Stenosis is the primary complication of current tissue-engineered vascular grafts used in pediatric congenital cardiac surgery. Murine models provide considerable insight into the possible mechanisms underlying this situation, but they are not efficient for identifying optimal changes in scaffold design or therapeutic strategies to prevent narrowing. In contrast, computational modeling promises to enable time- and cost-efficient examinations of factors leading to narrowing. Whereas past models have been limited by their phenomenological basis, we present a new mechanistic model that integrates molecular- and cellular-driven immuno- and mechano-mediated contributions to in vivo neotissue development within implanted polymeric scaffolds. Model parameters are inferred directly from in vivo measurements for an inferior vena cava interposition graft model in the mouse that are augmented by data from the literature. By complementing Bayesian estimation with identifiability analysis and simplex optimization, we found optimal parameter values that match model outputs with experimental targets and quantify variability due to measurement uncertainty. Utility is illustrated by parametrically exploring possible graft narrowing as a function of scaffold pore size, macrophage activity, and the immunomodulatory cytokine transforming growth factor beta 1 (TGF-β1). The model captures salient temporal profiles of infiltrating immune and synthetic cells and associated secretion of cytokines, proteases, and matrix constituents throughout neovessel evolution, and parametric studies suggest that modulating scaffold immunogenicity with early immunomodulatory therapies may reduce graft narrowing without compromising compliance.

中文翻译：

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体内组织工程化血管移植物发育的计算生物化学-力学模型。

狭窄是目前用于儿科先天性心脏手术的组织工程化血管移植的主要并发症。鼠模型可以深入了解这种情况的潜在机制，但是对于识别支架设计或治疗策略以防止变窄的最佳变化，它们并不有效。相反，计算建模有望实现对导致缩小范围的因素进行时间和成本高效的检查。尽管过去的模型受到其现象学基础的限制，但我们提出了一种新的力学模型，该模型整合了分子和细胞驱动的免疫和力学介导的对植入的聚合物支架内体内新组织发展的贡献。模型参数直接从小鼠下腔静脉插入移植模型的体内测量中推导，并通过文献数据进行补充。通过用可识别性分析和单纯形优化对贝叶斯估计进行补充，我们发现了最佳参数值，该参数值使模型输出与实验目标相匹配并量化了由于测量不确定性导致的可变性。通过参数研究可能的移植物变窄作为支架孔径，巨噬细胞活性和免疫调节细胞因子转化生长因子β1（TGF-β1）的函数，可以说明其实用性。该模型捕获了整个新血管演化过程中浸润的免疫细胞和合成细胞以及细胞因子，蛋白酶和基质成分的相关分泌的显着时间分布，