  Shear stress is an important physical factor that regulates proliferation,
migration and morphogenesis. In particular, the homeostasis of blood vessels is
dependent on shear stress. To mimic this process ex vivo, efforts have been
made to seed scaffolds with vascular and other cell types in the presence of
growth factors and under pulsatile flow conditions. However, the resulting
bioreactors lack information on shear stress and flow distributions within the
scaffold. Consequently, it is difficult to interpret the effects of shear
stress on cell function. Such knowledge would enable researchers to improve
upon cell culture protocols. Recent work has focused on optimizing the
microstructural parameters of the scaffold to fine tune the shear stress. In
this study, we have adopted a different approach whereby flows are redirected
throughout the bioreactor along channels patterned in the porous scaffold to
yield shear stress distributions that are optimized for uniformity centered on
a target value. A topology optimization algorithm coupled to computational
fluid dynamics simulations was devised to this end. The channel topology in the
porous scaffold was varied using a combination of genetic algorithm and fuzzy
logic. The method is validated by experiments using magnetic resonance imaging
(MRI) readouts of the flow field.
