Vascular Modelling of Complex Flow in Aneurysms and Endovascular Devices

动脉瘤和血管内装置中复杂血流的血管建模

• 批准号: RGPIN-2018-06260
• 负责人: Poepping, Tamie
• 金额: $ 1.97万
• 依托单位: University of Western Ontario
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=713618
• 关键词: Vascular; Modelling; Complex; Flow; Aneurysms

Vascular flow models and measurement platforms provide a critical tool for exploring complex flow in vascular geometries such as brain aneurysms, including the effects of interventional devices. Typical endovascular interventions for aneurysms include insertion of coils, stents, or flow diverters, which aim to achieve flow stagnation and thrombosis within the aneurysm. The outcome of a particular device implementation is dependent upon in vivo flow conditions namely flow rates, pressure gradients, and downstream impedances that critically determine device impact and potential complications. It is also increasingly recognized that disturbed and turbulent-like flow conditions play a fundamental role in vascular pathology, particularly through low and multidirectional oscillations in wall shear stress. Particle image velocimetry (PIV) is an essential benchmarking tool that provides instantaneous velocity vector measurements in a cross-section of flow via analysis of images of fluorescent micro-particles excited by laser illumination. PIV offers high temporal and spatial resolution mapping of 3D velocity vectors, and it is thus uniquely able to capture 3D flow disturbances, such as vortex shedding, high-frequency oscillations, and transition to turbulent-like flow, such as in vascular models. We aim to develop an integrated cerebrovascular flow simulation platform including our high-resolution PIV system that will enable the rapid testing of endovascular devices in patient-specific aneurysm geometries. We will develop methodology for the rapid 3D-printing of transparent patient-specific aneurysm geometries. These models will be incorporated into a cerebrovascular flow system with the capacity to vary downstream impedances in a predictive fashion as necessary to reproduce patient-specific pressure and flow waveforms. The proposed system will include the highest level of physiological realism to date, with patient-specific geometries and waveforms, compliant vessels, non-Newtonian fluid, and high temporal and spatial resolution to capture flow instabilities.

血管流动模型和测量平台为探索诸如脑动脉瘤等血管几何形状中的复杂流动（包括介入器械的影响）提供了关键工具。动脉瘤的典型血管内介入包括插入弹簧圈、支架或血流导向器，其目的是在动脉瘤内实现血流停滞和血栓形成。特定器械实施的结果取决于体内流动条件，即流速、压力梯度和下游阻抗，这些条件决定了器械影响和潜在并发症。 它也越来越多地认识到，扰动和类似的流动条件在血管病理学中发挥着重要作用，特别是通过低和多向振荡的壁剪切应力。粒子图像测速技术（PIV）是一种重要的基准测试工具，它通过分析激光激发的荧光微粒图像来提供流场横截面中的瞬时速度矢量测量。PIV提供了3D速度矢量的高时间和空间分辨率映射，因此它能够独特地捕获3D流动扰动，例如旋涡脱落，高频振荡和过渡到类似于血管模型的流动。 我们的目标是开发一个集成的脑血管血流模拟平台，包括我们的高分辨率PIV系统，这将使血管内器械在患者特定的动脉瘤几何形状的快速测试。我们将开发用于快速3D打印透明患者特定动脉瘤几何形状的方法。这些模型将被纳入脑血管流量系统，并能够以预测方式改变下游阻抗，以重现患者特定的压力和流量波形。所提出的系统将包括迄今为止最高水平的生理现实主义，具有患者特定的几何形状和波形、顺应性血管、非牛顿流体以及用于捕获流动不稳定性的高时间和空间分辨率。