Automated design of bone-preserving, insertable, and shape-matching patient-specific acetabular components

Journal Article (2024)
Author(s)

Eric Garner (TU Delft - Biomaterials & Tissue Biomechanics)

A. Meynen (Katholieke Universiteit Leuven)

Lennart Schey (Katholieke Universiteit Leuven)

J. Wu (TU Delft - Materials and Manufacturing)

A.A. Zadpoor (TU Delft - Biomaterials & Tissue Biomechanics)

Research Group
Biomaterials & Tissue Biomechanics
DOI related publication
https://doi.org/10.1002/jor.25927
More Info
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Publication Year
2024
Language
English
Research Group
Biomaterials & Tissue Biomechanics
Issue number
11
Volume number
42
Pages (from-to)
2535-2544
Reuse Rights

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Abstract

Effective treatment of large acetabular defects remains among the most challenging aspects of revision total hip arthroplasty (THA), due to the deficiency of healthy bone stock and degradation of the support columns. Generic uncemented components, which are favored in primary THA, are often unsuitable in revision cases, where the bone-implant contact may be insufficient for fixation, without significant reaming of the limited residual bone. This study presents a computational design strategy for automatically generating patient-specific implants that simultaneously maximize the bone-implant contact area, and minimize bone reaming while ensuring insertability. These components can be manufactured using the same additive manufacturing methods as porous components and may reduce cost and operating-time, compared to existing patient-specific systems. This study compares the performance of implants generated via the proposed method to optimally fitted hemispherical implants, in terms of the achievable bone-implant contact surface, and the volume of reamed bone. Computer-simulated results based on the reconstruction of a set of 15 severe pelvic defects (Paprosky 2A-3B) suggest that the patient-specific components increase bone-implant contact by 63% (median: 63%; SD: 44%; 95% CI: 52.3%–74.0%; RMSD: 42%), and reduce the volume of reamed bone stock by 97% (median: 98%; SD: 4%; 95% CI: 95.9%–97.4%; RMSD: 3.7%).