微血管网络中血压的三维离散连续模型。

IF 2.2 4区 医学 Q3 ENGINEERING, BIOMEDICAL International Journal for Numerical Methods in Biomedical Engineering Pub Date : 2024-05-21 DOI:10.1002/cnm.3832
Paul W. Sweeney, Claire Walsh, Simon Walker-Samuel, Rebecca J. Shipley
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引用次数: 0

摘要

我们提出了一种三维离散-连续模型,用于在没有已知毛细血管网络结构的情况下模拟大型微血管组织中的血压。我们的混合方法结合了对大型离散动脉和静脉网络的一维普瓦赛流描述,以及基于连续体的达西模型(点通量源),用于毛细血管床的传输。我们使用多重荧光高分辨率外显微镜(MF-HREM)对小鼠大脑髓质/大脑皮质的血管网络成像进行了评估。我们使用完全解析的血管网络预测毛细血管网络的水力传导性,并生成完全离散的压力解决方案作为基准。我们的研究结果表明,当毛细管微血管定义不清时,离散连续方法是预测真实世界微血管组织血压的一种计算上可行且有效的工具。
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A three-dimensional, discrete-continuum model of blood pressure in microvascular networks

We present a 3D discrete-continuum model to simulate blood pressure in large microvascular tissues in the absence of known capillary network architecture. Our hybrid approach combines a 1D Poiseuille flow description for large, discrete arteriolar and venular networks coupled to a continuum-based Darcy model, point sources of flux, for transport in the capillary bed. We evaluate our hybrid approach using a vascular network imaged from the mouse brain medulla/pons using multi-fluorescence high-resolution episcopic microscopy (MF-HREM). We use the fully-resolved vascular network to predict the hydraulic conductivity of the capillary network and generate a fully-discrete pressure solution to benchmark against. Our results demonstrate that the discrete-continuum methodology is a computationally feasible and effective tool for predicting blood pressure in real-world microvascular tissues when capillary microvessels are poorly defined.

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来源期刊
International Journal for Numerical Methods in Biomedical Engineering
International Journal for Numerical Methods in Biomedical Engineering ENGINEERING, BIOMEDICAL-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
4.50
自引率
9.50%
发文量
103
审稿时长
3 months
期刊介绍: All differential equation based models for biomedical applications and their novel solutions (using either established numerical methods such as finite difference, finite element and finite volume methods or new numerical methods) are within the scope of this journal. Manuscripts with experimental and analytical themes are also welcome if a component of the paper deals with numerical methods. Special cases that may not involve differential equations such as image processing, meshing and artificial intelligence are within the scope. Any research that is broadly linked to the wellbeing of the human body, either directly or indirectly, is also within the scope of this journal.
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