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Improving Tissue Engineered Vascular Graft Performance via Computational Modeling

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
批准号:
10461485
负责人:
Jay D. Humphrey
金额:
$73.13万
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
未结题
起止时间:
2018-01-01 至 2026-03-31

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中文摘要
翻译
项目总结 组织工程血管移植物(TEVGs)已显示出变革心血管治疗的潜力, 多个移植物目前正在儿童和成人身上进行临床试验。然而,仍然迫切需要优化 这些移植物可以改善结果,并实现广泛的使用。在这项提议中,我们建立在一个强大的 但引入了一种创新的多保真计算-实验方法, 承诺将极大地加速改进的TEVG的发展。虽然提议的方法是泛泛的 随着广泛的适用性,我们将专注于一个特定的应用-先天性心脏手术的TEVGs-以 改进方法并说明其实用性。具体地说,我们将使用临床前的幼羊模型来收集 开发和形成将被融合的新的多尺度计算模型所需的纵向数据 描述从植入的可生物降解的聚合物支架中体内发育的新生细胞。我们的 方法将由来自三个初始、非最优设计的数据来告知,然后通过正式方法用于识别 优选的微结构支架参数的优化和体内优化的整体几何形状 功能。特别新奇的是我们解释羔羊正常发育变化的能力。 在一种新的多保真度中,细胞信号、生长和重塑以及3D血流动力学的血管系统和耦合, 多尺度工作流程,允许优化所需的生物和生理结果。要实现这些目标 目标,我们提出三个具体目标:1)量化正常血管的发育和三个方面的表现 在Lamb模型中的基线TEVG设计;2)开发和使用一种新的多尺度流固生长(FSG) 优化TEVG设计的仿真框架;3)验证模型识别的最优TEVG设计 纵向大型动物研究。我们的团队是独一无二的,结合了动物方面的专业知识,能够取得成功 先天性心脏病模型,TEVGs的发展及其临床翻译,有限元 心血管血流动力学和生物力学的模拟,模拟血管生长和重塑,以及 机械生物学机制的识别和建模。我们的方法是创新的,因为我们将融合 心血管生物力学的宏观(器官)模拟和血管细胞的微观模拟 2)为组织工程的模型驱动优化开发了一种新的、普遍适用的范例 提供对结果的控制的结构,以及3)通过改进的 性能。这项研究的成功完成将在多个方面具有重要意义-它不仅将导致 Fontan手术中使用TEVG的新(最佳)设计,适用于出生时患有单纯性心脏病的儿童 它还将建立一种新的计算-实验范式 心血管组织工程,有望加速各种植入物的发展。
英文摘要
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.
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Computational model-driven design to mitigate vein graft failure after coronary artery bypass
  • 批准号:
    10683327
  • 项目类别:
  • 资助金额:
    $70.08万
  • 财政年份:
    2022
  • 负责人:
    Jay D. Humphrey
  • 依托单位:
Computational model-driven design to mitigate vein graft failure after coronary artery bypass
  • 批准号:
    10539814
  • 项目类别:
  • 资助金额:
    $75.24万
  • 财政年份:
    2022
  • 负责人:
    Jay D. Humphrey
  • 依托单位:
Modeling Multiscale Immuno-Mechanics in Aortic Disease
  • 批准号:
    10532786
  • 项目类别:
  • 资助金额:
    $49.18万
  • 财政年份:
    2022
  • 负责人:
    Jay D. Humphrey
  • 依托单位:
Modeling Multiscale Immuno-Mechanics in Aortic Disease
  • 批准号:
    10352581
  • 项目类别:
  • 资助金额:
    $50.02万
  • 财政年份:
    2022
  • 负责人:
    Jay D. Humphrey
  • 依托单位:
海外基金