A computational model of the G&R during atherosclerosis: Integrating mechanics and biology

G 的计算模型

• 批准号: 9448153
• 负责人: Heather Naomi Hayenga
• 金额: $ 36.5万
• 依托单位: UNIVERSITY OF TEXAS DALLAS
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9448153
• 关键词: Address; Anatomy; Area; Arterial Fatty Streak; Arteries; Atherosclerosis; Back; Basic Science; Behavior; Biochemical; Biological; Biological Models; Biology; Blood flow; Calcium; Cardiovascular Diseases; Cause of Death; Cells; Characteristics; Chemotaxis; Cholesterol; Clinical; Code; Communities; Computer Simulation; Coronary artery; Coupling; Cues; Data; Decision Making; Dependence; Detection; Development; Diagnosis; Diagnostic; Disease; Effectiveness; Environment; Equation; Event; Evolution; Family suidae; Finite Element Analysis; Foundations; Frequencies; Geometry; Goals; Grant; Growth; Health; Human; Imaging Techniques; Individual; Intervention; Lesion; Liquid substance; Literature; Maps; Mechanical Stress; Mechanics; Methods; Modeling; Molecular; Monitor; Morphology; Patients; Periodicity; Pharmacologic Substance; Physiological; Process; Property; Proteins; Research; Risk; Risk Assessment; Rupture; Solid; Specificity; Stenosis; Stents; Stress; Time; Tissues; United States; Validation; Variant; Work; arterial remodeling; atherogenesis; atherosclerotic plaque rupture; base; cell motility; clinical decision-making; clinical imaging; design; hemodynamics; human data; improved; in vivo; millisecond; molecular array; multi-scale modeling; multidisciplinary; non-invasive imaging; novel; open source; outcome forecast; personalized decision; predictive modeling; pressure; prognostic tool; programs; shear stress; simulation; tool; user-friendly; virtual

PROJECT SUMMARY / ABSTRACT: For over a century cardiovascular diseases have been the primary cause of death in the United States. Therefore, improved tools to aid in diagnosis and prognosis of atherosclerosis are needed. A step towards this goal is to evaluate the hypothesis that integrative multi-scale, multiphysics modeling is capable of predicting the growth and remodeling of atherogenesis in a simulated coronary artery. The methods required to accomplish this objective will involve 1) setting up a theoretical framework for a multiscale model capable of robustly integrating interactions from the protein to tissue level of a coronary artery, 2) establishing an accurate process to calculate the stresses resulting from pressurization and flow in this artery, 3) coupling these simulations to create a congruent multiscale model capable of simulating atherosclerotic plaque progression, and 4) validating model predictions to longitudinal in-vivo human and ex-vivo porcine data detailing plaque progression. Previously, we have shown that inclusive computational models are capable of predicting the hemodynamically, anatomically, and mechano-chemo-biologically varying aspects during arterial remodeling under healthy and hypertensive conditions. Since, this model was incapable of predicting the 3D changes, atherosclerotic plaques, and mechanical inhomogeneity present in the advanced stages of atherosclerosis, we present an approach combining agent based modeling (ABM) with finite element analysis (FEA) and computational fluid dynamics (CFD) to create a modeling tool that can predict the evolution of atherosclerotic plaque progression and instability. Together this model will be able to handle mechano-geometric complexity (FEA & CFD) and chemo- biological complexity (ABM) to a degree existing approaches cannot. From a basic science perspective, by integrating numerous cell-level behaviors one can better understand the underlying causes leading to plaque progression. Moreover, it will reveal areas that warrant further research or reveal emergent properties otherwise overlooked. Ultimately, a better multi-scale model of plaque evolution will be insightful for individualized decision making (e.g. to treat or not to treat a lesion) and foundational for design changes in interventional approaches (e.g. hypothesizing how an artery will respond to a pharmaceutical candidate, stent design or graft).

项目总结/摘要： 世纪以来，心血管疾病一直是人类死亡的主要原因。 美国的因此，改善工具，以帮助诊断和预后动脉粥样硬化 是必要的。实现这一目标的一个步骤是评估综合多尺度， 多物理场建模能够预测动脉粥样硬化的生长和重塑。 模拟冠状动脉。实现这一目标所需的方法包括：1） 建立了一个多尺度模式的理论框架， 从冠状动脉的蛋白质到组织水平的相互作用，2）建立准确的 计算由该动脉中的加压和流动引起的应力的过程，3） 耦合这些模拟以创建能够模拟 动脉粥样硬化斑块进展，和4）验证模型预测纵向体内 人和离体猪的数据详细描述了斑块进展。之前，我们已经证明， 包括的计算模型能够预测血流动力学，解剖学， 以及在健康和低血压条件下动脉重塑期间的机械-化学-生物学变化方面， 高血压病由于该模型无法预测3D变化， 动脉粥样硬化斑块和机械不均匀性存在于晚期 动脉粥样硬化，我们提出了一种基于代理的建模（ABM）与有限 有限元分析（FEA）和计算流体动力学（CFD），以创建一个建模工具， 可以预测动脉粥样硬化斑块的进展和不稳定性。一起这么 模型将能够处理机械几何复杂性（FEA & CFD）和化学， 生物复杂性（ABM）在一定程度上现有的方法不能。从一门基础科学 通过整合大量的细胞级行为，人们可以更好地理解 导致斑块进展的根本原因。此外，它还将揭示值得关注的领域， 进一步的研究或揭示否则被忽视的紧急性质。最终，一个更好的 斑块演变的多尺度模型对于个体化决策（例如， 治疗或不治疗病变）和介入治疗设计变更的基础 方法（例如，假设动脉将如何对候选药物、支架 设计或移植）。