Abstract

Developing patient-specific implants has an increasing interest in the application of emerging additive manufacturing (AM) technologies. On the other hand, despite advances in total knee replacement (TKR), studies suggest that up to 20% of patients with elective TKR are dissatisfied with the outcome. By creating 3D objects from digital models, AM enables the production of patient-specific implants with complex geometries, such as those required for knee replacements. Previous studies have highlighted concerns regarding the risk of residual stresses and shape distortions in AM parts, which could lead to structural failure or other complications. This article presents a computational framework that uses CT images to create patient-specific finite element models for optimizing AM knee replacements. The workflow includes image processing in the open-source software 3DSlicer and MeshLab and AM process simulations in the commercial platform 3DEXPERIENCE. The approach is demonstrated on a distal femur replacement for a 50-year-old male patient from the open-access Natural Knee Data. The results show that build orientations have a significant impact on both shape distortions and residual stresses. Support structures have a marginal effect on residual stresses but strongly influence shape distortions, whereas conical support exhibits a maximum distortion of 18.5 mm. Future research can explore how these factors affect the functionality of AM knee replacements under in-service loading.

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