Computers arrived late in orthopaedic surgery. While the rest of the world already happily integrated computers into daily life, business and production, orthopaedic surgeons remained sceptical and denied any need for help from modern technology. It was in the mid-eighties though, that a young veterinary surgeon from California, specializing in total hip replacement in dogs, was contemplating the problems that he encountered during surgery. This veterinary surgeon, the late Hap Paul, was one of the founding members of the custom – implant society, from which evolved ISTA. He struggled with wrong positioning of implants and broken bones, and wondered why implants that were manufactured with highest technology finally were placed into the bone with crude instruments reminiscent of those found in a carpenters workshop. With the help of IBM and engineers from the University of California he created a system which he called ROBODOC^®, and it became the first computer based system helping the surgeon during an orthopaedic procedure. The technological effort was huge, as many parts of the system and of the procedure using advance robotic tools had to be invented from scratch. There was nothing there they could copy, and the system they invented – an active robot performing a critical part of surgery – represented a very ambitious step forward. Some compare the development of ROBODOC^® with the technological history of the Concorde: very sophisticated technology, very early and very advanced, somewhat expensive and with an aura of vision and adventure

Of course this was not the only and ultimate solution of bringing computers into surgery. Other researchers took a step backwards: they invented systems that helped the surgeon to navigate hand held instruments and implants within the surgical field, so-called navigation systems. These were initially used by neurosurgeons to navigate probes within the brain. As neurosurgeons were closely related to and depending on CT-scan, the logic step was to use the CT- datasets, match them with real world (the process of registration) and create a virtual 3D space that is congruent to the real 3D space. Using CT provided orthopaedic surgeons increase visibility with less required exposure

With the help of optical systems (other options are mechanical or magnetic systems) instruments can be tracked outside and inside the surgical object and allow precise navigation within the surgical field. However, preparation of tissue and/or placement of implants were still done with manual tools. Very early application of this navigation technology was spine surgery in the mid-nineties, where utmost precision was needed during the placement of pedicle screws. Further applications were knee replacement, hip replacement and numerous applications in trauma surgery. Also the source of data was further developed: from the very precise but costly CT-scan to simple radiographs taken during surgery to so-called image free surgery, where data are retrieved directly from the surgical object and approximations are created to direct the placement of implants. Navigation systems, in contrast to the original robotic system, presented two major advantages: they were much cheaper, and they allowed the surgeon to use his standard instruments and, most important, to play a more active part in the surgery, “to stay in the loop” (Tony DiGioia).

Today there are thousands of navigations systems in routine use all over the world. Published results show benefits, but also limits. Surgery using navagation has become more precise and results more reproducible, yet there are still outliers which mainly stem from technical problems, but which are hard to detect and cause significant inaccuracy. Therefore the era of the robots is not over: robotic technology is currently revisited by numerous groups, and technically more advanced robots are developed and currently under testing. Robotic technology has continued to make inroads into the market with demonstrated capacity to assist the surgeon to reduce intraoperative complications, eliminate outliers, and achieve improved surgical outcomes consistently. Different types of robots (active, semi active and passive robots, such as systems which provide for constrained motion in the surgical field) are successfully moving into the operating theatre. ROBODOC^®, the forefather of all computer-assisted orthopaedic systems, is still around and actively applied during surgery, with published good results and high reliability.

The history of ROBODOC^® is a master piece of technological history. After initial successful human surgeries, embedded in the feasibility study required by the FDA, the next step was more difficult: the randomized study for FDA approval to prove the efficacy almost killed the company and with it the technology. In early optimistic statements the inventors foresaw major benefits, but overlooked the difficulties to prove these in the postoperative outcome. Disadvantages of the system, like longer OR times and higher blood loss, at least prevalent in the in the early trials of the FDA study, were obvious while the “clear” benefits in outcome were not so obvious. Thus marketing abroad became a major option, and Europe became the prime target. The attempt was successful, and rapidly 30 systems were busy all over Europe. This development was brought to a halt by a couple of unsubstantiated lawsuits in Germany and unprecedented negative press campaign accompanying this effort. The lawsuits were sponsored by the illusion to finally sue an American company and gain millions from that lawsuit. This process started in the early days of this century, and so far, in spite of numerous sentences proclaimed, not one court has condemned the technology or found any wrong doing in applying it. In parallel with the declining European market, the Asian market was developed, and surgeons there benefited from the experiences in Europe and the consecutive improvements of the system. Currently TKR and THR are routinely performed using the ROBODOC^® system in Japan, Korea and India.

This process let to recovery of the company, which tells us that technological progress also in medicine is inherently coupled to economic success. Although the first system applied in CAOS, Robodoc still is the most advanced system in technological terms. This is finally also accepted by the very critical USFDA, which had problems with the approval for such a long time because the system represents an autonomous robotic system working on patients.

Initial problems like bulkiness, software bugs and invasiveness have been overcome. Work is underway even now to make the system more flexible covering a wider range of surgical procedures like uni and multi compartmental knee, hip resurfacing and acetabular cup in THR and further expanding the functionality of the system supporting not just orthopedic procedures but Neurosurgical procedures as well.

Many of these developments are in the final stages of testing. In the meantime the CAOS community, i.e. the surgeons and engineers primarily working in application and development of the existing systems, more and more become convinced that computer assisted surgery undoubtedly is heading towards the integration of robotic systems into surgery: this is where ROBODOC^® came from.

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.

To introduce a new robot-assisted surgical system for spinal posterior fixation which called TiRobot, based on intraoperative three-dimensional images. TiRobot has three components: the planning and navigation system, optical tracking system and robotic arm system. By combining navigation and robot techniques, TiRobot can guide the screw trajectories for orthopedic surgeries. In this randomised controlled study approved by the Ethics Committee, 40 patients were involved and all has been fully informed and sign the informed consent. 17 patients were treated by free-hand fluoroscopy-guided surgery, and 23 patients were treated by robot-assisted spinal surgery. A total of 190 pedicle screws were implanted. The overall operation times were not different for both groups. None of the screws necessitated re-surgery for revised placement. In the robot-assisted group, assessment of pedicle screw accuracy showed that 102 of 102 screws (100%) were safely placed (<2 mm, category A+B). And mean deviation in entry point was 1.70 +/− 0.83mm, mean deviation in end point was 1.84 +/− 1.04mm. In the conventional freehand group, assessment of pedicle screw accuracy showed that 87 of 88 (98.9%) were safely placed (<2 mm, category A+B), 1 screw fall in category C, mean deviation in entry point was 3.73 +/− 2.28mm, mean deviation in end point was 4.11 +/− 2.31mm. This randomised controlled study verified that robot-assisted pedicle screw placement with real-time navigation is a more accuracy and safer method, and also revealed great clinical potential of robot-assisted surgery in the future

Background

Treating fractures is expensive and includes a long post-operative care. Intra-articular fractures are often treated with open surgery that require massive soft tissue incisions, long healing time and are often accompanied by deep wound infections. Minimally invasive surgery (MIS) is an alternative to this but when performed by surgeons and supported by X-rays does not achieve the required accuracy of surgical treatment.

While image guidance and neuro-navigation have enabled a more accurate positioning of pedicle implants, robot-assisted placement of pedicle screws appears to overcome the disadvantages of the two first systems. However, recent data concerning the superiority of robots currently available to assist spinal surgeons in the accurate positioning of implants are conflicting. The aim of our study was to evaluate the percentage of accurate positioning of pedicle screws inserted using a new robotic-guidance system.

Patients were operated on successively by the same surgeon using robotic-assistance (RA; n=40) or by the freehand conventional technique (FH; n=54). Ten and eleven patients from the robot (RG) and freehand (FHG) groups respectively, age-matched and all suffering from degenerative lumbar spine disease were compared. Patient characteristics as well as the duration of the operation and of exposure to X-rays were recorded. The Gertzbein Robbins classification was used to evaluate implant placement. Data wer compared between the groups. Pedicle screw placement in RG patients was achieved using the ROSA™ (Medtech) robot comprising a compact robotic arm on a floor-fixable mobile base. By permanently monitoring the patient's movements, this image-guided tool helps more accurately to pinpoint the pedicle entry point and to control the trajectory.

The mean age of patients in each group (RG and FHG) was 63 years. Mean BMI and operating time among the RG and FHG were respectively 26 and 27 kg/m², and 187 and 119 min. Accurate placement of the implant (score A-B) was achieved in 97.2% of patients in the RG (n=36) and in 92.6% of those in the FHG (n=54). Four implants in the RG were placed manually following failed robotic assistance. The mean duration of X-ray exposure per patient was 1 min 42s in the RG and 41s in the FHG.

We report a higher rate of accuracy with robotic assistance as compared to the FH technique. Exposure time was greater in the RG partly due to the fluoroscopic control of the implants required for this pilot study of feasibility. Limitations of the study include its small sized and non-randomised sample. Nevertheless, these preliminary results are encouraging for the development of new robotic techniques for spinal surgery.

A functional total knee replacement has to be well aligned, which implies that it should lie along the mechanical axis and in the correct axial and rotational planes. Incorrect alignment will lead to abnormal wear, early mechanical loosening, and patellofemoral problems. There has been increased interest of late in total knee arthroplasty with robot assistance. This study was conducted to determine if robot-assisted total knee arthroplasty is superior to the conventional surgical method with regard to the precision of implant positioning. Twenty knee replacements of ten robot-assisted and another ten conventional operations were performed on ten cadavers. Two experienced surgeons performed the surgery. Both procedures were undertaken by one surgeon on each cadaver. The choice of which was to be done first was randomized. After the implantation of the prosthesis, the mechanical-axis deviation, femoral coronal angle, tibial coronal angle, femoral sagittal angle, tibial sagittal angle, and femoral rotational alignment were measured via three-dimensional CT scanning. These variants were then compared with the preoperative planned values. In the robot-assisted surgery, the mechanical-axis deviation ranged from −1.94 to 2.13° (mean: −0.21°), the femoral coronal angle ranged from 88.08 to 90.99° (mean: 89.81°), the tibial coronal angle ranged from 89.01 to 92.36° (mean: 90.42°), the tibial sagittal angle ranged from 81.72 to 86.24° (mean: 83.20°), and the femoral rotational alignment ranged from 0.02 to 1.15° (mean: 0.52°) in relation to the transepicondylar axis. In the conventional surgery, the mechanical-axis deviation ranged from −3.19 to 3.84°(mean: −0.48°), the femoral coronal angle ranged from 88.36 to 92.29° (mean: 90.50°), the tibial coronal angle ranged from 88.15 to 91.51° (mean: 89.83°), the tibial sagittal angle ranged from 80.06 to 87.34° (mean: 84.50°), and the femoral rotational alignment ranged from 0.32 to 4.13° (mean: 2.76°) in relation to the transepicondylar axis. In the conventional surgery, there were two cases of outlier outside the range of 3° varus or valgus of the mechanical-axis deviation. The robot-assisted surgery showed significantly superior femoral-rotational-alignment results compared with the conventional surgery (p=0.006). There was no statistically significant difference between robot-assisted and conventional total knee arthroplasty in the other variants. All the variants were measured with high intraobserver and interobserver reliability. In conclusion, Robot-assisted total knee arthroplasty showed excellent precision in the sagittal and coronal planes of the three-dimensional CT. Especially, better accuracy in femoral rotational alignment was shown in the robot-assisted surgery than in the conventional surgery despite the fact that the surgeons who performed the operation were more experienced and familiar with the conventional surgery than with robot-assisted surgery. It can thus be concluded that robot-assisted total knee arthroplasty is superior to the conventional total knee arthroplasty

Introduction and Objective. Total knee arthroplasty (TKA) is a frequently and increasingly performed surgery in the treatment of disabling knee osteoarthritis. The rising number of procedures and related revisions pose an increasing economic burden on health care systems. In an attempt to lower the revision rate due to component malalignment and soft tissue imbalance in TKA, robotic assistance (RA) has been introduced in the operating theatre. The primary objective of this study is to provide the results of a theoretical, preliminary cost-effectiveness analysis of RA TKA. Materials and Methods. A Markov state-transition model was designed to model the health status of sixty-seven-year-old patients in need of TKA due to primary osteoarthritis over a twenty-year period following their knee joint replacement. Transitional probabilities and independent variables were extracted from existing literature. Patients’ state in the transition model was able to change on an annual basis. The main differences between the conventional and RA TKA were the outlier rate in the coronal plane and the cost of the procedure. In RA TKA, it was hypothesized that there were lower revision rates due to a lower outlier rate compared to conventional TKA. Results. The value attributed to the utility both for primary and revision surgery has the biggest impact on the ICER, followed by the rate of successful primary surgery and the cost of RA-technology. Only 2.18–2.34% of the samples yielded from the probabilistic sensitivity analysis proved to be cost-effective (threshold set at $50000/QALY). A calculated surgical volume of at least 191–253 cases per robot per year is needed to prove cost-effective taking the predetermined parameter values into account. Conclusions. Robot-assisted TKA might be a cost-effective procedure compared to conventional TKA if a minimum of 191 cases are performed on a yearly basis, depending on the cost of the robot. The cost-benefit of the robotic TKA surgery is mainly based on a decreased revision rate. This study is based on the assumption that alignment is a predictor of success in total knee arthroplasty. Until there is data confirming the assertion that alignment predicts success robot-assisted surgery cannot be recommended

The traditional stem in cement-less total hip replacement was designed as a straight stem. This design was chosen to compensate for lack of initial stability provided by cement. Specifically the box shape of the implant achieved rotational stability and the wedge shape promised proximal press fit. Therefore also the first robot-assisted surgeries were performed using straight stems. Primarily those surgeons using the antero-lateral approach soon felt limitations of the use of straight stems during robot-assisted surgery. The reamer, in order to guarantee a straight positioning of the implant, used a straight approach to the proximal femur, thereby damaging the insertion site of the gluteus muscle in some cases. This then led to persisting muscular deficit with a consecutive positive Trendelenburg sign. Surgeons began to monitor during computer–assisted planning not only the final position, but also the cutting path, which was – as requested by the surgeons – displayed on the screen. At the same time anatomic stems became available for computer-assisted planning and surgery. With the introduction of anatomic stems also oblique cutting became available, thus avoiding compromising the greater Trochanter. Clinical results of anatomic stems in robot-assisted surgery seem to be satisfactory. Although most users allow immediate weight bearing, no loosening or visible subsidence was reported. Cadaver studies and animal experiments suggest that exactness of robot-assisted preparation with the resulting close fit of the implant – no press fit though – provide sufficient stability to allow for anatomic designed stems in cement-less procedures

Robotic technology in adult reconstruction – initially the placement of the stem during THR – was introduced in the early nineties of last century, starting in the US. The underlying technology dated back to the year 1986. Because of regulatory restrictions the technology could not spread in the US, but was exported to Europe in 1994. There the technology – primarily distributed in Germany – had a great success and by the year 2000 roughly 50 centers were using Robodoc – the first robot on the market – and a very similar German competitor’s product, CASPAR. The initial robot was a crude machine, basically the unchanged beta version. Cumbersome fixation, a registration process using three fiducials, the requirement for second surgery to place the fiducials, and last but not least raw and hardly elaborated cutting files made surgery with Robodoc a demanding undertaking. Yet feedback from the surgeons, sometimes vigorously expressed during regular user meetings, let to continuous evolution of the system and resulted in an advanced and stable technology. Also training – with important input from the already experienced sites – improved significantly, which can best be demonstrated by procedure time for first surgery: in Frankfurt 1994 roughly four hours, while today first surgeries at new sites rarely exceed two hours. Further applications – revision surgery, total knee replacement – helped to justify the significant investment into the system. While robotic technology underwent evolution, other related technologies were developed and entered the market. Main products were the navigation systems, which initially were developed for neurosurgery and spine surgery and which, due to easier handling and lower costs, found more acceptance on behalf of the surgeons. Although the navigation technology in some regards is a step back from the robotic technology, it appealed for just that reason: the surgeon stays in the loop. The surgeon uses the traditional instruments, and the navigator helps him to achieve precision in reaming or placement of implants. In orthopaedic surgery navigators became very popular in TKR, but also in THR. Another development, completely unrelated to the mentioned technology, presented a new challenge: minimal invasive surgery. While in knee surgery the introduction of arthroscopy in the late seventies already proved the feasibility of minimal invasive techniques, adult reconstruction remained the domain of sometimes aggressive and robust surgery. Only recently minimal invasive procedures were introduced and standardized for a couple of applications. It is important to stress the fact that the term ‘minimal invasive’ did not relate to the size of skin incision only, but to the overall degree of soft tissue damage necessary to prepare for and place the implants. Some companies now offer new instruments allowing for very minimal incisions and reduced soft tissue compromise. In contrast to this development robot assisted surgery remained – in spite of numerous improvements – a rather invasive piece of surgery. These separate developments – navigators and minimal invasive surgery – made robot assisted joint surgery in the eyes of many potential users a rather outdated, superfluous and expensive type of technology. It is therefore time to revisit the original intentions that let to the development of robot assisted surgery. The original ideas were sponsored by veterinary surgeons specializing in cementless THR for dogs. They experimented with custom implants, but they identified two fields of concerns: fractures and poor placement. Both problems are – still – common in human THR. Robot-assisted surgery was supposed to mainly address these problems. Another asset of robot-assisted surgery is seen in machine milling, which was invented as part of the robotic procedure and which turned out to be superior to conventional reaming. The published results of robot-assisted THR (i.e. Nishihara et al, 2006) prove that these requirements were met. In our own series in Spain we had no fracture and every single implant was seated according to the preoperative plan. Animal experiments allowing for histological examination of the bone-implant interface showed the uncompromised cancellous scaffolding supporting the implant, while hand-reamed interfaces showed signs of destruction and atrophy. On the other hands there are concerns that current minimal invasive approaches do cause problems in these regards: control of position is mainly feasible by use of intraoperative x-ray, and fractures do occur. Therefore robot-assisted surgery seems to be the ideal complement for the minimal invasive approach. The deficits of MIS regarding orientation and visualization of the surgical object can be compensated by the robots proven ability to execute preoperative established plans. The challenge is the current invasiveness of robotic surgery, which – as primary tests and studies show – can be easily accounted for. In conclusion there is an ever increasing role for robot-assisted surgery in adult reconstruction. It is up to the surgeons to define the requirements and ask for specifications that will meet their and the patient’s expectations regarding the degree of invasiveness involved

Introduction. The placement of a large interbody implant allows for a larger surface area for fusion, vis a vis, via retroperitoneal direct anterior, antero-lateral and lateral approaches. At the same time, spinal navigation facilitates a minimally invasive fixation for inserting posterior pedicle screws. We report on the first procedures in the United Kingdom performed by a single-surgeon at a single- centre using navigated robot-assisted spine surgery without the need for guide-wires. Materials and Methods. Whilst positioned in the supine or lateral position, a routine supine anterior lumbar interbody fusion (ALIF), and/or antero-lateral ALIF (AL-ALIF) and/or lateral lateral interbody fusion (LLIF) is performed. The patient is then turned prone or kept in the single lateral position (SPL) for insertion of the posterior screws performed under robotic guidance. Intraoperative CT scan 3D images captured then are sent to the Robotic software platform for planning of the screw trajectories and finally use again at the end of the procedure to confirm screw accuracy. We identified 34 consecutive patients from October 2019 to January 2020 who underwent robotic assisted spine surgery. The demographic, intraoperative, and perioperative data of all these patients were reviewed and presented. Results. Of the 34 patients, 65 levels were treated in total using 204 screws. Of the 21 patients (60%) who underwent single-level fixation, 14 of them (67%) were treated at the L5/S1 level, 3 at L3/L4, 3 at L4/L5 and 1 at L2/L3 level. The remaining 13 patients (40%) underwent multi-level fixation, of which 4 were adult scoliosis. 15 underwent a supine ALIF approach, 1 underwent AL-ALIF, 8 patients underwent combined LLIF and AL-ALIF approach in a lateral decubitus, whilst 9 underwent pure LLIF approach (of which 3 patients were in the single position lateral) and one patient had previous TLIF surgery. The average estimated blood loss was 60 cc. The average planning time was 10 min and the average duration of surgery was 50 min. The average patient age was 54 years and 64% (22/34) were male. The average BMI was 28.1 kg/m. 2. There were no re-interventions due to complications or mal positioned screws. Conclusion. Minimally invasive spine surgery using robot-assisted navigation yields an improved level of accuracy, decreased radiation exposure, minimal muscle disruption, decreased blood loss, shorter operating theatre time, length of stay, and lower complication rates. Further follow-up of the patients treated will help compare the clinical outcomes with other techniques

Introduction. Mechanically aligned total knee arthroplasty(TKA) relies on restoring the hip-knee-ankle angle of the limb to neutral or as close to a straight line as possible. This principle is based on studies that suggest limb and knee alignment is related long term survival and wear. For that cause, there has been recent attention concerning computer-assisted TKA and robot is also one of the most helpful instruments for restoring neutral alignment as known. But many reported data have shown that 20% to 25% of patients with mechanically aligned TKA are dissatisfied. Accordingly, kinematically aligned TKA was implemented as an alternative alignment strategy with the goal of reducing prevalence of unexplained pain, stiffness, and instability and improving the rate of recovery, kinematics, and contact forces. So, we want to report our extremely early experience of robot-assisted TKA planned by kinematic method. Materials and Methods. This study evaluated the very short term results (6 weeks follow up) after robot-assisted TKA aligned kinematically. 50 knees in 36 patients, who could be followed up more than 6 weeks after surgery from December 2014 to January 2015, were evaluated prospectively. The diagnosis was primary osteoarthritis in all cases. The operation was performed with ROBODOC (ISS Inc., CA, USA) along with the ORTHODOC (ISS Inc., CA, USA) planning computer. The cutting plan was made by single radius femoral component concept, each femoral condyles shape-matched method along the transverse axis using multi-channel CT and MRI to place the implant along the patient's premorbid joint line. Radiographic measurements were made from long bone scanograms. Clinical outcomes and motion were measured preoperatively and 6 weeks postoperatively. Results. The range of motion increased from preoperative mean 113.4 (±5.4, 85 to 130) to postoperative mean 127.3 (±7.4, 90 to 140) at last follow up. The mean knee score and functional score improved from 35.4 (±10.3, 10 to 55) and 30.1 (±7.7, 10 to 60) before surgery to 88.6 (±5.8, 60 to 100) and 90.7 (±9.6, 60 to 100) at last follow up. The WOMAC score was improved from 52(±15.5) to 20(±14.8) at last follow up. The postoperative Hip-knee-ankle alignment was −1.3±2.8. The femoral component was 2.1 valgus and tibial component was 2.8 varus along the mechanical axis in coronal plane. There were no complications and failures. Conclusion. On the basis of our results, we are cautiously optimistic about robot-assisted TKA by kinematically alignment. More anatomic alignment of the implant can be associated with better flexion and better clinical outcomes scores in the kinematically aligned method in our thinking. But, at this starting point, more comparative studies with mechanical aligned group are needed and we must explore about implant survivalship issues and implant loading issues in dynamic and static condition that someone is worrying about. If the problem can be solved, there is no use worrying about it in our thinking. And what is more, the robot-assisted surgery will be very useful especially in those cases of severely deformed knees and distorted anatomy to be aligned kinematically

INTRODUCTION. Allograft reconstruction after resection of primary bone sarcomas has a non-union rate of approximately 20%. Achieving a wide surface area of contact between host and allograft bone is one of the most important factors to help reduce the non-union rate. We developed a novel technique of haptic robot-assisted surgery to reconstruct bone defects left after primary bone sarcoma resection with structural allograft. METHODS. Using a sawbone distal femur joint-sparing hemimetaphyseal resection/reconstruction model, an identical bone defect was created in six sawbone distal femur specimens. A tumor-fellowship trained orthopedic surgeon reconstructed the defect using a simulated sawbone allograft femur. First, a standard, ‘all-manual’ technique was used to cut and prepare the allograft to best fit the defect. Then, using an identical sawbone copy of the allograft, the novel haptic-robot technique was used to prepare the allograft to best fit the defect. All specimens were scanned via CT. Using a separately validated technique, the surface area of contact between host and allograft was measured for both (1) the all-manual reconstruction and (2) the robot-assisted reconstruction. All contact surface areas were normalized by dividing absolute contact area by the available surface area on the exposed cut surface of host bone. RESULTS. The mean area of contact between host and allograft bone was 24% (of the available host surface area) for the all-manual group and 76% for the haptic robot-assisted group (p=0.004). CONCLUSIONS. This is the first report to our knowledge of using haptic robot technology to assist in structural bone allograft reconstruction of defects left after primary bone tumor resection. The findings strongly indicate that this technology has the potential to be of substantial clinical benefit. Further studies are warranted

INTRODUCTION. Unicompartmental knee arthroplasty (UKA) allows replacement of a single compartment in patients who have isolated osteoarthritis as a minimally invasive procedure. However, limited visualization of the surgical site provides challenges in ensuring accurate alignment and placement of the prosthesis. With robot-assisted surgery, correct implant positioning and ligament balancing are obtainable with increased accuracy. To date, there has not been a large series reported in the literature of UKAs performed with robotic assistance. The aim of this study was to examine the clinical outcomes of robot-assisted UKA patients. METHODS. 510 patients who underwent robotic-assisted UKA between July 2008 and June 2010 were identified (average age 63.7 years, range: 22 to 28 years). Clinical outcomes were evaluated using the Oxford Knee Score (OKS) and patients without recent follow-up were phoned. Revision rate and time to revision were also examined. RESULTS. Average length of stay was 1.4 days (range: 1 to 7 days). There was minimal blood loss with most procedures. There were two intra-operative complications, both in early patients in the series. The first intra-operative complication was broken alignment pins in both the femur and tibia. In the second complication, preparation was finished manually with a burr due to registration problems with the software. Both patients were doing well at most recent follow up and neither experienced further complications. At latest clinical follow-up, patients reported a mean OKS of 36.1 + 9.92. The revision rate was 2.5% with 13 patients either converted from an inlay to onlay prosthesis or conversion to TKA. The most common indication for revision was tibial component loosening, followed by progression of arthritis. One patient was revised due to infection. Mean time to revision was 9.55 + 5.48 months (range: 1 to 19 months). CONCLUSION. UKA with a robotic system provides good pain relief and functional outcomes at short-term follow-up. Ensuring correct component alignment and ligament balancing increases the probability of a favorable outcome. Proper patient selection for appropriate UKA candidates remains an important factor for successful outcomes. In combination with robotic assistance there can be a reduction in many of the failures seen with early systems

Aims

The Coronal Plane Alignment of the Knee (CPAK) classification has been developed to predict individual variations in inherent knee alignment. The impact of preoperative and postoperative CPAK classification phenotype on the postoperative clinical outcomes of total knee arthroplasty (TKA) remains elusive. This study aimed to examine the effect of postoperative CPAK classification phenotypes (I to IX), and their pre- to postoperative changes on patient-reported outcome measures (PROMs).

Unicompartmental knee arthroplasty (UKA) is an increasingly attractive and clinically successful treatment for individuals with isolated medial compartment disease who demand high levels of function. A major challenge with UKA is to place the components accurately so they are mechanically harmonious with the retained joint surfaces, ligaments and capsule. Misalignment of UKA components compromises clinical outcomes and implant longevity. Cobb et al. (JBJS-Br 2006) showed that robot-assisted placement of UKA components was more accurate than traditional techniques, and subsequently that the clinical outcomes were improved. Cobb’s method, however, employed rigid intraoperative stabilization of the bones in a stereotactic frame, which is impractical for routine clinical use. Robotic systems have now advanced to include dynamic bone tracking technologies so that rigid fixation is no longer required. The question is -Do these robotic systems with dynamic bone tracking provide the same accuracy advantages demonstrated with robotic systems with rigidly fixed bones? We compared robot-assisted and traditionally instrumented UKA in six bilateral pairs of cadaver specimens. In all knees, a CT-based preoperative plan was performed to determine the ideal positions and orientations for the implant components. Traditional manual instruments were utilized with a tissue-sparing approach to implant one knee of each pair. A haptic robotic system acting as a virtual cutting guide was used to perform the robot-assisted UKA, again with a tissue-sparing approach. Postoperative CT scans were obtained from all knees, and the 3D placement errors were quantified using 3D-to-3D registration of implant and bone models to the reconstructed CT volumes. The magnitudes of femoral implant orientation error were significantly smaller for the robot-assisted implants compared to traditionally implanted components (4° vs 11°, p< 0.001), but the magnitudes of femoral placement error did not reach significance (3mm vs. 5mm, p=0.056). The magnitudes of tibial implant placement error were not significantly different (4mm vs. 5mm and 7° vs. 7°, p> 0.05). Well-placed UKA implants can provide durable and excellent functional results, which is an increasingly attractive option for young and active patients with severe compartmental osteoarthritis who wish not to have or to delay a total knee replacement. Previous studies have demonstrated significant improvement in implant placement accuracy and clinical results with robot-assisted surgery using rigid bone fixation. This study demonstrates it is possible to achieve significant accuracy improvements with robot-assisted techniques allowing free bone movement. Additional larger trials will be required to determine if these differences are realized in clinical populations

Aims

The aim of this study was to determine the risk of tibial eminence avulsion intraoperatively for bi-unicondylar knee arthroplasty (Bi-UKA), with consideration of the effect of implant positioning, overstuffing, and sex, compared to the risk for isolated medial unicondylar knee arthroplasty (UKA-M) and bicruciate-retaining total knee arthroplasty (BCR-TKA).

In robot-assisted orthopaedic surgery, registration is a key step, which defines the position of the patient in the robot frame so that the preoperative plan can be performed. Current registration methods have their limitations, such as the requirement of immobilisation of the limbs or the line of sight (LOS) issues. These issues cause inconvenience for the surgeons and interrupt the surgical workflow in the operating room. Targetting these issues of current registration methods, we propose a camera-robot registration system for joint replacement. The bone geometry, which is measured directly by a depth camera, is aligned to a preoperatively obtained bone model to calculate the pose of the target. Simultaneously, in order to avoid registration failure caused by LOS interruptions, the depth camera tracks objects that may occlude the target bone, and a robot manipulator is used to move the camera away from the nearest obstacle. The optimal camera motion is calculated based on the position and velocity of the obstacle, which avoids the occlusion efficiently without changing the target position in the camera frame. Inverse kinematics of the robot is used to project the Cartesian velocity of the end-effector into the joint space, with kinematic singularities considered for stable robotic control. An admittance controller is designed as the human-robot interface so that the surgeon can directly set the robot configuration by hand according to the actual environment. Simulations and experiments were conducted to test the performance. The results show that the proposed obstacle avoidance method can effectively increase the distance between the obstacle and the LOS, which lowers the risk of registration failure due to obstacle occlusion. This pilot study is promising in reducing distractions to the surgeon and can help achieve a fluent and surgeon-centred workflow

Aims

The number of convolutional neural networks (CNN) available for fracture detection and classification is rapidly increasing. External validation of a CNN on a temporally separate (separated by time) or geographically separate (separated by location) dataset is crucial to assess generalizability of the CNN before application to clinical practice in other institutions. We aimed to answer the following questions: are current CNNs for fracture recognition externally valid?; which methods are applied for external validation (EV)?; and, what are reported performances of the EV sets compared to the internal validation (IV) sets of these CNNs?

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