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Updated: Dec 31, 2025

Stepwise Cell Seeding on Tessellated Scaffolds to Study Sprouting Blood Vessels
Published on: January 14, 2021
A 3D computational model of perfusion seeding for investigating cell transport and adhesion within a porous scaffold
Ziying Zhang1, Jun Du1, Zhengying Wei2
1School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, People's Republic of China.
Abstract:
The process of cell seeding within a porous scaffold is an essential first step in the development of tissue-engineered bone grafts. Understanding the underlying mechanisms of cell distribution and adhesion is fundamental for the design and optimization of the seeding process. To that end, we present a numerical model to investigate the perfusion cell seeding process that incorporates cell mechanics, cell-fluid interaction, and cell-scaffold adhesion. The individual cells are modeled as deformable spherical capsules capable of adhering to the scaffold surface as well as to other cells with probabilistic bond formation and rupture. The mechanical deformation of the cell is calibrated with the stretching of mice mesenchymal stem cells induced by optical tweezers, while the predicted adhesive forces are consistent with the experimental data reported in the literature. A sub-domain is numerically reconstructed as the region of interest (ROI) which is representative of an actual scaffold. Through the simulations, the perfusion seeding kinetics within the ROI involving detailed transport and adhesion of cells over time is analyzed. The effects of the perfusion pressure and initial cell concentration on the seeding kinetics are studied in terms of adhesion rates, cell cluster formation, seeding uniformity, and efficiency, as well as scaffold permeability. The results highlight the importance of cell-fluid interaction and adhesion dynamics in modeling the dynamic seeding process. This bottom-up model provides a way to bridge detailed behaviors of individual cells to the seeding outcomes at the macroscopic scale, allowing for finding the best configuration to enhance cell seeding.

