Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy; PoliTo(BIO)Med Lab, Politecnico di Torino, Turin, Italy.
BioCardioLab, Bioengineering Unit - Heart Hospital, Fondazione Toscana "G. Monasterio", Massa, Italy.
J Biomech. 2023 Jun;154:111620. doi: 10.1016/j.jbiomech.2023.111620. Epub 2023 May 8.
In the context of aortic hemodynamics, uncertainties affecting blood flow simulations hamper their translational potential as supportive technology in clinics. Computational fluid dynamics (CFD) simulations under rigid-walls assumption are largely adopted, even though the aorta contributes markedly to the systemic compliance and is characterized by a complex motion. To account for personalized wall displacements in aortic hemodynamics simulations, the moving-boundary method (MBM) has been recently proposed as a computationally convenient strategy, although its implementation requires dynamic imaging acquisitions not always available in clinics. In this study we aim to clarify the real need for introducing aortic wall displacements in CFD simulations to accurately capture the large-scale flow structures in the healthy human ascending aorta (AAo). To do that, the impact of wall displacements is analyzed using subject-specific models where two CFD simulations are performed imposing (1) rigid walls, and (2) personalized wall displacements adopting a MBM, integrating dynamic CT imaging and a mesh morphing technique based on radial basis functions. The impact of wall displacements on AAo hemodynamics is analyzed in terms of large-scale flow patterns of physiological significance, namely axial blood flow coherence (quantified applying the Complex Networks theory), secondary flows, helical flow and wall shear stress (WSS). From the comparison with rigid-wall simulations, it emerges that wall displacements have a minor impact on the AAo large-scale axial flow, but they can affect secondary flows and WSS directional changes. Overall, helical flow topology is moderately affected by aortic wall displacements, whereas helicity intensity remains almost unchanged. We conclude that CFD simulations with rigid-wall assumption can be a valid approach to study large-scale aortic flows of physiological significance.
在主动脉血液动力学的背景下,影响血流模拟的不确定性阻碍了它们作为临床辅助技术的转化潜力。即使主动脉对全身顺应性有显著贡献,并具有复杂的运动,刚性壁假设下的计算流体动力学(CFD)模拟仍然被广泛采用。为了在主动脉血液动力学模拟中考虑个性化的管壁位移,最近提出了移动边界方法(MBM)作为一种计算方便的策略,尽管其实施需要动态成像采集,而这些采集在临床上并不总是可用。在这项研究中,我们旨在阐明在 CFD 模拟中引入主动脉壁位移以准确捕捉健康人类升主动脉(AAo)中的大尺度流动结构的实际需求。为此,我们使用基于径向基函数的动态 CT 成像和网格变形技术的个性化壁位移,分析了壁位移的影响,使用特定于个体的模型执行了两种 CFD 模拟:(1)刚性壁,(2)采用 MBM 的个性化壁位移。壁位移对 AAo 血液动力学的影响是通过具有生理意义的大尺度流动模式来分析的,即轴向血流相干性(通过复杂网络理论来量化)、二次流、螺旋流和壁面剪切应力(WSS)。与刚性壁模拟的比较表明,壁位移对 AAo 的大尺度轴向流动的影响较小,但会影响二次流和 WSS 的方向变化。总体而言,主动脉壁位移对螺旋流拓扑结构的影响较小,但对螺旋强度的影响几乎不变。我们得出结论,刚性壁假设下的 CFD 模拟可以是研究具有生理意义的大尺度主动脉流的有效方法。