Aim. Aim of this study was to establish the first clinical results after implantation of ultrathin silver-polysiloxane-coated. 1. plates in the treatment of infected non-union of the femoral shaft. Method. As part of the REFECT study, a prospective, non-interventional analysis was conducted encompassing all patients who received internal stabilization with a silver-coated. 1. plate from 01/2023 to 09/2024 as part of the treatment for infected non-union of the femur. Standardized clinical follow-ups including PROMs (WOMAC-Index, LEF-S, EQ-5D, VAS) and X-rays were performed 3, 6, 12 (and 24) months postoperatively. For comparison, a retrospective analysis of 76 patients with infected femoral non-union, who had received a stabilization with an uncoated plate in the past 10 years, was performed. Results. The mean follow-up of the 8 included patients (mean bone defect: 3.6 cm) was 9 months (as of 04/24). Multiresistant bacteria were found in the intraoperative samples of 5 patients. The concentration of silver ions in blood serum reached a maximum of 0.014 mg/l in the laboratory controls. All patients showed a positive healing process with no sign of re-infection and no adverse procedure-associated events. Full weight bearing was achieved after an average of 4 months (n=6) with improved WOMAC-, LEF-S-, EQ-5D and VAS-score at 1-year FU. In the reference group (uncoated, mean FU: 3.5 years), there was a re-infection rate of 25 %, mostly in the first 2 years. Difficult-to-treat bacteria were detected in 22%, multiresistant Staph. epidermidis in 28% of cases. Conclusions. -. The silver-coated. 1. implants showed good biocompatibility with no evidence of procedure-associated complications. -. The use of silver-coated. 1. implants could reduce the risk of re-infection. -. Further clinical data with longer follow-up are needed to assess the long-term value of the procedure

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

Introduction. Knee arthroplasty (KA), encompassing Total Knee Replacement (TKR) and Unicompartmental Knee Replacement (UKR), is one of the most common orthopedic procedures, aimed at alleviating severe knee arthritis. Postoperative KA management, especially radiographic imaging, remains a substantial financial burden and lacks standardised protocols for its clinical utility during follow-up. Method. In this retrospective multicentre cohort study, data were analysed from January 2014 to March 2020 for adult patients undergoing primary KA at Imperial NHS Trust. Patients were followed over a five-year period. Four machine learning models were developed to evaluate if post-operative X-ray frequency can predict revision surgery. The best-performing model was used to assess the risk of revision surgery associated with different number of X-rays. Result. The study assessed 289 knees with a 2.4% revision rate. The revision group had more X-rays on average than the primary group. The best performing model was Logistic Regression (LR), which indicated that each additional X-ray raised the revision risk by 52% (p<0.001). Notably, having four or more X-rays was linked to a three-fold increase in risk of revision (OR=3.02; p<0.001). Our results align with the literature that immediate post-operative X-rays have limited utility, making the 2nd post-operative X-ray of highest importance in understanding the patient's trajectory. These insights can enhance management by improving risk stratification for patients at higher revision surgery risk. Despite LR being the best-performing model, it is limited by the dataset's significant class imbalance. Conclusion. X-ray frequency can independently predict revision surgery. This study provides insights that can guide surgeons in evidence-based post-operative decision-making. To use those findings and influence post-operative management, future studies should build on this predictive model by incorporating a more robust dataset, surgical indications, and X-ray findings. This will allow early identification of high-risk patients, allowing for personalised post-operative recommendations

Introduction. Shoulder arthroplasty (SA) has been performed with different types of implants, each requiring different replacement systems. However, data on previously utilized implant types are not always available before revision surgery, which is paramount to determining the appropriate equipment and procedure. Therefore, this meta-analysis aimed to evaluate the accuracy of the AI models in classifying SA implant types. Methods. This systematic review was conducted in Pubmed, Embase, SCOPUS, and Web of Science from inception to December 2023, according to PRISMA guidelines. Peer-reviewed research evaluating the accuracy of AI-based tools on upper-limb X-rays for recognizing and categorizing SA implants was included. In addition to the overall meta-analysis, subgroup analysis was performed according to the type of AI model applied (CNN (Convolutional neural network), non-CNN, or Combination of both) and the similarity of utilized datasets between studies. Results. 13 articles were eligible for inclusion in this meta-analysis (including 138 different tests assessing models’ efficacy). Our meta-analysis demonstrated an overall sensitivity and specificity of 0.891 (95% CI:0.866-0.912) and 0.549 (95% CI:0.532,0.566) for classifying implants in SA, respectively. The results of our subgroup analyses were as follows: CNN-subgroup: a sensitivity of 0.898 (95% CI:0.873-0.919) and a specificity of 0.554 (95% CI:0.537,0.570), Non-CNN subgroup: a sensitivity of 0.809 (95% CI:0.665-0.900) and specificity of 0.522 (95% CI:0.440,0.603), combined subgroup: a sensitivity of 0.891 (95% CI:0.752-0.957) and a specificity of 0.547 (95% CI:0.463,0.629). Studies using the same dataset demonstrated an overall sensitivity and specificity of 0.881 (95% CI:0.856-0.903) and 0.542 (95% CI:0.53,0.554), respectively. Studies that used other datasets showed an overall sensitivity and specificity of 0.995 (95% CI:969,0.999) and 0.678 (95% CI:0.234, 0.936), respectively. Conclusion. AI-based classification of shoulder implant types can be considered a sensitive method. Our study showed the potential role of using CNN-based models and different datasets to enhance accuracy, which could be investigated in future studies

Introduction. Inaccurate identification of implants on X-rays may lead to prolonged surgical duration as well as increased complexity and costs during implant removal. Deep learning models may help to address this problem, although they typically require large datasets to effectively train models in detecting and classifying objects, e.g. implants. This can limit applicability for instances when only smaller datasets are available. Transfer learning can be used to overcome this limitation by leveraging large, publicly available datasets to pre-train detection and classification models. The aim of this study was to assess the effectiveness of deep learning models in implant localisation and classification on a lower limb X-ray dataset. Method. Firstly, detection models were evaluated on their ability to localise four categories of implants, e.g. plates, screws, pins, and intramedullary nails. Detection models (Faster R-CNN, YOLOv5, EfficientDet) were pre-trained on the large, freely available COCO dataset (330000 images). Secondly, classification models (DenseNet121, Inception V3, ResNet18, ResNet101) were evaluated on their ability to classify five types of intramedullary nails. Localisation and classification accuracy were evaluated on a smaller image dataset (204 images). Result. The YOLOv5s model showed the best capacity to detect and distinguish between different types of implants (accuracy: plate=82.1%, screw=72.3%, intramedullary nail=86.9%, pin=79.9%). Screw implants were the most difficult implant to detect, likely due to overlapping screw implants visible in the image dataset. The DenseNet121 classification model showed the best performance in classifying different types of intramedullary nails (accuracy=73.7%). Therefore, a deep learning model pipeline with the YOLOv5s and DenseNet121 was proposed for the most optimal performance of automating implants localisation and classification for a relatively small dataset. Conclusion. These findings support the potential of deep learning techniques in enhancing implant detection accuracy. With further development, AI-based implant identification may benefit patients, surgeons and hospitals through improved surgical planning and efficient use of theatre time

Increasing the accuracy of information provided through X-Rays maximises pre-operative planning. Aim of this project is to determine the necessity of calibration probes that would improve the accuracy of pre-operative templating. This is a retrospective study involving leg length and pelvis X-Rays performed across the NHS Lanarkshire from 01/03/2023 until 31/04/2024. A total of 87 leg length X-Rays were identified, 18 had a calibration probe present. Leg length was measured on each and the X-Rays were calibrated against the existing probe. In 66.7% of cases there was a major leg length discrepancy of over 2cm between the pre-calibrated and post-calibrated X-Rays. Pelvic X-Rays of 80 patients that underwent total hip replacement were reviewed. Preoperative templating was compared to the implants inserted. An average of 1.94 discrepancy in the size of the acetabular implant was identified whilst in 30 cases the size of the femoral stem was incorrect by at least 1 size. Magnification of 119.7% on X-Rays was found to provide the most accurate templating. Seventy seven cases of pelvic X-Rays before and after hip hemiarthroplasty were also reviewed. The implant head was templated incorrectly in 74% of cases and the stem in 51%. It was identified that pelvic X-Ray magnification of 121.7% would provide the most accurate results. X-Rays with no calibration probes provide inaccurate measurements leading to faulty preoperative planning. Standardised use of a calibration sphere is strongly suggested and whenever that is not available, we suggest magnification of 121%

Hip precautions following total hip arthroplasty (THA) limits flexion, adduction and internal rotation, yet these precautions cause unnecessary psychological stress. This study aims to assess bony and implant impingement using virtual models from actual patient's bony morphology and spinopelvic parameters to deduce whether hip precautions are necessary with precise implant positioning in the Asian population. Individualized sitting and standing sacral slope data of robotic THAs performed at two tertiary referral centers in Hong Kong was inputted into the simulation system based on patients’ pre-operative sitting and standing lumbar spine X-rays. Three-dimensional dynamic models were reconstructed using the Stryker Mako THA 4.0 software to assess bony and implant impingement both anteriorly and posteriorly, with default cup placement at 40° inclination and 20° anteversion. Femoral anteversion followed individual patient's native version. A 36mm hip ball was chosen for all cups equal or above 48mm and 32mm for those below. Anterior impingement was assessed by hip flexion and posterior impingement was assessed by hip extension. 113 patients were included. At neutral rotation and adduction, no patients had anterior implant impingement at hip flexion of 100°. 1.7% had impingement at 110°, 3.5% had impingement at 120°, 9.7% had impingement at 130°. With 20° of internal rotation and adduction, 0.8% had anterior implant impingement at hip flexion of 90°, 7.1% had impingement at 100° and 18.5% had impingement at 110°. With the hip externally rotated by 20°, 0.8% of patients had posterior implant impingement, and 8.8% bony impingement at 0° extension. With enabling technology allowing accurate component positioning, hip precautions without limiting forward flexion in neutral position is safe given precise implant positioning and adequate osteophyte removal. Patients should only be cautioned about combined internal rotation, adduction with flexion

Short stems have been developed to conserve bone stock, especially in younger populations undergoing a total hip arthroplasty (THA), and showed similar functional outcomes compared to conventional stems. Recent literature suggested that stem length might be an independent risk factor for acute periprosthetic femoral fracture in direct anterior THA (1) or with different short stem designs (2). The purpose of the present study was to compare the incidence of acute periprosthetic femoral fractures, between stems of the same manufacture (Taperloc microplasty vs Taperloc complete), which have the same stem characteristics, except for the stem length which is 35 mm shorter in Taperloc microplasty during posterior and lateral THA. Our institution's arthroplasty database was searched for all primary total hip arthroplasties utilizing short femoral stems performed between August 2016 and August 2023. Pre-operative X-rays for each case were analysed to characterize the proximal femoral geometry, specifically the canal bone ratio (CBR) and canal flare index (CFI). Data analysis was performed to identify risk factors for periprosthetic fractures. For the time period assessed, 2107 femoral stems (Taperloc Microplasty:1727, Taperloc complete: 380) were implanted. Females constituted 53% of the cohort. The average patient age was 70±11 years. The periprosthetic fracture rate was 0.94%, with 20 periprosthetic fractures (Taperloc Microplasty:17, Taperloc complete: 3) excluding 2 greater trochanteric fractures (1 at each group), identified at follow-up of three months. There was no significant difference between the periprosthetic fracture rates between the two stems (0.98% vs 0.79%, p>0.72) The multivariate regression analysis demonstrated that the stem length, CBR, CFI, age, and gender were not risk factors for periprosthetic fracture. The present study demonstrated that both Taperloc Microplasty and Taperloc complete stems had similar rates of periprosthetic fractures, and the stem length was not a risk factor for a periprosthetic fracture during uncemented THA. 1. Tamaki T, Cementless Tapered-Wedge Stem Length Affects the Risk of Periprosthetic Femoral Fractures in Direct Anterior Total Hip Arthroplasty. J Arthroplasty. 2018 Mar;33(3):805-809. 2. Staunton P. Acute Periprosthetic Hip Fracture with Short Uncemented Femoral Stems. J Arthroplasty 2024 accepted

Introduction. Cheilectomy is a recommended procedure for the earlier stages of osteoarthritis of the 1. st. metatarsophalangeal joint. Although good improvement in symptoms have been reported in many studies, the long term performance of this procedure is not well understood. It is thought that a significant number of patients go onto have arthrodesis or joint replacement. We report on a large cohort of patients who received this procedure and report on the complications and mid-term outcome. Methods. This is a retrospective study looking at all patients who underwent cheilectomy for hallux rigidus between November 2007 and August 2018. Departmental database was used to access patient details and outcome measures recorded include: postoperative wound infection, patient reported improvement in pain and the incidence of further surgical interventions like revision cheilectomy and conversion to arthrodesis and arthroplasty. X-rays were studied using PACS to stage the osteoarthritis (Hattrup and Johnson classification). Results. A total of 240 feet in 220 patients (20 bilateral surgeries) were included in the study, there were 164 Females (75%) and 56 Males (25%), the median age was 55 years (range 22–90 years). Radiological assessment showed 89 Stage 1 arthritis(42%), 105 Stage 2 (50%), 17 Stage 3 (8%) and 9 patients were excluded due to unavailable X-rays. 5 patients (2%) had superficial wound infection. There were 16 further surgeries (7%) performed in this cohort, 12 arthrodesis (5%), 3 revision cheilectomy and 1conversion to arthroplasty. 157 patients were found to be pain-free at the latest post-operative visit (77%), 48 reported minimal pain (23%), 15 patients were excluded due to unavailable data. Conclusion. Cheilectomy appears to produce good improvement in pain with a low complication rate. The rate of conversion to arthrodesis/arthroplasty is lower than in many reported studies

INTRODUCTION. Simulation plays an important role in surgical education and the ability to perfect surgical performance. Simulation can be enhanced by adding various layers of realism to the experience. Haptic feedback enhances the simulation experience by providing tactile responses and virtual reality imagery provides an immersive experience and allows for greater appreciation of three-dimensional structures. In this study, we present a proof-of-concept haptic simulator to replicate key steps of a cervical laminoplasty procedure. The technology uses affordable components and is easily modifiable so that it can be used from novice through to expert level. Custom models can be easily added ensuring the simulator can be used in a wide range of orthopaedic applications from baseline education through to day of surgery pre-operative simulation. METHOD. We used the Unity Game Engine, the 3D Systems “Touch” Haptic Feedback Device (HFD), and a Meta Quest VR headset. Our system uses a number of complex algorithms to track the shape and provide haptic feedback of a virtual bone model. This allows for simulation of various tools including a high-speed burr, Kerrison rongeur and intraoperative X-rays. RESULTS. Our simulator replicates the tactile sensations of bone-burring tasks. Although we focused on the cervical laminoplasty procedure, the system can load data from CT scans, enabling the simulation of multiple other procedures. The parts cost of our system, $10,000 NZD, is a fraction of the cost of traditional surgical simulators. DISCUSSION. Our simulator reduces financial barriers to accessing orthopaedic simulators. Trainees can perform hands-on practice without compromising patient safety. The immersive nature of VR, combined with realistic haptic feedback, enables trainees to develop the dexterity and three-dimensional understanding of detailed bony work. Further refinements are needed before we can perform validation studies on our system. CONCLUSIONS. We present an affordable surgical simulator capable of simulating bony surgical procedures in a VR environment using haptic feedback technology and consumer-grade components. ACKNOWLEDGEMENTS. This research was made possible by the generosity of the Wishbone Trust

Introduction. AlloStem/Cellular Bone Allograft and autologous bone graft are accepted methods for managing hindfoot degenerative arthritis. The purpose was to evaluate outcomes of AlloStem and autograft in subtalar arthrodesis and compare overall fusion rates. Methods. This study was conducted in IRB compliance. Patients between 18–80 years who qualified for a subtalar fusion were randomized 1:1 to AlloStem or autologous graft. The AOFAS hindfoot ankle scale, FFI-R and SF-12 were collected pre-operatively, 6 weeks, 3 & 6 months, 1 and 2 year. Weight-bearing 3-view ankle X-rays were done at the same intervals. A CT scan was obtained at 6 months. Results. 140 patients were enrolled; 124 patients had surgery(60-AlloStem and 64-Control). Withdrawals included 14 voluntarily before surgery and 2 intra-operative failures. 19 were lost to follow-up. Mean age for AlloStem was 56.69(20.3–79.6) and Autograft was 54.60(20.74–80.07). 59 AlloStem patients completed their 6 month visit and 45 completed 2 years. AOFAS score improved: 40.02 at pre-op to 72.16(6 mo) to 79.51 at 1 year and 80.38 at 2 year. SF-12 improved 58.29 at pre-op to 65.67 at 6 month and 71.59 at 2 year. FFI-R improved 236.88 at pre-op to 203.53 at 6 month 149.93 at 2 year.60 Autograft patients completed their 6 month visit and 51 patients completed their 2 year. AOFAS score improved 42.89 at pre-op to 75.67 (6 mo) to 79.75 at 1 year and 78.62 at 2 year. Autograft SF-12 improved 60.55 at pre-op to 70.40 at 6 month and 75.26 at 2 year. Autograft FFI-R improved 217.16 at pre-op to 166.77 at 6 month and 145.43 at 2 year. AlloStem patients had a mean posterior fusion rate of 28.9% at 6 months whereas the Autograft had 46.3%(p=.049). Non-union rates were AlloStem(9/57)(15.7%) whereas Autograft was 3/60(5%). Conclusion. AlloStem trended to be inferior to Autologous graft

Introduction. Frame HI is the #Days for device removal/cm. IM Nail HI is less relevant (31–45 D/cm). Albizzia HI was 33 D/cm (1991–2003). Patients felt fine approximately 1M after end of lengthening (EoL), resuming normal life and sports. This sometimes resulted in implants fractures (e.g. skying before bone fusion). Ideally, the full fusion should occur at the EoL. We decided to shorten the HI to reach this target, optimising all parameters. Materials & Methods. The evolution of care has been monitored over a 32-year clinical experience with a fully weight-bearing nails (Albizzia then G-nail). Monitoring was with X-rays, DEXA, blood bone activity, and in London with special 5G CBCT Scans. We implemented several changes in the Care of patients and measured them according to the ‘Five Principles’ (stability, function, ‘Roads-vascular supply’, ‘Materials-calories’ and ‘Workers-BFC’, with actions on food intake, activity levels and on muscle and bone vascular growths. Results. Preop: training (vascularity, muscle force). Op & Postop: spine morphine, IM sawing preserving BFC, controlled hypo-pressure, low hydration, 50 cm leg elevation, walking, resistance bike, full motion (drainage, muscle reactivation), discharge 3–4h postop (including bilateral). Postop daily intense gym training. POD07-21: Distraction increased to fight non-linear hyper-ossification (44–50 mm gain at POD30) +/- aided by NSAIDs. HI decreased to 12–20D/cm, sometimes 8D/cm with some ‘soft fusion’ during lengthening, hardening within 1W after EoL. Conclusions. The surgeon is not a passive X-rays observer, but has an active role in changing the healing speed and decreasing HI for patient safety. Electro/Magnetic nails (torque 1 Nm) may be clocked by bone fusion, which does not occur with the G-Nail (19 Nm). An holistic vision for patients and treatments at several levels is essential to accelerate bone healing, and to return fast to full normal life, after a short ‘lengthening parenthesis’

Aims

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.

Aims

While internet search engines have been the primary information source for patients’ questions, artificial intelligence large language models like ChatGPT are trending towards becoming the new primary source. The purpose of this study was to determine if ChatGPT can answer patient questions about total hip (THA) and knee arthroplasty (TKA) with consistent accuracy, comprehensiveness, and easy readability.

Aims

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.

Aims

Distal femoral resection in conventional total knee arthroplasty (TKA) utilizes an intramedullary guide to determine coronal alignment, commonly planned for 5° of valgus. However, a standard 5° resection angle may contribute to malalignment in patients with variability in the femoral anatomical and mechanical axis angle. The purpose of the study was to leverage deep learning (DL) to measure the femoral mechanical-anatomical axis angle (FMAA) in a heterogeneous cohort.

In absence of available quantitative measures, the assessment of fracture healing based on clinical examination and X-rays remains a subjective matter. Lacking reliable information on the state of healing, rehabilitation is hardly individualized and mostly follows non evidence-based protocols building on common guidelines and personal experience. Measurement of fracture stiffness has been demonstrated as a valid outcome measure for the maturity of the repair tissue but so far has not found its way to clinical application outside the research space. However, with the recent technological advancements and trends towards digital health care, this seems about to change with new generations of instrumented implants – often unfortunately termed “smart implants” – being developed as medical devices. The AO Fracture Monitor is a novel, active, implantable sensor system designed to provide an objective measure for the assessment of fracture healing progression (1). It consists of an implantable sensor that is attached to conventional locking plates and continuously measures implant load during physiological weight bearing. Data is recorded and processed in real-time on the implant, from where it is wirelessly transmitted to a cloud application via the patient's smartphone. Thus, the system allows for timely, remote and X-ray free provision of feedback upon the mechanical competence of the repair tissue to support therapeutic decision making and individualized aftercare. The device has been developed according to medical device standards and underwent extensive verification and validation, including an in-vivo study in an ovine tibial osteotomy model, that confirmed the device's capability to depict the course of fracture healing as well as its long-term technical performance. Currently a multi-center clinical investigation is underway to demonstrate clinical safety of the novel implant system. Rendering the progression of bone fracture healing assessable, the AO Fracture Monitor carries potential to enhance today's postoperative care of fracture patients

Freehand distal interlocking of intramedullary nails remains a challenging task. If not performed correctly it can be a time consuming and radiation expensive procedure. Recently, the AO Research Institute developed a new training device for Digitally Enhanced Hands-on Surgical Training (DEHST) that features practical skills training augmented with digital technologies, potentially improving surgical skills needed for distal interlocking. Aim of the study: To evaluate weather training with DEHST enhances the performance of novices without surgical experience in free-hand distal nail interlocking compared to a non-trained group of novices. 20 novices were assigned in two groups and performed distal interlocking of a tibia nail in an artificial bone model. Group 1: DEHST trained novices (virtual locking of five nail holes during one hour of training). Group 2: untrained novices without DEHST training. Time, number of x-rays, nail hole roundness, critical events and success rates were compared between the groups. Time to complete the task (sec.) and x-ray exposure (µGcm2) were significantly lower in Group1 414.7 (290–615) and 17.8 (9.8–26.4) compared to Group2 623.4 (339–1215) and 32.6 (16.1–55.3); p=0.041 and 0.003. Perfect circle roundness (%) was 95.0 (91.1–98.0) in Group 1 and 80.8 (70.1–88.9) in Group 2; p<0.001. In Group 1 90% of the participants achieved successful completion of the task (hit the nail with the drill), whereas only 60% of the participants in group 2 achieved this; p=0.121. Training with DEHST significantly enhances the performance of novices without surgical experience in distal interlocking of intramedullary nails. Besides radiation exposure and operation time the com-plication rate during the operation can be significantly reduced

Title. Longitudinal Intravital Imaging to Quantify the “Race for the Surface” Between Host Immune Cell and Bacteria for Orthopaedic Implants with S. aureus Colonization in a Murine Model. Aim. To assess S. aureus vs. host cell colonization of contaminated implants vis intravital multiphoton laser scanning microscopy (IV-MLSM) in a murine model. Method. All animal experiments were approved by IACUC. A flat stainless steel or titanium L-shaped pin was contaminated with 10. 5. CFU of a red fluorescent protein (RFP) expressing strain of USA300LAC, and surgically implanted through the femur of global GFP-transgenic mice. IV-MLSM was performed at 2, 4, and 6 hours post-op. Parallel cross-sectional CFU studies were performed to quantify the bacteria load on the implant at 2,4,6,12,18 and 24 hours. Results. 1) We developed a high-fidelity reproducible IV-MLSM system to quantify S. aureus and host cell colonization of a bone implant in the mouse femur. Proper placement of all implants were confirmed with in vivo X-rays, and ex vivo photos. We empirically derive the ROI during each imaging session by aggregating the imaged volume which ranges from (636.4um × 636.4um × 151um) = 0.625 +/- 0.014 mm. 3. of bone marrow in a global GFP-transgenic mouse. 2) IV-MLSM imaging acquisition of the “race for the surface”.In vitro MPLSM images of implants partially coated with USA300LAC (RFP-MRSA) were verified by SEM image. Results from IV-MLSM of RFP-MRSA and GFP. +. host cell colonization of the contaminated implants illustrated the mutually exclusive surface coating at 3hrs, which to our knowledge is the first demonstration of “the race for the surface” between bacteria and host cells via intravital microscopy. 3) Quantifying the “race for the surface” with CFU verification of S. aureus on the implant. 3D volumetric rendering of the GFP. +. voxels and RFP+ voxels within the ROI were generated in Imaris. The voxel numbers suggeste that the fight for the surface concludes ∼3hrs post-infection, and then transitions to an aggressive MRSA proliferation phase. The results of WT control demonstrate a significant increase in CFU by 12hrs post-op for both stainless steel (P<0.01) and titanium (P<0.01). Conclusions. We developed IV-MLSM to quantify the “Race for the Surface” between host cells and contaminating S. aureus in a murine femur implant model. This race is remarkably fast, as the implant surface is completely covered with 3hrs, peak bacterial growth on the implant occurs between 2 and 12 hours and is complete by 12hrs

Abstract. Approximately 20% of primary and revision Total Knee Arthroplasty (TKA) patients require multiple revisions, which are associated with poor survivorship, with worsening outcomes for subsequent revisions. For revision surgery, either endoprosthetic replacements or metaphyseal sleeves can be used for the repair, however, in cases of severe defects that are deemed “too severe” for reconstruction, endoprosthetic replacement of the affected area is recommended. However, endoprosthetic replacements have been associated with high complication rates (high incidence rates of prosthetic joint infection), while metaphyseal sleeves have a more acceptable complication profile and are therefore preferred. Despite this, no guidance exists as to the maximal limit of bone loss, which is acceptable for the use of metaphyseal sleeves to ensure sufficient axial and rotational stability. Therefore, this study assessed the effect of increasing bone loss on the primary stability of the metaphyseal sleeve in the proximal tibia to determine the maximal bone loss that retains axial and rotational stability comparable to a no defect control. Methods. to determine the pattern of bone loss and the average defect size that corresponds to the clinically defined defect sizes of small, medium and large defects, a series of pre-operative x-rays of patients with who underwent revision TKA were retrospectively analysed. Ten tibiae sawbones were used for the experiment. To prepare the bones, the joint surface was resected the typical resection depth required during a primary TKA (10mm). Each tibia was secured distally in a metal pot with perpendicular screws to ensure rotational and axial fixation to the testing machine. Based on X-ray findings, a fine guide wire was placed 5mm below the cut joint surface in the most medial region of the plateau. Core drills (15mm, 25mm and 35mm) corresponding to small, medium and large defects were passed over the guide wire allowing to act at the centre point, before the bone defect was created. The test was carried out on a control specimen with no defect, and subsequently on a Sawbone with a small, medium or large defect. Sleeves were inserted using the published operative technique, by trained individual using standard instruments supplied by the manufacturers. Standard axial pull-out (0 – 10mm) force and torque (0 – 30°) tests were carried out, recording the force (N) vs. displacement (mm) curves. Results. A circular defect pattern was identified across all defects, with the centre of the defect located 5mm below the medial tibial base plate, and as medial as possible. Unlike with large defects, small and medium sized defects reduced the pull-out force and torque at the bone-implant interface, however, these reductions were not statistically significant when compared to no bony defect. Conclusions. This experimental study demonstrated that up to 35mm radial defects may be an acceptable “critical limit” for bone loss below which metaphyseal sleeve use may still be appropriate. Further clinical assessment may help to confirm the findings of this experimental study. This study is the first in the literature to aim to quantify “critical bone loss” limit in the tibia for revision knee arthroplasty. Declaration of Interest. (a) fully declare any financial or other potential conflict of interest