Multi-Physics Modeling and Meshless Methods for Atherosclerotic Plaque Progression

心血管疾病（CVD）是发达国家的主要死因，预计到2020年将成为全球主要死因。仅在美国，36%的45奥尔兹和80%的75岁及以上人群患有CVD（美国心脏协会统计数据，2005年）。 动脉粥样硬化斑块可能在没有警告的情况下破裂，并引起急性心血管综合征，如心脏病发作和中风。 许多表面上健康的患者在没有任何症状的情况下突然死亡。迫切需要非侵入性筛查和诊断方法，以及早识别受害者并避免这些悲惨事件。 本项目的目标是将联合收割机计算建模、磁共振成像（MRI）和病理分析相结合，以模拟斑块进展并量化可能发生斑块破裂的临界血流和斑块应力/应变条件。 MRI和病理学分析将用于量化人颈动脉斑块形态和进展，并评估斑块易损性。 将首次获得多年MRI患者跟踪数据，以量化人类动脉粥样硬化斑块进展。 将开发具有多组分斑块结构和流体-结构相互作用（FSI）的基于MRI的三维（3D）计算模型，并通过基于无网格局部Petrov-Galerkin（MLPG）方法的数值方法进行求解，以获得临界流量和斑块应力/应变条件，识别合适的斑块破裂风险指标，以进行更准确的斑块评估，该计算模型、MLPG方法以及对斑块进展和破裂的更好理解将对计算数学、生物科学、生物工程、特别是在具有现实的潜在临床应用的心血管研究领域。 计算流体动力学、固体力学、MRI多光谱斑块分析和患者跟踪、体外斑块建模和组织病理学分析的组合可以创建用于斑块进展和破裂的真实综合模型。 该模型和方法将适用于生物和材料科学中涉及多物理，生长和移动几何的问题。 这种综合计算模型可以适用于其他成本较低的非侵入性模式，如超声，以促进更广泛的使用。这个合作项目将建立一个研究教学基础设施，促进所有相关领域的多学科研究教学活动。将为研究生和本科生开发和提供多学科课程。将大力鼓励代表性不足的群体（非裔美国人、妇女、残疾人和其他少数群体）参加。多学科导向的毕业生将拥有应用和计算数学，生物工程和一般生物应用方面的技能和知识。研究进展将在网络上发布，并经常更新，在专业会议上发表，并在专业期刊上发表。 该项目的成功将导致更好的和定量的了解斑块的进展和破裂和相当大的改善的准确性，可靠性和适用性的计算建模在真实的生活中的生物应用。 改善颈动脉粥样硬化所有阶段的诊断将扩大早期治疗的选择，减少脑血管事件和医疗费用，并改善生活质量。

Cardiovascular disease (CVD) is the leading cause of death in the developed world and is expected to become the leading cause of death worldwide by 2020. In the US alone, 36% of 45 year olds and 80% of those 75 and older have CVD (American Heart Association Statistics 2005). Atherosclerotic plaques may rupture without warning and cause acute cardiovascular syndromes such as heart attack and stroke. Many victims of the disease who are apparently healthy die suddenly without prior symptoms. Non-invasive screening and diagnostic methods are urgently needed to identify the victims early and avoid those tragic events. The objective of this project is to combine computational modeling, magnetic resonance imaging (MRI) and pathological analysis to simulate plaque progression and quantify critical blood flow and plaque stress/strain conditions under which plaque rupture is likely to occur. MRI and pathological analysis will be used to quantify human carotid plaque morphology and progression and to assess plaque vulnerability. For the first time, multi-year MRI patient-tracking data will be obtained to quantify human atherosclerotic plaque progression. MRI-based three-dimensional (3D) computational models with multi-component plaque structure and fluid-structure interactions (FSI) will be developed and solved by numerical methods based on the meshless local Petrov-Galerkin (MLPG) method to obtain critical flow and plaque stress/strain conditions, to identify suitable plaque rupture risk indicators for more accurate plaque assessment, and to simulate plaque progression for early prediction and diagnosis of related cardiovascular diseases.The computational model, MLPG method, and a better understanding of plaque progression and rupture will be considerable contributions to computational mathematics, biological sciences, bioengineering, especially in the cardiovascular research area with realistic potential clinical applications. The combination of computational fluid dynamics, solid mechanics, MRI multi-spectral plaque analysis and patient tracking, in vitro plaque modeling, and histopathological analysis can create a realistic integrative model for plaque progression and rupture. The models and methods will be applicable to problems in biological and material sciences involving multi-physics, growth, and moving geometries. This integrative computational model can be adapted to other less costly non-invasive modalities such as ultrasound to facilitate a wider use. This collaborative project will establish a research-teaching infrastructure that facilitates multi-disciplinary research-teaching activities for all related areas. Multi-disciplinary courses will be developed and offered to graduate and undergraduate students. Participation of underrepresented groups (African Americans, women, people with disabilities, and other minority groups) will be strongly encouraged. The multi-disciplinary oriented graduates will have skills and knowledge in applied and computational mathematics, bioengineering, and general biological applications. Research progress will be posted on the web with frequent updates, presented at professional meetings, and published in professional journals. Success of this project will lead to a better and quantitative understanding of plaque progression and rupture and considerable improvement in accuracy, reliability and applicability of computational modeling in real life biological applications. Improved diagnosis of all stages of carotid atherosclerosis will expand options for early treatment and result in a reduction of cerebrovascular events and healthcare costs, and improve quality of life.