Resynchronizing the Failing Heart: Insights from a Multiscale Cardiac Model

描述（由申请人提供）：本提案是对PAR-08-023“健康和疾病中的心脏预测模型”的响应。心力衰竭是发病率和死亡率的一个主要原因，对全球卫生支出的贡献很大。心力衰竭患者通常表现为收缩不同步，从而降低心脏收缩功能。心脏再同步化治疗（CRT）采用双心室起搏来重新协调心脏收缩。CRT已被证明可以改善心衰症状并减少住院时间，但大约30%的患者对治疗没有反应。目前识别CRT潜在应答者的方法预测能力较差，反映了对机械不同步背后复杂的病理生理和机电因素的不完全理解。具体而言，鉴于大部分CRT无应答者是心力衰竭合并慢性心肌梗死（MI）的患者，确定慢性心肌梗死对非同步心力衰竭（DHF）的贡献，并彻底探索其限制CRT益处的机制，对提高CRT有效性至关重要。当前的应用程序满足了这一需求。本研究的总体目的是阐明慢性心肌梗死在心衰非同步化中的作用及其对CRT疗效的影响。为了实现所提出的研究目标，我们将从磁共振成像（MRI）和扩散张量MRI扫描，从分子水平到完整心脏的分子水平，从包含DHF和慢性心肌梗死相关的有害结构，机械和电生理重塑的犬心脏的个体化3D图像为基础的心室电力学多尺度计算模型。这种强大的预测建模方法将用于1)提供梗死位置和跨壁疤痕程度对左心室心力衰竭收缩非同步化的贡献机制，以及2)确定最佳CRT策略。在本应用中提出的DHF和慢性心肌梗死（DHF+心肌梗死心脏模型）设置的心室电力学预测模型的开发，克服了当前实验技术无法同时以高时空分辨率记录心脏的3D电和机械活动的缺点，从而提供了对慢性心肌梗死对心力衰竭非同步化和CRT有效性的贡献的理解。本研究将获得DHF+MI心脏机电行为的新基础科学见解，预计最终将导致缺血性心肌病患者CRT输送的合理优化，并改善可行CRT候选者的选择标准。

DESCRIPTION (provided by applicant): This proposal is in response to PAR-08-023 "Predictive Models of the Heart in Health and Disease". Heart failure is a major cause of morbidity and mortality, contributing significantly to global health expenditure. Heart failure patients often exhibit contractile dyssynchrony, which diminishes cardiac systolic function. Cardiac resynchronization therapy (CRT) employs bi-ventricular pacing to re-coordinate the contraction of the heart. CRT has been shown to improve heart failure symptoms and reduce hospitalization, yet approximately 30% of patients fail to respond to the therapy. The poor predictive ability of current approaches to identify potential responders to CRT reflects the incomplete understanding of the complex pathophysiologic and electromechanical factors that underlie mechanical dyssynchrony. Specifically, given that a large portion of CRT non-responders are heart failure patients with chronic myocardial infarction (MI), it is of paramount importance to the improvement in CRT effectiveness that the contribution of chronic MI to dyssynchronous heart failure (DHF) is identified, and the mechanisms by which it limits CRT benefit thoroughly explored. The present application addresses this need. The overall objective of this research is to elucidate the role of chronic MI in heart failure dyssyn- chrony and its effect on CRT effectiveness. To achieve the objective of the proposed research, we will de- flop, from magnetic resonance imaging (MRI) and diffusion tensor MRI scans, individualized 3D image-based multiscale computational models of ventricular electromechanics in canine hearts that incorporate the deleterious- ous structural, mechanical, and electrophysiological remodeling associated with DHF and chronic MI, from the level of the molecule to that of the intact heart. This powerful predictive modeling approach will then be used 1) to provide mechanistic insight into the contribution of the infarct location and of the degree of transmural scar extent to left ventricular heart failure contractile dyssynchrony, and 2) to determine the optimal CRT strategy. The development of a validated predictive model of ventricular electromechanics in the setting of DHF and chronic MI (DHF+MI heart model), as proposed in this application, overcomes the inability of current experimental techniques to simultaneously record the 3D electrical and mechanical activity of the heart with high spatiotemporal resolution, and thus to provide an understanding of the contribution of chronic MI to heart failure dyssynchrony and CRT effectiveness. The new basic-science insights into the electromechanical behavior in the DHF+MI heart to be acquired under this study are expected to ultimately lead to rational optimization of CRT delivery in patients with ischemic cardiomyopathy and to improvements in the selection criteria for viable CRT candidates.