Department of Biomedical Engineering, Yale University, New Haven, CT, USA.
Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, USA.
Integr Biol (Camb). 2020 Apr 14;12(3):47-63. doi: 10.1093/intbio/zyaa004.
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.
狭窄是目前用于儿科先天性心脏病手术的组织工程血管移植物的主要并发症。鼠模型为理解这种情况的潜在机制提供了重要的见解，但它们在确定支架设计或治疗策略的最佳变化以防止狭窄方面效率不高。相比之下，计算建模有望实现对导致狭窄的因素进行高效、省时的检查。虽然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机制模型，该模型将分子和细胞驱动的免疫和机械介导作用整合到植入的聚合物支架内的体内新组织发育中。模型参数是直接从体内测量值推断出来的，这些测量值是通过补充来自文献的数据对小鼠下腔静脉间置移植物模型进行的。通过将贝叶斯估计与可识别性分析和单纯形优化相结合，我们找到了与实验目标匹配的最佳参数值，并量化了由于测量不确定性引起的变异性。通过参数化探索支架孔径、巨噬细胞活性和免疫调节细胞因子转化生长因子-β1 (TGF-β1) 对移植物狭窄的影响，说明了模型的实用性。该模型捕获了在整个新血管进化过程中浸润性免疫和合成细胞及其相关细胞因子、蛋白酶和基质成分分泌的重要时间分布，参数研究表明，早期免疫调节治疗可以调节支架的免疫原性，从而减少移植物狭窄，而不会影响顺应性。
