The use of robots in orthopaedic surgery is an emerging field that is gaining momentum. It has the potential for significant improvements in surgical planning, accuracy of component implantation and patient safety. Advocates of robot-assisted systems describe better patient outcomes through improved pre-operative planning and enhanced execution of surgery. However, costs, limited availability, a lack of evidence regarding the efficiency and safety of such systems and an absence of long-term high-impact studies have restricted the widespread implementation of these systems. We have reviewed the literature on the efficacy, safety and current understanding of the use of robotics in orthopaedics.

Cite this article: Bone Joint J 2015; 97-B:292–9.

Introduction

Robotically-assisted unicondylar knee arthroplasty (UKA) is intended to improve the precision with which the components are implanted, but the impact of alignment using this technique on subsequent polyethylene surface damage has not been determined. Therefore, we examined retrieved ultra-high-molecular-weight polyethylene UKA tibial inserts from patients who had either robotic-assisted UKA or UKA performed using conventional manual techniques and compared differences in polyethylene damage with differences in implant component alignment between the two groups. We aimed to answer the following questions: (1) Does robotic guidance improve UKA component position compared to manually implanted UKA? (2) Is polyethylene damage or edge loading less severe in patients who had robotically aligned UKA components? (3) Is polyethylene damage or edge loading less severe in patients with properly aligned UKA components?

Glenoid replacement is a manual bone removal procedure that can be difficult for surgeons to perform. Surgical robotics have been utilized successfully in hip and knee orthopaedic procedures but there are no systems currently available in the shoulder. These robots tend to have low adoption rates by surgeons due to high costs, disruption of surgical workflow and added complexity. As well, these systems typically use optical tracking which needs a constant line-of-sight which is not conducive to a crowded operating room. The purpose of this work was developing and testing a surgical robotic system for glenoid replacement. The new surgical system utilizes flexible components that tether a Stewart Platform robot to the patient through a patient specific 3D printed mount. As the robot moves relative to the bone, reaction loads from the flexible components bending are measured by a load cell allowing the robot to “feel” its way around. As well, a small bone burring tool was attached to the robot to facilitate the necessary bone removal. The surgical system was tested against a fellowship-trained surgeon performing standard surgical techniques. Both the robot and the surgeon performed glenoid replacement on two different scapula analogs: standard anatomy and posterior glenoid edge wear referred to as a Walch B2. Six of each scapula model was tested by the robot and the surgeon. The surgeon created a pre-operative plan for both scapula analogs as a target for both methodologies. CT scans of the post-operative cemented implants were compared to the pre-operative target and implant position and orientation errors were measured. For the standard shoulder analogs the net implant position and orientation errors were 1.47 ± 0.48 mm and 2.57 ± 2.30° for the robot and 1.61 ± 0.29 mm and 5.04 ± 1.92° for the surgeon respectively. For the B2 shoulders, the net implant position and orientation errors were 2.16 ± 0.36 mm and 2.89 ± 0.88° for the robot and 3.01 ± 0.42 mm and 4.54 ± 1.49° for the surgeon respectively. The new tracking system was shown to be able to match or outperform the surgeon in most metrics. The surgeon tended to have difficulty gauging the depth needed as well as the face rotation of the implant. This was not surprising as the reaming tool used by the surgeon obscures the view of the anatomy and the spherical cutter hinders the ability to index the tool. The robot utilized only one surgical tool, the bone burr, precluding the need for multiple instruments used by the surgeon to prepare the glenoid bone bed. The force-space navigation method can be generalized to other joints, however, further work is needed to validate the system using cadaveric specimens

Computer assisted orthopaedic surgery (CAOS) is an emerging and expanding filed. There are some old classification systems that are too comprehensive to cover all new CAOS tools and hybrid devises that are currently present and others that are expected to appear in the near future. Based on our experience and on the literature review, we grouped CAOS devises on the basis of their functionality and clinical use into 6 categories, which are then sub-grouped on technical basis. In future, new devices can be added under new categories or subcategories. This grouping scheme is meant to provide a simple guide on orthopaedic systems rather than a comprehensive classification for all computer assisted systems in surgical practice. For example, the number and diversity of tasks of surgical robots is enormous, up to 159 surgical robots with different mechanisms and functions reported in the literature. These can be classified according to their tasks, mechanism of actions, degree of freedom and level of activity but for the purpose of simplicity we subcategorised the orthopaedic robots to only industrial, hand-held and bone-mounted. Table 1 shows the classification system with the 6 categories and other subcategories

Introduction. Innovations in surgical robotics and navigation have significantly improved implant placement accuracy in total knee arthroplasty (TKA). However, many comparative studies have not been shown to substantially improve revision rates or other clinical outcome scores. We conducted a simulation study based on the reported distribution of patient-specific characteristics and estimated potential effect of coronal plane alignment (CPA) on risk of revision to evaluate the hypothesis that most published study designs in this area have been too underpowered to detect improvements in revision rates. Methods. To model previously reported studies, we generated a series of simulated TKA patient populations, assigning each patient a set of patient-specific factors (age at index surgery, BMI, and sex (Fig.1a)), as well as one surgeon-controlled factor (CPA) (Fig.1b) based on registry data and published literature. We modelled the survival probability for an individual patient at time t as a Gaussian function (exp[-(t/(k∗τ. max. )). 2. ]), where τ. max. (99.5 years) is selected to ensure the mean survival probability of the patient population matched 92% at 15 years. The value of k was adjusted for simulated patients within a range of 0 to 1 as a function of their patient and surgeon-specific factors (Fig.2). To evaluate power associated with a study design, we ran a Monte Carlo simulation generating 10,000 simulated populations of ten different cohort sizes. We divided the patient population into two groups: one group was assigned CPAs governed by the precision of a navigated/robotic approach (σ=1.5°), and the other CPAs governed by the precision of a conventional approach (σ=3°). We then simulated the time to failure for each patient, computed the corresponding Kaplan-Meier survival curves, and applied a Log-Rank test to each study to test for statistical difference. From the 10,000 simulations associated with each cohort size, we determined the percentage of simulated studies that found a statistically significant difference at each time point. Results. Figure 3 shows a contour plot illustrating the probability that a survival analysis with a specific study design would find statistical significance between the conventional and navigated/robotic patient groups. Entries from recently published literature are overlaid for context. No studies achieved statistical significance (p<0.05). Discussion. The effectiveness of navigated/robotic surgery is one of the most controversial debates in orthopedic surgery. The results from this simulation suggest that most revision studies aiming to settle this debate are likely significantly underpowered, falling below the normal 80% threshold. Limitations of this analysis include using only a single surgeon-controlled variable in the survival simulation, and only a single precision for the navigated/robotic approaches. Further studies will include more implant-related risk factors and a wider range of precisions for navigated/robotic procedures. Based on this simulation, it appears the effect size afforded by navigated/robotic surgeries on revision rates in TKA surgery is too small to recommend broad application, especially since adoption could involve added costs and unforeseen risks associated with novelty. Clinically, it may be beneficial to examine the use of robotics/navigation on high-risk patients, where studies are likely to have higher power due to larger effect sizes. For any figures or tables, please contact the authors directly

Background. Use of a robotic tool to perform surgery introduces a risk of unexpected soft tissue damage due to the uncommon tactile feedback for the surgeon. Early experience with robotics in total hip and knee replacement surgery reported having to abort the procedure in 18–34 percent of cases due to inability to complete preoperative planning, hardware and soft tissue issues, registration issues, as well as concerns over actual and potential soft tissue damage. These can result in significant morbidity to the patient, negating all the desired advantages of precision and reproducibility with robotic assisted surgery. The risk of soft tissue damage can be mitigated by haptic software prohibiting the cutting tip from striking vital soft tissues and by the surgeon making sure there is a clear workspace path for the cutting tool. This robotic total knee system with a semi-active haptic guided technique was approved by the FDA on 8/5/2015 and commercialized in August of 2016. Two year clinical results have not been reported to date. Objective. To review an initial and consecutive series of robotic total knee arthroplasties for safety in regard to avoidance of known or delayed soft tissue injuries and the necessity to abort the using the robot to complete the procedure. Report the clinical outcomes with robotic total knee replacement at or beyond two years to demonstrate no delayed effect on expected outcome. Methods. The initial consecutive series of 65 Triathlon. TM. total knee replacements using a semi-active haptic guided system that were performed after commercialization that would be eligible for two year follow-up were reviewed. Pre-operative planning utilizing CT determined the implant placement and boundaries and thus the limit of excursion from any part of the end effector saw tip. Self-retaining retractors were also utilized. Operative reports, 2, 6, and 12 week, and yearly follow-up visit reports were reviewed for any evidence of inadvertent injury to the medial collateral ligament, patellar tendon, or a neurovascular structure from the cutting tool. Operative notes were also reviewed to determine if the robotic procedure was partially or completely aborted due to any issue. Knee Society Knee Scores (KS-KS) and Functional Scores (KS-FS) were recorded from pre-operative and yearly. Any complications were recorded. Results. 40 cases had two year follow-up. The average follow-up for this series was 1.51 years. No cases were unable to be completed robotically. No case had evidence for acute or delayed injury to the medial collateral ligament, patellar tendon, or neurovascular structure. The only complication was a revision total knee for tibial component loosening after a fall induced periprosthetic tibial fracture. Average pre-operative KS-KS and KS-FS improved from 46.9 and 52.1 to 99.2 and 88.6 at one year follow-up, 100.5 and 86.9 at two year follow-up. Conclusions. A semi-active haptic guided robotic system is a safe and reliable method to perform total knee replacement surgery. This series of initial robotic arm assisted surgery had no intraoperative or delayed soft tissue injuries. Preliminary short-term outcomes at up to two years show excellent outcomes

Background. Manually instrumented knee arthroplasty is associated with variability in implant and limb alignment and ligament balance. When malalignment, patellar maltracking, soft tissue impingement or ligament instability result, this can lead to decreased patient satisfaction and early failure. Robotic technology was introduced to improve surgical planning and execution. Haptic robotic-arm assisted total knee arthroplasty (TKA) leverages three-dimensional planning, optical navigation, dynamic intraoperative assessment of soft tissue laxity, and guided bone preparation utilizing a power saw constrained within haptic boundaries by the robotic arm. This technology became clinically available for TKA in 2016. We report our early experience with adoption of this technique. Methods. A retrospective chart review compared data from the first 120 robotic-arm assisted TKAs performed December 2016 through July 2018 to the last 120 manually instrumented TKAs performed May 2015 to January 2017, prior to introduction of the robotic technique. Level of articular constraint selected, surgical time, complications, hemoglobin drop, length of stay and discharge disposition were collected from the hospital record. Knee Society Scores (KSS) and range of motion (were derived from office records of visits preoperatively and at 2-weeks, 7-weeks and 3-month post-op. Manipulations under anesthesia and any reoperations were recorded. Results. Less articular constraint was used to achieve balance in the robotic group, with a higher incidence of cruciate retaining retention (92% vs. 55%, p < 0.01) and a trend towards lower use of varus-valgus constrained articulations (5% vs. 11%, p = 0.068). Robotic surgery increased mean operative time by 22 minutes (p < 0.001). Operative time improved by 26 minutes from the first 10 robotic cases to the last 10 robotic cases. The robotic group had a lower hospital length of stay (2.7 vs. 3.4 days, p < 0.001). Discharge home was not significantly different between robotic and manual groups (89% vs. 83%, p = 0.2). Postoperative Knee Society scores were similar between groups at each postoperative time interval. Robotic-arm assisted TKA patients demonstrated lower mean flexion contracture at 2-weeks (1.8 vs. 3.3 degrees, p < 0.01), 7-weeks (1.0 vs. 1.8 degrees, p <0.01), and 3-months (0.6 vs 2.1 degrees, p = 0.02) post-surgery, but these differences were small. Mean flexion did not differ between groups at 3-month follow-up, but motion was achieved with a significantly lower rate of manipulation under anesthesia in the robotic group (4% vs 17%, p = 0.013). Conclusion. Preliminary findings demonstrate robotic-arm assisted TKA is safe and efficacious with outcomes comparable, if not superior, to that of manually instrumented TKA. Keywords. total knee arthroplasty, robotic arm-assisted total knee arthroplasty. For any figures or tables, please contact authors directly

Background. Use of a robotic tool to perform surgery introduces a risk of unexpected soft tissue damage due to the lack of tactile feedback for the surgeon. Early experience with robotics in total hip and knee replacement surgery reported having to abort the procedure in 18–34 percent of cases due to inability to complete preoperative planning, hardware and soft tissue issues, registration issues, as well as concerns over actual and potential soft tissue damage. These damages to the soft tissues resulted in significant morbidity to the patient, negating all the desired advantages of precision and reproducibility with robotic assisted surgery. The risk of soft tissue damage can be mitigated by haptic software prohibiting the cutting tip from striking vital soft tissues and by the surgeon making sure there is a clear workspace path for the cutting tool. This robotic total knee system with a semi-active haptic guided technique was approved by the FDA on 8/5/2015 and commercialized in August of 2016. One year clinical results have not been reported to date. Objective. To review an initial and consecutive series of robotic total knee arthroplasties for safety in regard to avoidance of known or delayed soft tissue injuries and the necessity to abort the robotic assisted procedure and resort to the use of conventional implantation. Report the clinical outcomes with robotic total knee replacement at or beyond one year to demonstrate satisfactory to excellent performance. Methods. The initial consecutive series of 100 robotic total knee replacements using a semi-active haptic guided system including 34 from the initial IDE series in 2014 and those performed after commercial approval beginning in 2016 were reviewed. Pre- operative planning utilizing CT determined the implant placement and boundaries and thus the limit of excursion from any part of the end effector saw tip. Self-retaining retractors were also utilized. Operative reports, 2, 6, and 12 week, and yearly follow-up visit reports were reviewed for any evidence of inadvertent injury to the medial collateral ligament, patellar tendon, or a neurovascular structure from the cutting tool. Operative notes were also reviewed to determine if the robotic procedure was partially or completely aborted due to any issue. Knee Society and Functional scores were recorded from pre-operative and yearly. Results. No cases were unable to be completed robotically. No case had evidence for acute or delayed injury to the medial collateral ligament, patellar tendon, or neurovascular structure. The average follow-up for this series was 1.54 years. Average pre- operative Knee Society and Functional Scores improved from 44.7 and 50 to 98.1 and 87.8 at one year follow-up, 93.8 and 83.1 at two year follow-up, 98.5 and 87.7 at three year follow-up, and 99 and 85 at four year follow-up. Conclusions. A semi-active haptic guided robotic system is a safe and reliable method to perform total knee replacement surgery. Preliminary short-term outcomes data shows excellent clinical and functional results

One of the more difficult tasks in surgery is to apply the optimal instrument forces and torques necessary to conduct an operation without damaging the tissue of the patient. This is especially problematic in surgical robotics, where force-feedback is totally eliminated. Thus, force sensing instruments emerge as a critical need for improving safety and surgical outcome. We propose a new measurement system that can be used in real fracture surgeries to generate quantitative knowledge of forces/torques applied by surgeon on tissues. We instrumented a periosteal elevator with a 6-DOF load-cell in order to measure forces/torques applied by the surgeons on live tissues during fracture surgeries. Acquisition software was developed in LabView to acquire force/torque data together with synchronised visual information (USB camera) of the tip interacting with the tissue, and surgeon voice recording (microphone) describing the actual procedure. Measurement system and surgical protocol were designed according to patient safety and sterilisation standards. The developed technology was tested in a pilot study during real orthopaedic surgery (consisting of removing a metal plate from the femur shaft of a patient) resulting reliable and usable. As demonstrated by subsequent data analysis, coupling force/torque data with video and audio information produced quantitative knowledge of forces/torques applied by the surgeon during the surgery. The outlined approach will be used to perform intensive force measurements during orthopaedic surgeries. The generated quantitative knowledge will be used to design a force controller and optimised actuators for a robot-assisted fracture surgery system under development at the Bristol Robotics Laboratory

Background. Acetabulum positioning affects dislocation rates, component impingement, bearing surface wear rates, and need for revision surgery. Novel techniques purport to improve the accuracy and precision of acetabular component position, but may come have significant learning curves. Our aim was to assess whether adopting robotic or fluoroscopic techniques improve acetabulum positioning compared to manual THA during the learning curve. Methods. Three types of THAs were compared in this retrospective cohort: 1) the first 100 fluoroscopically guided direct anterior THAs (fluoroscopic anterior, FA) done by a posterior surgeon learning the anterior approach, 2) the first 100 robotic assisted posterior THAs done by a surgeon learning robotic assisted surgery (robotic posterior, RP) and 3) the last 100 manual posterior THAs done by each surgeon (total 200 THAs) prior to adoption of novel techniques (manual posterior, MP). Component position was measured on plain radiographs. Radiographic measurements were done by two blinded observers. The percentage of hips within the surgeons' target zone (inclination 30°–50°, anteversion 10°–30°) was calculated, along with the percentage within the safe zone of Lewinnek (inclination 30°–50°; anteversion 5°–25°) and Callanan (inclination 30°–45°; anteversion 5°–25°). Relative risk and absolute risk reduction were calculated. Variances (square of the SDs) were used to describe the variability of cup position. Results. 76% of MP THAs were within the surgeons' target zone compared with 84% of FA THAs and 97% of RP THAs. This difference was statistically significant, associated with a relative risk reduction of 87% (RR 0.13 [0.04–0.40], p<.01, ARR 21%, NNT 5) for RP compared to MP THAs. Compared to FA THAs, RP THAs were associated with a relative risk reduction of 81% (RR 0.19 [0.06–0.62], p<.01, ARR 13%, NNT 8). Variances were lower for acetabulum inclination and anteversion in RP THAs (14.0 and 19.5) as compared to the MP (37.5 and 56.3) and FA (24.5 and 54.6) groups. These differences were statistically significant (P<.01). Conclusion. Adoption of robotic techniques delivers significant and immediate improvement in the precision of acetabular component positioning during the learning curve. While fluoroscopy has been shown to be beneficial with experience, a learning curve exists before precision improves significantly

Introduction:. The robot-assisted cementless total hip arthroplasty has theoretical advantages of providing better fit and mechanical stability of the stem. However, no previous study has been reported on a short stem implantation using surgical robot. We compared early clinical and radiographic results between robotic milling and manual rasping in short stem total hip arthroplasty. Materials & Methods:. We designed a prospective randomized controlled trial to determine whether robot-assisted short stem total hip arthroplasty improves the implant position represented by stem alignment, leg length equality, and reduces the intraoperative and early postoperative complications. A total of 40 patients were enrolled with informed consents and randomly assigned to robotic milling group (20 hips) and manual rasping group (20 hips) by means of a computer-generated random number table. There were no statistically significant differences in the demographics of the patients between the two groups. Results:. Total operation time of the robotic milling group was significantly longer than that of the manual rasping group (p = 0.015) with average 8.8 minutes registration time and average 11.1 minutes milling time. There was no significantly difference in total blood loss between the two groups. The robotic milling group showed superior results on stem alignment and leg length equality compared with the manual rasping group. Only in the manual rasping group, there were 2 intraoperative femoral fractures. No complications such as infection, nerve palsy or dislocation encountered in both groups. Conclusions:. Robotic-assisted short stem total hip arthroplasty has advantages in increased accuracy of stem alignment and leg length equality, and also helps reduce the potential risk of intraoperative femoral fracture

The conventional Knee arthroplasty jigs, while being usually accurate, often result in prostheses being inserted in an undesired alignment resulting in poor postoperative outcome. This is especially true about unicompartmental knee replacement. Computer navigation and roboticaly assisted unicompartmental knee replacement were introduced in order to improve surgical accuracy of the femoral and tibial bone cuts. The aim of this study was to assess accuracy and reliability of robotic assisted, unicondylar knee surgery (Makoplasty) in producing reported bony alignment. Two hundred and twenty consecutive patients who underwent medial robotic assisted unicondylar knee surgery (Makoplasty) performed by two surgeons (RJ & GP) were retrospectively identified and included in the study. Femoral and tibial sagittal and coronal alignments and posterior slope of the tibial component were measured in the post-operative radiographs. These measurements were compared with the equivalent measurements collected during intra-operative period by the navigation to study the reliability and accuracy of femoral and tibial cuts. Results. We found an average difference of 2.2 to 3.6 degrees between the intra-operatively planned and post-operative radiological equivalent measurements. In conclusion: assuming appropriate planning, robotically assisted surgery in unicondylar knee replacement will result in reliably accurate positioning of component and reduce early component failures caused by malpositioning. Mismatch between preplanning and post-op radiography is caused by poor cementing technique of the prosthesis rather than wrong bony cuts

Unicondylar knee arthroplasty (UKA) is a treatment for osteoarthritis when the disease only affects one compartment of the knee joint. The popularity in UKA grew in the 1980s but due to high revision rates the usage decreased. A high incidence of implant malalignment has been reported when using manual instrumentation. Recent developments include surgical robotics systems with navigation which have the potential to improve the accuracy and precision of UKA. UKA was carried out using an imageless navigation system – the Navio Precision Freehand Sculpting system (Blue Belt Technologies, Pittsburgh, USA) with a medical Uni Knee Tornier implant (Tornier, Montbonnot Saint Martin, France) on nine fresh frozen cadaveric lower limbs (8 males, 1 females, mean age 71.7 (SD 13.3)). Two users (consultant orthopaedic surgeon and post doctoral research associate) who had been trained on the system prior to the cadaveric study carried out 4 and 5 implants respectively. The aim of this study was to quantify the differences between the planned and achieved cuts. A 3D image of the ‘actual’ implant position was overlaid on the planned implant image. The errors between the ‘actual’ and the planned implant placement were calculated in three planes and the three rotations. The maximum femoral implant rotational error was 3.7° with a maximum RMS angular error of 2°. The maximum femoral implant translational error was 2.6mm and the RMS translational error across all directions was up to 1.1mm. The maximum tibial implant rotational error was 4.1° with a maximum RMS angular error was 2.6°. The maximum translational error was 2.7mm and the RMS translational error across all directions was up to 2.0mm. The results were comparable to those reported by other robotic assistive devices on the market for UKA. This technology still needs clinical assessment to confirm these promising results

An intelligent bone cutting tool as well as a navigation system is of high potential to provide great assistance for the surgeons in computer assisted orthopedic surgery. In this paper we designed a coordinated controller for the surgical robot to perform bone cutting more safely, easily and fast compared with being performed by manual bone saw. Coordinated control is in an outer control loop and determines suitable parameters of the inner control loop of the robot. The inner control loop is an admittance controller for the master site and a compliance controller for the slave site. Coordinated control consists of three modes, i.e. automated cutting, cautious cutting and automated prevention depending on bone cutting conditions and human intention. In automated cutting mode, the coordinated control will set larger admittance gain and smaller compliance gain to provide an assistant force to the human for completion of bone cutting. In cautious cutting mode, smaller admittance gain and larger compliance gain will be set and a resistant force will be provided to the operator for micro progress of bone cutting. In emergence mode, the robot will stop the cutter going forward. Experimental result shows that in automated mode of the proposed coordinated control was able to assist bone cutting at the same time to avoid undesired large cutting force and cutter breakage. The moving speed of cutter slowed down as the cutting forces increased due to the cutter hitting harder bone, thus alleviated sawblade bouncing up and achieved less deviation from designed cutting plane. In cautious cutting mode the cutting forces were magnified to be felt by the operator. The operator was able to perform micro progress of bone cutting with intensive monitoring of the cutting forces. This functionality is especially useful as the cutter approaches the critical area where the surgeon regards as dangerous region. The emergent mode was also successfully triggered by calculating the defined apparent admittance. The apparent admittance is more reliable than using the cutting force only in detection of cutting boundary. A hand's on robot under coordinated control is demonstrated in conjunction with surgical navigation system in computer assisted orthopedic surgery. This paper experimentally showed that the coordinated control can effective provide assistive and resistant forces to achieve safe and accurate bone cutting in total knee arthroplasty

The knee is one of the most commonly affected joints in osteoarthritis. Unicompartmental knee replacement (UKA) was developed to address patients with this disease in only one compartment. The conventional knee arthroplasty jigs, while usually being accurate, may result in the prosthesis being inserted in an undesired alignment which may lead to poor post-operative outcomes. Common modes of failure in UKA include edge loading due to incorrect sizing or positioning, development of disease in the other compartment due to over-stuffing or over-correction and early loosening or stress fractures due to inaccurate bone cuts. Computer navigation and robotically assisted unicompartmental knee replacement were introduced in order to improve the surgical accuracy of both the femoral and tibial bone cuts. The aim of this study was to assess accuracy and reliability of robotic assisted, unicondylar knee surgery in producing reported bony alignment. Two hundred and twenty consecutive patients with a mean age of 64 + 11 years who underwent successful medial robotic assisted unicondylar knee surgery performed by two senior total joint arthroplasty surgeons were identified retrospectively. The mean body mass index of the cohort was 33.5 + 8 kg/m. 2. with a minimum follow-up of 6 months (range: 6–18 months). Femoral and tibial sagittal and coronal alignments as well as the posterior slope of the tibial component were measured in the post-operative radiographs. These measurements were compared with the equivalent measurements collected during intra-operative period by the navigation to study the reliability and accuracy of femoral and tibial cuts. Radiographic evaluation was independently conducted by two observers. There was an average difference of 2.2 to 3.6 degrees between the intra-operatively planned and post-operative radiological equivalent measurements. For the femur, mean varus/valgus angulation was 2.8 + 2.5 degrees with 83% of those measured within 5% of planned. For the tibia mean varus/valgus angulation was 2.4 + 1.9 degrees with 93% within 5% of planned resection. There was minimal inter-observer variability between radiographic measurements. There were no infections in the evaluated group at the time of radiographic examination. Alignment for unicondylar knee arthroplasty is important for implant survival and is a more difficult procedure to instrument as it is a minimally invasive surgery. Assuming appropriate planning, robotically assisted surgery in unicondylar knee replacement will result in reliably accurate positioning of component and reduce early component failures caused by malpositioning. A mismatch between pre-planning and post-operative radiography is often caused by poor cementing technique of the prosthesis rather than incorrect bony cuts. Addressing these factors can lead to greater success and improved outcomes for patients

Introduction. Our clinic has started to use MAZOR's Spine-Assist(r) robotic device in routine spinal surgery practice since 2006. The use of this system is diverse and now applicable for Vertebroplasty, Biopsy procedures and different techniques of Spinal fusion. During this time our clinic performed near 150 robotic assisted surgeries. Amongst its benefits the system allows the reduction of the duration of fluoroscopic exposure in the OR, better accuracy due to computerized assisted planning and navigation, avoidance of human caused complications and a less traumatic procedure for the patient. On the other hand, the duration of the procedure is prolonged, the wound is subdued to a longer exposure in cases of the open surgery, and the operational cost is higher and requires a good trained medical staff. Materials and Methods. In the last 2 years we have performed 56 robotic assisted Vertebroplasty procedures (research group). At the same time we have performed 44 non assisted Vertebroplasty procedures. There was a significant difference in the fluoroscopic time and subsequent exposure time to radiation between the groups: in the research group we used only an average of 3 seconds of staff fluoroscopic exposure (an average of 5 fluoroscopic images) compared to an average of 11 seconds of exposure (an average of 24 fluoroscopic images). Furthermore, we have successfully inserted more than 400 pedical screws with less than 1mm accuracy from planning, out which only 8 were misplaced. Subsequently we have also performed 16 biopsies, which were effective as CT based biopsies. The average duration of a surgical procedure without the use of the system in 1 level fusion was 82 min. With the use of the system the average time was 106 min. The operational cost with the use of the system was about 1,000 ∊ more expensive. Furthermore, the use of the system required performing of an additional CT scan with 1 mm slices, which caused an additional exposure to patient radiation. Results. Robotic assisted spinal surgery is a new and safe approach aiming to dramatically shorten the duration of fluoroscopic exposure of the staff and surgeon thus reducing the exposure to radiogenic dose. This novel procedure, promotes a better accuracy with regard to Vertebroplasty, Spinal fusion, insertion of Pedical Screws and also for biopsies procedures. We continue to broaden the usage of the robotic assisted device to other fields of spinal surgery and to general orthopaedic surgery. However, we have to resolve some issues such as cost, operation time and less fluoroscopic exposure for the patient

Robotic assisted spine surgery was a breakthrough in the evolution of spinal surgery, gradually gaining its place as an alternative technique for conventional spinal procedures. As the general population's life expectancy increased so does the incidence of spinal pathology and with it emerged an urging need for a safer and more accurate means of treatment. In our institute we apply the “Spine Assist” platform for a variety of spinal procedures as Vertebroplasties, biopsies, Pedicular screws insertion and an inter-vertebral fusion – GOLIF procedures. This study is designed to analyze the learning curve of each procedure, regarding the amount of fluoro images (FI) taken, fluoro exposure (FE) time and net operation time. All spinal procedures using the “Spine Assist” platform were included in this study; all took place from 2006 until September 2010. Exclusion criteria were procedures with failed pre-op registration, and robotic assisted procedures that were converted to conventional fluoroscopic assisted during the operation. Every single surgery of all types of procedures was analyzed regarding the amount of FI taken, FE time and net operation time. Pedicular screws insertion was grouped into sets of four, where the same parameters were evaluated. Altogether we preformed 106 robotic assisted Vertebroplasty procedures. During this period a distinct learning curve was observed and analyzed. For the first ten Vertebroplasties an average of 12 FI were taken with a net operation time of 53.6 min per procedure. Analyzing the first 40 procedures has shown less FI per procedure (5 FI) and a net operation time of 48.6 min/procedure. Data drawn from the 51 following Vertebroplasties has set the standards of 4 FI with a net operation time of 25.6 min/procedure. Two Vertebroplasty procedures were not completed due to failure of software registration. Pedicular screws are a mean for stabilization of vertebral motion units. During a six years period 706 screws were inserted, out of whom 98 were inserted using percutaneous technique. Comparing the insertion of a set of 4 screws we found a significant improvement regarding the number of FI, FE time and the net operation time between the first ten procedures and the rest with a mean of 20 FI /4 FI and net screw insertion time of 82 min/ 25 min respectively. We found no difference in the parameters comparing percutaneous Vs open Pedicular screws insertion. The mean accuracy of all procedures was 0.3 mm compared to the pre planned screw trajectory. No false route was detected in any of the 506 procedures. This robotic assisted technique is a new and safe approach aiming to shorten the duration of the procedure, thus reducing the patient and surgeon exposure to radiogenic dose. The essence of robotic assisted surgery is a pre planned needle/screw trajectory aiming to reduce the possible intra-operative complication, inaccuracies and possible mishaps emerging during “free hand” procedures. Gaining more experience using the spine assist platform, as shown in this detailed learning curve, enabled us to leverage the platform for ultra-accurate procedures as the percutaneous intervertebral fusion – GOLIF, Vertebroplasty for burst fractures etc

To close the surgeon in the control loop is able to take advantages of the fertile sensing information and intelligence from human being so that the complex and unpredictable surgical procedure can be better handled properly. However, there is also weakness to be strengthened. For example, the motion control of the human being is not as accurate as required. Assisted equipment for such purpose may be helpful to the procedure. Exerting large forces during the cutting process may exhaust the operator and cause fatigue. The operator may need power assistance during the surgery procedure. The response speed of human being's may not be adequate to take immediate action in certain critical situations. The constraints from the limbs and human's attention usually cause a significant delay to react the critical situations. This may lead to serious damage by failing to response immediately. For example, in knee replacement procedure, the shape of the knee joint has to be prepared by performing bone resection procedure. The surgeon cuts the bone at certain position and orientation with the help of the cutting jig from the surgical planning. The cutter cut the bone by inserting vibration saw through the slot of the cutting block. The surgeon has to stop the cutter right after the bone has been cut through by the saw so that no surrounding soft tissue, blood vessel, and even important nerves, be damaged. Currently the tactile sensing from the hand is heavily relied on by the surgeon. He has also to be experienced and dexterous. If he fails to draw back the cutter after the bone being cut through, damages to the patient may occur. Therefore there is need to develop a cutting tool, which is intelligent, knows where it is, and is able to judge what the cutting situation is, and further assists the operator to stop the cutter in case that the operator fails to do so, or too slow to response. The benefit to the patient as well as the surgeon will be significant. Therefore the purpose of the paper is to develop an algorithm to implement such functionality of auto-detection of bone cutting through for a bone cutting tool when the cutter has cut through the bone. By the developed method, the intelligent cutter can effectively detect the cutting through condition and then adopt an immediate reaction to prevent the cutter from going further and to avoid unexpected damage. An auto-detection scheme has also been developed for assisting the operator in judging whether the cutter has reached the boundary or not. The auto-detection scheme is based on analyzing the cutting force pattern in conjunction with a bilateral force controller for the hand's on robot. The bilateral force controller consists of two force controllers. The force controller on the master calculates the feedrate of the cutter according to the push force by the operator. Meanwhile, the operator can also feel the cutting force by the force controller on the slave site, which revises the feedrate of the cutter by the measured cutting force. The operator can kinesthetically feel the cutting force from the variation of the feedrate. When the cutter breaks through the boundary of the bone, the cutting force will drop suddenly to almost zero. When this special force pattern occurs, an acknowledge signal of bone been broken through will be activated. The subsequent action will be followed to stop the cutter going further. We implement this concept by defining a “cutting admittance” indicating the resistance encountered by the cutting during bone resection at different cutting feedrate. During the bone resection, the cutting admittance varies from cutting through hard or soft portions of bone. As reaching the cutting boundary, the cutting admittance will suddenly increase. A threshold value will experimentally be determined to indicate cutting through condition. Together with pushing force by the human operator, the criterion for cutting-through detection is defined. Once cutting through is detected, the admittance for cutter movement will be set zero. The cutter stops going further and the operator feel like hitting a virtual wall in front. In this paper we proposed a human robot cooperative operation method by which the robotic system can intelligently detect where the cutter has cut through the bone. Characterisation of bone cutting procedure was performed. This auto detection scheme was developed by analyzing the information of the motion and cutting force information during the bone cutting process, no medical images are required. The auto-detection bone cut through was able to transfer the experiences of human being to quantitative modeling. The developed model has been tested for its applicability and robustness by saw bones and pig's knee joints. Results have shown the virtual wall generated by the real-time bone detection scheme and active constraint control is very accurate and capable of providing a safety enhance module for computer assisted orthopaedic surgery, in particular, in total knee replacement. By this method the robot system can accomplish a safe and accurate bone cutting with a complement of an imageless navigation system and results in a low cost, but safe and effective surgical robot system