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
Implantation of allograft bone is an integral part of revision surgery of the hip. One major concern with its use is the risk of transmission of infective agents. There are a number of methods of processing allograft bone in order to reduce this risk. One method requires washing the tissue using pulsed irrigation immediately before implantation. We report the incidence of deep bacterial infection in 138 patients (144 revision hip arthroplasties) who had undergone implantation of allograft bone. The bone used was fresh-frozen, non-irradiated and pulse-washed with normal saline before implantation. The deep infection rate at a minimum follow-up of one year was 0.7%. This method of processing appears to be associated with a very low risk of allograft-related bacterial infection.
