Multi-Physics Modeling and Meshless Methods for Atherosclerotic Plaque Progression

动脉粥样硬化斑块进展的多物理场建模和无网格方法

基本信息

  • 批准号:
    0540684
  • 负责人:
  • 金额:
    $ 184.75万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2006
  • 资助国家:
    美国
  • 起止时间:
    2006-03-15 至 2012-02-29
  • 项目状态:
    已结题

项目摘要

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.
心血管疾病(CVD)是发达国家的主要死亡原因,预计到2020年将成为全球范围内的主要死亡原因。仅在美国,36%的45岁和80%的75岁及以上的人患有心血管疾病(美国心脏协会统计,2005年)。动脉粥样硬化斑块可能在没有预警的情况下破裂,并导致心脏病发作和中风等急性心血管综合征。许多看似健康的这种疾病的受害者突然死亡,没有先前的症状。迫切需要非侵入性的筛查和诊断方法,以及早确定受害者的身份,避免发生这些悲惨事件。该项目的目标是将计算建模、磁共振成像(MRI)和病理分析相结合,以模拟斑块的进展并量化可能发生斑块破裂的临界血流量和斑块应力/应变条件。MRI和病理分析将用于量化人类颈动脉斑块的形态和进展,并评估斑块的脆弱性。将首次获得多年的MRI患者跟踪数据,以量化人类动脉粥样硬化斑块的进展。基于无网格局部Petrov-Galerkin(MLPG)方法的基于MRI的具有多组分斑块结构和流体-结构相互作用(FSI)的三维计算模型的建立和求解,将获得临界流动和斑块应力/应变条件,识别合适的斑块破裂风险指标以更准确地评估斑块,并模拟斑块进展以早期预测和诊断相关心血管疾病。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,特别是在具有现实潜在临床应用的心血管研究领域做出重要贡献。结合计算流体力学、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,可以创建一个逼真的斑块进展和破裂的综合模型。这些模型和方法将适用于生物和材料科学中涉及多物理、生长和运动几何的问题。这种综合计算模型可以适用于其他成本较低的非侵入性方式,如超声波,以促进更广泛的使用。这一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。将开发多学科课程,并向研究生和本科生提供课程。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)参与。这些面向多学科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。研究进展将发布在网站上,并经常更新,在专业会议上展示,并在专业期刊上发表。该项目的成功将导致对斑块进展和破裂的更好和定量的了解,并在计算模型在实际生物应用中的准确性、可靠性和适用性方面有相当大的改进。颈动脉粥样硬化所有阶段诊断的改进将扩大早期治疗的选择,减少脑血管事件和医疗费用,并提高生活质量。

项目成果

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Dalin Tang其他文献

Using Intravascular Ultrasound Image-Based Fluid-Structure Interaction Models and Machine Learning Method to Predict Coronary Plaque Vulnerability Change
使用基于血管内超声图像的流固耦合模型和机器学习方法来预测冠状动脉斑块脆弱性变化
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    1.6
  • 作者:
    Liang Wang;Dalin Tang;Akiko Maehara;Zheyang Wu;Chun Yang;David Muccigrosso;Mitsuaki Matsumura;Jie Zheng;Richard Bach;Kristen L. Billiar;Gregg W. Stone;Gary S. Mintz
  • 通讯作者:
    Gary S. Mintz
Using 3D Echo-Based Modeling to Quantify In Vivo Ventricle Material Properties: A Multi-Patient Study
  • DOI:
  • 发表时间:
    2015
  • 期刊:
  • 影响因子:
  • 作者:
    Jing Yao;Chun Yang;Di Xu;Dalin Tang;
  • 通讯作者:
Génération automatique de modèle vasculaire sur la base d'interactions fluide-structure (fsi)
流体结构相互作用基础血管模型自动生成 (FSI)
  • DOI:
  • 发表时间:
    2010
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Dalin Tang;Zhongzhao Teng
  • 通讯作者:
    Zhongzhao Teng
Editorial: Computational Biomechanics of the Heart and Vasculature With Potential Clinical and Surgical Applications
  • DOI:
    10.3389/fphys.2022.872774
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    4
  • 作者:
    Zhiyong Li;Youjun Liu;Estefania Peña;Daniela Valdez-Jasso;Dalin Tang
  • 通讯作者:
    Dalin Tang
Multi‑factor decision‑making strategy for better coronary plaque burden increase prediction: a patient‑specifc 3D FSI study using IVUS follow‑up data
更好地预测冠状动脉斑块负荷增加的多因素决策策略:使用 IVUS 随访数据的患者特异性 3D FSI 研究
  • DOI:
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    3.5
  • 作者:
    Liang Wang;Dalin Tang;Akiko Maehara;David Molony;Jie Zheng;Habib Samady;Zheyang Wu;Wenbin Lu;Jian Zhu;Genshan Ma;Don P. Giddens;Gregg W. Stone;Gary S. Mintz
  • 通讯作者:
    Gary S. Mintz

Dalin Tang的其他文献

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{{ truncateString('Dalin Tang', 18)}}的其他基金

Experiment-Based 3-D Computational Studies of Blood Flow in Stenotic Carotid Arteries with Dynamic Wall Properties
基于实验的具有动态壁特性的狭窄颈动脉血流的 3D 计算研究
  • 批准号:
    0072873
  • 财政年份:
    2001
  • 资助金额:
    $ 184.75万
  • 项目类别:
    Standard Grant
Mathematical Sciences: Mathematical and Experimental Studies of Blood Flow in Collapsible Carotid Arteries with Stenoses
数学科学:狭窄颈动脉塌陷血流的数学和实验研究
  • 批准号:
    9505685
  • 财政年份:
    1996
  • 资助金额:
    $ 184.75万
  • 项目类别:
    Continuing Grant
Mathematical Sciences: Mathematical and Experimental Studiesof Pulsatile Flow in Free Moving Elastic Tubes
数学科学:自由运动弹性管中脉动流的数学和实验研究
  • 批准号:
    9209129
  • 财政年份:
    1992
  • 资助金额:
    $ 184.75万
  • 项目类别:
    Standard Grant

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