Aims. Recurrent dislocation is both a cause and consequence of glenoid bone loss, and the extent of the bony defect is an indicator guiding operative intervention. Literature suggests that loss greater than 25% requires glenoid reconstruction. Measuring bone loss is controversial; studies use different methods to determine this, with no clear evidence of reproducibility. A systematic review was performed to identify existing CT-based methods of quantifying glenoid bone loss and establish their reliability and reproducibility. Methods. A Preferred Reporting Items for Systematic reviews and Meta-Analyses-compliant systematic review of conventional and grey literature was performed. Results. A total of 25 studies were initially eligible. Following screening, nine papers were included for review. Main themes identified compared 2D and 3D imaging, as well as linear- compared with area-based techniques. Heterogenous data were acquired, and therefore no meta-analysis was performed. Conclusion. No ideal CT-based method is demonstrated in the current literature, however evidence suggests that surface area methods are more reproducible and lead to fewer over-estimations of bone loss, provided the views used are standardized. A prospective imaging trial is required to provide a more definitive answer to this research question. Cite this article: Bone Jt Open 2022;3(2):114–122

Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered.

Cite this article: Bone Joint J 2022;104-B(12):1292–1303.

Aims

Biofilm-related infection is a major complication that occurs in orthopaedic surgery. Various treatments are available but efficacy to eradicate infections varies significantly. A systematic review was performed to evaluate therapeutic interventions combating biofilm-related infections on in vivo animal models.

Aims

Computer-based applications are increasingly being used by orthopaedic surgeons in their clinical practice. With the integration of technology in surgery, augmented reality (AR) may become an important tool for surgeons in the future. By superimposing a digital image on a user’s view of the physical world, this technology shows great promise in orthopaedics. The aim of this review is to investigate the current and potential uses of AR in orthopaedics.

Despite its intrinsic ability to regenerate form and function after injury, bone tissue can be challenged by a multitude of pathological conditions. While innovative approaches have helped to unravel the cascades of bone healing, this knowledge has so far not improved the clinical outcomes of bone defect treatment. Recent findings have allowed us to gain in-depth knowledge about the physiological conditions and biological principles of bone regeneration. Now it is time to transfer the lessons learned from bone healing to the challenging scenarios in defects and employ innovative technologies to enable biomaterial-based strategies for bone defect healing. This review aims to provide an overview on endogenous cascades of bone material formation and how these are transferred to new perspectives in biomaterial-driven approaches in bone regeneration.

Cite this article: T. Winkler, F. A. Sass, G. N. Duda, K. Schmidt-Bleek. A review of biomaterials in bone defect healing, remaining shortcomings and future opportunities for bone tissue engineering: The unsolved challenge. Bone Joint Res 2018;7:232–243. DOI: 10.1302/2046-3758.73.BJR-2017-0270.R1.

Aims

The success of anterior cruciate ligament reconstruction (ACLR) depends on osseointegration at the graft-tunnel interface and intra-articular ligamentization. Our aim was to conduct a systematic review of clinical and preclinical studies that evaluated biological augmentation of graft healing in ACLR.