Computers in biology and medicine | 2021

Simulated tissue growth in tetragonal lattices with mechanical stiffness tuned for bone tissue engineering.

 
 
 

Abstract


Bone tissue engineering approaches have recently begun considering 3D printed lattices as viable scaffold solutions due to their highly tunable geometries and mechanical efficiency. However, scaffold design remains challenging due to the numerous biological and mechanical trade-offs related to lattice geometry. Here, we investigate novel tetragonal unit cell designs by independently adjusting unit cell height and width to find scaffolds with improved tissue growth while maintaining suitable scaffold mechanical properties for bone tissue engineering. Lattice tissue growth behavior is evaluated using a curvature-based growth model while elastic modulus is evaluated with finite element analysis. Computationally efficient modeling approaches are implemented to facilitate bulk analysis of lattice design trade-offs using design maps for biological and mechanical functionalities in relation to unit cell height and width for two contrasting unit cell topologies. Newly designed tetragonal lattices demonstrate higher tissue growth per unit volume and advantageous stiffness in preferred directions compared to cubically symmetric unit cells. When lattice beam diameter is fixed to 200 μm, Tetra and BC-Tetra lattices with elastic moduli of 200\xa0MPa-400\xa0MPa are compared for squashed, cubic, and stretched topologies. Squashed Tetra lattices demonstrated higher growth rates and growth densities compared to symmetrically cubic lattices. BC-Tetra lattices with the same range of elastic moduli show squashed lattices tend to achieve higher growth rates, whereas stretched lattices promote higher growth density. The results suggest tetragonal unit cells provide favorable properties for biological and mechanical tailoring, therefore enabling new strategies for diverse patient needs and applications in regenerative medicine.

Volume 138
Pages \n 104913\n
DOI 10.1016/j.compbiomed.2021.104913
Language English
Journal Computers in biology and medicine

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