Computational design is growing in necessity for advancing biomedical technologies, particularly when considering complex systems with numerous trade-offs among design decisions and resulting biomechanical behavior. In tissue engineering applications, porous bone scaffold structures enabled by 3D printing can have intricate lattice structures and hierarchical features that mimic the biological hierarchy of natural bone. However, these hierarchies create challenges in predicting the tissue regeneration process and how different scales of the hierarchy drive varied biological behaviors. Smaller pores facilitate tissue growth while larger pores are necessary for blood vessel growth, however, identifying favorable trade-offs to maximize growth of both tissue and blood vessels remains a challenge, especially for complex 3D printed structures. Here, we adapt tissue and blood vessel growth models for predicting biological growth in scaffolds with varied combinations of beam diameter size, unit cell topology, and hierarchical pore size/distribution. Findings demonstrate that on a normalized scale lattices with no large voids provide greater tissue growth but less blood vessel growth in comparison to lattice layouts with large void areas. A lattice with large void channels provided the greatest blood vessel growth but poorer tissue growth, while a lattice with evenly distributed large voids provided a better compromise between the two types of growth. Overall, these findings demonstrate the merit in computational investigations for design trade-off comparisons in tissue scaffolds, and provide a foundation for future explorations of biological design decisions for regenerative medicine and 3D printed systems.

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