By combining load adaptive algorithms with mechanobiological algorithms, a computational framework was developed to design and optimize the microarchitecture of irregular load adapted scaffolds for bone tissue engineering. Skeletonized cancellous bone-inspired lattice structures were built including linear fibers oriented along the internal flux of forces induced by the hypothesized boundary conditions. These structures were then converted into solid finite element models, which were optimized with mechanobiology-based optimization algorithms. The design variable was the diameter of the beams included in the scaffold, while the design objective was the maximization of the fraction of the scaffold volume predicted to be occupied by neo-formed bony tissue. The performance of the designed irregular scaffolds, intended as the capability to favor the formation of bone, was compared with that of the regular ones based on different unit cell geometries. Three different boundary and loading conditions were hypothesized, and for all of them, it was found that the irregular load adapted scaffolds perform better than the regular ones. Interestingly, the numerical predictions of the proposed framework are consistent with the results of experimental studies reported in the literature. The proposed framework appears to be a powerful tool that can be utilized to design high-performance irregular load adapted scaffolds capable of bearing complex load distributions.

Irregular Load Adapted Scaffold Optimization: A Computational Framework Based on Mechanobiological Criteria / Rodríguez-Montaño, Óscar L.; Julio Cortés-Rodríguez, Carlos; Naddeo, Francesco; Uva, Antonio E.; Fiorentino, Michele; Naddeo, Alessandro; Cappetti, Nicola; Gattullo, Michele; Monno, Giuseppe; Boccaccio, Antonio. - In: ACS BIOMATERIALS SCIENCE & ENGINEERING. - ISSN 2373-9878. - ELETTRONICO. - 5:10(2019), pp. 5392-5411. [10.1021/acsbiomaterials.9b01023]

Irregular Load Adapted Scaffold Optimization: A Computational Framework Based on Mechanobiological Criteria

Antonio E. Uva;Michele Fiorentino;Michele Gattullo;Antonio Boccaccio
2019-01-01

Abstract

By combining load adaptive algorithms with mechanobiological algorithms, a computational framework was developed to design and optimize the microarchitecture of irregular load adapted scaffolds for bone tissue engineering. Skeletonized cancellous bone-inspired lattice structures were built including linear fibers oriented along the internal flux of forces induced by the hypothesized boundary conditions. These structures were then converted into solid finite element models, which were optimized with mechanobiology-based optimization algorithms. The design variable was the diameter of the beams included in the scaffold, while the design objective was the maximization of the fraction of the scaffold volume predicted to be occupied by neo-formed bony tissue. The performance of the designed irregular scaffolds, intended as the capability to favor the formation of bone, was compared with that of the regular ones based on different unit cell geometries. Three different boundary and loading conditions were hypothesized, and for all of them, it was found that the irregular load adapted scaffolds perform better than the regular ones. Interestingly, the numerical predictions of the proposed framework are consistent with the results of experimental studies reported in the literature. The proposed framework appears to be a powerful tool that can be utilized to design high-performance irregular load adapted scaffolds capable of bearing complex load distributions.
2019
Irregular Load Adapted Scaffold Optimization: A Computational Framework Based on Mechanobiological Criteria / Rodríguez-Montaño, Óscar L.; Julio Cortés-Rodríguez, Carlos; Naddeo, Francesco; Uva, Antonio E.; Fiorentino, Michele; Naddeo, Alessandro; Cappetti, Nicola; Gattullo, Michele; Monno, Giuseppe; Boccaccio, Antonio. - In: ACS BIOMATERIALS SCIENCE & ENGINEERING. - ISSN 2373-9878. - ELETTRONICO. - 5:10(2019), pp. 5392-5411. [10.1021/acsbiomaterials.9b01023]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/206662
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