Variability of Computational Fluid Dynamics Solutions for Pressure and Flow in a Giant Aneurysm: The ASME 2012 Summer Bioengineering Conference CFD Challenge
Variability of Computational Fluid Dynamics Solutions for Pressure and Flow in a Giant Aneurysm: The ASME 2012 Summer Bioengineering Conference CFD Challenge
复制标题
巨型动脉瘤中压力和流量的计算流体动力学解决方案的可变性：ASME 2012 夏季生物工程会议 CFD 挑战赛
DOI：
10.1115/1.4023382
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发表时间：
2013-02-01
影响因子：
1.7
通讯作者：
Loth, Francis
中科院分区：
文献类型：
--
作者：
Steinman, David A.;Hoi, Yiemeng;Loth, Francis
受最近关于近端狭窄的巨大动脉瘤中预测的压降的争议的刺激，本研究试图评估各个研究小组对压力和流量的预测的可变性。在第一阶段，指定了管腔几何形状、流速和流体特性，让每个研究小组选择他们的求解器、离散化和求解策略。通过让每组将其结果插值到标准化网格和中心线上来评估变异性。对于第二阶段，构建了几何形状的物理模型，并根据该模型测量压力和流量。各小组使用通过物理模型的微计算机断层扫描 (CT) 扫描重建的几何结构以及测量的流速和流体特性来重复他们的模拟。 25 组的 I 期结果显示压力模式具有显着的一致性，大多数预测收缩压峰值下降幅度在 8% 以内。动脉瘤囊血流模式变化较大，只有少数组报告由于使用高时间分辨率而出现收缩期血流峰值不稳定。第二阶段的变异性相当，预测压降中值与测量值相差几毫米汞柱，但前提是考虑了通过微型 CT 重建真人大小的流动模型时的亚毫米误差。总之，可以通过 CFD 在各种求解器和求解策略中一致地预测压力，但这对于特定的流动模式或派生量可能并不成立。未来的挑战是需要的，并且应该集中于被认为具有临床意义的血流动力学量。
Stimulated by a recent controversy regarding pressure drops predicted in a giant aneurysm with a proximal stenosis, the present study sought to assess variability in the prediction of pressures and flow by a wide variety of research groups. In phase I, lumen geometry, flow rates, and fluid properties were specified, leaving each research group to choose their solver, discretization, and solution strategies. Variability was assessed by having each group interpolate their results onto a standardized mesh and centerline. For phase II, a physical model of the geometry was constructed, from which pressure and flow rates were measured. Groups repeated their simulations using a geometry reconstructed from a micro-computed tomography (CT) scan of the physical model with the measured flow rates and fluid properties. Phase I results from 25 groups demonstrated remarkable consistency in the pressure patterns, with the majority predicting peak systolic pressure drops within 8% of each other. Aneurysm sac flow patterns were more variable with only a few groups reporting peak systolic flow instabilities owing to their use of high temporal resolutions. Variability for phase II was comparable, and the median predicted pressure drops were within a few millimeters of mercury of the measured values but only after accounting for submillimeter errors in the reconstruction of the life-sized flow model from micro-CT. In summary, pressure can be predicted with consistency by CFD across a wide range of solvers and solution strategies, but this may not hold true for specific flow patterns or derived quantities. Future challenges are needed and should focus on hemodynamic quantities thought to be of clinical interest.