A bidomain model based BEM-FEM coupling formulation for anisotropic cardiac tissue

Area of Science:

• Computational electrophysiology
• Biophysics
• Medical imaging

Background:

• Accurate modeling of cardiac electrical activity is crucial for interpreting electrocardiographic (ECG) and magnetocardiographic (MCG) signals.
• The anisotropic nature of cardiac muscle significantly influences these bioelectrical fields.
• Existing models often simplify or neglect myocardial anisotropy, potentially leading to inaccuracies.

Purpose of the Study:

• To develop and validate a hybrid boundary element method (BEM)/finite element method (FEM) approach for the electrocardiographic and magnetocardiographic forward problem.
• To incorporate the anisotropic properties of the myocardium within a bidomain model.
• To assess the impact of cardiac muscle anisotropy on body surface potentials and extracorporeal magnetic fields.

Main Methods:

• A hybrid BEM/FEM formulation was developed, applying FEM to the anisotropic myocardium (bidomain model) and BEM to the surrounding isotropic volume conductor.
• Coupling was achieved by ensuring continuity of electric potential and current density normal across the heart boundary.
• The BEM component was integrated as an equivalent finite element into the FEM stiffness matrix, preserving sparsity.
• Convergence was demonstrated using a spherical model with an analytic solution.
• The method was applied to a fibrous dog ventricle model, using a precomputed activation sequence to calculate body surface potentials and magnetic fields.

Main Results:

• The hybrid BEM/FEM scheme demonstrated continuous convergence for the spherical model.
• Calculations using the dog ventricle model, incorporating anisotropic bidomain conductivities, yielded body surface potentials and magnetic fields.
• Comparison with models neglecting anisotropy (oblique or uniform dipole layer) revealed significant errors.
• These errors highlight cardiac muscle as a major torso inhomogeneity.

Conclusions:

• The proposed hybrid BEM/FEM method accurately accounts for cardiac muscle anisotropy in electrophysiological modeling.
• Neglecting myocardial anisotropy can lead to substantial errors in computed ECG and MCG signals.
• Cardiac muscle anisotropy is a critical factor that must be considered for precise forward problem solutions in electrocardiology.