PDE constrained optimization of electrical defibrillation in a 3D ventricular slice geometry.

Area of Science:

• Computational biology
• Biomedical engineering
• Cardiac electrophysiology

Background:

• Cardiac arrhythmias pose a significant health risk, necessitating effective defibrillation strategies.
• Accurate modeling of cardiac bioelectric activity is crucial for developing advanced defibrillation techniques.

Purpose of the Study:

• To develop and computationally investigate an optimal control approach for cardiac defibrillation.
• To model cardiac tissue and surrounding bath using the bidomain equations with realistic parameters.

Main Methods:

• Utilized the bidomain model equations to simulate cardiac bioelectric activity in a 3D geometry.
• Incorporated intramural fiber rotation and anisotropic conductivity derived from histological data.
• Employed the regularized Mitchell-Schaeffer model for ionic current dynamics.
• Applied Newton techniques for numerical optimization of electrode placement and control.

Main Results:

• Demonstrated an optimal control strategy for cardiac defibrillation.
• Successfully modeled complex cardiac bioelectric phenomena, including fiber rotation and anisotropy.
• Showcased the efficacy of electrode placement for arrhythmia dampening.
• Validated a parallel architecture for efficient multidomain potential computation and optimization.

Conclusions:

• The presented optimal control approach offers a promising strategy for cardiac defibrillation.
• Computational modeling provides valuable insights into optimizing defibrillation therapies.
• Advanced numerical techniques and parallel computing are essential for tackling complex bioelectric problems.