State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou, China.
Department of Vascular Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Int J Numer Method Biomed Eng. 2022 Nov;38(11):e3652. doi: 10.1002/cnm.3652. Epub 2022 Oct 13.
Fibrin is an important product of the coagulation cascade, and plays an eminent role in platelet stabilization. Since coagulation cascade models typically involve the reaction kinetics of dozens of proteins, which will incur burdensome computational costs when coupled to blood flow in complex geometries, researchers often ignore this process when constructing thrombosis models. However, previous studies have shown that fundamental aspects of coagulation can be reproduced with simpler models, which motivated us to obtain a reduced-order model of fibrin generation through a systematic approach. Therefore, we introduced a semi-automatic framework to perform model-reduction of cascade reactions in this study, which consisted of two processes. Specifically, the retained protein species and cascade reactions were determined based on published studies and simulation results from the full cascade model, while the optimal reaction rates for the new cascade network were determined using a genetic algorithm. The framework has been applied to a 19-species coagulation model that triggers fibrin generation in internal fields via reactive boundaries, and a 10-species reduced-order model was obtained to reproduce the kinetics of fibrinogenesis in the full cascade model at different boundary tissue factor concentrations. This reduced-order model of fibrinogenesis would be valuable for thrombosis modeling that considers both the coagulation cascade and platelet activity. Furthermore, the framework proposed herein can also be applied to the reductions of other cascade reaction models.
纤维蛋白是凝血级联反应的重要产物,在血小板稳定中起着重要作用。由于凝血级联模型通常涉及数十种蛋白质的反应动力学,当与复杂几何形状中的血流结合时,会产生繁重的计算成本,因此研究人员在构建血栓形成模型时经常忽略此过程。然而,先前的研究表明,凝血的基本方面可以用更简单的模型来再现,这促使我们通过系统的方法获得纤维蛋白生成的降阶模型。因此,我们在本研究中引入了一种半自动框架来执行级联反应的模型简化,该框架由两个过程组成。具体来说,根据已发表的研究和全级联模型的模拟结果确定保留的蛋白质种类和级联反应,而新级联网络的最佳反应速率则使用遗传算法确定。该框架已应用于一种 19 种物质的凝血模型,该模型通过反应性边界在内场中触发纤维蛋白生成,并获得了一种 10 种物质的简化模型,以在不同边界组织因子浓度下再现全级联模型中的纤维蛋白生成动力学。这种纤维蛋白生成的降阶模型对于同时考虑凝血级联和血小板活性的血栓形成建模将是有价值的。此外,本文提出的框架还可以应用于其他级联反应模型的简化。