IEEE J Biomed Health Inform. 2018 Sep;22(5):1445-1455. doi: 10.1109/JBHI.2017.2768534. Epub 2017 Nov 1.
Myocardial infarction (MI) is among the leading causes of death in the United States. It is imperative to identify and characterize MIs for timely delivery of life-saving medical interventions. Cardiac electrical activity propagates in space and evolves over time. Traditional works focus on the analysis of time-domain ECG (e.g., 12-lead ECG) on the body surface for the detection of MIs, but tend to overlook spatiotemporal dynamics in the heart. Body surface potential mappings (BSPMs) provide high-resolution distribution of electric potentials over the entire torso, and therefore provide richer information than 12-lead ECG. However, BSPM are available on the body surface. Clinicians are in need of a closer look of the electric potentials in the heart to investigate cardiac pathology and optimize treatment strategies. In this paper, we applied the method of spatiotemporal inverse ECG (ST-iECG) modeling to map electrical potentials from the body surface to the heart, and then characterize the location and extent of MIs by investigating the reconstructed heart-surface electrograms. First, we investigate the impact of mesh resolution on the inverse ECG modeling. Second, we solve the inverse ECG problem and reconstruct heart-surface electrograms using the ST-iECG model. Finally, we propose a wavelet-clustering method to investigate the pathological behaviors of heart-surface electrograms, and thereby characterize the extent and location of MIs. The proposed methodology is evaluated and validated with real data of MIs from human subjects. Experimental results show that negative QRS waves in heart-surface electrograms indicate potential regions of MI, and the proposed ST-iECG model yields superior characterization results of MIs on the heart surface over existing methods.
心肌梗死（MI）是美国主要的死亡原因之一。及时识别和描述 MI 对于及时提供救生医疗干预至关重要。心脏的电活动在空间中传播并随时间演变。传统的研究工作主要集中在分析体表心电图（例如 12 导联心电图）的时域特征，以检测 MI，但往往忽略了心脏的时空动力学。体表电位图（BSPM）提供了整个躯干上高分辨率的电位分布，因此比 12 导联心电图提供了更丰富的信息。然而，BSPM 只能在体表获得。临床医生需要更近距离地观察心脏内的电位，以研究心脏病理并优化治疗策略。在本文中，我们应用时空逆心电图（ST-iECG）建模方法，将体表的电位映射到心脏上，并通过研究重建的心脏表面电图来描述 MI 的位置和范围。首先，我们研究了网格分辨率对逆心电图建模的影响。其次，我们使用 ST-iECG 模型解决逆心电图问题并重建心脏表面电图。最后，我们提出了一种小波聚类方法来研究心脏表面电图的病理行为，从而描述 MI 的范围和位置。该方法使用来自人体 MI 的真实数据进行了评估和验证。实验结果表明，心脏表面电图中的负 QRS 波表明 MI 的潜在区域，并且所提出的 ST-iECG 模型在心脏表面上对 MI 的特征描述结果优于现有方法。
