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The treatment of large bone defects is a clinical challenge. 3D printed scaffolds are a promising treatment option for such critical-size defects. However, the design of scaffolds to treat such defects is challenging due to the large number of variables impacting bone regeneration; material stiffness, architecture or equivalent scaffold stiffness-due it specific architecture-have all been demonstrated to impact cell behavior and regeneration outcome. Computer design optimization is a powerful tool to find optimal design solutions within a large parameter space for given anatomical constraints. Following this approach, scaffold structures have been optimized to avoid mechanical failure while providing beneficial mechanical stimulation for bone formation within the scaffold pores immediately after implantation. However, due to the dynamics of the bone regeneration process, the mechanical conditions do change from immediately after surgery throughout healing, thus influencing the regeneration process. Therefore, we propose a computer framework to optimize scaffold designs that allows to promote the final bone regeneration outcome. The framework combines a previously developed and validated mechanobiological bone regeneration computer model, a surrogate model for bone healing outcome and an optimization algorithm to optimize scaffold design based on the level of regenerated bone volume. The capability of the framework is verified by optimization of a cylindrical scaffold for the treatment of a critical-size tibia defect, using a clinically relevant large animal model. The combined framework allowed to predict the long-term healing outcome. Such novel approach opens up new opportunities for sustainable strategies in scaffold designs of bone regeneration.
Perier-Metz et al. (Wed,) studied this question.