Evidence map›Paper›PMID 38433178›Full record

ArticleMedical & biological engineering & computing2024

Influence of build orientation and support structure on additive manufacturing of human knee replacements: a computational study.

Stephanie DeCarvalho, Osama Aljarrah, Zi Chen, Jun Li

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Article in Medical & biological engineering & computing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Stephanie DeCarvalhoDepartment of Mechanical Engineering, University of Massachusetts Dartmouth, 285 Old Westport Road, Dartmouth, MA, 02747, USA.
Osama AljarrahDepartment of Industrial and Manufacturing Engineering, Kettering University, 1700 University Ave, Flint, MI, 48504, USA.
Zi ChenDivision of Thoracic Surgery, Brigham & Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA, 02115, USA.
Jun LiDepartment of Mechanical Engineering, University of Massachusetts Dartmouth, 285 Old Westport Road, Dartmouth, MA, 02747, USA. jun.li@umassd.edu.ORCID http://orcid.org/0000-0003-0162-1063

Funding

National Science Foundation ACI-1548562
6 · The paper itself

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.

Indexed as

Arthroplasty, Replacement, KneeFinite Element AnalysisComputer-Aided DesignComputer SimulationHumansImaging, Three-DimensionalKnee ProsthesisMaleMiddle AgedProsthesis DesignTomography, X-Ray ComputedAdditive manufacturingFinite element simulationsKnee replacementsResidual stressShape distortion

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.