Metabolic/Electrophysiological Model of the Heart under Ischemia/Reperfusion

描述（由申请人提供）：心源性猝死（SCD）通常归因于心室颤动，这是一种致命的心律失常，导致心脏不协调收缩。实验表明，心肌细胞的电兴奋性在缺血和再灌注状态下会降低或消除。其机制涉及肌细胞功能的一系列失效，其中代谢应激条件下活性氧（ROS）的产生增加，降低甚至消除了肌细胞的兴奋性。实验证据表明，心肌中的这些不可兴奋区域可以阻断电兴奋的传播。然而，代谢应激区的三维分布如何影响心脏的电生理行为仍然未知。利用多尺度综合代谢和电生理全心模型，可以为解剖缺血再灌注条件下心律失常的发生机制提供机会。本研究的总体目标是解决整个心脏代谢和电生理过程之间的耦合在缺血和再灌注下导致心律失常风险的方式。为了实现这一目标，我将从磁共振成像（MRI）和扩散张量磁共振成像（DTMRI）、电生理记录和线粒体代谢数据，开发和验证整个豚鼠心脏中新的生物物理、代谢和解剖学详细的电传导计算模型。这些模型将用于验证代谢汇（代谢诱导的不兴奋性区域）促进再入的假设，从而有助于心律失常的产生。在缺血和再灌注下的代谢和电生理过程的验证现实模型的发展克服了当前实验技术无法同时记录高空间和时间分辨率的心脏三维电和代谢活动的缺陷。从这项研究中获得的新见解有望最终改善识别ICD候选者的选择标准，并开发新的诊断和治疗方法来对抗心律失常。这与NHLBI的使命有关，即支持调查心脏病病因和治疗的基础研究。具体目的如下：1)利用MRI和DTMRI重建豚鼠心脏的几何形状、纤维和片向。结合成像数据、电生理记录和线粒体生物能量学数据，开发和验证豚鼠心脏电和代谢耦合的详细高分辨率3D计算模型。2)使用具体目标1下开发的计算模型；探讨豚鼠心脏缺血-再灌注条件下线粒体区域解耦导致再入回路形成的机制。

DESCRIPTION (provided by applicant): Sudden Cardiac Death (SCD) is often attributed to ventricular fibrillation, a lethal arrhythmia that results in uncoordinated contraction of the heart. Experiments have demonstrated that the cardiac myocyte electrical excitability can be reduced or eliminated during conditions of ischemia and reperfusion. The mechanism involves a series of failures in myocyte function, in which increased production of reactive oxygen species (ROS) during conditions of metabolic stress reduces or even eliminates myocyte excitability. Experimental evidence has demonstrated that these inexcitable regions within the myocardium could block propagation of electrical excitation. However, how the 3D distribution of metabolically-stressed regions affects the electrophysiological behavior of the heart remains unknown. Utilizing multi-scale integrated metabolic and electrophysiological whole heart models could provide an opportunity to dissect the mechanisms for arrhythmia generation under the conditions of ischemia and reperfusion. The overall objective of this research is to address the ways in which coupling between metabolic and electrophysiological processes in the whole heart contribute to the risk of arrhythmia under ischemia and reperfusion. To achieve this objective, I will develop and validate, from magnetic resonance imaging (MRI) and diffusion-tensor magnetic resonance imaging (DTMRI), electrophysiological recordings, and mitochondrial metabolic data, novel biophysically-, metabolically- and anatomically-detailed computational models of electrical conduction in whole guinea pig hearts. These models will be used to test the hypothesis that the metabolic sinks (regions of metabolically- induced inexcitability) promote reentry and thus contribute to the generation of arrhythmia. The development of a validated realistic model of metabolic and electrophysiological processes under ischemia and reperfusion overcomes the inability of current experimental techniques to simultaneously record the 3D electrical and metabolic activity of the heart with high spatial and temporal resolution. The new insights gained from this study are expected to ultimately lead to improvement in the selection criteria for identifying ICD candidates, and in the development of novel diagnostic and therapeutic procedures for combating arrhythmias. This relates to the NHLBI mission to support basic research that investigates the causes and treatments of heart disease. The specific aims are as follows 1) Use MRI and DTMRI to reconstruct the geometry, fiber and sheet orientation of guinea pig hearts. Combine the imaging data, electrophysiological recordings, and mitochondrial bioenergetics data, to develop and validate electrically and metabolically coupled detailed high-resolution 3D computational models of guinea pig hearts. 2) Using the computational models developed under Specific Aim 1; investigate the mechanisms by which regional mitochondrial uncoupling under the conditions of ischemia- reperfusion results in the formation of reentrant circuits in the guinea pig heart. PUBLIC HEALTH RELEVANCE: This research will help explain how the metabolic and electrophysiological processes in the heart contribute to the risk of arrhythmia under ischemia/reperfusion. The insights gained from this research will ultimately help better identify candidates for implantable cardioverter defibrillators and develop new strategies for combating arrhythmias.