Computational Modeling of Tissue Engineering Scaffolds as Delivery Devices for Mechanical and Mechanically Modulated Signals - Computational Modeling in Tissue Engineering - page 135

[ 21 ], which shows that different pore sizes and porosities cause different wall shear
stress on surface of the scaffolds (Table 1 )[ 2 , 30 , 36 , 44 , 45 ].
Flow regimes within a rapid prototyped scaffold have been studied previously
to predict the effect of geometric discrepancies due to imperfect manufacturing,
e.g., differences between target and actual manufactured scaffold geometries [ 38 ].
CFD can also be used to analyze differences in flow that are attributable to dif-
ferences in actual geometries compared to target ideal geometries; for example,
CFD accurately predicts the average fluid velocity across 81 % of the sample
volume and the wall shear stress across 73 % of the sample surface, when com-
pared to experimental validation of actual values using l-PIV [ 16 ].
7 Conclusion
This chapter has outlined to major advantages of using CFD to design and optimize
tissue engineering scaffold geometry, material behavior (including biodegradation),
and tissue ingrowth over time. One major advantage is that CFD predicts flow
conditions for precise delivery of mechanical signals to stem cells to direct cell fate
(cell scale). A second advantage is that CFD can be used to optimize tissue engi-
neering scaffold geometries, including pore size, pore distribution and connectivity,
as well as scaffold wall thickness, to modulate flow regimes within the scaffold
(tissue to cell scale). As multiscale CFD and finite element modeling approaches
converge, we anticipate that multiscale modeling will become an even more
powerful tool to predict cell-organ scale system behavior, seamlessly, over multiple
time scales that span the life of the patient or test subject.
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