A new physiologically-based computational heart model successfully matched human action potentials and generated complex arrhythmias when connected in closed loop with a pacing device.
Can a high-level physiologically-based computational heart model accurately simulate cardiac electrophysiology and device-induced arrhythmias in a closed-loop system?
A novel time-critical computational heart model can accurately simulate cardiac electrophysiology and device-induced arrhythmias, offering a tool for device validation and personalized treatment design.
OBJECTIVE: Evaluating and testing cardiac electrical devices in a closed-physiologic-loop can help design safety, but this is rarely practical or comprehensive. Furthermore, in silico closed-loop testing with biophysical computer models cannot meet the requirements of time-critical cardiac device systems, while simplified models meeting time-critical requirements may not have the necessary dynamic features. We propose a new high-level (abstracted) physiologically-based computational heart model that is time-critical and dynamic. METHODS: The model comprises cardiac regional cellular-electrophysiology types connected by a path model along a conduction network. The regional electrophysiology and paths are modeled with hybrid automata that capture non-linear dynamics, such as action potential and conduction velocity restitution and overdrive suppression. The hierarchy of pacemaker functions is incorporated to generate sinus rhythms, while abnormal automaticity can be introduced to form a variety of arrhythmias such as escape ectopic rhythms. Model parameters are calibrated using experimental data and prior model simulations. CONCLUSION: Regional electrophysiology and paths in the model match human action potentials, dynamic behavior, and cardiac activation sequences. Connected in closed loop with a pacing device in DDD mode, the model generates complex arrhythmia such as atrioventricular nodal reentry tachycardia. Such device-induced outcomes have been observed clinically and we can establish the key physiological features of the heart model that influence the device operation. SIGNIFICANCE: These findings demonstrate how an abstract heart model can be used for device validation and to design personalized treatment.
Ai et al. (Thu,) conducted a other in Cardiac arrhythmias. Physiologically-based computational heart model was evaluated on Matching human action potentials, dynamic behavior, and cardiac activation sequences. A new physiologically-based computational heart model successfully matched human action potentials and generated complex arrhythmias when connected in closed loop with a pacing device.