Cardiac digital twins (CDTs) have the potential to offer individualized evaluation of cardiac function in a non-invasive manner, making them a promising approach for personalized diagnosis and treatment planning of my-ocardial infarction (MI). The inference of accurate myocardial tissue properties is crucial in creating a reliable CDT of MI. In this work, we investigate the feasibility of inferring myocardial tissue properties from the electrocardiogram (ECG) within a CDT platform. The platform integrates multi-modal data, such as cardiac MRI and ECG, to enhance the accuracy and reliability of the inferred tissue properties. We perform a sensitivity analysis based on computer simulations, systematically exploring the effects of infarct location, size, degree of transmurality, and electrical ac-tivity alteration on the simulated QRS complex of ECG, to establish the limits of the approach. We subsequently present a novel deep computational model, comprising a dual-branch variational autoencoder and an inference model, to infer infarct location and distribution from the simulated QRS. The proposed model achieves mean Dice scores of 0.457 \pm 0.317 and 0.302 \pm 0.273 for the inference of left ventricle scars and border zone, respectively. The sensitivity analysis enhances our understanding of the complex relationship between infarct characteristics and electrophysiological features. The in silico experimental results show that the model can effectively capture the relationship for the inverse inference, with promising potential for clinical application in the future. The code will be released publicly once the manuscript is accepted for publication.

翻译：心脏数字孪生（CDT）有望以无创方式提供个体化的心功能评估，因此成为心肌梗死（MI）个性化诊断与治疗方案制定的重要技术路径。精准推断心肌组织特性是构建可靠MI数字孪生的关键。本研究在CDT平台框架内，探索从心电图（ECG）推断心肌组织特性的可行性。该平台融合心脏磁共振成像与心电图等多模态数据，以提升推断组织特性的准确性与可靠性。我们基于计算机模拟开展敏感性分析，系统探究梗死位置、大小、透壁程度及电活动改变对模拟ECG QRS波群的影响，从而明确该方法的适用范围。随后我们提出一种新型深度计算模型，该模型包含双分支变分自编码器与推断模块，可从模拟QRS波群中推断梗死位置与分布。所提模型对左心室瘢痕与边缘区的推断平均Dice系数分别为0.457±0.317和0.302±0.273。敏感性分析增强了对梗死特征与电生理特征间复杂关系的理解。计算机模拟实验结果表明，该模型能有效捕捉逆推断所需的关系映射，具有未来临床应用的潜力。稿件被接收发表后，相关代码将开源发布。