Department of Bioengineering, University of Utah, Salt Lake City, UT, USA.
Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA.
Ann Biomed Eng. 2018 Sep;46(9):1325-1336. doi: 10.1007/s10439-018-2048-0. Epub 2018 May 21.
The biophysical basis for electrocardiographic evaluation of myocardial ischemia stems from the notion that ischemic tissues develop, with relative uniformity, along the endocardial aspects of the heart. These injured regions of subendocardial tissue give rise to intramural currents that lead to ST segment deflections within electrocardiogram (ECG) recordings. The concept of subendocardial ischemic regions is often used in clinical practice, providing a simple and intuitive description of ischemic injury; however, such a model grossly oversimplifies the presentation of ischemic disease-inadvertently leading to errors in ECG-based diagnoses. Furthermore, recent experimental studies have brought into question the subendocardial ischemia paradigm suggesting instead a more distributed pattern of tissue injury. These findings come from experiments and so have both the impact and the limitations of measurements from living organisms. Computer models have often been employed to overcome the constraints of experimental approaches and have a robust history in cardiac simulation. To this end, we have developed a computational simulation framework aimed at elucidating the effects of ischemia on measurable cardiac potentials. To validate our framework, we simulated, visualized, and analyzed 226 experimentally derived acute myocardial ischemic events. Simulation outcomes agreed both qualitatively (feature comparison) and quantitatively (correlation, average error, and significance) with experimentally obtained epicardial measurements, particularly under conditions of elevated ischemic stress. Our simulation framework introduces a novel approach to incorporating subject-specific, geometric models and experimental results that are highly resolved in space and time into computational models. We propose this framework as a means to advance the understanding of the underlying mechanisms of ischemic disease while simultaneously putting in place the computational infrastructure necessary to study and improve ischemia models aimed at reducing diagnostic errors in the clinic.
心电图评估心肌缺血的生物物理基础源于这样一种观念，即缺血组织相对均匀地沿着心脏的心内膜面发展。这些心内膜下损伤组织产生的腔内电流导致心电图（ECG）记录中的 ST 段偏移。心内膜下缺血区域的概念在临床实践中经常被使用，为缺血损伤提供了一个简单直观的描述；然而，这种模型过于简化了缺血性疾病的表现，导致基于心电图的诊断出现错误。此外，最近的实验研究对心内膜下缺血模型提出了质疑，而是提出了一种更分布式的组织损伤模式。这些发现来自于实验，因此既有来自活体测量的影响，也有其局限性。计算机模型经常被用来克服实验方法的限制，并在心脏模拟方面有着悠久的历史。为此，我们开发了一个计算模拟框架，旨在阐明缺血对可测量心脏电位的影响。为了验证我们的框架，我们模拟、可视化和分析了 226 个急性心肌缺血事件的实验结果。模拟结果在定性（特征比较）和定量（相关性、平均误差和显著性）方面与实验获得的心外膜测量结果一致，特别是在缺血应激升高的情况下。我们的模拟框架引入了一种新方法，将具有特定个体的、几何模型和在空间和时间上高度解析的实验结果纳入计算模型中。我们提出这个框架是为了推进对缺血性疾病潜在机制的理解，同时建立计算基础设施，以研究和改进旨在减少临床诊断错误的缺血模型。
