Flow perfusion rate modulates cell deposition onto scaffold substrate during cell seeding.

The combination of perfusion bioreactors with porous scaffolds is beneficial for the transport of cells during cell seeding. Nonetheless, the fact that cells penetrate into the scaffold pores does not necessarily imply the interception of cells with scaffold substrate and cell attachment. An in vitro perfusion system was built to relate the selected flow rate with seeding efficiency. However, the in vitro model does not elucidate how the flow rate affects the transport and deposition of cells onto the scaffold. Thus, a computational model was developed mimicking in vitro conditions to identify the mechanisms that bring cells to the scaffold from suspension flow. Static and dynamic cell seeding configurations were investigated. In static seeding, cells sediment due to gravity until they encounter the first obstacle. In dynamic seeding, 12, 120 and 600 [Formula: see text] flow rates were explored under the presence or the absence of gravity. Gravity and secondary flow were found to be key factors for cell deposition. In vitro and in silico seeding efficiencies are in the same order of magnitude and follow the same trend with the effect of fluid flow; static seeding results in higher efficiency than dynamic perfusion although irregular spatial distribution of cells was found. In dynamic seeding, 120 [Formula: see text] provided the best seeding results. Nevertheless, the perfusion approach reports low efficiencies for the scaffold used in this study which leads to cell waste and low density of cells inside the scaffold. This study suggests gravity and secondary flow as the driving mechanisms for cell-scaffold deposition. In addition, the present in silico model can help to optimize hydrodynamic-based seeding strategies prior to experiments and enhance cell seeding efficiency.

2D µ-Particle Image Velocimetry and Computational Fluid Dynamics Study Within a 3D Porous Scaffold.

Transport properties of 3D scaffolds under fluid flow are critical for tissue development. Computational fluid dynamics (CFD) models can resolve 3D flows and nutrient concentrations in bioreactors at the scaffold-pore scale with high resolution. However, CFD models can be formulated based on assumptions and simplifications. µ-Particle image velocimetry (PIV) measurements should be performed to improve the reliability and predictive power of such models. Nevertheless, measuring fluid flow velocities within 3D scaffolds is challenging. The aim of this study was to develop a µPIV approach to allow the extraction of velocity fields from a 3D additive manufacturing scaffold using a conventional 2D µPIV system. The µ-computed tomography scaffold geometry was included in a CFD model where perfusion conditions were simulated. Good agreement was found between velocity profiles from measurements and computational results. Maximum velocities were found at the centre of the pore using both techniques with a difference of 12% which was expected according to the accuracy of the µPIV system. However, significant differences in terms of velocity magnitude were found near scaffold substrate due to scaffold brightness which affected the µPIV measurements. As a result, the limitations of the µPIV system only permits a partial validation of the CFD model. Nevertheless, the combination of both techniques allowed a detailed description of velocity maps within a 3D scaffold which is crucial to determine the optimal cell and nutrient transport properties.

The inter-sample structural variability of regular tissue-engineered scaffolds significantly affects the micromechanical local cell environment.

Rapid prototyping techniques have been widely used in tissue engineering to fabricate scaffolds with controlled architecture. Despite the ability of these techniques to fabricate regular structures, the consistency with which these regular structures are produced throughout the scaffold and from one scaffold to another needs to be quantified. Small variations at the pore level can affect the local mechanical stimuli sensed by the cells thereby affecting the final tissue properties. Most studies assume rapid prototyping scaffolds as regular structures without quantifying the local mechanical stimuli at the cell level. In this study, a computational method using a micro-computed tomography-based scaffold geometry was developed to characterize the mechanical stimuli within a real scaffold at the pore level. Five samples from a commercial polycaprolactone scaffold were analysed and computational fluid dynamics analyses were created to compare local velocity and shear stress values at the same scaffold location. The five samples did not replicate the computer-aided design (CAD) scaffold and velocity and shear stress values were up to five times higher than the ones calculated in the CAD scaffold. In addition high variability among samples was found: at the same location velocity and shear stress values could be up to two times higher from sample to sample. This study shows that regular scaffolds need to be thoroughly analysed in order to quantify real cell mechanical stimuli so inspection methods should be included as part of the fabrication process.