Bone tissue engineering (BTE) presents a transformative solution for critical-sized bone defects, yet optimizing scaffold geometry remains a significant challenge. Inspired by the natural structure of bone, this work explores five pivotal geometrical parameters—porosity, pore size, pore architecture, interconnectivity and permeability, and curvature—and elucidates their impact on scaffold performance. Approximately 70% porosity, mid-sized pores (∼400–650 μm), high interconnectivity, and concave surfaces emerge as the most promising features for bone regeneration, while optimal pore architecture remains cryptic. In the intricate design space defined by the interdependence of these parameters, artificial intelligence (AI) is proposed as a tool to accelerate the scaffold design process. By critically evaluating the implications of scaffold geometry, this work sheds light on current research gaps and lays a strong foundation for future studies. Integrating experimental findings with AI-driven insights, it paves the way for the design of more effective and clinically applicable BTE scaffolds.

Structural influences on bone tissue engineering: A review and perspective

Sebastiani, Sara;Buccino, Federica;Vergani, Laura Maria
2025-01-01

Abstract

Bone tissue engineering (BTE) presents a transformative solution for critical-sized bone defects, yet optimizing scaffold geometry remains a significant challenge. Inspired by the natural structure of bone, this work explores five pivotal geometrical parameters—porosity, pore size, pore architecture, interconnectivity and permeability, and curvature—and elucidates their impact on scaffold performance. Approximately 70% porosity, mid-sized pores (∼400–650 μm), high interconnectivity, and concave surfaces emerge as the most promising features for bone regeneration, while optimal pore architecture remains cryptic. In the intricate design space defined by the interdependence of these parameters, artificial intelligence (AI) is proposed as a tool to accelerate the scaffold design process. By critically evaluating the implications of scaffold geometry, this work sheds light on current research gaps and lays a strong foundation for future studies. Integrating experimental findings with AI-driven insights, it paves the way for the design of more effective and clinically applicable BTE scaffolds.
2025
artificial intelligence; bone tissue engineering; multi-scale; porosity; scaffold;
artificial intelligence
bone tissue engineering
multi-scale
porosity
scaffold
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1295992
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