(5cw) Bone Tissue Growth Mechanism Fundamentals Via Fluid Shear and Nutrient Transport Simulation in 3D Porous Scaffolds Cultured in a Perfusion Bioreactor

A wide variety of scaffold geometries utilized for culturing osteoblastic cells in a flow perfusion bioreactor for bone regeneration, yet the question remains unanswered as to what scaffold design is optimal for bone tissue growth. The answer depends on several factors, such as the flow regime under which the tissue is cultured, the amount of fluid shear forces experienced by the cells within the scaffold (mechanostimulation, detachment, bursting) and the efficiency of nutrient/waste transport to/away from the cells (osteoblast differentiation, proliferation, upregulation of angiogenic and osteogenic factors, and mineralized matrix production). Fundamental understanding of factors that lead to favorable cell differentiation can lead to design procedures for scaffolds that would maximize tissue growth. However, due to the inherently random architecture of porous scaffolds internal structure theoretical prediction of tissue growth is impractical. Therefore, the primary goal of this work is to obtain local shear force and mass transport distributions within typical bone engineering scaffolds (salt leeched and non-woven fiber mesh PLLA) via computation. The juxtaposition of the local tissue growth and computer simulation results is used to obtain insight into the tissue growth process with the ultimate goal of being able to predict where the tissue will grow a priori ? based on the plain scaffold geometry, only.

Flows of osteogenic media through the scaffolds are modeled via fluid dynamics simulations Lattice Boltzmann Method. Macroscopic mass transfer is modeled using the Lagrangian Scalar Tracking method. High performance computing in conjunction with a house hybrid parallelized scheme is employed in order to take advantage inherent code parallelizability. Various scaffold design parameters are explored for optimal tissue growth and the obtained results are parametrized based on geometric characteristics of the scaffolds (such as tortuosity, surface area to volume ratio, and porosity). Micro-Computed Tomography (μCT) with 10 μm resolution is used to obtain 3D structure of the scaffolds. Modeling results are validated against experiments via μCT and histological imaging of tissue growth as the tissue culturing experiment progresses with time.