not estimated on a segmented level, but in a single segment representing the entire wall to include ventricular interaction. Regional myocardial contractility, compliance, and activation delay were used to quantify regional mechanical tissue properties. In brief, segmental contractility was defined as the maximum rate of active stress rise Contractility = max dσact dt , which can be seen as the equivalent of the maximum rate of ventricular systolic pressure rise (dP/dtmax) on a local tissue level. Segmental wall compliance was defined as the inverse slope of the end-diastolic passive myofibre stress ( Compliance = dϵ dσpas ) and strain ( Compliance = dϵ dσpas ) relationship, obtained using a preload manipulation. This is the regional equivalent of the slope of the global end-diastolic pressure-volume relation. Furthermore, regional activation delay was defined as the time delay of onset active stress development relative to the first activated segment. Their equations are given by Contractility = max dσact dt Compliance = dϵ dσpas tcon =t max dσact dt Activation Delay= tcon − σact tcon Contractility −tRA activation Reproducibility To determine reproducibility, a separate validation set was used. Two separate observers blinded to clinical data performed deformation analysis twice in nine subjects with a pathogenic desmosomal mutation, resulting in four different deformation datasets per patient. (5) (6) (7) (8) 4
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