AbstractQuantification of the uncertainty in constitutive model predictions describing arterial wall m'/> Uncertainty quantification and sensitivity analysis of an arterial wall mechanics model for evaluation of vascular drug therapies
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Uncertainty quantification and sensitivity analysis of an arterial wall mechanics model for evaluation of vascular drug therapies

机译:血管药物疗法评估动脉壁力学模型的不确定性量化及敏感性分析

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AbstractQuantification of the uncertainty in constitutive model predictions describing arterial wall mechanics is vital towards non-invasive assessment of vascular drug therapies. Therefore, we perform uncertainty quantification to determine uncertainty in mechanical characteristics describing the vessel wall response upon loading. Furthermore, a global variance-based sensitivity analysis is performed to pinpoint measurements that are most rewarding to be measured more precisely. We used previously published carotid diameter–pressure and intima–media thickness (IMT) data (measured in triplicate), and Holzapfel–Gasser–Ogden models. A virtual data set containing 5000 diastolic and systolic diameter–pressure points, and IMT values was generated by adding measurement error to the average of the measured data. The model was fitted to single-exponential curves calculated from the data, obtaining distributions of constitutive parameters and constituent load bearing parameters. Additionally, we (1) simulated vascular drug treatment to assess the relevance of model uncertainty and (2) evaluated how increasing the number of measurement repetitions influences model uncertainty. We found substantial uncertainty in constitutive parameters. Simulating vascular drug treatment predicted a 6% point reduction in collagen load bearing ($$L_mathrm {coll}$$Lcoll), approximately 50% of its uncertainty. Sensitivity analysis indicated that the uncertainty in
机译:<![cdata [ <标题>抽象 ara id =“par1”>在构成模型预测中的不确定性的量化描述动脉墙力学对于对血管药物治疗的非侵入性评估至关重要。因此,我们执行不确定性定量以确定在装载时描述血管壁响应的机械特性的不确定性。此外,执行基于差异的基于方差的敏感性分析,以确定最有价值的测量值更好地测量。我们使用先前发表的颈动脉直径压力和内膜介质厚度(IMT)数据(以三份测量),以及Holzapfel-Gasser-Ogden型号。通过向测量数据的平均值添加测量误差来产生包含5000个舒张和收缩直径压力点和IMT值的虚拟数据集。该模型安装在由数据计算的单指数曲线上,获得本构载体参数和组成负载承载参数的分布。此外,我们(1)模拟血管药物治疗,以评估模型不确定性的相关性和(2)评估了测量重复的数量如何影响模型不确定性。我们在本构参数中发现了很大的不确定性。模拟血管药物治疗预测胶原橡胶轴承的6%减少( $$ l_ mathrm {coll} $$ < mateLutegariant =“普通”> coll < / InlineEquation>),约50%的不确定性。敏感性分析表明 <内联的不确定性

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