Utilisation of unicondylar knee arthroplasty (UKA) has been limited due in part to high revision rates. Only 8% of knee arthroplasty surgeries completed in England and Wales are UKAs. It is reported that the revision rate at 9 years for Total Knee Arthroplasty (TKA) was 3% compared to 12% for UKAs. In the last decade semi active robots have been developed to be used for UKA procedures. These systems allow the surgeon to plan the size and orientation of the tibial and femoral component to match the patient's specific anatomy and to optimise the balancing the soft tissue of the joint. The robotic assistive devices allow the surgeon to execute their plan accurately removing only ‘planned’ bone from the predefined area. This study investigates the accuracy of an imageless navigation system with robotic control for UKA, reporting the errors between the ‘planned’ limb and component alignment with the post-operative limb and component alignment using weight bearing long leg radiographs. We prospectively collected radiographic data on 92 patients who received medial UKA using an imageless robotic assisted device across 4 centres (4 surgeons). This system is CT free, so relies on accurate registration of intra-operative knee kinematic and anatomic landmarks to determine the mechanical and rotational axis systems of the lower limb. The surface of the condylar is based on a virtual model of the knee created intra-operatively by ‘painting’ the surface with the tip of a tracked, calibrated probe. The burring mechanism is robotically controlled to prepare the bone surface and remove the predefined volume of bone. The study shows the 89% of the patients' post-operative alignment recorded by the system was within 30 of the planned coronal mechanical axis alignment. The RMS error was 1.980. The RMS errors between the robotic system's implant plan and the post-operative radiographic implant position was; femoral coronal alignment (FCA) 2.6o, tibial coronal alignment (TCA) 2.9o and tibial slope (TS) 2.9o. In conclusion, the imageless robotic surgical system for UKA accurately prepared the bone surface of the tibia and femur which resulted in low errors when comparing planned and achieved component placement. This resulted in a high level of accuracy in the planned coronal mechanical axis alignment compared to that measured on post-operative radiographs.

Unicondylar knee arthroplasty (UKA) is growing in popularity with an increase in utilisation. As a less invasive, bone preserving procedure suitable for knee osteoarthritic patients with intact cruciate ligaments and disease confined to one compartment of the knee joint. The long term survival of a UKA is dependent on many factors, including the accuracy of prosthesis implantation and soft tissue balance. Robotic assisted procedures are generally technically demanding, can increase the operation time and are associated with a learning curve. The learning curve for new technology is likely to be influenced by previous experience with similar technologies, the frequency of use and general experience performing the particular procedure. The purpose of this study was to determine the time to achievement of a steady state with regards to surgical time amongst surgeons using a novel hand held robotic device.

This study examined consecutive UKA cases which used a robotic assistive device from five surgeons. The surgeons had each performed at least 15 surgeries each. Two of the surgeons had previous experience with another robotic assistive device for UKA. All of the surgeons had experience with conventional UKA. All of the surgeons have used navigation for other knee procedures within their hospital. The system uses image free navigation with infrared optical tracking with real time feedback. The handheld robotic assistive system for UKA is designed to enable precision of robotics in the hands of the surgeon. The number of surgeries required to reach ‘steady state’ surgical time was calculated as the point in which two consecutive cases were completed within the 95% confidence interval of the surgeon's ‘steady state’ time.

The average surgical time (tracker placement to implant trial acceptance phase) from all surgeons across their first 15 cases was 56.8 minutes (surgical time range: 27–102 minutes). The average improvement was 46 minutes from slowest to quickest surgical times. The ‘cutting’ phase was reported as decreasing on average by 31 minutes. This clearly indicates the presence of a learning curve. The surgeons recorded a significant decrease in their surgical time where the most improvement was in the process of bone cutting (as opposed to landmark registration, condyle mapping and other preliminary or planning steps). There was a trend towards decreasing surgical time as case numbers increase for the group of five surgeons. On average it took 8 procedures (range 5–11) to reach a steady state surgical time. The average steady state surgical time was 50 minutes (range 37–55 minutes).

In conclusion, the average operative time was comparable with clinical cases reported using other robotic assistive devices for UKA. All five surgeons using the novel handheld robotic-assisted orthopaedic system for UKA reported significant improvement in bone preparation and overall operative times within the first 15 cases performed, reaching a steady state in surgical times after a mean of 8 cases. Therefore, this novel handheld device has a similar learning curve to other devices on the market.

For patients suffering from osteoarthritis confined to one compartment of the knee joint, a successful unicondylar knee arthroplasty (UKA) has demonstrated an ability to provide pain relief and restore function while preserving bone and cruciate ligaments that a total knee arthroplasty (TKA) would sacrifice. Long-term survival of UKA has traditionally been inconsistent, leading to decreased utilisation in favour of alternative surgical treatment. Robot-assisted UKA has demonstrated an ability to provide more consistent implantation of UKA prosthesis, with the potential to increase long-term survivorship.

This study reports on 65 patients undergoing UKA using an image-free, handheld robotic assistive navigation system. The condylar surface was mapped by the surgeon intra-operatively using a probe to capture a 3-dimensional representation of the area of the knee joint to be replaced. The intra operative planning phase allows the surgeon to determine the size and orientation of the femoral and tibial implant to suit the patients’ anatomy. The plan sets the boundaries of the bone to be removed by the robotic hand piece. The system dynamically adjusts the depth of bone being cut by the bur to achieve the desired result. The planned mechanical axis alignment was compared with the system's post-surgical alignment and to post-operative mechanical axis alignment using long leg, double stance, weight bearing radiographs.

All 65 knees had knee osteoarthritis confined to the medial compartment and UKA procedures were completed using the handheld robotic assistive navigation system. The average age and BMI of the patient group was 63 years (range 45–82 years) and 29 kg/m² (range 21–37 kg/m²) respectively. The average pre-operative deformity was 4.5° (SD 2.9°, Range 0–12° varus). The average post-operative mechanical axis deformity was corrected to 2.1° (range 0–7° varus). The post-operative mechanical axis alignment in the coronal plane measured by the system was within 1° of intra-operative plan in 91% of the cases. 3 out of 6 of the cases where the post-operative alignment was greater than 1° resulted due to an increase in the thickness of the tibia prosthesis implanted. The average difference between the ‘planned’ mechanical axis alignment and the post-operative long leg, weight bearing mechanical axis alignment was 1.8°. The average Oxford Knee Score (old version) pre and post operation was 38 and 24 respectively, showing a clinical and functional improvement in the patient group at 6 weeks post-surgery.

The surgical system allowed the surgeons to precisely plan a UKA and then accurately execute their intra operative plan using a hand held robotically assisted tool. It is accepted that navigation and robotic systems have a system error of about 1° and 1mm. Therefore, this novel device recorded accurate post-operative alignment compared to the ‘planned’ post-operative alignment. The patients in this group have shown clinical and functional improvement in the short term follow up. The importance of precision of component alignments while balancing existing soft-tissue structures in UKA has been documented. Utilisation of robotic-assisted devices may improve the accuracy and long-term survivorship UKA procedure.

NavioPFS™ unicondylar knee replacement (UKR) system combines CT-free planning and navigation with robotically assisted bone preparation. In the planning procedure, all relevant anatomic information is collected under navigation, either directly with the point probe or by kinematic manipulation. In addition to key anatomic landmarks and the maps of the articulating surfaces of the femur and tibia, kinematic assessment of the joint laxity is performed. Relative positions of femur and tibia are collected through the flexion/extension range, with the pressure applied to fully stretch the collateral ligament on the operative side.

The planning procedure involves three stages: (1) the implant sizing and initial placement,(2) balancing of the gap on the operative side and (3) evaluating the contact points for the recorded flexion data and the planned placement of implants. In the gap balancing stage, the implants are repositioned until they allow for a positive gap, preferably uniform, throughout the entire range of flexion. UKR was planned and prepared on six cadaver knees with the help of NavioPFS system. All knees were normal without any signs of osteoarthritis. Two surgeons have performed medial UKR (4+2), and the bones were prepared using the NavioPFS handheld robotic tool.

Postoperatively, we have re-used the data collected during the planning procedure to compare the kinematic (gap balancing) performance of the used implant with three different commercial implant designs. All implants were placed in the orientation recommended by the respective manufacturer, sized to best fit the original bone geometry, and repositioned optimally balance the gap curve through the entire flexion range, without any negative gaps (overlaps). Since these were nonarthritic cadaver knees, the intent was to restore the original preoperative varus/valgus in neutral (zero) flexion.

The three implant designs demonstrated variable degree of capability to uniformly balance the knee gap over the entire range of flexion. The first implant (A) required a gap larger than 2 mm in one case out of six, the second (B) was capable of producing the positive gap curve under 2mm of gap in all six cases, and the third (C) required a gap larger than 2 mm in 3 (50%) of cases. All three designs exhibit the reduced gap space in mid (30°–90°) flexion.

Despite the best attempts, the artificial implants do not fully replicate the healthy knee kinematics. This is manifested by increased tightness in the mid flexion. In order to balance the gap in mid flexion, additional laxity has to be allowed in full flexion, extension, or both. NavioPFS allows for patient specific planning that takes into account this information, only available intraoperatively. This kind of evaluation on a patient specific basis is a very important planning tool and it allows the insight on the implant performance in mid flexion, typically not available using conventional planning techniques. It can also help in improving kinematic performance of future implant designs.