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An Improved Coarse-Grained Model to Accurately Predict Red Blood Cell Morphology and Deformability

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Computational Biomechanics for Medicine (MICCAI 2019, MICCAI 2018)

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Abstract

Accurate modelling of red blood cells (RBCs) has greater potential over experiments, as it can be more robust and significantly cheaper than equivalent experimental procedures to investigate the mechanical properties, rheology and dynamics of RBCs. The recent advances in numerical modelling techniques for RBC studies are reviewed in this study, and in particular, the discrete models for a triangulated surface to represent the in-plane stretching energy and out-of-plane bending energy of the RBC membrane are discussed. In addition, an improved RBC membrane model is presented based on coarse-grained (CG) technique that accurately and efficiently predicts the morphology and deformability of a RBC. The CG-RBC membrane model predicts the minimum energy configuration of the RBC from the competition between the in-plane stretching energy of the cytoskeleton and the out-of-plane bending energy of the lipid-bilayer under the given reference states of the cell surface area and volume. A quantitative evaluation of several cellular measurements including length, thickness and shape factor, is presented between the CG-RBC membrane model and three-dimensional (3D) confocal microscopy imaging generated RBC shapes at equivalent reference states. The CG-RBC membrane model predicts agreeable deformation characteristics of a healthy RBC with the analogous experimental observations corresponding to optical tweezers stretching deformations. The numerical approach presented here forms the foundation for investigations into RBC morphology and deformability under diverse shape-transforming scenarios, in vitro RBC storage, microvascular circulation and flow through microfluidic devices.

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Abbreviations

2D:

Two-dimensional

3D:

Three-dimensional

ADE:

Area-difference-elasticity

AFM:

Atomic force microscopy

BCM:

Bilayer-coupling model

BIM:

Boundary integral method

CG:

Coarse-graining

CGMD:

Coarse-grained molecular dynamics

DPD:

Dissipative particle dynamics

FEM:

Finite element method

HE:

Hereditary elliptocytosis

HPC:

High performance computing

HS:

Hereditary spherocytosis

IBM:

Immersed boundary method

MD:

Molecular dynamics

QUT:

Queensland University of Technology

RBC:

Red blood cell

SAGM:

Saline-adenine-glucose-mannitol

SCM:

Spontaneous curvature model

SEM:

Scanning electron microscopy

SF:

Shape factor

SP:

Spring-particle

SPH:

Smoothed particle hydrodynamics

TEM:

Transmission electron microscopy

WLC:

Worm-like-chain

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Authors and Affiliations

  1. School of Mechanical, Medical and Process Engineering, Queensland University of Technology (QUT), Brisbane, QLD, Australia

    Nadeeshani Maheshika Geekiyanage, Yuan Tong Gu & Emilie Sauret

  2. Research & Development, Red Cross Lifeblood, Brisbane, QLD, Australia

    Robert Flower

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  1. Nadeeshani Maheshika Geekiyanage
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  2. Robert Flower
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  3. Yuan Tong Gu
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  4. Emilie Sauret
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Correspondence to Emilie Sauret .

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  1. Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, WA, Australia

    Karol Miller

  2. Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, WA, Australia

    Adam Wittek

  3. Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, WA, Australia

    Grand Joldes

  4. Department of Engineering Science, Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand

    Martyn P. Nash

  5. Department of Engineering Science, Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand

    Poul M. F. Nielsen

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Geekiyanage, N.M., Flower, R., Gu, Y.T., Sauret, E. (2020). An Improved Coarse-Grained Model to Accurately Predict Red Blood Cell Morphology and Deformability. In: Miller, K., Wittek, A., Joldes, G., Nash, M., Nielsen, P. (eds) Computational Biomechanics for Medicine. MICCAI MICCAI 2019 2018. Springer, Cham. https://doi.org/10.1007/978-3-030-42428-2_5

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