Computational Modeling of Scar Formation After Myocardial Infarction

每年有超过一百万的美国人遭受心脏病发作（心肌梗塞）。对于大多数 在初始事件中存活，严重并发症的风险，如梗死破裂和心力衰竭 取决于替代受损心脏的疤痕组织的结构和机械特性 肌肉在最初的几个星期。疤痕组织是由心脏成纤维细胞产生的， 表明瘢痕结构和机械性能受到机械拉伸的强烈影响， 在愈合过程中。成纤维细胞如何对单个信号（如机械拉伸）作出反应的生物学 已经被广泛研究;然而，我们仍然对成纤维细胞如何整合和 对愈合伤口中存在的多种信号做出反应。因此，我们开发了一个基于代理的 瘢痕形成模型（ABM），代表单个成纤维细胞-每个迁移，对齐， 沉积和重塑胶原蛋白，分裂，死亡，并对个体化学，结构， 和机械信号-并预测由此产生的演变 组织水平的胶原蛋白含量和纤维排列在不同模式的拉伸下愈合的疤痕。 在这里，我们建议将ABM与梗死左心室的有限元模型（FEM）耦合， 产生一个耦合模型，该模型可以预测演变中的疤痕结构、疤痕 心肌梗死后的心脏功能以及对改变梗死力学的治疗的反应 (Aim 1）。然后，我们将使用实验和建模相结合的方法来更好地理解细胞 机械拉伸调节胶原蛋白含量和愈合中排列的机制 心肌梗塞具体来说，我们将测试胶原蛋白的机械调节 降解显著影响机械卸载过程中的胶原含量和排列（Aim 2），并且瘢痕压实显著影响胶原纤维密度，但不影响面内纤维 在一系列载荷条件下的对齐（目标3）。拟议的研究具有潜在意义 因为他们将产生第一个经过验证的，预测梗死愈合的模型， 机械条件-使计算筛选和设计新的治疗方法-和 因为它们将提供重要的新的见解，了解细胞机制， 环境调节瘢痕形成，这可能导致新的治疗方法的确定。 调节梗死愈合的方法。

Over a million Americans suffer a heart attack (myocardial infarction) each year. For the majority who survive the initial event, the risks of serious complications such as infarct rupture and heart failure depend on the structure and mechanical properties of the scar tissue that replaces damaged heart muscle over the first few weeks. That scar tissue is produced by cardiac fibroblasts, and we recently showed that scar structure and mechanical properties are strongly influenced by mechanical stretch during healing. The biology of how fibroblasts respond to individual signals such as mechanical stretch has been studied extensively; yet we still understand relatively little about how fibroblasts integrate and respond to the multiple signals present in a healing wound. We therefore developed an agent-based model (ABM) of scar formation that represents individual fibroblasts - each migrating, aligning, depositing and remodeling collagen, dividing, dying, and responding to individual chemical, structural, and mechanical signals according to experimental measurements - and predicts the resulting evolution of tissue-level collagen content and fiber alignment in scars healing under different patterns of stretch. Here, we propose to couple this ABM with a finite-element model (FEM) of the infarct left ventricle to produce a coupled model that can predict the dynamic interplay between evolving scar structure, scar mechanics, and heart function after infarction and in response to therapies that alter infarct mechanics (Aim 1). Then, we will use a combination of experiments and modeling to better understand the cellular mechanisms by which mechanical stretch regulates collagen content and alignment in healing myocardial infarcts. Specifically, we will test the hypotheses that mechanical regulation of collagen degradation significantly influences collagen content and alignment during mechanical unloading (Aim 2), and that scar compaction significantly influences collagen fiber density but not in-plane fiber alignment across a range of loading conditions (Aim 3). The proposed studies are potentially significant both because they will generate the first validated, predictive model of infarct healing across a range of mechanical conditions - enabling computational screening and design of novel therapies - and because they will provide important new insight into the cellular mechanisms by which mechanical environment regulates scar formation, which could lead to the identification of new therapeutic approaches to modulating infarct healing.