Total hip arthroplasty (THA) and total knee arthroplasty (TKA) are common orthopaedic procedures requiring postoperative radiographs to confirm implant positioning and identify complications. Artificial intelligence (AI)-based image analysis has the potential to automate this postoperative surveillance. The aim of this study was to prepare a scoping review to investigate how AI is being used in the analysis of radiographs following THA and TKA, and how accurate these tools are. The Embase, MEDLINE, and PubMed libraries were systematically searched to identify relevant articles. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews and Arksey and O’Malley framework were followed. Study quality was assessed using a modified Methodological Index for Non-Randomized Studies tool. AI performance was reported using either the area under the curve (AUC) or accuracy.Aims
Methods
We reviewed the outcome of 69 uncemented, custom-made,
distal femoral endoprosthetic replacements performed in 69 patients
between 1994 and 2006. There were 31 women and 38 men with a mean
age at implantation of 16.5 years (5 to 37). All procedures were
performed for primary malignant bone tumours of the distal femur.
At a mean follow-up of 124.2 months (4 to 212), 53 patients were
alive, with one patient lost to follow-up. All nine implants (13.0%)
were revised due to aseptic loosening at a mean of 52 months (8
to 91); three implants (4.3%) were revised due to fracture of the
shaft of the prosthesis and three patients (4.3%) had a peri-prosthetic
fracture.
