In this work, we present a computational study of the Brugada Syndrome (BrS) phenotype aimed at investigating the main factors contributing to the development of arrhythmias. We developed a model that incorporated a BrS substrate within a region resembling the right ventricular outflow tract (RVOT) in a three-dimensional anisotropic ventricular cardiac tissue with transmural heterogeneity. Consistent with our previous two-dimensional study, our results confirmed the requirement of both electrophysiological alterations and structural abnormalities to trigger arrhythmic events. In particular, we found that the combination of electrophysiological alterations and structural abnormalities caused percolation in the tissue, eventually leading to sustained reentry. Moreover, our model is able to replicate the majority of epicardial electrogram features observed in the arrhythmic substrate of Brugada patients, furthermore, the behavior of our model agrees with clinical findings on BrS patients. We identified the density and size of structural abnormalities, the degree of myocyte electrophysiological alteration, and the size of the arrhythmic substrate as risk factors for the genesis of arrhythmias. These findings could be used in a model-based approach to develop processing techniques that highlight arrhythmogenic features in BrS patients’ recorded electrograms, improving risk stratification in patients.
A 3D transmurally heterogeneous computational model of the Brugada Syndrome phenotype
Biasi, Niccolò;Tognetti, Alessandro
2023-01-01
Abstract
In this work, we present a computational study of the Brugada Syndrome (BrS) phenotype aimed at investigating the main factors contributing to the development of arrhythmias. We developed a model that incorporated a BrS substrate within a region resembling the right ventricular outflow tract (RVOT) in a three-dimensional anisotropic ventricular cardiac tissue with transmural heterogeneity. Consistent with our previous two-dimensional study, our results confirmed the requirement of both electrophysiological alterations and structural abnormalities to trigger arrhythmic events. In particular, we found that the combination of electrophysiological alterations and structural abnormalities caused percolation in the tissue, eventually leading to sustained reentry. Moreover, our model is able to replicate the majority of epicardial electrogram features observed in the arrhythmic substrate of Brugada patients, furthermore, the behavior of our model agrees with clinical findings on BrS patients. We identified the density and size of structural abnormalities, the degree of myocyte electrophysiological alteration, and the size of the arrhythmic substrate as risk factors for the genesis of arrhythmias. These findings could be used in a model-based approach to develop processing techniques that highlight arrhythmogenic features in BrS patients’ recorded electrograms, improving risk stratification in patients.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.