Robotics in arthroplasty has been introduced to improve the accuracy in implant alignment and soft-tissue balance in total knee arthroplasty(TKA), thus striving to further improve upon patient satisfaction. MAKO robots are one of the most versatile systems in use for TKA. It is an image-based system utilising a preoperative CT scan for precise planning. The workflow involves preoperative planning, bone registration, intraoperative planning, robotic-arm assisted bone preparation and ligament balancing, trialling and standard implantation. This semi-active system, with its haptic guidance and augmented reality, improves the precision in bone preparation and soft-tissue balance by providing real-time feedback. In this video, we aim to demonstrate the workflow involved in robotic arm assisted TKA in the planning and execution of the individualised alignment.

Nonunion is a complication of long bone fracture treatment that leads to disability, morbidity and high costs. Early detection is difficult and treatment through external stimulation and revision surgery is often a lengthy process. Therefore, alternative diagnostic and therapeutic options are currently being explored, including the use of external and internal sensors. Apart from monitoring fracture stiffness and displacement directly at the fracture site, it would be desirable if an implant could also vary its stiffness and perform an intervention to promote healing, if needed. This could be achieved either by a predetermined protocol, by remote control, or even by processing data and triggering the intervention itself (self-regulated ‘intelligent’ or ‘smart’ implant). So-called active or smart materials like shape memory alloys (SMA) or electroactive polymers (EAP) have opened up the possibility of building active implants. For example, implants could monitor as well as stimulate the fracture site by active shortening and lengthening via SMA actuator wires. The Smart Implants 2.0-project, funded by the Werner Siemens-Foundation, aims to develop a smart and active plate for the treatment of long bone fractures. This talk will demonstrate our first SMA wire-based patented mechanisms and review the literature on what application types, forces, frequencies, force directions, durations and time-periods such active implants should ideally deliver to improve fracture healing.

Background
Unicompartmental knee arthroplasty (UKA) has significant advantages over total knee arthroplasty (TKA). However, due to its need for precise positioning and soft tissue balancing, UKA failures and revision rates may be higher than that of TKA. Robotic-assisted UKA offers more accurate implant positioning, soft tissue balancing, improved lower limb alignment, and a reduction in surgical error. There are few studies studying functional outcomes post robotic-assisted UKA. The aim of this study was to compare the functional outcomes between robotic-assisted and conventional medial UKA.

Methods
A retrospective review was done of 159 patients; 110 patients underwent conventional UKA while 49 patients underwent robotic-assisted UKA. Outcome measures included the Oxford Knee Score (OKS), Knee Society Score (KSS), and Visual Analogue Score (VAS) for pain at 3 months, 1 year and 2 years post-UKA.

Results
Pre-operative patient demographics and outcome scores were not significantly different between both groups. ROM was significantly greater in the MAKO compared to the Oxford group at 3 months (p=0.039), 1 year (0.053) and 2 years (0.001) post-operation. While OKS, KSS and VAS scores improved for both groups, there were no significant differences in the final outcome measures.
None of the patients experienced a mechanical failure, infection, or revision post-surgery. 1 patient each in the Oxford and MAKO group suffered a periprosthetic fracture.

Conclusion
Both robotic-assisted MAKO UKA and conventional Oxford UKA showed good clinical outcomes. Robotic-assisted MAKO UKA had superior ROM outcomes compared to conventional Oxford UKA up to 2 years post-surgery.

Aim of the Study was to determine the accuracy of “Hand held Robotic” UKA with respect to tibial component positioning and also to observe the static (weight bearing) and dynamic (non-weight bearing) effect on HKA alignment.
Methods: 47 consecutive patients with AMOA underwent hand held robotic UKA. The intra-operative assessment of dynamic (NWB) HKA axis with the help of trackers was done and posterior tibial slope was planned intra-operatively based on patient profile. Planned HKA axis as per the robotic feedback was compared to the one observed on postoperative alignment x rays. Accuracy of tibial component placement was noted by measuring the posterior tibial slope and varus/valgus position on postoperative radiographs.
Results: The mean age of the cohort was 62.3 (±8.3; range 45-76 yrs.) with average BMI of 30.1 (± 4.5; range 21.0-40.1) The gender distribution was M:F : 11: 36. The postoperative stay in hospital was 3.4 (±1.1; range 1-6 days). The mean pre-operative and post-operative Oxford knee scores were 25.5 (±1.2; range 24-29) and 44.3 ± 2.7; range 40-48).
Conclusion: In our study, the difference in planned and achieved posterior tibial slope was 0.5 degrees and varus/valgus deviation of the tibial component was 1.2 degree. Average correction of HKA axis noted on static WB x rays was 4.19 degrees and dynamic NWB HKA axis correction noted was 2.88 degrees.
The results indicate that the semi-autonomous hand held robotic TKA achieve the targeted alignments and implant positions without the patients undergoing the pre-surgical CT scan imaging.

The purpose of this study was to assess if a calipered kinematic alignment philosophy delivered tibio-femoral balancing in TKA performed on varus aligned knees with osteoarthritis.
This was a single-centre retrospective cohort study of 102 patients undergoing TKA using a robotic platform. Soft tissue laxity was assessed intra-operatively and the effect on predicted gaps was analysed to see if the original KA plan would deliver a balanced knee. Balance was considered achieved if tibio-femoral compartments (medial/lateral) were equal to or less than 1.5mm, or if the estimated final gap position more than 2mm from the global implant thickness (17mm). Implant positioning was modified to achieve balancing (functional alignment). Two groups were defined; the KA group considered resection depth according to the caliper method and the second group (functional alignment) considered additional soft tissue balancing in the implant positioning and bone cuts. Resection thickness and implant positioning were compared between groups. The frequency that the KA plan achieved balanced gaps in the two aforementioned states was recorded.
A KA plan delivered medial-lateral tibio-femoral compartment balancing in 67 cases (65.7%) for the extension gap and in 50 cases (49.1%) for the flexion gap. All measured bone resection depths were significantly less for the functional alignment compared to the kinematic plan.
Conclusion : A KA plan failed to deliver a balanced TKA in more than 50% of cases, especially regarding the flexion gap. Calipered kinematic alignment may not deliver a well-balanced flexion space in TKA for varus knees.

Introduction: 3D printing is a latest technique used in fracture management which helps to plan accurate surgery leading to better results than traditional management of fractures. Methods: In this study 30 patients between 18- 65 years of age having proximal tibia fractures AO type 41B and 41C were included. They were divided into two groups , 15 cases each of 3D model group and traditional surgery group. The 3D model group were assessed pre-operatively with 3D printed model and pre-operative planning was done using the model, while the traditional surgery group of patients were assessed pre-operatively with radiological assessment like X-Rays and 3D Reconstruction CT SCAN. Both groups were then subjected to standard surgical management. Operative time, blood loss, and number of intra-operative fluoroscopy were recorded. Through the follow-up, the recovery of patients were observed. Statistical Analysis: The P value was highly significant in HSS scores, operative time, blood loss and number of intra-operative fluoroscopy between 3D model group and traditional surgery group. Results: The functional outcomes of surgically treated tibial plateau fractures was assessed using HSS scores which was better in the 3D-Group than the traditional group. Operative time, blood loss, and number of intra-operative fluoroscopy was less in 3D model group than traditional group. Conclusion: This study showed that use of 3D printing pre-operatively gives better result than traditional surgery.

This study aims to describe an accessible and reproducible model of knee arthroscopy simulator for teaching and training purposes. For the elaboration of the arthroscopic camera, it was used an endoscopic camera for mobile phones and computers. The camera was inserted into a metal tube, which was coupled to a set of three 20 mm PVC hydraulic connectors to simulate the handle and sleeve of the arthroscope. The camera has a resolution of 1280 x 720 pixels and is equipped with six built-in white LED lamps, simulating and eliminating the use of an additional light source. The knee model was developed using a PVC pipe fixed on a wooden support, to which synthetic femur and tibia models were coupled. Four 3 cm diameter holes, compatible with the standard arthroscopic portals, were made in the body of the PVC pipe. The menisci were designed using modeling clay model (Corfix®) and included the anatomic shape of both menisci and the intercondylar eminence, simulating a real tibial articular surface. The clay model was the basis to produce the Thin Crystal Polyester Resin mold. Making use of the resin mold, the meniscal models were made of Silicone Rubber Type II. A functional and reproducible simulator was obtained. The simulator works properly adapted to a TV, monitor or computer, and permits to simulate diagnostic procedures, meniscectomy and meniscoplasty. In conclusion, this study demonstrates that is possible to create a low-cost and reproducible knee arthroscopy simulator.

Introduction: There is upcoming evidence of robotic arm-assisted unicompartmental knee arthroplasty (RUKA) in improving lower limb alignment, soft-tissue balance and component positioning. In our study, we aim to assess the accuracy and patient-reported outcome measures(PROMs) of RUKA. Methods: A total of 83 consecutive patients (104 knees) underwent RUKA from two surgeons at a tertiary-care centre between July-2017 and December-2019. Each patient was assessed radiologically with their respective preoperative plan for accuracy in the execution of implant positioning using scanogram and lateral knee xrays. The PROMs were assessed with the New Knee Society Score(2011) preoperatively and at a minimum two-year follow-up in the domains of symptoms, satisfaction, expectation and functional activities. Results: The accuracy of implant positioning was within 0.49 degrees from the preoperative plan. The average follow-up was 27.5 months(24-51months). At a mean of 2.4-years follow-up, there was a significant improvement in objective knee scores and the PROMs - symptoms, satisfaction and functional activities. 89.7% of patients felt their knees were “normal” to them. One knee was reported as revised and one patient had a periprosthetic fracture, which resulted in survivorship of 99.03%. Conclusion: RUKA was found to have high accuracy in implant positioning and excellent PROMs at short-term follow-up. However, further follow-up is required to determine if robotics improves implant survivorship.

Virtual Reality (VR) and Cognitive Simulation (CS) are two approaches that are becoming increasingly appreciated for their value as tools for learning orthopaedic procedures. Yet, is one of these tools more effective than the other? Answering such a question has important implications regarding which method would merit greater investment for orthopaedic education, especially considering the significant differences in cost and availability between these two techniques. In this small-sample pilot quasi-randomised study comparing VR and CS as tools in reverse shoulder arthroplasty (RSA) training, we divided 16 orthopaedic registrars into a VR group and CS group. The VR group undertook a 30-minute VR experience using PrecisionOS VR headsets, while the CS group underwent a 30-minute CS exercise. Both groups were subsequently assessed using the Objective Structured Assessment of Technical Skills (OSATS) score on their RSA performance on Sawbone models. Overall, no significant difference was found in the average OSATS scores achieved between the VR group and CS group (VR=15.0±1.25 versus CS=12.2±0.167; p=0.117). Participant ratings of the two tools in terms of usefulness, instilling procedural confidence and likelihood of future use also found no significant differences (usefulness: p=0.695; confidence: p=0.203; future utility: p>0.999). While VR technology feels more futuristic as a training tool, considering the expense of equipment, there may be value in further developing CS, especially for use in resource-deplete environments. However, both VR and CS are incredibly valuable learning assets and may have their own unique and non-mutually exclusive places within the armamentarium of orthopaedic training tools.