Ninos G, Bartzis V, Merlemis N, Sarris I E
Department of Biomedical Sciences, University of West Attica, 12243, Athens, Greece; Department of Mechanical Engineering, University of West Attica, 12244, Athens, Greece.
Department of Food Science & Technology, University of West Attica, 12243, Athens, Greece.
Comput Methods Programs Biomed. 2021 May;203:106021. doi: 10.1016/j.cmpb.2021.106021. Epub 2021 Mar 2.
Human hemodynamic modeling is usually influenced by uncertainties occurring from a considerable unavailability of information linked to the boundary conditions and the physical properties used in the numerical models. Calculating the effect of these uncertainties on the numerical findings along the cardiovascular system is a demanding process due to the complexity of the morphology of the body and the area dynamics. To cope with all these difficulties, Uncertainty Quantification (UQ) methods seem to be an ideal tool.
This study focuses on analyzing and summarizing some of the recent research efforts and directions of implementing UQ in human hemodynamic flows by analyzing 139 research papers. Initially, the suitability of applying this approach is analyzed and demonstrated. Then, an overview of the most significant research work in various fields of biomedical hemodynamic engineering is presented. Finally, it is attempted to identify any possible forthcoming directions for research and methodological progress of UQ in biomedical sciences.
This review concludes that by finding the best statistical methods and parameters to represent the propagated uncertainties, while achieving a good interpretation of the interaction between input-output, is crucial for implementing UQ in biomedical sciences.
人体血液动力学建模通常受到诸多不确定性因素的影响，这些不确定性源于数值模型中与边界条件及物理特性相关的大量信息缺失。由于人体形态的复杂性和区域动力学特性，计算这些不确定性因素对心血管系统数值结果的影响是一个艰巨的过程。为应对所有这些困难，不确定性量化（UQ）方法似乎是一种理想工具。
本研究通过分析139篇研究论文，着重分析和总结了近期在人体血液动力学流动中实施不确定性量化的一些研究成果和方向。首先，分析并论证了应用该方法的适用性。然后，概述了生物医学血液动力学工程各个领域中最重要的研究工作。最后，尝试确定不确定性量化在生物医学科学领域研究和方法进展方面可能出现的任何未来方向。
本综述得出结论，在生物医学科学中实施不确定性量化时，找到最佳统计方法和参数来表示传播的不确定性，同时对输入 - 输出之间的相互作用进行良好解释至关重要。
