A particle-based model for endothelial cell migration under flow conditions
Endothelial cells (ECs) play a major role in the healing process following angioplasty to inhibit excessive neointima. This makes the process of EC healing after injury, in particular EC migration in a stented vessel, important for recovery of normal vessel function. In that context, we present a novel particle-based model of EC migration and validate it against in vitro experimental data. We have developed a particle-based model of EC migration under fow conditions in an in vitro vessel with obstacles. Cell movement in the model is a combination of random walks and directed movement along the local fow velocity vector. For model calibration, a set of experimental data for cell migration in a similarly shaped channel has been used. We have calibrated the model for a baseline case of a channel with no obstacles and then applied it to the case of a channel with ridges on the bottom surface, representative of stent strut geometry. We were able to closely reproduce the cell migration speed and angular distribution of their movement relative to the fow direction reported in vitro. The model also reproduces qualitative aspects of EC migration, such as entrapment of cells downstream from the fow-disturbing ridge. The model has the potential, after more extensive in vitro validation, to study the efect of variation in strut spacing and shape, through modifcation of the local fow, on EC migration. The results of this study support the hypothesis that EC migration is strongly afected by the direction and magnitude of local wall shear stress.
|Keywords||Computational model · Endothelial cells · Particle-based model · Shear stress · Cell migration|
|Persistent URL||dx.doi.org/10.1007/s10237-019-01239-w, hdl.handle.net/1765/120468|
|Journal||Biomechanics and Modeling in Mechanobiology|
Zun, P.S., Narracott, A.J., Evans, P.C, van Rooij, B.J.M., & Hoekstra, A.G. (2019). A particle-based model for endothelial cell migration under flow conditions. Biomechanics and Modeling in Mechanobiology. doi:10.1007/s10237-019-01239-w