Computer simulations reveal complex distribution of haemodynamic forces in a mouse retina model of angiogenesis

Author:

Bernabeu Miguel O.12,Jones Martin L.3,Nielsen Jens H.4,Krüger Timm25,Nash Rupert W.2,Groen Derek2,Schmieschek Sebastian2,Hetherington James4,Gerhardt Holger3,Franco Claudio A.36,Coveney Peter V.2

Affiliation:

1. CoMPLEX, University College London, Physics Building, Gower St., London WC1E 6BT, UK

2. Centre for Computational Science, Department of Chemistry, University College London, 20 Gordon St., London WC1H 0AJ, UK

3. Vascular Biology Laboratory, London Research Institute, Cancer Research UK, Lincoln's Inn Laboratories, 44 Lincoln's Inn Fields, London WC2A 3LY, UK

4. Research Software Development Team, Research Computing and Facilitating Services, University College London, Podium Building—1st Floor, Gower St., London WC1E 6BT, UK

5. Institute for Materials and Processes, School of Engineering, University of Edinburgh, King's Buildings, Mayfield Road, Edinburgh EH9 3JL, UK

6. Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa 1649-028, Portugal

Abstract

There is currently limited understanding of the role played by haemodynamic forces on the processes governing vascular development. One of many obstacles to be overcome is being able to measure those forces, at the required resolution level, on vessels only a few micrometres thick. In this paper, we present an in silico method for the computation of the haemodynamic forces experienced by murine retinal vasculature (a widely used vascular development animal model) beyond what is measurable experimentally. Our results show that it is possible to reconstruct high-resolution three-dimensional geometrical models directly from samples of retinal vasculature and that the lattice-Boltzmann algorithm can be used to obtain accurate estimates of the haemodynamics in these domains. We generate flow models from samples obtained at postnatal days (P) 5 and 6. Our simulations show important differences between the flow patterns recovered in both cases, including observations of regression occurring in areas where wall shear stress (WSS) gradients exist. We propose two possible mechanisms to account for the observed increase in velocity and WSS between P5 and P6: (i) the measured reduction in typical vessel diameter between both time points and (ii) the reduction in network density triggered by the pruning process. The methodology developed herein is applicable to other biomedical domains where microvasculature can be imaged but experimental flow measurements are unavailable or difficult to obtain.

Publisher

The Royal Society

Subject

Biomedical Engineering,Biochemistry,Biomaterials,Bioengineering,Biophysics,Biotechnology

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