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The assessment of radiolucency around an implant is qualitative, poorly defined and has low agreement between clinicians. Accurate and repeatable assessment of radiolucency is essential to prevent misdiagnosis, minimize cases of unnecessary revision, and to correctly monitor and treat patients at risk of loosening and implant failure. The purpose of this study was to examine whether a semi-automated imaging algorithm could improve repeatability and enable quantitative assessment of radiolucency. Six surgeons assessed 38 radiographs of knees after unicompartmental knee arthroplasty for radiolucency, and results were compared with assessments made by the semi-automated program. Large variation was found between the surgeon results, with total agreement in only 9.4% of zones and a kappa value of 0.602; whereas the automated program had total agreement in 81.6% of zones and a kappa value of 0.802. The software had a 'fair to excellent' prediction of the presence or the absence of radiolucency, where the area under the curve of the receiver operating characteristic curves was 0.82 on average. The software predicted radiolucency equally well for cemented and cementless implants (p = 0.996). The identification of radiolucency using an automated method is feasible and these results indicate that it could aid the definition and quantification of radiolucency.

Type

Journal article

Journal

Journal of the Royal Society, Interface

Publication Date

07/2014

Volume

11

Addresses

Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, , Oxford OX3 7LD, UK.

Keywords

Knee, Humans, Image Interpretation, Computer-Assisted, Arthroplasty, Technology, Radiologic, Prostheses and Implants, Algorithms, Software