A Computational Framework to Optimize the Mechanical Behavior of Synthetic Vascular Grafts

David Jiang, Andrew J Robinson, Abbey Nkansah, Jonathan Leung, Leopold Guo, Steve A Maas, Jeffrey A Weiss, Elizabeth M Cosgriff-Hernandez, Lucas H Timmins
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Abstract

The failure of synthetic small-diameter vascular grafts has been attributed to a mismatch in the compliance between the graft and native artery, driving mechanisms that promote thrombosis and neointimal hyperplasia. Additionally, the buckling of grafts results in large deformations that can lead to device failure. Although design features can be added to lessen the buckling potential, the addition is detrimental to decreasing compliance (e.g., reinforcing coil). Herein, we developed a novel finite element framework to inform vascular graft design by evaluating compliance and resistance to buckling. A batch-processing scheme iterated across the multi-dimensional design parameter space, which included three parameters: coil thickness, modulus, and spacing. Three types of finite element models were created in FEBio for each unique coil-reinforced graft parameter combination to simulate pressurization, axial buckling, and bent buckling, and results were analyzed to quantify compliance, buckling load, and kink radius, respectively, from each model. Importantly, model validation demonstrated that model predictions agree qualitatively and quantitatively with experimental observations. Subsequently, data for each design parameter combination were integrated into an optimization function for which a minimum value was sought. The optimization values identified various candidate graft designs with promising mechanical properties. Our investigation successfully demonstrated the model-directed framework identified vascular graft designs with optimal mechanical properties, which can potentially improve clinical outcomes by addressing device failure. In addition, the presented computational framework promotes model-directed device design for a broad range of biomaterial and regenerative medicine strategies.
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优化合成血管移植物机械行为的计算框架
合成小直径血管移植物失效的原因是移植物与原生动脉之间的顺应性不匹配,导致血栓形成和新内膜增生。此外,移植物的弯曲会导致较大的变形,从而导致装置失效。虽然可以通过增加设计功能来减少屈曲的可能性,但增加设计功能不利于降低顺应性(如加固线圈)。在此,我们开发了一种新型有限元框架,通过评估顺应性和抗屈曲性为血管移植物的设计提供信息。批量处理方案在多维设计参数空间内进行迭代,其中包括三个参数:线圈厚度、模量和间距。在 FEBio 中为每种独特的线圈增强移植物参数组合创建了三种有限元模型,以模拟加压、轴向屈曲和弯曲屈曲,并对结果进行了分析,以量化每个模型的顺应性、屈曲载荷和扭结半径。重要的是,模型验证表明,模型预测结果在定性和定量方面都与实验观测结果一致。随后,每个设计参数组合的数据都被整合到一个优化函数中,以寻求最小值。优化值确定了具有良好机械性能的各种候选接枝设计。我们的研究成功证明,模型导向框架确定了具有最佳机械性能的血管移植物设计,通过解决装置故障问题,有可能改善临床疗效。此外,所提出的计算框架还促进了以模型为导向的设备设计,适用于广泛的生物材料和再生医学策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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