Epicardial potential reconstruction in magnetocardiography imaging using Laplace-prior Tikhonov regularization

Electrocardiographic imaging (ECGI) has been widely adopted as a standard technique for cardiac electrophysiological imaging. However, due to variations in tissue conductivity, the electric field propagation is often subject to significant attenuation and distortion. In recent years, with advances in ultra-sensitive magnetic sensor technology, magnetocardiographic imaging (MCGI) has emerged as a promising alternative for non-invasive reconstruction of cardiac electrophysiological activity. In this paper, a biophysical forward model describing the relationship between epicardial potentials and surface magnetic fields is established. Based on this forward model, a Laplace prior-based Tikhonov regularization method for MCGI (LTR-MCGI) is proposed to reconstruct epicardial potentials. The single dipole model is utilized to simulate the epicardial potential. Meanwhile, the corresponding surface magnetic field was calculated using the Biot-Savart law. Experimental results under different magnetic field signal-to-noise ratios (SNRs) demonstrate that at an SNR of 100 dB, the reconstructed epicardial potentials achieve a correlation coefficient of 0.875 with reference potentials, along with significantly reduced error metrics (RMSE reduces to 1.771, MSE reduces to 3.135, RE reduces to 18.194%), which effectively capturing the heart’s electrophysiological state. These findings indicate that the proposed LTR-MCGI method can accurately reconstruct cardiac electrophysiological information non-invasively, offering promising clinical applications for cardiac diagnosis and treatment guidance.