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Multiscale modelling of blood flow in cerebral microcirculation: Details at capillary scale control accuracy at the level of the cortex

Peyrounette, Myriam and Davit, Yohan and Quintard, Michel and Lorthois, Sylvie Multiscale modelling of blood flow in cerebral microcirculation: Details at capillary scale control accuracy at the level of the cortex. (2018) PLoS ONE, 13 (1). 1-35. ISSN 1932-6203

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Official URL: http://dx.doi.org/10.1371/journal.pone.0189474

Abstract

Aging or cerebral diseases may induce architectural modifications in human brain microvascular networks, such as capillary rarefaction. Such modifications limit blood and oxygen supply to the cortex, possibly resulting in energy failure and neuronal death. Modelling is key in understanding how these architectural modifications affect blood flow and mass transfers in such complex networks. However, the huge number of vessels in the human brain—tens of billions—prevents any modelling approach with an explicit architectural representation down to the scale of the capillaries. Here, we introduce a hybrid approach to model blood flow at larger scale in the brain microcirculation, based on its multiscale architecture. The capillary bed, which is a space-filling network, is treated as a porous medium and modelled using a homogenized continuum approach. The larger arteriolar and venular trees, which cannot be homogenized because of their fractal-like nature, are treated as a network of interconnected tubes with a detailed representation of their spatial organization. The main contribution of this work is to devise a proper coupling model at the interface between these two components. This model is based on analytical approximations of the pressure field that capture the strong pressure gradients building up in the capillaries connected to arterioles or venules. We evaluate the accuracy of this model for both very simple architectures with one arteriole and/or one venule and for more complex ones, with anatomically realistic tree-like vessels displaying a large number of coupling sites. We show that the hybrid model is very accurate in describing blood flow at large scales and further yields a significant computational gain by comparison with a classical network approach. It is therefore an important step towards large scale simulations of cerebral blood flow and lays the groundwork for introducing additional levels of complexity in the future.

Item Type:Article
Additional Information:This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Thanks to Public Library of Science editor. The definitive version is available at http://journals.plos.org/ The original PDF of the article can be found at http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0189474
Audience (journal):International peer-reviewed journal
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Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Other partners > Cornell University (USA)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
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Funders:
European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ ERC grant agreement n ̊ 615102 - MP was the recipient of a doctoral fellowship from Institut National Polytechnique de Toulouse (http://www.inp-toulouse.fr/) and an international mobility grant from Ecole Doctorale MEGeP, Toulouse (www.ed-megep.fr/) - This work was performed using HPC resources from CALMIP (Grant 2016-P1541)
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Deposited On:09 Feb 2018 14:16

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