Aims

The “2 to 10% strain rule” for fracture healing has been widely interpreted to mean that interfragmentary strain greater than 10% predisposes a fracture to nonunion. This interpretation focuses on the gap-closing strain (axial micromotion divided by gap size), ignoring the region around the gap where osteogenesis typically initiates. The aim of this study was to measure gap-closing and 3D interfragmentary strains in plated ovine osteotomies and associate local strain conditions with callus mineralization.

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Limb salvage surgery (LSS) is the primary treatment option for primary bone malignancy. It involves the removal of bone and tissue, followed by reconstruction with endoprosthetic replacements (EPRs) to prevent amputation. Trabecular metal (TM) collars have been developed to encourage bone ingrowth (osseointegration (OI)) into EPRs. The primary aim of this study was to assess whether OI occurs when TM collars are used in EPRs for tumour.

Lisfranc injuries were previously described as fracture-dislocations of the tarsometatarsal joints. With advancements in modern imaging, subtle Lisfranc injuries are now more frequently recognized, revealing that their true incidence is much higher than previously thought. Injury patterns can vary widely in severity and anatomy. Early diagnosis and treatment are essential to achieve good outcomes. The original classification systems were anatomy-based, and limited as tools for guiding treatment. The current review, using the best available evidence, instead introduces a stability-based classification system, with weightbearing radiographs and CT serving as key diagnostic tools. Stable injuries generally have good outcomes with nonoperative management, most reliably treated with immobilization and non-weightbearing for six weeks. Displaced or comminuted injuries require surgical intervention, with open reduction and internal fixation (ORIF) being the most common approach, with a consensus towards bridge plating. While ORIF generally achieves satisfactory results, its effectiveness can vary, particularly in high-energy injuries. Primary arthrodesis remains niche for the treatment of acute injuries, but may offer benefits such as lower rates of post-traumatic arthritis and hardware removal. Novel fixation techniques, including suture button fixation, aim to provide flexible stabilization, which theoretically could improve midfoot biomechanics and reduce complications. Early findings suggest promising functional outcomes, but further studies are required to validate this method compared with established techniques. Future research should focus on refining stability-based classification systems, validation of weightbearing CT, improving rehabilitation protocols, and optimizing surgical techniques for various injury patterns to ultimately enhance patient outcomes.

Cite this article: Bone Joint J 2024;106-B(12):1431–1442.

Introduction. With advances in artificial intelligence, the use of computer-aided detection and diagnosis in clinical imaging is gaining traction. Typically, very large datasets are required to train machine-learning models, potentially limiting use of this technology when only small datasets are available. This study investigated whether pretraining of fracture detection models on large, existing datasets could improve the performance of the model when locating and classifying wrist fractures in a small X-ray image dataset. This concept is termed “transfer learning”. Method. Firstly, three detection models, namely, the faster region-based convolutional neural network (faster R-CNN), you only look once version eight (YOLOv8), and RetinaNet, were pretrained using the large, freely available dataset, common objects in context (COCO) (330000 images). Secondly, these models were pretrained using an open-source wrist X-ray dataset called “Graz Paediatric Wrist Digital X-rays” (GRAZPEDWRI-DX) on a (1) fracture detection dataset (20327 images) and (2) fracture location and classification dataset (14390 images). An orthopaedic surgeon classified the small available dataset of 776 distal radius X-rays (Arbeidsgmeischaft für Osteosynthesefragen Foundation / Orthopaedic Trauma Association; AO/OTA), on which the models were tested. Result. Detection models without pre-training on the large datasets were the least precise when tested on the small distal radius dataset. The model with the best accuracy to detect and classify wrist fractures was the YOLOv8 model pretrained on the GRAZPEDWRI-DX fracture detection dataset (mean average precision at intersection over union of 50=59.7%). This model showed up to 33.6% improved detection precision compared to the same models with no pre-training. Conclusion. Optimisation of machine-learning models can be challenging when only relatively small datasets are available. The findings of this study support the potential of transfer learning from large datasets to improve model performance in smaller datasets. This is encouraging for wider application of machine-learning technology in medical imaging evaluation, including less common orthopaedic pathologies

Aims

The aim of this study was to create artificial intelligence (AI) software with the purpose of providing a second opinion to physicians to support distal radius fracture (DRF) detection, and to compare the accuracy of fracture detection of physicians with and without software support.

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The optimum type of antibiotics and their administration route for treating Gram-negative (GN) periprosthetic joint infection (PJI) remain controversial. This study aimed to determine the GN bacterial species and antibacterial resistance rates related to clinical GN-PJI, and to determine the efficacy and safety of intra-articular (IA) antibiotic injection after one-stage revision in a GN pathogen-induced PJI rat model of total knee arthroplasty.

Despite the vast quantities of published artificial intelligence (AI) algorithms that target trauma and orthopaedic applications, very few progress to inform clinical practice. One key reason for this is the lack of a clear pathway from development to deployment. In order to assist with this process, we have developed the Clinical Practice Integration of Artificial Intelligence (CPI-AI) framework – a five-stage approach to the clinical practice adoption of AI in the setting of trauma and orthopaedics, based on the IDEAL principles (https://www.ideal-collaboration.net/). Adherence to the framework would provide a robust evidence-based mechanism for developing trust in AI applications, where the underlying algorithms are unlikely to be fully understood by clinical teams.

Cite this article: Bone Joint Res 2024;13(9):507–512.

Aims. To propose a new method for evaluating paediatric radial neck fractures and improve the accuracy of fracture angulation measurement, particularly in younger children, and thereby facilitate planning treatment in this population. Methods. Clinical data of 117 children with radial neck fractures in our hospital from August 2014 to March 2023 were collected. A total of 50 children (26 males, 24 females, mean age 7.6 years (2 to 13)) met the inclusion criteria and were analyzed. Cases were excluded for the following reasons: Judet grade I and Judet grade IVb (> 85° angulation) classification; poor radiograph image quality; incomplete clinical information; sagittal plane angulation; severe displacement of the ulna fracture; and Monteggia fractures. For each patient, standard elbow anteroposterior (AP) view radiographs and corresponding CT images were acquired. On radiographs, Angle P (complementary to the angle between the long axis of the radial head and the line perpendicular to the physis), Angle S (complementary to the angle between the long axis of the radial head and the midline through the proximal radial shaft), and Angle U (between the long axis of the radial head and the straight line from the distal tip of the capitellum to the coronoid process) were identified as candidates approximating the true coronal plane angulation of radial neck fractures. On the coronal plane of the CT scan, the angulation of radial neck fractures (CTa) was measured and served as the reference standard for measurement. Inter- and intraobserver reliabilities were assessed by Kappa statistics and intraclass correlation coefficient (ICC). Results. Angle U showed the strongest correlation with CTa (p < 0.001). In the analysis of inter- and intraobserver reliability, Kappa values were significantly higher for Angles S and U compared with Angle P. ICC values were excellent among the three groups. Conclusion. Angle U on AP view was the best substitute for CTa when evaluating radial neck fractures in children. Further studies are required to validate this method. Cite this article: Bone Joint J 2024;106-B(9):964–969

Aims

Although low-intensity pulsed ultrasound (LIPUS) combined with disinfectants has been shown to effectively eliminate portions of biofilm in vitro, its efficacy in vivo remains uncertain. Our objective was to assess the antibiofilm potential and safety of LIPUS combined with 0.35% povidone-iodine (PI) in a rat debridement, antibiotics, and implant retention (DAIR) model of periprosthetic joint infection (PJI).

Aims

Isolated fractures of the ulnar diaphysis are uncommon, occurring at a rate of 0.02 to 0.04 per 1,000 cases. Despite their infrequency, these fractures commonly give rise to complications, such as nonunion, limited forearm pronation and supination, restricted elbow range of motion, radioulnar synostosis, and prolonged pain. Treatment options for this injury remain a topic of debate, with limited research available and no consensus on the optimal approach. Therefore, this trial aims to compare clinical, radiological, and functional outcomes of two treatment methods: open reduction and internal fixation (ORIF) versus nonoperative treatment in patients with isolated ulnar diaphyseal fractures.

Introduction. Major trauma during military conflicts involve heavily contaminated open fractures. Staphylococcus aureus (S. aureus) commonly causes infection within a protective biofilm. Lactoferrin (Lf), a natural milk glycoprotein, chelates iron and releases bacteria from biofilms, complimenting antibiotics. This research developed a periprosthetic biofilm infection model in rodents to test an Lf based lavage/sustained local release formulation embedded in Stimulin beads. Method. Surgery was performed on adult rats and received systemic Flucloxacillin (Flu). The craniomedial tibia was exposed, drilled, then inoculated with S. aureus biofilm. A metal pin was placed within the medullary cavity and treatments conducted. Lf in lavage solutions: The defect was subject to 2× 50 mL lavage with 4 treatment groups (saline only, Lf only, Bactisure with Lf, Bactisure with saline). Lf embedded in Stimulin beads: 4 bead types were introduced (Stimulin only, Lf only, Flu only, Lf with Flu). At day 7, rats are processed for bioluminescent and X-ray imaging, and tibial explants/pins collected for bacterial enumeration (CFU). Results. Rats without treatments established a mean infection of 2×106 CFU/tibia. 4 treatment groups with a day 0, one-off lavage demonstrated >95% reduction in bacterial load 7 days post-op, with a reduction in CFU from 1×106/tibia down to 1×104/tibia. There was no statistically significant difference between each group (p = 0.55 with one way ANOVA). The stimulin bead experiments are ongoing and complete results will be obtained in the end of July. Conclusions. This research demonstrated a clinically relevant animal model of implanted metalware that establishes infection. No additional benefit was observed with a one-off, adjuvant Lf lavage during the initial decontamination of the surgical wound, compared with saline alone, and in combination with the antiseptic Bactisure. This animal model provides the foundation for future antibiofilm therapies

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The aim of this study was to explore clinicians’ experience of a paediatric randomized controlled trial (RCT) comparing surgical reduction with non-surgical casting for displaced distal radius fractures.

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This study was designed to develop a model for predicting bone mineral density (BMD) loss of the femur after total hip arthroplasty (THA) using artificial intelligence (AI), and to identify factors that influence the prediction. Additionally, we virtually examined the efficacy of administration of bisphosphonate for cases with severe BMD loss based on the predictive model.

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The underlying natural history of suspected scaphoid fractures (SSFs) is unclear and assumed poor. There is an urgent requirement to develop the literature around SSFs to quantify the actual prevalence of intervention following SSF. Defining the risk of intervention following SSF may influence the need for widespread surveillance and screening of SSF injuries, and could influence medicolegal actions around missed scaphoid fractures.

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Occult (clinical) injuries represent 15% of all scaphoid fractures, posing significant challenges to the clinician. MRI has been suggested as the gold standard for diagnosis, but remains expensive, time-consuming, and is in high demand. Conventional management with immobilization and serial radiography typically results in multiple follow-up attendances to clinic, radiation exposure, and delays return to work. Suboptimal management can result in significant disability and, frequently, litigation.

The February 2024 Research Roundup³⁶⁰ looks at: If you use a surgical helmet, you should seal your gown-glove interface; The use of iodophor-impregnated drapes in patients with iodine-related allergies: a case series and review of the literature; Location of the ovaries in children and efficacy of gonadal shielding in hip and pelvis radiography; Prehospital tranexamic acid administration does not improve outcomes in severe trauma patients; Silver-coated distal femur megaprosthesis in chronic infections with severe bone loss: a multicentre case series.

Abstract. Objectives. Spinal disorders such as back pain incur a substantial societal and economic burden. Unfortunately, there is lack of understanding and treatment of these disorders are further impeded by the inability to assess spinal forces in vivo. The aim of this project is to address this challenge by developing and testing a novel image-driven approach that will assess the forces in an individual's spine in vivo by incorporating information acquired from multimodal imaging (magnetic resonance imaging (MRI) and biplane X-rays) in a subject-specific model. Methods. Magnetic resonance and biplane X-ray imaging are used to capture information about the anatomy, tissues, and motion of an individual's spine as they perform a range of everyday activities. This information is then utilised in a subject-specific computational model based on the finite element method to predict the forces in their spine. The project is also utilising novel machine learning algorithms and in vitro, six-axis mechanical testing on human, porcine and bovine samples to develop and test the modelling methods rigorously. Results & Discussion. MRI sequences have been identified that provide high-quality image data and information on different tissue types which will be used to predict subject-specific disc properties. In-vivo protocols to capture motion analysis, EMG muscle activity, and video X-rays of the spine have been designed with planned data collection of 15 healthy volunteers. Preliminary modelling work has evaluated potential machine learning approaches and quantified the sensitivity of the models developed to material properties. Conclusion. The development and testing of these image-driven subject-specific spine models will provide a new tool for determining forces in the spine. It will also provide new tools for measuring and modelling spine movement and quantifying the properties of the spinal tissues. Acknowledgments. Funding from the EPSRC: EP/V036602/1 (Meakin, Holsgrove & Javadi) and EP/V032275/1 (Holt & Williams). Declaration of Interest. (b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project

Aims

Accurate skeletal age and final adult height prediction methods in paediatric orthopaedics are crucial for determining optimal timing of growth-guiding interventions and minimizing complications in treatments of various conditions. This study aimed to evaluate the accuracy of final adult height predictions using the central peak height (CPH) method with long leg X-rays and four different multiplier tables.

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction.

Cite this article: Bone Joint Res 2023;12(7):447–454.