A hybrid discrete–continuum approach for modelling microcirculatory blood flow

Rebecca J Shipley;Amy F Smith;Paul W Sweeney;Axel R Pries;Timothy W Secomb
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引用次数: 24

Abstract

In recent years, biological imaging techniques have advanced significantly and it is now possible to digitally reconstruct microvascular network structures in detail, identifying the smallest capillaries at sub-micron resolution and generating large 3D structural data sets of size >10 6 vessel segments. However, this relies on ex vivo imaging; corresponding in vivo measures of microvascular structure and flow are limited to larger branching vessels and are not achievable in three dimensions for the smallest vessels. This suggests the use of computational modelling to combine in vivo measures of branching vessel architecture and flows with ex vivo data on complete microvascular structures to predict effective flow and pressures distributions. In this paper, a hybrid discrete–continuum model to predict microcirculatory blood flow based on structural information is developed and compared with existing models for flow and pressure in individual vessels. A continuum-based Darcy model for transport in the capillary bed is coupled via point sources of flux to flows in individual arteriolar vessels, which are described explicitly using Poiseuille's law. The venular drainage is represented as a spatially uniform flow sink. The resulting discrete–continuum framework is parameterized using structural data from the capillary network and compared with a fully discrete flow and pressure solution in three networks derived from observations of the rat mesentery. The discrete–continuum approach is feasible and effective, providing a promising tool for extracting functional transport properties in situations where vascular branching structures are well defined.
模拟微循环血流的一种混合离散-连续方法
近年来,生物成像技术取得了显著进步,现在可以对微血管网络结构进行详细的数字重建,以亚微米分辨率识别最小的毛细血管,并生成大小>106个血管段的大型3D结构数据集。然而,这依赖于离体成像;微血管结构和流动的相应体内测量仅限于较大的分支血管,并且对于最小的血管来说在三维中是不可实现的。这表明使用计算建模将分支血管结构和流量的体内测量与完整微血管结构的离体数据相结合,以预测有效流量和压力分布。本文开发了一种基于结构信息的混合离散-连续模型来预测微循环血流,并与现有的单个血管中的流量和压力模型进行了比较。毛细管床中传输的基于连续介质的Darcy模型通过点通量源与单个小动脉中的流动相耦合,这是使用Poiseuille定律明确描述的。小静脉引流表现为空间上均匀的流汇。使用毛细管网络的结构数据对所得的离散-连续框架进行参数化,并将其与根据大鼠肠系膜观察得出的三个网络中的完全离散的流量和压力溶液进行比较。离散-连续方法是可行和有效的,为在血管分支结构明确的情况下提取功能转运特性提供了一种很有前途的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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