Multi-Scale Modeling of the Failing Heart for Cardiac Rysynchronization Therapy

描述（由申请人提供）：摘要心力衰竭影响着超过500万美国人，是导致死亡的主要原因。心脏再同步化治疗（CRT）在心力衰竭治疗中取得了重大进展，其中使用电起搏来改善机械泵功能。然而，由于缺乏对患者选择和引线放置的预测性客观标准，约30%的患者接受该手术后没有反应。拟议研究的总体目标是解决涉及使用心脏的多尺度计算模型来预测心脏再同步化治疗的患者结果的挑战。有三个具体目标：(1)建立人类衰竭心脏的三维多尺度计算模型。虽然详细的心室电力学模型已经开发出来，并在动物身上得到了验证，但仍需要对衰竭的人类心脏进行可比的模型。使用已发表的人体数据和临床可获得的测量，我们将开发和测试一种新的心室电力学模型在人类心脏衰竭；(2)建立适合患者临床测量的三维多尺度心脏模型参数的有效方法。我们将开发和测试方法，使衰竭的人类心脏基线模型适应于个体心力衰竭患者，利用心室几何形状、心内膜活动、血流动力学和泵功能的临床测量。我们将检验这一假设，即调整模型参数的子集将有可能匹配我们在心脏再同步化治疗的患者中获得的区域和整体心室机械功能和同步；(3)验证非同步性心力衰竭的患者特异性模型，以预测心脏再同步化治疗的反应。心脏再同步化可增强中重度心衰伴脑室传导延迟的心功能，并可导致逆转重构。通过施加心室起搏并使用患者特异性模型计算全局和局部机械功能，我们建议测试心室机电力学多尺度模型预测心脏再同步化治疗急性功能改善的能力。我们将检验区域壁应力的减少或区域张力发展同步性的改善，这一假设是由模型计算的，以响应再同步治疗，预测三个月后的逆转重塑。我们还将探讨使用患者特异性模型来优化CRT起搏方案。

DESCRIPTION (provided by applicant): Abstract Heart failure affects over five million Americans and is a leading cause of death. A significant recent advancement in the treatment of heart failure has been cardiac resynchronization therapy (CRT) in which electrical pacing is used to improve mechanical pump function. However, about 30% of patients indicated for the procedure do not respond owing to a lack of predictive objective criteria for patient selection and lead placement. The overall goal of the proposed research is to address the challenges involved using multi-scale computational models of the heart for predicting patient outcomes of cardiac resynchronization therapy. There are three specific aims: (1) To develop three-dimensional multi-scale computational models of the failing human heart. While detailed models of ventricular electromechanics have already been developed and validated for animals, there is a need for comparable models of the failing human heart. Using published human data and clinically accessible measurements, we will develop and test a new model of ventricular electromechanics in the failing human heart; (2) To develop efficient methods for fitting parameters of three- dimensional multi-scale models of the heart to patient-specific clinical measurements. We will develop and test methods for adapting the baseline model of the failing human heart to individual heart failure patients making use of clinical measurements of ventricular chamber geometry, endocardial activity, hemodynamics, and pump function. We will test the hypothesis that adjusting a subset of model parameters will make it possible to match regional and global ventricular mechanical function and synchrony that we obtain in patients indicated for cardiac resynchronization therapy; (3) To validate patient-specific models of dyssynchronous heart failure for predicting responses to cardiac resynchronization therapy. Cardiac resynchronization augments cardiac function in moderate-to-severe heart failure with an intraventricular conduction delay, and can lead to reverse remodeling. By imposing ventricular pacing and computing global and local mechanical function with the patient-specific models, we propose to test the ability of multi-scale models of ventricular electromechanics to predict acute functional improvements with cardiac resynchronization therapy. We will test the hypothesis that the reduction in regional wall stress or an improvement in the synchrony of regional tension development computed by the model in response to resynchronization therapy predicts reverse remodeling after three months. We will also explore the use of patient-specific models to optimize the CRT pacing protocol. PUBLIC HEALTH RELEVANCE: Not only is cardiac disease the leading cause of death among citizens of the USA, but heart failure - when the heart fails to supply the body's demand of blood - affects all aspects of the lives of patients and curtails everyday activities. A significant recent advancement in the treatment of a common type of heart failure - in which the heart is activated slower than normal - has been cardiac resynchronization therapy. In this therapy, a pacemaker is used to improve the timing of the beating of the left and right ventricles. However, about 30% of patients do not respond to this therapy for unknown reasons. The specific focus of this proposal is the development of computer models of failing human hearts, which are patient-specific. The models can then be used to predict the outcome - and thus to improve the number of patients to respond - and optimize this pacemaker therapy for patients.