PRESENTING A NEW MESH-FREE APPROACH TO CT-BASED BONE SIMULATION WITH CASE STUDY OF 3D-PRINTED TIBIAL TRAY INSERTION

This case study demonstrates the use of a particle-based bone model to explore the risk of fracture and high bone strains experienced during implantation by impaction of a cementless 3D printed knee implant. The objective was to determine the sensitivity to fracture strains of nine implant press-fit design factors, each at three levels of intensity, under realistic repeated impact conditions to simulate multiple hammer blows by a surgeon, until the implant was fully seated in a prepared medial tibial condyle cadaveric model with heterogeneous bone mineral density distribution derived from a CT scan. This study was designed using a Taguchi method orthogonal array to test twenty-seven design variants and was performed using Alfonso particle-based modeling and simulations. The simulation parameters allowed the model to be sensitive to crack formation such that the influence of the implant press-fit design factors could be analyzed. To quantify the differences in performance between designs, the percentage of failed bone particles in multiple regions of interest were recorded during each simulated test. Trends that were observed included a tendency for cortical bone cracks to form during impaction with greater keel length. Using an unpaired Student's t-test, we found a statistically significant relationship between the bone failure ratio in the Anterolateral region and cortical bone cracking (p=0.04). This suggests that designs that reduce bone failure in the Anterolateral region may result in fewer cortical bone cracks during impaction.

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Publication Details

Journal
Orthopaedic Proceedings
Published
2025-09-29
DOI
https://doi.org/10.1302/1358-992x.2025.8.053
Primary Topic
Anatomy and Medical Technology
Type
article
Field-Weighted Citation Impact
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article

PRESENTING A NEW MESH-FREE APPROACH TO CT-BASED BONE SIMULATION WITH CASE STUDY OF 3D-PRINTED TIBIAL TRAY INSERTION

Sloan Kulper, Christian Fang, Jennifer C. Stoddart, Maxwell J. Munford et al.
Orthopaedic Proceedings
Anatomy and Medical Technology
article

PRESENTING A NEW MESH-FREE APPROACH TO CT-BASED BONE SIMULATION WITH CASE STUDY OF 3D-PRINTED TIBIAL TRAY INSERTION

Sloan Kulper, Christian Fang, Jennifer C. Stoddart, Maxwell J. Munford, Jonathan R.T. Jeffers, Erica Ueda, Katie Whiffin
article en

Abstract

This case study demonstrates the use of a particle-based bone model to explore the risk of fracture and high bone strains experienced during implantation by impaction of a cementless 3D printed knee implant. The objective was to determine the sensitivity to fracture strains of nine implant press-fit design factors, each at three levels of intensity, under realistic repeated impact conditions to simulate multiple hammer blows by a surgeon, until the implant was fully seated in a prepared medial tibial condyle cadaveric model with heterogeneous bone mineral density distribution derived from a CT scan. This study was designed using a Taguchi method orthogonal array to test twenty-seven design variants and was performed using Alfonso particle-based modeling and simulations. The simulation parameters allowed the model to be sensitive to crack formation such that the influence of the implant press-fit design factors could be analyzed. To quantify the differences in performance between designs, the percentage of failed bone particles in multiple regions of interest were recorded during each simulated test. Trends that were observed included a tendency for cortical bone cracks to form during impaction with greater keel length. Using an unpaired Student's t-test, we found a statistically significant relationship between the bone failure ratio in the Anterolateral region and cortical bone cracking (p=0.04). This suggests that designs that reduce bone failure in the Anterolateral region may result in fewer cortical bone cracks during impaction.

Orthopaedic ProceedingsVol. 107-B(SUPP_8)
Imperial College London (GB), University of Hong Kong (HK)
Openalex Percentile: Top 74%
Anatomy and Medical Technology
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