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
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Alcoholism is a well-known detrimental factor in fracture healing. However, the underlying mechanism of alcohol-inhibited fracture healing remains poorly understood. MicroRNA (miR) sequencing was performed on bone mesenchymal stem cells (BMSCs). The effects of alcohol and miR-19a-3p on vascularization and osteogenic differentiation were analyzed in vitro using BMSCs and human umbilical vein endothelial cells (HUVECs). An in vivo alcohol-fed mouse model of femur fracture healing was also established, and radiological and histomorphometric analyses were used to evaluate the role of miR-19a-3p. The binding of miR-19a-3p to forkhead box F2 (FOXF2) was analyzed using a luciferase reporter assay.Aims
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