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+ 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.
Guo et al. (Sat,) studied this question.
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