Central to the clinical adoption of patient-specific modeling strategies is demonstrating that simulation results are reliable and safe. Indeed, simulation frameworks must be robust to uncertainty in model input(s), and levels of confidence should accompany results. In this study, we applied a coupled uncertainty quantification–finite element (FE) framework to understand the impact of uncertainty in vascular material properties on variability in predicted stresses. Univariate probability distributions were fit to material parameters derived from layer-specific mechanical behavior testing of human coronary tissue. Parameters were assumed to be probabilistically independent, allowing for efficient parameter ensemble sampling. In an idealized coronary artery geometry, a forward FE model for each parameter ensemble was created to predict tissue stresses under physiologic loading. An emulator was constructed within the UncertainSCI software using polynomial chaos techniques, and statistics and sensitivities were directly computed. Results demonstrated that material parameter uncertainty propagates to variability in predicted stresses across the vessel wall, with the largest dispersions in stress within the adventitial layer. Variability in stress was most sensitive to uncertainties in the anisotropic component of the strain energy function. Moreover, unary and binary interactions within the adventitial layer were the main contributors to stress variance, and the leading factor in stress variability was uncertainty in the stress-like material parameter that describes the contribution of the embedded fibers to the overall artery stiffness. Results from a patient-specific coronary model confirmed many of these findings. Collectively, these data highlight the impact of material property variation on uncertainty in predicted artery stresses and present a pipeline to explore and characterize forward model uncertainty in computational biomechanics.

临床采用患者特定建模策略的核心是证明模拟结果可靠且安全。事实上，模拟框架必须对模型输入的不确定性具有鲁棒性，并且置信水平应该伴随结果。在这项研究中，我们应用耦合不确定性量化-有限元（FE）框架来了解血管材料特性的不确定性对预测应力变异性的影响。单变量概率分布适合从人体冠状组织的层特定机械行为测试得出的材料参数。假设参数在概率上是独立的，从而允许有效的参数集合采样。在理想化的冠状动脉几何形状中，为每个参数集合创建了正向有限元模型，以预测生理负荷下的组织应力。使用多项式混沌技术在 UncertainSCI 软件中构建模拟器，并直接计算统计数据和灵敏度。结果表明，材料参数的不确定性会传播到血管壁上预测应力的变化，其中外膜层内的应力分散最大。应力的变化对应变能函数各向异性分量的不确定性最敏感。此外，外膜层内的一元和二元相互作用是造成应力变化的主要因素，而应力变化的主要因素是类应力材料参数的不确定性，该参数描述了嵌入纤维对整体动脉硬度的贡献。患者特异性冠状动脉模型的结果证实了其中许多发现。总的来说，这些数据突出了材料特性变化对预测动脉应力不确定性的影响，并提供了探索和表征计算生物力学中正向模型不确定性的管道。