Advanced Simulation and Measurement of the Magnetocardiography Forward Problem Based on a Novel Electromagnetic Conversion Analytical Model

In the electrophysiological study of ischemic chronic heart failure (I-CHF) patients, cardiac electrical activity is captured using body surface electrodes in traditional electrocardiography (ECG). However, due to its limited spatial resolution, surface potential changes are reflected by ECG, and deep cardiac electrophysiological signals are struggled to be accurately detected, especially under complex pathological conditions. To address this limitation, a forward problem analytical model based on a 3-D cardiac-torso model for magnetocardiography (MCG) is proposed. An individualized ventricular-torso dual-domain model is constructed, and an improved diffusion equation is employed to accurately simulate the potential distribution between the endocardium (ENDO) and epicardium (EPI) in I-CHF patients. The dynamic characteristics of the 3-D equivalent current density within cardiac tissue are analyzed. The simulated 3-D potential distribution is converted into a body surface magnetic field (BSMF) distribution and compared with MCGs obtained using a spin-exchange relaxation-free (SERF) magnetometer array. The proposed electromagnetic conversion analytical model demonstrates improvements in accuracy. At the peak moments of the R-wave and T-wave, significant differences in SSIM values are observed between normal individuals and I-CHF patients. SSIM values for normal individuals are higher (R-wave of 0.9066 and T-wave of 0.8537) compared to I-CHF patients (R-wave of 0.8135 and T-wave of 0.8231). The simulated and measured data for the healthy group are consistent, while for the I-CHF group, the simulated gain and offset increase from 0.98 and 1.98 to 1.06 and 2.25, and the measured gain and offset decrease from 0.81 and 3.02 to 0.78 and 2.87. These results highlight the model’s ability to differentiate between normal and I-CHF conditions, providing a promising tool for early diagnosis of diseases.