Ngwenya Tinashe, Grundlingh Divan, Ngoepe Malebogo N
Centre for Research in Computational and Applied Mechanics (CERECAM), University of Cape Town, South Africa; Department of Mechanical Engineering, University of Cape Town, South Africa.
Department of Mechanical Engineering, University of Cape Town, South Africa.
J Biomech. 2024 Mar;165:111994. doi: 10.1016/j.jbiomech.2024.111994. Epub 2024 Feb 16.
Thrombosis is an important contributor to cerebral aneurysm growth and progression. A number of sophisticated multiscale and multiphase in silico models have been developed with a view towards interventional planning. Many of these models are able to account for clotting outcomes, but do not provide detailed insight into the role of flow during clot development. In this study, we present idealised, two-dimensional in silico cerebral fibrin clot model based on computational fluid dynamics (CFD), biochemical modelling and variable porosity, permeability, and diffusivity. The model captures fibrin clot growth in cerebral aneurysms over a period at least 1000 s in five different geometries. The fibrin clot growth results were compared to an experiment presented in literature. The biochemistry was found to be more sensitive to mesh size compared to the haemodynamics, while larger timesteps overpredicted clot size in pulsatile flow. When variable diffusivity was used, the predicted clot size was 25.4% lesser than that with constant diffusivity. The predicted clot size in pulsatile flow was 14.6% greater than in plug flow. Different vortex modes were observed in plug and pulsatile flow; the latter presented smaller intermediate modes where the main vortex was smaller and less likely to disrupt the growing fibrin clot. Furthermore, smaller vortex modes were seen to support fibrin clot propagation across geometries. The model clearly demonstrates how the growing fibrin clot alters vortical structures within the aneurysm sac and how this changing flow, in turn, shapes the growing fibrin clot.
血栓形成是脑动脉瘤生长和进展的一个重要因素。为了进行介入规划,已经开发了许多复杂的多尺度和多相计算机模拟模型。这些模型中的许多都能够考虑凝血结果,但没有详细深入地研究凝血形成过程中血流的作用。在本研究中,我们基于计算流体动力学(CFD)、生化建模以及可变孔隙率、渗透率和扩散率,提出了理想化的二维计算机模拟脑纤维蛋白凝块模型。该模型在五种不同几何形状下捕捉脑动脉瘤中纤维蛋白凝块至少1000秒的生长过程。将纤维蛋白凝块的生长结果与文献中提出的一项实验进行了比较。结果发现,与血液动力学相比,生物化学对网格大小更敏感,而在脉动流中较大的时间步长会高估凝块大小。当使用可变扩散率时,预测的凝块大小比使用恒定扩散率时小25.4%。脉动流中预测的凝块大小比塞流中预测的凝块大小大14.6%。在塞流和脉动流中观察到不同的涡旋模式;后者呈现出较小的中间模式,其中主涡旋较小,不太可能破坏正在生长的纤维蛋白凝块。此外,较小的涡旋模式被认为有助于纤维蛋白凝块在不同几何形状之间传播。该模型清楚地展示了生长中的纤维蛋白凝块如何改变动脉瘤囊内的涡旋结构,以及这种变化的血流又如何塑造生长中的纤维蛋白凝块。