Bone tissue engineering using polycaprolactone scaffolds fabricated via selective laser sintering
- PMID: 15763261
- DOI: 10.1016/j.biomaterials.2004.11.057
Bone tissue engineering using polycaprolactone scaffolds fabricated via selective laser sintering
Abstract
Polycaprolactone (PCL) is a bioresorbable polymer with potential applications for bone and cartilage repair. In this work, porous PCL scaffolds were computationally designed and then fabricated via selective laser sintering (SLS), a rapid prototyping technique. The microstructure and mechanical properties of the fabricated scaffolds were assessed and compared to the designed porous architectures and computationally predicted properties. Scaffolds were then seeded with bone morphogenetic protein-7 (BMP-7) transduced fibroblasts and implanted subcutaneously to evaluate biological properties and to demonstrate tissue in-growth. The work done illustrates the ability to design and fabricate PCL scaffolds with porous architecture that have sufficient mechanical properties for bone tissue engineering applications using SLS. Compressive modulus and yield strength values ranged from 52 to 67 MPa and 2.0 to 3.2 Mpa, respectively, lying within the lower range of properties reported for human trabecular bone. Finite element analysis (FEA) results showed that mechanical properties of scaffold designs and of fabricated scaffolds can be computationally predicted. Histological evaluation and micro-computed tomography (microCT) analysis of implanted scaffolds showed that bone can be generated in vivo. Finally, to demonstrate the clinical application of this technology, we designed and fabricated a prototype mandibular condyle scaffold based on an actual pig condyle. The integration of scaffold computational design and free-form fabrication techniques presented here could prove highly useful for the construction of scaffolds that have anatomy specific exterior architecture derived from patient CT or MRI data and an interior porous architecture derived from computational design optimization.
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