Multiscale Model—Differential Evolutionary Algorithm for Inverse Solution of T-Wave Inversion in Electrocardiography

T-wave inversion (TWI) on an electrocardiogram (ECG) is a key indicator of myocardial ischemia, yet existing inverse ECG methods lack quantitative physiological parameter resolution. This study aims to propose a novel multiscale computational framework to inversely identify the ionic mechanisms underlying TWI. A cell–tissue–torso cardiac electrophysiological model was integrated with a differential evolution (DE) algorithm. The forward model combined the Grandi atrial model and BPS2020 ventricular model, simulating action potential propagation via cellular automata and body surface ECGs via field point potentials. The inverse solution optimized 29 physiological parameters by minimizing the root-mean-square error between the simulated and clinical ECGs. The method was applied to 30 normal and 30 TWI cases to analyze the repolarization abnormalities. The study revealed that extracellular Ca2+ > 2.88 mmol/L and K+ < 3.4 mmol/L in ventricular myocytes (Endo, M, Epi) induce TWI. Quantitative analysis identified specific 95% confidence intervals for ionic imbalances in three scenarios: Case 1 (VEpi>VEndo>VM) with [Ca2+] 2.60–3.30 mmol/L and [K+] 1.9–4.7 mmol/L; Case 2 (VM>VEpi>VEndo) with [Ca2+] 2.36–3.68 mmol/L and [K+] 3.13–4.07 mmol/L; and Case 3 (VEpi>VM>VEndo) with [Ca2+] 2.67–3.91 mmol/L and [K+] 3.11–3.45 mmol/L. This approach enables cellular-scale mechanistic insights into TWI by quantifying ionic concentration changes. The framework supports the advancement of personalized cardiac diagnostics and drug development.