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 >106 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.

中文翻译：

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用于模拟微循环血流的混合离散连续方法。


近年来，生物成像技术取得了显着进步，现在可以详细地数字化重建微血管网络结构，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。微血管结构和流量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无法在三个维度上实现。这表明使用计算模型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，以预测有效的流量和压力分布。在本文中，开发了一种基于结构信息预测微循环血流的混合离散连续模型，并与现有的单个血管中的流量和压力模型进行了比较。用于毛细血管床中传输的基于连续体的达西模型通过点通量源耦合到单个小动脉血管中的流动，这使用泊肃叶定律明确地描述。静脉引流被表示为空间均匀的流汇。使用来自毛细管网络的结构数据对所得的离散连续体框架进行参数化，并与从大鼠肠系膜观察得出的三个网络中完全离散的流量和压力解进行比较。离散连续方法是可行且有效的，为在血管分支结构明确的情况下提取功能运输特性提供了一种有前景的工具。