Abstract
Array topology in magnetocardiography system dictates spatial resolution and clinical applicability, impacting topographic reconstruction, which affects the accuracy of feature and source localization. Existing array designs rely on task-driven or empirical criteria without accounting for intrinsic imaging properties to ensure complete high-precision reconstruction and broad applicability, and analyses regarding the impact of array parameters on imaging remain lacking. To address these limitations, a computationally efficient electromagnetic simulation framework is proposed to guide array topological optimization. A three-dimensional electrophysiological forward model, combining the monodomain equation with phenomenological formulation, is constructed and regional parameters are optimized to rapidly simulate transmembrane potential. Following rigorous multidimensional validation of the mapped magnetic distribution against real data, high-fidelity signals are utilized to demonstrate the necessity of parameter optimization for imaging and to establish universally applicable criteria for the effective coverage to completely capture signals. The Manifold Harmonic Transform and the sampling theorem are employed to analyze dynamic anti-aliasing sampling requirements across cardiac cycle. Ultimately, integrating the spatial coverage and sampling criteria with a highly efficient hexagonal layout yields a broadly applicable and cost-effective topology. The reliability of array is verified and results demonstrate that the optimized configuration can achieve complete and robust reconstruction of spatiotemporally evolving signals, thereby establishing a quantitative foundation and reliable paradigm for the clinical deployment and application of system. Meanwhile, the analysis process of array optimization can serve as a reference for other application scenarios.