Groen Derek, Richardson Robin A, Coy Rachel, Schiller Ulf D, Chandrashekar Hoskote, Robertson Fergus, Coveney Peter V
Department of Computer Science, Brunel University London, London, United Kingdom.
Centre for Computational Science, University College London, London, United Kingdom.
Front Physiol. 2018 Jun 19;9:721. doi: 10.3389/fphys.2018.00721. eCollection 2018.
We present a validation study comparing results from a patient-specific lattice-Boltzmann simulation to transcranial Doppler (TCD) velocity measurements in four different planes of the middle cerebral artery (MCA). As part of the study, we compared simulations using a Newtonian and a Carreau-Yasuda rheology model. We also investigated the viability of using downscaled velocities to reduce the required resolution. Simulations with unscaled velocities predict the maximum flow velocity with an error of less than 9%, independent of the rheology model chosen. The accuracy of the simulation predictions worsens considerably when simulations are run at reduced velocity, as is for example the case when inflow velocities from healthy individuals are used on a vascular model of a stroke patient. Our results demonstrate the importance of using directly measured and patient-specific inflow velocities when simulating blood flow in MCAs. We conclude that localized TCD measurements together with predictive simulations can be used to obtain flow estimates with high fidelity over a larger region, and reduce the need for more invasive flow measurement procedures.
我们开展了一项验证研究，将针对特定患者的格子玻尔兹曼模拟结果与大脑中动脉（MCA）四个不同平面的经颅多普勒（TCD）速度测量结果进行比较。作为该研究的一部分，我们比较了使用牛顿流变学模型和卡罗厄-亚苏达流变学模型的模拟。我们还研究了使用缩减速度以降低所需分辨率的可行性。使用未缩放速度进行的模拟预测最大流速时的误差小于9%，与所选的流变学模型无关。当以降低的速度运行模拟时，例如在中风患者的血管模型上使用健康个体的流入速度时，模拟预测的准确性会大幅下降。我们的结果证明了在模拟MCA中的血流时使用直接测量的特定患者流入速度的重要性。我们得出结论，局部TCD测量与预测性模拟相结合可用于在更大区域获得高保真的血流估计，并减少对更具侵入性的血流测量程序的需求。
