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In silico evaluation of lattice designs for additively manufactured total hip implants

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Izri, Zineddine
Bijanzad, Armin

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Additive manufacturing restructures the fabrication of custom medical implants and transforms the design, topology optimization, and material selection perspectives in biomechanical applications. Additionally, it facilitated the design and fabrication of patient-oriented hip implants. Selection of proper lattice type is critical in additive manufacturing of hip implants. The lattice types reduce the implant mass and, due to higher stress distribution and deformations as compared to the rigid implants, it brings down the stress shielding issues. This study introduces a rigid shell structure and infill lattice hip implant.Additionally, the effect of various lattice unit cell thickness (0.2-1 mm) and elemental size (2.5-5 mm) while applying 2300 N axial force is explored numerically. A cubic structure with two rigid surfaces on the top and bottom is outlined to separate the effect of the hip implant cross-sectional area variations. The stress distribution and deformation characteristics are validated with the hip implant design. The Finite Element Analysis (FEA) demonstrated that the Weaire-Phelan lattice structure exhibits the least stress and deformation among the other types at various design parameters. Additionally, the same methodology is applied to three biocompatible hip implant materials as Ti-6Al-4V, TA15 (Ti-6Al-2Zr-1Mo-1V), and CoCr28Mo6. Finally, the effect of the unit cell thickness and size on the implant's mass reduction considering the lattice's safety factor is investigated for the mentioned materials. The selection of a Weaire-Phelan lattice with the optimized safety factor and mass reduction is represented considering all the results. The optimized parameters for Titanium-based alloys are approximately 3.5 mm unit cell size with 0.6 mm beam thickness. However, the CoCr Mo-based alloy requires a thicker beam size (about 0.8 mm) due to lower safety factors.

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Elsevier

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Biology, Computer science, Interdisciplinary applications, Engineering, biomedical, Mathematical and computational biology

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Computers in Biology and Medicine

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10.1016/j.compbiomed.2022.105353

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