A computational framework was developed to simulate action potential propagation and generate simulated ECG signals, linking re-entry configurations to clinical ECG observations.
A computational framework was developed to simulate ventricular action potential propagation and generate corresponding ECG signals, providing a link between experimental re-entry models and clinical ECG observations.
Ventricular arrhythmias remain an important cause of morbidity and mortality in the Western world. Although the underlying mechanisms of these arrhythmias can be studied experimentally, these investigations are in general limited to mapping electrical activity on the heart surface. Computational models of action potential propagation offer a potentially powerful way to study electrical activation and arrhythmias, but current models are not easy to link to the clinical environment. In this paper, we describe a framework for computing action potential propagation in which the geometry, electrophysiology and regional properties of ventricular myocardium can be specified so that, for example, different models for cardiac cellular electrophysiology can be used. We have computed action potential propagation during both normal beats and re-entry in an anatomically accurate model of ventricular geometry. By computing the resultant electric current flow in the torso we have also generated simulated ECG signals that result from specific activation patterns in the ventricular model. Models can be powerful tools for explaining observations, and this approach is able to provide a direct link between the different configurations of re-entry observed in computational and experimental studies, and the ECG signals observed in patients.
Clayton et al. (Thu,) conducted a other in Ventricular arrhythmias. Computational framework for simulating action potential propagation was evaluated. A computational framework was developed to simulate action potential propagation and generate simulated ECG signals, linking re-entry configurations to clinical ECG observations.