通过实验验证体外解剖脑血管模型中的流动模型。

Frontiers in Medical Technology Pub Date : 2023-02-23 eCollection Date: 2023-01-01 DOI:10.3389/fmedt.2023.1130201
Saurabh Bhardwaj, Brent A Craven, Jacob E Sever, Francesco Costanzo, Scott D Simon, Keefe B Manning
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引用次数: 0

摘要

急性缺血性中风(AIS)是栓子滞留在脑血管中并阻碍脑血流时导致死亡的主要原因。AIS 的严重程度取决于栓子滞留的位置和范围,这在很大程度上取决于脑流和栓子迁移的动态,而在 AIS 患者体内很难测量这些因素。计算流体动力学(CFD)可用于预测特定患者的血流动力学以及栓子在脑血管中的迁移和着床情况,从而更好地了解 AIS 的基本机制。然而,计算模拟必须经过验证和确认才能作为依据。本研究建立了一个逼真的体外实验模型和相应的脑血管计算模型,可用于研究脑内血流和栓子的迁移与滞留。首先,介绍了体外解剖模型,包括如何调整模型中的血流分布以符合文献中的生理测量结果。测量正常和中风情况下的压力和流速,并进行相应的 CFD 模拟,与实验进行比较,以验证流量预测。总体而言,CFD 模拟结果与实验结果比较接近,在平均实验数据的 ±7% 范围内,许多 CFD 预测结果在实验测量的不确定性范围内。这项工作为现实脑血管模型中的流动提供了体外基准数据集,是验证 AIS 计算模型的第一步。
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Modeling flow in an in vitro anatomical cerebrovascular model with experimental validation.

Acute ischemic stroke (AIS) is a leading cause of mortality that occurs when an embolus becomes lodged in the cerebral vasculature and obstructs blood flow in the brain. The severity of AIS is determined by the location and how extensively emboli become lodged, which are dictated in large part by the cerebral flow and the dynamics of embolus migration which are difficult to measure in vivo in AIS patients. Computational fluid dynamics (CFD) can be used to predict the patient-specific hemodynamics and embolus migration and lodging in the cerebral vasculature to better understand the underlying mechanics of AIS. To be relied upon, however, the computational simulations must be verified and validated. In this study, a realistic in vitro experimental model and a corresponding computational model of the cerebral vasculature are established that can be used to investigate flow and embolus migration and lodging in the brain. First, the in vitro anatomical model is described, including how the flow distribution in the model is tuned to match physiological measurements from the literature. Measurements of pressure and flow rate for both normal and stroke conditions were acquired and corresponding CFD simulations were performed and compared with the experiments to validate the flow predictions. Overall, the CFD simulations were in relatively close agreement with the experiments, to within ±7% of the mean experimental data with many of the CFD predictions within the uncertainty of the experimental measurement. This work provides an in vitro benchmark data set for flow in a realistic cerebrovascular model and is a first step towards validating a computational model of AIS.

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