Department of Cardiovascular Engineering, Institute of Applied Medical Engineering, Helmholtz Institute, RWTH Aachen University, Aachen, Germany.
Department of Cardiovascular Engineering, Institute of Applied Medical Engineering, Helmholtz Institute, RWTH Aachen University, Aachen, Germany.
J Biomech. 2014 Feb 7;47(3):729-35. doi: 10.1016/j.jbiomech.2013.11.005. Epub 2013 Dec 10.
Stroke and cerebral hypoxia are among the main complications during cardiopulmonary bypass (CPB). The two main reasons for these complications are the cannula jet, due to altered flow conditions and the sandblast effect, and impaired cerebral autoregulation which often occurs in the elderly. The effect of autoregulation has so far mainly been modeled using lumped parameter modeling, while Computational Fluid Dynamics (CFD) has been applied to analyze flow conditions during CPB. In this study, we combine both modeling techniques to analyze the effect of lumped parameter modeling on blood flow during CPB. Additionally, cerebral autoregulation is implemented using the Baroreflex, which adapts the cerebrovascular resistance and compliance based on the cerebral perfusion pressure. The results show that while a combination of CFD and lumped parameter modeling without autoregulation delivers feasible results for physiological flow conditions, it overestimates the loss of cerebral blood flow during CPB. This is counteracted by the Baroreflex, which restores the cerebral blood flow to native levels. However, the cerebral blood flow during CPB is typically reduced by 10-20% in the clinic. This indicates that either the Baroreflex is not fully functional during CPB, or that the target value for the Baroreflex is not a full native cerebral blood flow, but the plateau phase of cerebral autoregulation, which starts at approximately 80% of native flow.
中风和脑缺氧是体外循环(CPB)期间的主要并发症之一。这些并发症的两个主要原因是由于流动条件改变和喷砂效应导致的套管射流,以及老年人经常发生的脑自动调节受损。到目前为止,自动调节的效果主要是通过集中参数建模来建模的,而计算流体动力学(CFD)已被应用于分析 CPB 期间的流动条件。在这项研究中,我们结合了这两种建模技术来分析集中参数建模对 CPB 期间血流的影响。此外,通过压力反射来实现脑自动调节,根据脑灌注压来调节脑血管阻力和顺应性。结果表明,虽然没有自动调节的 CFD 和集中参数建模的组合可为生理流动条件提供可行的结果,但它高估了 CPB 期间的脑血流损失。压力反射会将脑血流恢复到自然水平,从而抵消了这种情况。然而,CPB 期间的脑血流通常会在临床上减少 10-20%。这表明,压力反射在 CPB 期间不是完全有效的,或者压力反射的目标值不是完全自然的脑血流,而是脑自动调节的平台期,该平台期大约在自然血流的 80%处开始。