Topology Optimization of Magnetocardiographic Array Based on Cardiac Electromagnetic Simulation Model.

Area of Science:

• Biomedical Engineering
• Computational Electromagnetics
• Medical Imaging

Background:

• Magnetocardiography (MCG) array topology is crucial for spatial resolution and clinical use, impacting topographic reconstruction accuracy.
• Current MCG array designs lack optimization based on intrinsic imaging properties, hindering high-precision reconstruction and broad applicability.
• Limited analysis exists on how array parameters affect MCG imaging performance.

Purpose of the Study:

• To develop a computationally efficient electromagnetic simulation framework for optimizing MCG array topology.
• To establish universally applicable criteria for effective signal coverage and sampling in MCG.
• To design a broadly applicable and cost-effective MCG array topology.

Main Methods:

• Constructed a 3D electrophysiological forward model combining the monodomain equation and phenomenological formulation.
• Optimized regional parameters to simulate transmembrane potential and validated magnetic distribution against real data.
• Employed Manifold Harmonic Transform and sampling theorem to analyze dynamic anti-aliasing sampling requirements.

Main Results:

• Demonstrated the necessity of parameter optimization for accurate MCG imaging and established effective coverage criteria.
• Developed a hexagonal array layout integrating spatial coverage and sampling criteria, yielding a cost-effective topology.
• Verified array reliability, showing the optimized configuration achieves complete and robust spatiotemporal signal reconstruction.

Conclusions:

• The proposed simulation framework and optimization criteria provide a quantitative foundation for clinical MCG deployment.
• The optimized hexagonal array topology enhances reconstruction accuracy and broadens clinical applicability.
• The array optimization analysis methodology can inform other application scenarios.