Resynchronizing the Failing Heart: Insights from a Multiscale Cardiac Model

描述(申请人提供)：本提案是对PAR-08-023《健康和疾病中心脏的预测模型》的回应。心力衰竭是发病率和死亡率的主要原因，对全球卫生支出有很大贡献。心力衰竭患者经常表现出收缩不同步，这会降低心脏收缩功能。心脏再同步治疗(CRT)使用双室起搏来重新协调心脏的收缩。CRT已被证明可以改善心力衰竭症状并减少住院时间，但约30%的患者对该疗法没有反应。目前识别CRT潜在应答者的方法预测能力差，反映了对导致机械不同步的复杂病理生理和机电因素的不完全理解。具体地说，考虑到CRT无反应者中有很大一部分是慢性心肌梗死(MI)的心力衰竭患者，确定慢性MI对非同步性心力衰竭(DHF)的贡献并深入探讨其限制CRT益处的机制对于CRT疗效的改善至关重要。本申请解决了这一需求。本研究的总体目标是阐明慢性心肌梗死在心力衰竭不同步性中的作用及其对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)和弥散张量MRI扫描中，分离基于3D图像的犬心脏的多尺度计算模型，该模型包含与DHF和慢性MI相关的有害的结构、机械和电生理重构，从分子水平到完整心脏的水平。这一强大的预测建模方法将被用于1)提供对梗塞位置和跨室壁疤痕程度对左心衰竭收缩不同步的影响的机械性洞察，以及2)确定最佳的CRT策略。本申请中提出的在DHF和慢性心肌梗死(DHF+MI)环境下建立有效的心室电力学预测模型(DHF+MI心脏模型)，克服了现有实验技术无法以高时空分辨率同时记录心脏的3D电和机械活动的问题，从而提供了对慢性MI对心力衰竭不同步性和CRT有效性的贡献的理解。根据这项研究，对DHF+MI心脏的机电行为的新的基础科学见解有望最终导致合理地优化缺血性心肌病患者的CRT输送，并改进可行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.