Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

One of the most important causes of failure in unicompartmental knee replacement (UKR) is polyethylene wear. The aim of this study was to develop and assess a novel Roentgen stereophotogrammetric analysis (RSA)-based method for the measurement of linear wear suitable for UKR. Model-based RSA was used to estimate the linear wear of polyethylene bearings in UKR. A phantom was used to validate the method using in vitro measured bearing thicknesses and the linear wear of ten control bearings was estimated in vivo. Computer aided design (CAD) models for the UKRs were used in the model-based RSA system. There was no statistically significant difference between the estimated and measured bearing thicknesses using the CAD models (p = 0.386). The precision of the linear wear measurement, expressed as the standard deviation of the difference between the estimated and measured bearing thickness was 0.163 mm. The bias (mean difference) was 0.030 mm. The use of RSA to measure in vivo wear in a UKR has been shown to be accurate in a phantom, and has been verified with in vivo measured controls. The technique does not require surgical implantation of marker balls and can be used retrospectively.

Original publication

DOI

10.1243/09544119JEIM812

Type

Journal article

Journal

Proc Inst Mech Eng H

Publication Date

11/2010

Volume

224

Pages

1235 - 1243

Keywords

Arthroplasty, Replacement, Knee, Computer-Aided Design, Equipment Failure Analysis, Humans, Knee, Knee Prosthesis, Materials Testing, Models, Biological, Phantoms, Imaging, Photogrammetry, Polyethylene, Radiographic Image Enhancement, Radiography