Shear stress is an important physical factor that regulates proliferation, migration and morphogenesis. In regenerative medicine, one approach to generate 3D tissues has been to seed a porous scaffold with cells and growth factors under pulsatile flow conditions. However, the resulting bioreactors frequently lack information on intrinsic shear stress and flow distributions . Recent studies have focused on optimizing the microstructural parameters of the scaffold to gain more control over the shear stress. In this study, we adopt a different approach whereby macroscopic flows are redirected throughout the bioreactor along patterned channels in the scaffold that result in optimized shear stress distributions  . A topology optimization algorithm coupled to effective-medium Lattice Boltzmann simulations was devised to find an optimal channel design that yields a target shear stress that is uniformly distributed throughout the scaffold . The channel topology in the porous scaffold was varied using a combination of genetic algorithm and fuzzy logic. Unlike methods based on varying micro-architectures, the described approach has the ability to achieve a target shear stress and to distribute the shear stress uniformly throughout the scaffold. The ability of topology optimization to alter the shear stress distribution is implemented in experiments where magnetic resonance imaging (MRI) is used to image the flow field.
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.
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regenerative medicine, one approach to generate 3D tissues has been to seed a porous scaffold with cells and growth factors
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
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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
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gain more control over
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patterned channels in the scaffold that result in optimized
channels patterned in the porous scaffold to yield
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that are optimized for uniformity centered on a target value
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effective-medium Lattice Boltzmann
computational fluid dynamics
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find an optimal channel design that yields a target shear stress that is uniformly distributed throughout the scaffold
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Unlike methods based on varying micro-architectures, the described approach has the ability to achieve a target shear stress and to distribute the shear stress uniformly throughout the scaffold. The ability of topology optimization to alter the shear stress distribution is implemented in experiments where
The method is validated by experiments using
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is used to image
readouts of