Aims

Around the world, the emergence of robotic technology has improved surgical precision and accuracy in total knee arthroplasty (TKA). This territory-wide study compares the results of various robotic TKA (R-TKA) systems with those of conventional TKA (C-TKA) and computer-navigated TKA (N-TKA).

Aims. The aims of this study were to develop an automatic system capable of calculating four radiological measurements used in the diagnosis and monitoring of cerebral palsy (CP)-related hip disease, and to demonstrate that these measurements are sufficiently accurate to be used in clinical practice. Methods. We developed a machine-learning system to automatically measure Reimer’s migration percentage (RMP), acetabular index (ACI), head shaft angle (HSA), and neck shaft angle (NSA). The system automatically locates points around the femoral head and acetabulum on pelvic radiographs, and uses these to calculate measurements. The system was evaluated on 1,650 pelvic radiographs of children with CP (682 females and 968 males, mean age 8.3 years (SD 4.5)). Each radiograph was manually measured by five clinical experts. Agreement between the manual clinical measurements and the automatic system was assessed by mean absolute deviation (MAD) from the mean manual measurement, type 1 and type 2 intraclass correlation coefficients (ICCs), and a linear mixed-effects model (LMM) for assessing bias. Results. The MAD scores were 5.7% (SD 8.5%) for RMP, 4.3° (SD 5.4°) for ACI, 5.0° (SD 5.2°) for NSA, and 5.7° (SD 6.1°) for HSA. Overall ICCs quantifying the agreement between the mean manual measurement and the automatic results were 0.91 for RMP, 0.66 for ACI, 0.85 for NSA, and 0.73 for HSA. The LMM showed no statistically significant bias. Conclusion. The results showed excellent agreement between the manual and automatic measurements for RMP, good agreement for NSA, and moderate agreement for HSA and ACI. The performance of the system is sufficient for application in clinical practice to support the assessment of hip migration based on RMP. The system has the potential to save clinicians time and to improve patient care by enabling more comprehensive, consistent, and reliable monitoring of hip migration in children with CP. Cite this article: Bone Joint J 2025;107-B(1):124–132

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.

Aims. Excellent outcomes have been reported following CT-based robotic arm-assisted total hip arthroplasty (rTHA) compared with manual THA; however, its superiority over CT-based navigation THA (nTHA) remains unclear. This study aimed to determine whether a CT-based robotic arm-assisted system helps surgeons perform accurate cup placement, minimizes leg length, and offsets discrepancies more than a CT-based navigation system. Methods. We studied 60 hips from 54 patients who underwent rTHA between April 2021 and August 2023, and 45 hips from 44 patients who underwent nTHA between January 2020 and March 2021 with the same target cup orientation at the Department of Orthopedic Surgery at Ozu Memorial Hospital, Japan. After propensity score matching, each group had 37 hips. Postoperative acetabular component position and orientation were measured using the planning module of the CT-based navigation system. Postoperative leg length and offset discrepancies were evaluated using postoperative CT in patients who have unilateral hip osteoarthritis. Results. The absolute differences in radiological inclination (RI) and radiological anteversion (RA) from the target were significantly smaller in rTHA (RI 1.2° (SD 1.2°), RA 1.4° (SD 1.2°)) than in nTHA (RI 2.7° (SD 1.9°), RA 3.0° (SD 2.6°)) (p = 0.005 for RI, p = 0.002 for RA). The absolute distance of the target’s postoperative centre of rotation was significantly smaller in the mediolateral (ML) and superoinferior (SI) directions in rTHA (ML 1.1 mm (SD 0.8), SI 1.3 mm (SD 0.5)) than in nTHA (ML 1.9 mm (SD 0.9), SI 1.6 mm (SD 0.9)) (p = 0.002 for ML, p = 0.042 for SI). Absolute leg length and absolute discrepancies in the acetabular, femoral, and global offsets were significantly lower in the rTHA group than in the nTHA group (p = 0.042, p = 0.004, p = 0.003, and p = 0.010, respectively). In addition, the percentage of hips significantly differed with an absolute global offset discrepancy of ≤ 5 mm (p < 0.001). Conclusion. rTHA is more accurate in cup orientation and position than nTHA, effectively reducing postoperative leg length and offset discrepancy. Cite this article: Bone Jt Open 2024;6(1):3–11

Aims. The aim of this study was to perform an incremental cost-utility analysis and assess the impact of differential costs and case volume on the cost-effectiveness of robotic arm-assisted medial unicompartmental knee arthroplasty (rUKA) compared to manual (mUKA). Methods. Ten-year follow-up of patients who were randomized to rUKA (n = 64) or mUKA (n = 65) was performed. Patients completed the EuroQol five-dimension health questionnaire preoperatively, at three months, and one, two, five, and ten years postoperatively, which was used to calculate quality-adjusted life years (QALY) gained and the incremental cost-effectiveness ratio (ICER). Costs for the index and additional surgery and healthcare costs were calculated. Results. mUKA had a lower survival for reintervention (84.8% (95% CI 76.2 to 93.4); p = 0.001), all-cause revision (88.9% (95% CI 81.3 to 96.5); p = 0.007) and aseptic revision (91.9% (95% CI 85.1 to 98.7); p = 0.023) when compared to the rUKA group at ten years, which was 100%. The rUKA group had a greater QALY gain per patient (mean difference 0.186; p = 0.651). Overall rUKA was the dominant intervention, being cost-saving and more effective with a greater health-related quality of life gain. On removal of infected reinterventions (n = 2), the ICER was £757 (not discounted) and £481 (discounted). When including all reintervention costs, rUKA was cost-saving when more than 100 robotic cases were performed per year. When removing the infected cases, rUKA was cost-saving when undertaking more than 800 robotic cases per year. Conclusion. rUKA had lower reintervention and revision risks at ten years, which was cost-saving and associated with a greater QALY gain, and was the dominant procedure. When removing the cost of infection, which could be a random event, rUKA was a cost-effective intervention with an ICER (£757) which was lower than the willingness-to-pay threshold (£20,000). Cite this article: Bone Joint J 2025;107-B(1):72–80

Aims

Unicompartmental knee arthroplasty (UKA) and total knee arthroplasty (TKA) have both been shown to be effective treatments for osteoarthritis (OA) of the knee. Many studies have compared the outcomes of the two treatments, but less so with the use of robotics, or individualized TKA alignment techniques. Functional alignment (FA) is a novel technique for performing a TKA and shares many principles with UKA. Our aim was to compare outcomes from a case-matched series of robotic-assisted UKAs and robotic-assisted TKAs performed using FA.

Aims

The free latissimus dorsi muscle (LDM) flap represents a workhorse procedure in the field of trauma and plastic surgery. However, only a small number of studies have examined this large group of patients with regard to the morbidity of flap harvest. The aim of this prospective study was therefore to objectively investigate the morbidity of a free LDM flap.

Aims

Better prediction of outcome after total hip arthroplasty (THA) is warranted. Systemic inflammation and central neuroinflammation are possibly involved in progression of osteoarthritis and pain. We explored whether inflammatory biomarkers in blood and cerebrospinal fluid (CSF) were associated with clinical outcome, and baseline pain or disability, 12 months after THA.

Aims

Lower limb reconstruction (LLR) has a profound impact on patients, affecting multiple areas of their lives. Many patient-reported outcome measures (PROMs) are employed to assess these impacts; however, there are concerns that they do not adequately capture all outcomes important to patients, and may lack content validity in this context. This review explored whether PROMs used with adults requiring, undergoing, or after undergoing LLR exhibited content validity and adequately captured outcomes considered relevant and important to patients.

The December 2024 Research Roundup³⁶⁰ looks at: Skeletal muscle composition, power, and mitochondrial energetics in older men and women with knee osteoarthritis; Machine-learning models to predict osteonecrosis in patients with femoral neck fractures undergoing internal fixation; Aetiology of patient dissatisfaction following primary total knee arthroplasty in the era of robotic-assisted technology; Efficacy and safety of commonly used thromboprophylaxis agents following hip and knee arthroplasty; The COVID-19 effect continues; Nickel allergy in knee arthroplasty: does self-reported sensitivity affect outcomes?; Tranexamic acid use and joint infection risk in total hip and knee arthroplasty.

Aims

Day-case knee and hip replacement, in which patients are discharged on the day of surgery, has been gaining popularity during the last two decades, and particularly since the COVID-19 pandemic. This systematic review presents the evidence comparing day-case to inpatient-stay surgery.

Periprosthetic joint infection (PJI) represents a complex challenge in orthopaedic surgery associated with substantial morbidity and healthcare expenditures. The debridement, antibiotics, and implant retention (DAIR) protocol is a viable treatment, offering several advantages over exchange arthroplasty. With the evolution of treatment strategies, considerable efforts have been directed towards enhancing the efficacy of DAIR, including the development of a phased debridement protocol for acute PJI management. This article provides an in-depth analysis of DAIR, presenting the outcomes of single-stage, two-stage, and repeated DAIR procedures. It delves into the challenges faced, including patient heterogeneity, pathogen identification, variability in surgical techniques, and antibiotics selection. Moreover, critical factors that influence the decision-making process between single- and two-stage DAIR protocols are addressed, including team composition, timing of the intervention, antibiotic regimens, and both anatomical and implant-related considerations. By providing a comprehensive overview of DAIR protocols and their clinical implications, this annotation aims to elucidate the advancements, challenges, and potential future directions in the application of DAIR for PJI management. It is intended to equip clinicians with the insights required to effectively navigate the complexities of implementing DAIR strategies, thereby facilitating informed decision-making for optimizing patient outcomes.

Cite this article: Bone Joint J 2024;106-B(12):1377–1384.

The December 2024 Foot & Ankle Roundup³⁶⁰ looks at: Tibiotalar sector and lateral ankle instability; Isolated subtalar fusion and correction of progressive collapsing foot deformity; Diabetic control and postoperative complications following ankle fracture fixation; Are insoles of any benefit for plantar fasciitis?; Postoperative foot shape and patient-reported outcome following surgery for progressing collapsing foot deformity; Calcaneo-stop procedure for symptomatic flexible flatfoot in children.

As advancements in total knee arthroplasty progress at an exciting pace, two areas are of special interest, as they directly impact implant design and surgical decision making. Knee morphometry considers the three-dimensional shape of the articulating surfaces within the knee joint, and knee phenotyping provides the ability to categorize alignment into practical groupings that can be used in both clinical and research settings. This annotation discusses the details of these concepts, and the ways in which they are helping us better understand the individual subtleties of each patient’s knee.

Cite this article: Bone Joint J 2024;106-B(12):1363–1368.

Background. The molecular mechanisms underlying non-union bone fractures largely remain elusive. Recently, spatial transcriptomics approaches for musculoskeletal tissue samples have been developed requiring direct placement of histology sections on barcoded slides. However, Formalin-Fixed-Paraffin-Embedded (FFPE) bone sections have been associated with limited RNA quality and read depth compared to soft tissue. Here, we test spatial transcriptomics workflows based on transcriptomic probe transfer to characterize molecular features discriminating non-union and union bone fractures in mice. Method. Histological sections (n=8) used for spatial transcriptomics (Visium CytAssist FFPE; 10x Genomics, n=4 on glass slides, n=4 on hydrogel-coated slides) were obtained from a fracture healing study in female 20-week-old C57BL/6J mice receiving either a femur osteotomy (0.7mm) or a segmental defect (2.4mm) (license 22/2022, Grisons CH). Sequence alignment and manual segmentation of different tissues (bone, defect region/callus, bone marrow, muscle) were performed using SpaceRanger and LoupeBrowser (10x Genomics). Differential gene expression was performed using DESeq2 (Seurat) followed by Gene-Set-Enrichment-Analysis (GSEA) of Gene Ontology (ClusterProfiler). Group comparison of quality measures was done using a Welch's t-test. Results are given as mean±standard deviation. Result. The quality measures, mean counts, and genes per spot, were significantly ~10× higher for sections on hydrogel slides (counts: 4700±1796, genes: 2389±1170) compared to glass slides (counts: 463±415, genes: 250±223). In challenging tissues like cortical bone, we reached high counts+genes in comparison to published data. Direct comparison of a non-union and union section showed a total of 432 differentially regulated genes, 538 in the defect region/callus. GSEA revealed differential regulation of pathways involved in muscle organ morphogenesis, cartilage development and endochondral ossification. Conclusions. Optimized spatial transcriptomics workflows based on transcriptomic probe transfer enable for improved read depth in musculoskeletal tissue enabling the characterization of molecular features discriminating non-union and union bone fractures. Acknowledgements. AO Foundation (AOTRAUMA), SNSF (PhD salary)

Introduction. Accurate assessment of alignment in pre-operative and post-operative knee radiographs is important for planning and evaluating knee replacement surgery. Existing methods predominantly rely on manual measurements using long-leg radiographs, which are time-consuming to perform and are prone to reliability errors. In this study, we propose a machine-learning-based approach to automatically measure anatomical varus/valgus alignment in pre-operative and post-operative standard AP knee radiographs. Method. We collected a training dataset of 816 pre-operative and 457 one-year post-operative AP knee radiographs of patients who underwent knee replacement surgery. Further, we have collected a separate distinct test dataset with both pre-operative and one-year post-operative radiographs for 376 patients. We manually outlined the distal femur and the proximal tibia/fibula with points to capture the knee joint (including implants in the post-operative images). This included point positions used to permit calculation of the anatomical tibiofemoral angle. We defined varus/valgus as negative/positive deviations from zero. Ground truth measurements were obtained from the manually placed points. We used the training dataset to develop a machine-learning-based automatic system to locate the point positions and derive the automatic measurements. Agreement between the automatic and manual measurements for the test dataset was assessed by intra-class correlation coefficient (ICC), mean absolute difference (MAD) and Bland-Altman analysis. Result. Analysing the agreement between the manual and automated measurements, ICC values were excellent pre-/post-operatively (0.96, CI: 0.94-0.96) / (0.95, CI: 0.95-0.96). Pre-/post-operative MAD values were 1.3°±1.4°SD / 0.7°±0.6°SD. The Bland-Altman analysis showed a pre-/post-operative mean difference (bias) of 0.3°±1.9°SD/-0.02°±0.9°SD, with pre-/post-operative 95% limits of agreement of ±3.7°/±1.8°, respectively. Conclusion. The developed machine-learning-based system demonstrates high accuracy and reliability in automatically measuring anatomical varus/valgus alignment in pre-operative and post-operative knee radiographs. It provides a promising approach for automating the measurement of anatomical alignment without the need for long-leg radiographs. Acknowledgements. This research was funded by the Wellcome Trust [223267/Z/21/Z]

Introduction. Three-dimensional (3D) morphological understanding of the hip joint, specifically the joint space and surrounding anatomy, including the proximal femur and the pelvis bone, is crucial for a range of orthopedic diagnoses and surgical planning. While deep learning algorithms can provide higher accuracy for segmenting bony structures, delineating hip joint space formed by cartilage layers is often left for subjective manual evaluation. This study compared the performance of two state-of-the-art 3D deep learning architectures (3D UNET and 3D UNETR) for automated segmentation of proximal femur bone, pelvis bone, and hip joint space with single and multi-class label segmentation strategies. Method. A dataset of 56 3D CT images covering the hip joint was used for the study. Two bones and hip joint space were manually segmented for training and evaluation. Deep learning models were trained and evaluated for a single-class approach for each label (proximal femur, pelvis, and the joint space) separately, and for a multi-class approach to segment all three labels simultaneously. A consistent training configuration of hyperparameters was used across all models by implementing the AdamW optimizer and Dice Loss as the primary loss function. Dice score, Root Mean Squared Error, and Mean Absolute Error were utilized as evaluation metrics. Results. Both the models performed at excellent levels for single-label segmentations in bones (dice > 0.95), but single-label joint space performance remained considerably lower (dice < 0.87). Multi-class segmentations remained at lower performance (dice < 0.88) for both models. Combining bone and joint space labels may have introduced a class imbalance problem in multi-class models, leading to lower performance. Conclusion. It is not clear if 3D UNETR provides better performance as the selection of hyperparameters was the same across the models and was not optimized. Further evaluations will be needed with baseline UNET and nnUNET modeling architectures

Introduction. The objective assessment of shoulder function is important for personalized diagnosis, therapies and evidence-based practice but has been limited by specialized equipment and dedicated movement laboratories. Advances in AI-driven computer vision (CV) using consumer RGB cameras (red-blue-green) and open-source CV models offer the potential for routine clinical use. However, key concepts, evidence, and research gaps have not yet been synthesized to drive clinical translation. This scoping review aims to map related literature. Method. Following the JBI Manual for Evidence Synthesis, a scoping review was conducted on PubMed and Scholar using search terms including “shoulder,” “pose estimation,” “camera”, and others. From 146 initial results, 27 papers focusing on clinical applicability and using consumer cameras were included. Analysis employed a Grounded Theory approach guided iterative refinement. Result. Studies primarily used Microsoft Kinect (infrared-based depth sensing, RGB camera; discontinued) or monocular consumer cameras with open-source CV-models, sometimes supplemented by LiDAR (laser-based depth sensing), wearables or markers. Technical validation studies against gold standards were scarce and too inconsistent for comparison. Larger range of motion (RoM) movements were accurately recorded, but smaller movements, rotations and scapula tracking remained challenging. For instance, one larger validation study comparing shoulder angles during arm raises to a marker-based gold-standard reported Pearson's R = 0.98 and a standard error of 2.4deg. OpenPose and Mediapipe were the most used CV-models. Recent efforts try to improve model performance by training with shoulder specific movements. Conclusion. Low-cost, routine clinical movement analysis to assess shoulder function using consumer cameras and CV seems feasible. It can provide acceptable accuracy for certain movement tasks and larger RoM. Capturing small, hidden or the entirety of shoulder movement requires improvements such as via training models with shoulder specific data or using dual cameras. Technical validation studies require methodological standardization, and clinical validation against established constructs is needed for translation into practice

Introduction. Experimental bone research often generates large amounts of histology and histomorphometry data, and the analysis of these data can be time-consuming and trivial. Machine learning offers a viable alternative to manual analysis for measuring e.g. bone volume versus total volume. The objective was to develop a neural network for image segmentation, and to assess the accuracy of this network when applied to ectopic bone formation samples compared to a ground truth. Method. Thirteen tissue slides totaling 114 megapixels of ectopic bone formation were selected for model building. Slides were split into training, validation, and test data, with the test data reserved and only used for the final model assessment. We developed a neural network resembling U-Net that takes 512×512 pixel tiles. To improve model robustness, images were augmented online during training. The network was trained for 3 days on a NVidia Tesla K80 provided by a free online learning platform against ground truth masks annotated by an experienced researcher. Result. During training, the validation accuracy improved and stabilised at approx. 95%. The test accuracy was 96.1 %. Conclusion. Most experiments using ectopic bone formation will yield an inter-observer or inter-method variance of far more than 5%, so the current approach may be a valid and feasible technique for automated image segmentation for large datasets. More data or a consensus-based ground truth may improve training stability and validation accuracy. The code and data of this project are available upon request and will be available online as part of our publication

Introduction. A long nail is often recommended for treatment of complex trochanteric fractures but requires longer surgical and fluoroscopy times. A possible solution could be a nail with an appropriate length which can be locked in a minimally invasive manner by the main aiming device. We aimed to determine if such a nail model* offers similar structural stability on biomechanical testing on artificial bone as a standard long nail when used to treat complex trochanteric fractures. Method. An artificial osteoporotic bone model was chosen. As osteosynthesis material two cephalomedullary nails (CMN) were chosen: a superior locking nail (SL-Nail) which can be implanted with a singular targeting device, and a long nail (long-nail) with distal locking using free-hand technique. AO31-A2.2 fractures were simulated in a standardized manner. The insertion of the nail was strictly in accordance with the IFU and surgical manual of the manufacturer. The nail was locked dynamically proximally and statically distally. Axial height of the construct, varus collapse, and rotational deformity directly after nail insertion were simulated. A Universal Testing Machine was used. Measurements were made with a stereo-optic tracking system. Reactive movements were recorded and evaluated in all six degrees of freedom. A comparative analysis provided information about the stability and deformation of the assemblies to be compared. Result. There was a detectable difference in the axial fracture movement resulting in narrowing of the fracture gap. The load displacement was 1.7mm higher for the SL-Nail. There was no difference in varus collapse or rotational deformity between the nail variants. Conclusion. We conclude that there are small differences which are clinically insignificant and that a superior locking nail can safely be used to manage complex trochanteric fractures. *DCN SL nail, SWEMAC, Linköping, Sweden. Funding: no funding