Improving Tissue Engineered Vascular Graft Performance via Computational Modeling

通过计算建模提高组织工程血管移植物的性能

基本信息

项目摘要

PROJECT SUMMARY Tissue engineered vascular grafts (TEVGs) have demonstrated potential to revolutionize cardiovascular care, with multiple grafts now in clinical trials in children and adults. Yet, there remains a pressing need to optimize these grafts to improve outcomes and enable wide-spread usage. In this proposal, we build upon a strong foundation of prior findings but introduce an innovative multi-fidelity computational-experimental approach that promises to accelerate greatly the development of improved TEVGs. Although the proposed approach is general with broad applicability, we will focus on one particular application – TEVGs for congenital heart surgery – to refine the approach and illustrate its utility. Specifically, we will use a pre-clinical juvenile ovine model to collect the longitudinal data needed to develop and inform novel multiscale computational models that will be melded to describe the in vivo development of a neovessel from an implanted biodegradable polymeric scaffold. Our approach will be informed by data from three initial, non-optimal designs, then used to identify via formal methods of optimization preferred microstructural scaffold parameters and an overall geometry that optimizes in vivo function. Particularly novel will be our ability to account for normal developmental changes in the lamb vasculature and coupling of cell signaling, growth and remodeling, and 3D hemodynamics in a novel multi-fidelity, multiscale workflow that allows optimization of desired biological and physiological outcomes. To achieve these goals, we propose three Specific Aims: 1) To quantify normal vascular development and performance of three baseline TEVG designs in a lamb model; 2) To develop and employ a novel multiscale fluid-solid-growth (FSG) simulation framework to optimize TEVG design; 3) To validate the model-identified optimal TEVG design in a longitudinal large animal study. Our team is uniquely positioned for success, combining expertise in animal models of congenital heart disease, development of TEVGs and their clinical translation, finite element simulations of cardiovascular hemodynamics and biomechanics, modeling vascular growth and remodeling, and identifying and modeling mechanisms of mechanobiology. Our approach is innovative in that we will 1) meld macro (organ) level simulations of cardiovascular biomechanics with micro level simulations of vascular cell signaling, 2) develop a novel, generally applicable paradigm for model-driven optimization of tissue engineered structures that provides control over outcomes, and 3) facilitate clinical translation of TEVGs with improved performance. Successful completion of this study will be significant in multiple ways – not only will it result in a new (optimal) design of a TEVG for use in the Fontan surgical procedure, performed in children born with single ventricle congenital heart defects, it will also establish a novel computational-experimental paradigm in cardiovascular tissue engineering that promises to accelerate the development of diverse implants.
项目摘要 组织工程血管移植物(TEVG)已被证明有可能彻底改变心血管护理, 现在在儿童和成人的临床试验中有多种移植物。然而,仍然迫切需要优化 这些移植物,以改善结果,并使广泛的使用。在这一建议中,我们建立在一个强大的 的基础上,但引入了一种创新的多保真度计算实验方法, 有望大大加快改进的TEVG的发展。虽然所提出的方法是一般性的, 由于具有广泛的适用性,我们将重点关注一个特殊的应用-先天性心脏手术的TEVG- 改进方法并说明其效用。具体而言,我们将使用临床前幼龄绵羊模型收集 纵向数据需要开发和通知新的多尺度计算模型, 描述了从植入的可生物降解的聚合物支架体内发育新血管。我们 方法将由来自三个初始非最优设计的数据提供信息,然后用于通过正式方法识别 优化优选的微结构支架参数和整体几何形状, 功能特别新颖的是我们能够解释羔羊正常的发育变化 血管系统和细胞信号传导的耦合,生长和重塑,以及3D血液动力学在一个新的多保真度, 多尺度工作流程,允许优化所需的生物和生理结果。实现这些 目标,我们提出了三个具体目标:1)量化正常血管发育和性能的三个 在兰姆模型中的基线TEVG设计; 2)开发和采用新的多尺度流固生长(FSG) 仿真框架,以优化TEVG设计; 3)为了验证模型识别的最佳TEVG设计在一个 纵向大型动物研究。我们的团队拥有独特的成功定位,结合动物领域的专业知识, 先天性心脏病模型,TEVG的发展及其临床应用,有限元 模拟心血管血液动力学和生物力学,模拟血管生长和重塑,以及 机械生物学的识别和建模机制。我们的方法是创新的,因为我们将1)融合 心血管生物力学的宏观(器官)级模拟与血管细胞的微观级模拟 2)开发一种新的,普遍适用的范式,用于模型驱动的组织工程优化 结构,提供对结果的控制,以及3)促进TEVG的临床翻译, 性能成功完成本研究将在多个方面具有重要意义-不仅会导致 用于Fontan外科手术的TEVG的新(最佳)设计,用于出生时患有单胎畸形的儿童 心室先天性心脏病,它也将建立一个新的计算实验范式, 心血管组织工程有望加速各种植入物的发展。

项目成果

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Jay D. Humphrey其他文献

A Computational Framework to Predict and Understand in situ Heart Valve Tissue Engineering
  • DOI:
    10.1080/24748706.2021.1900703
  • 发表时间:
    2021-06-01
  • 期刊:
  • 影响因子:
  • 作者:
    Elmer Middendorp;Marcos Latorre;Jason M. Szafron;Frank P.T. Baaijens;Jay D. Humphrey;Sandra Loerakker
  • 通讯作者:
    Sandra Loerakker
ブレインサイエンス・レビュー2004
脑科学评论 2004
  • DOI:
  • 发表时间:
    2004
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Daisuke Mori;Guido David;Jay D. Humphrey;James E. Moore Jr.;Miho Terunuma;平田 雅人
  • 通讯作者:
    平田 雅人
Multi-Scale Multi-Cell Computational Model of Inflammation-Mediated Aortic Remodeling in Hypertension
  • DOI:
    10.1007/s10439-025-03685-3
  • 发表时间:
    2025-02-04
  • 期刊:
  • 影响因子:
    5.400
  • 作者:
    Ana C. Estrada;Jay D. Humphrey
  • 通讯作者:
    Jay D. Humphrey
Journal of Mechanics of Materials and Structures SPONTANEOUS UNWINDING OF A LABILE DOMAIN IN A COLLAGEN TRIPLE HELIX
材料与结构力学杂志 胶原三螺旋中不稳定域的自发展开
  • DOI:
  • 发表时间:
    2007
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Krishnakumar M. Ravikumar;Jay D. Humphrey;Wonmuk Hwang
  • 通讯作者:
    Wonmuk Hwang
Altered mechanical behavior and properties of the human anterior lens capsule after cataract surgery.
白内障手术后人类晶状体前囊的机械行为和特性发生改变。
  • DOI:
    10.1016/j.exer.2009.06.001
  • 发表时间:
    2009
  • 期刊:
  • 影响因子:
    3.4
  • 作者:
    R. Pedrigi;J. Dziezyc;Jay D. Humphrey
  • 通讯作者:
    Jay D. Humphrey

Jay D. Humphrey的其他文献

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{{ truncateString('Jay D. Humphrey', 18)}}的其他基金

Computational model-driven design to mitigate vein graft failure after coronary artery bypass
计算模型驱动的设计可减轻冠状动脉搭桥术后静脉移植失败的风险
  • 批准号:
    10683327
  • 财政年份:
    2022
  • 资助金额:
    $ 73.13万
  • 项目类别:
Computational model-driven design to mitigate vein graft failure after coronary artery bypass
计算模型驱动设计减轻冠状动脉搭桥术后静脉移植失败
  • 批准号:
    10539814
  • 财政年份:
    2022
  • 资助金额:
    $ 73.13万
  • 项目类别:
Modeling Multiscale Immuno-Mechanics in Aortic Disease
主动脉疾病的多尺度免疫力学建模
  • 批准号:
    10532786
  • 财政年份:
    2022
  • 资助金额:
    $ 73.13万
  • 项目类别:
Modeling Multiscale Immuno-Mechanics in Aortic Disease
主动脉疾病的多尺度免疫力学建模
  • 批准号:
    10352581
  • 财政年份:
    2022
  • 资助金额:
    $ 73.13万
  • 项目类别:
Multiscale Modeling of Aortic Homeostasis
主动脉稳态的多尺度建模
  • 批准号:
    10471254
  • 财政年份:
    2021
  • 资助金额:
    $ 73.13万
  • 项目类别:
Multiscale Modeling of Aortic Homeostasis
主动脉稳态的多尺度建模
  • 批准号:
    10189114
  • 财政年份:
    2021
  • 资助金额:
    $ 73.13万
  • 项目类别:
Smooth Muscle Cell Proliferation and Degradative Phenotype in Thoracic Aorta Aneurysm and Dissection
胸主动脉瘤和夹层中的平滑肌细胞增殖和降解表型
  • 批准号:
    10184861
  • 财政年份:
    2020
  • 资助金额:
    $ 73.13万
  • 项目类别:
Smooth Muscle Cell Proliferation and Degradative Phenotype in Thoracic Aorta Aneurysm and Dissection
胸主动脉瘤和夹层中的平滑肌细胞增殖和降解表型
  • 批准号:
    10376852
  • 财政年份:
    2019
  • 资助金额:
    $ 73.13万
  • 项目类别:
Smooth Muscle Cell Proliferation and Degradative Phenotype in Thoracic Aorta Aneurysm and Dissection
胸主动脉瘤和夹层中的平滑肌细胞增殖和降解表型
  • 批准号:
    10573756
  • 财政年份:
    2019
  • 资助金额:
    $ 73.13万
  • 项目类别:
Smooth Muscle Cell Proliferation and Degradative Phenotype in Thoracic Aorta Aneurysm and Dissection
胸主动脉瘤和夹层中的平滑肌细胞增殖和降解表型
  • 批准号:
    10132382
  • 财政年份:
    2019
  • 资助金额:
    $ 73.13万
  • 项目类别:

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