Computational physiological models are promising tools to enhance the design of clinical trials and to assist in decision making. Organ-scale haemodynamic models are gaining popularity to evaluate perfusion in a virtual environment both in healthy and diseased patients. Recently, the principles of verification, validation, and uncertainty quantification of such physiological models have been laid down to ensure safe applications of engineering software in the medical device industry. The present study sets out to establish guidelines for the usage of a three-dimensional steady state porous cerebral perfusion model of the human brain following principles detailed in the verification and validation (V&V 40) standard of the American Society of Mechanical Engineers. The model relies on the finite element method and has been developed specifically to estimate how brain perfusion is altered in ischaemic stroke patients before, during, and after treatments. Simulations are compared with exact analytical solutions and a thorough sensitivity analysis is presented covering every numerical and physiological model parameter. The results suggest that such porous models can approximate blood pressure and perfusion distributions reliably even on a coarse grid with first order elements. On the other hand, higher order elements are essential to mitigate errors in volumetric blood flow rate estimation through cortical surface regions. Matching the volumetric flow rate corresponding to major cerebral arteries is identified as a validation milestone. It is found that inlet velocity boundary conditions are hard to obtain and that constant pressure inlet boundary conditions are feasible alternatives. A one-dimensional model is presented which can serve as a computationally inexpensive replacement of the three-dimensional brain model to ease parameter optimisation, sensitivity analyses and uncertainty quantification. The findings of the present study can be generalised to organ-scale porous perfusion models. The results increase the applicability of computational tools regarding treatment development for stroke and other cerebrovascular conditions.

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用于脑灌注估计的多孔有限元模型敏感性分析

计算生理模型是增强临床试验设计和辅助决策的有前途的工具。器官规模的血液动力学模型越来越受欢迎，用于评估健康和患病患者在虚拟环境中的灌注。最近，已经制定了此类生理模型的验证、验证和不确定性量化的原则，以确保工程软件在医疗器械行业的安全应用。本研究旨在根据美国机械工程师协会的验证和验证 (V&V 40) 标准中详述的原则，制定人脑三维稳态多孔脑灌注模型的使用指南。该模型依赖于有限元方法，专门用于估计缺血性中风患者在治疗前、治疗中和治疗后的脑灌注如何改变。将模拟与精确解析解进行比较，并提供涵盖每个数值和生理模型参数的全面灵敏度分析。结果表明，即使在具有一阶元素的粗网格上，这种多孔模型也可以可靠地近似血压和灌注分布。另一方面，高阶元素对于通过皮质表面区域减少体积血流量估计中的错误至关重要。匹配对应于主要脑动脉的体积流量被确定为验证里程碑。发现入口速度边界条件很难获得，而恒压入口边界条件是可行的替代方案。提出了一个一维模型，它可以作为三维大脑模型的计算成本低廉的替代品，以简化参数优化、灵敏度分析和不确定性量化。本研究的结果可以推广到器官规模的多孔灌注模型。结果增加了计算工具在中风和其他脑血管疾病治疗开发方面的适用性。敏感性分析和不确定性量化。本研究的结果可以推广到器官规模的多孔灌注模型。结果增加了计算工具在中风和其他脑血管疾病治疗开发方面的适用性。敏感性分析和不确定性量化。本研究的结果可以推广到器官规模的多孔灌注模型。结果增加了计算工具在中风和其他脑血管疾病治疗开发方面的适用性。