Continuum microhaemodynamics modelling using inverse rheology
File(s)
Published version
Author(s)
van Batenburg-Sherwood, Joseph
Balabani, Stavroula
Type
Journal Article
Abstract
Modelling blood flow in microvascular networks is challenging due to the complex nature of haemorheology. Zero- and onedimensional approaches cannot reproduce local haemodynamics, and models that consider individual red blood cells (RBCs) are prohibitively computationally expensive. Continuum approaches could provide an efficient solution, but dependence on a large parameter space and scarcity of experimental data for validation has limited their application. We describe a method to assimilate experimental RBC velocity and concentration data into a continuum numerical modelling framework. Imaging data of RBCs were acquired in a sequentially bifurcating microchannel for various flow conditions. RBC concentration distributions were evaluated and mapped into computational fluid dynamics simulations with rheology prescribed by the Quemada model. Predicted velocities were compared to particle image velocimetry data. A subset of cases was used for parameter optimisation, and the resulting model was applied to a wider data set to evaluate model efficacy. The pre-optimised model reduced errors in predicted velocity by 60% compared to assuming a Newtonian fluid, and optimisation further reduced errors by 40%. Asymmetry of RBC velocity and concentration profiles was demonstrated to play a critical role. Excluding asymmetry in the RBC concentration doubled the error, but excluding spatial distributions of shear rate had little effect. This study demonstrates that a continuum model with optimised rheological parameters can reproduce measured velocity if RBC concentration distributions are known a priori. Developing this approach for RBC transport with more network configurations has the potential to provide an efficient approach for modelling network-scale haemodynamics.
Date Issued
2022-02-01
Date Acceptance
2021-11-23
Citation
Biomechanics and Modeling in Mechanobiology, 2022, 21, pp.335-361
ISSN
1617-7940
Publisher
Springer
Start Page
335
End Page
361
Journal / Book Title
Biomechanics and Modeling in Mechanobiology
Volume
21
Copyright Statement
© The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Sponsor
Royal Academy Of Engineering
Engineering & Physical Science Research Council (EPSRC)
Identifier
10.1007/s10237-021-01537-2
Grant Number
BMPF_P67271
EP/T023155/1
Subjects
0903 Biomedical Engineering
0913 Mechanical Engineering
Biomedical Engineering
Publication Status
Published
Date Publish Online
2021-12-14