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Simulation of microcirculatory hemodynamics: estimation of boundary condition using particle swarm optimization

Issue title: Frontiers in Biomedical Engineering and Biotechnology – Proceedings of the 3rd International Conference on Biomedical Engineering and Biotechnology, 25–28 September 2014, Beijing, China

Article type: Research Article

Authors: Pan, Qing | Wang, Ruofan | Reglin, Bettina | Fang, Luping | Pries, Axel R.; | Ning, Gangmin;

Affiliations: College of Information Engineering, Zhejiang University of Technology, 310023 Hangzhou, China | Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of MOE, Zhejiang University, 310027 Hangzhou, China | Department of Physiology and CCR, Charité, Charitéplatz 1, 10117 Berlin, Germany | Deutsches Herzzentrum Berlin, Augustenburger Platz 1, D-13353 Berlin, Germany

Note: [] Corresponding author: Gangmin Ning, Department of Biomedical Engineering, Zhejiang University, Zheda Rd. 38, 310027 Hangzhou, China. Tel.: +86-571-87951091; Fax: +86-571-87951676; E-mail: [email protected].

Keywords: Microcirculation, particle swarm optimization, mathematical model, boundary condition

DOI: 10.3233/BME-141047

Journal: Bio-Medical Materials and Engineering, vol. 24, no. 6, pp. 2341-2347, 2014

Published: 2014
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Abstract

Estimation of the boundary condition is a critical problem in simulating hemodynamics in microvascular networks. This paper proposed a boundary estimation strategy based on a particle swarm optimization (PSO) algorithm, which aims to minimize the number of vessels with inverted flow direction in comparison to the experimental observation. The algorithm took boundary values as the particle swarm and updated the position of the particles iteratively to approach the optimization target. The method was tested in a real rat mesenteric network. With random initial boundary values, the method achieved a minimized 9 segments with an inverted flow direction in the network with 546 vessels. Compared with reported literature, the current work has the advantage of a better fit with experimental observations and is more suitable for the boundary estimation problem in pulsatile hemodynamic models due to the experiment-based optimization target selection.

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