Computer-assisted surgery (CAS)
Computer-assisted surgery: Current use in hips and knees
Part 2 examines the current use of computer-assisted systems in hip and knee surgery. Weighing the pros and cons, we look at benefits, economic considerations, limitations, concerns, and impact on patient outcomes. We also reveal how orthopedic surgeons are using these technologies in the operating rooms right now and how they perform after simulation training.
Globally, the number of total hip (THA) and knee arthroplasties (TKA) performed each year is increasing.[1–3] They can be life changing procedures that, when successful, alleviate pain from conditions such as osteoarthritis, and return mobility to patients. Finding new ways to improve patient outcomes is of highest priority for healthcare systems and surgeons.
From CAS to CAOS
In Part 2 of this Insights Newsletter, we narrow our focus to computer-assisted orthopedic surgery (CAOS) systems currently used for hip and knee surgery. Part 1 introduced the different types of navigation and robotic systems used in CAS, their classification, applications, historical background, and terminology.
Orthopedic surgeons are seeing an increasing availability of CAOS systems to train them, support and guide preoperative planning, and even conduct procedures with a robotic “partner”. A study that looked at the use of navigation and robot-assisted surgery in TKAs in the US between 2005 and 2014, found that by 2014, 7% of the country’s TKAs involved navigation or robots compared with 1.2% in 2005. Robots were more likely to be involved in TKAs performed in the Northeast of the country, while navigation was more likely to be used in the Western states. The Australian National Joint Replacement Registry showed that in 2012, 22.8% of all primary TKAs in the country were performed using navigation—an increase from 2.4% in 2003. Similar trends have been identified in the number of computer-assisted total hip arthroplasties (THAs).
For most complicated procedures there is an acknowledged benefit to practice. Surgery combines a honed skill set of cognitive, communication, and manual abilities that require training and ongoing practice. For many years, surgical skills have been taught via the master-apprentice model with sheer volume of exposure building competence. However, with decreased working hours, and increasing hospital costs and jurisdictional restrictions, it can be challenging for trainee surgeons to accumulate hand-on experience. A 2019 study found surgeon experience level to be a risk factor in primary TKA malalignment, with trainee surgeons and low-volume non-trainee surgeons performing similarly.
For Justin Chang, Senior Clinical Fellow, University College London Hospital, UK, using computer navigation and robotic software as learning tools, particularly for knees, “can help trainees understand principles of balancing a knee. It provides visual and objective measurements for something that is usually learned by subjective feel.”
In terms of robot-assisted surgery, “the learning curve is primarily getting familiar to the functionality and registration of the robot. Surgical outcomes are generally less affected early in the learning curve because the robot ensures components are aligned in the planned position,” says Justin Chang.
Orthopedics is considered high risk for malpractice claims.[11,12] In France, orthopedic patients make 20% of malpractice claims. Being able to train to a standardized level of competence before having access to patients is an attractive prospect. Training tools have been developed for surgeons that offer the opportunity to practice the skills needed to improve operative accuracy and potentially decrease complications, without having to touch a patient.
CAOS training systems that employ virtual reality (VR), which is a completely simulated experience, offer highly interactive simulations without the need of supervision, with benefits offered to both trainee and practicing orthopedic surgeons. Indeed, simulation training is something that residents have indicated they are interested in accessing.
Studies into the effectiveness of VR simulation training in orthopedics have found that the simulation-trained orthopedic surgeons, particularly trainees, were more surgically accurate when conducting the procedure.[8,17,18] It also offers a way to assess basic competency before operating on a patient.
Efficacy of CAOS
Without adequate research it is not possible to evaluate the degree to which a technology or procedure is effective in meeting its goals. Despite growing adoption of CAOS systems, they are still not available to many surgeons around the world, particularly in less urban environments.
Justin Chang notes that this is due in part to “cost being an important factor which may limit the ability to use robotic surgery, and the operative time is usually longer as well.”
What evidence is there to support or refute the use of CAOS navigation and robot systems in hip and knee surgery? Let's examine some findings.
CAUTIONARY NOTE FROM JUSTIN CHANG: CAOS does not replace surgeon skill
“Technological assists are no replacement for understanding how to apply the fundamentals of orthopedic practice. Learning the basic principles and standard guides is very important. If the software fails or the array positions are knocked mid-procedure, conversion to standard instrumentation may be necessary. Surgeons must have the skills to quickly adapt in this type of situation.”
CAOS in TKA
It is well known that up to 30% of patients describe residual pain, disability, and limited quality of life after an otherwise uncomplicated TKA.[20–23] Innovative technology such as navigation and robotic-assisted surgery was initially designed to improve the accuracy and precision of the bone cuts; it was believed that improved alignment of components would subsequently lead to improved functional outcomes and survivorship.
Navigation in TKA
The use of computer-assisted navigation in TKA has decreased in use after an initial surge in popularity. Despite the discovery that a beginner surgeon using navigation could reproduce the results of an expert TKA surgeon using navigation in a learning curve of 16 cases, there is varying evidence as to its effectiveness in improving alignment and functional outcomes in comparison to conventional techniques.
Multiple studies have reported that computer-assisted navigation is associated with improved alignment compared to conventional jig-based techniques.[27,28] However, the improved alignment achieved with navigation in these studies was not subsequently shown to affect patient reported outcome measures (PROMs). In a group of 60 patients who received bilateral TKA, performed with navigation in one knee and conventionally in the other, researchers determined there were no differences between the clinical outcomes at a mean follow-up of 8 years—this is despite documenting better alignment and fewer outliers of the lower limb and prosthetic component positions in the navigated knees.
Randomized controlled trials have not reported any differences in Knee Society Scores (KSS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Oxford Knee Scores (OKS), patient satisfaction scores postoperatively, or at 12.3 years of follow-up. Some researchers have recommended against its use in TKA after indications that the risks (femoral notching, pin site fracture) and increased costs were not justified by documented benefits.
Navigation can be useful in the setting of extra-articular femoral deformity or in situ intramedullary devices that would preclude use of standard intramedullary guides. Some proponents of navigation suggest that the elimination of intramedullary instrumentation itself results in a smaller increase of systemic inflammatory markers postoperatively. However, there is no conclusive evidence that this leads to a decreased risk of intraoperative or early postoperative complications compared to standard intramedullary jig techniques.
It may be that specific patient characteristics suggest the use of navigation in TKA in terms of cost savings and risk benefits. After examining outcomes of 44,573 navigated TKAs from 2003 till the end of 2012, de Steiger et al reported that younger patients (<65 years of age) experienced overall reduced revision rates and fewer revisions for prosthetic loosening compared with both younger and older patients that had non-navigated primary TKA.
Key points concerning navigation in TKA:
- Navigation in TKA has been shown to improve implant alignment and positioning compared to conventional techniques.
- Long-term follow-up indicates little difference in clinical outcomes between these groups.
A note on planning software for knees
Procedure planning software currently does not include the patella, even in its native form. (See Figure 2.) This is a feature that needs to be integrated in the future to help surgeons determine the optimal patellar resection and component position. Additionally, surgical robots and navigation should evolve to be able to provide a dynamic evaluation of knee motion that incorporates the kinetic data through the tibiofemoral and patellofemoral articulations to reflect our changing understanding of the relationships between these variables.
Although use of navigation for TKA is decreasing, robotic-assisted TKA is rapidly gaining popularity and acceptance. Having performed robot-assisted TKA, Justin Chang feels that “the robot allows surgeons to provide patient-specific alignment through dynamic assessment of joint gaps, intraoperative manipulation of planned component position, and accurate execution of bone cuts. For surgeons who perform a low volume of unicompartimental knee arthroplasty (UKA) and TKA, it is a reliable way to ensure accurate placement of components.”
Robotic arm-assisted TKA offers additional advantages compared to navigation including haptic feedback during bone cuts, and dynamic assessment of the soft tissue envelope. Similar to navigation, robotic arm assisted TKA has been associated with improved alignment compared to conventional TKA.[34,35] Robot-assisted TKA has also been reported to improve early outcomes including short-term pain, physical function, and overall satisfaction.[36,37]
A prospective cohort study comparing robot-assisted TKA to conventional jig-based TKA reported improved early functional recovery, decreased pain, and reduced time to hospital discharge. These improvements in early outcome measures are likely due to the decreased risk of injury to soft tissue envelope; haptic boundaries alert the surgeon to possible soft tissue injury via visual, auditory, and tactile feedback.[36–38]
One study compared bone and soft tissue injury in conventional TKA versus robot-assisted TKA by analyzing intraoperative photographs after tibial and femoral bone cuts. The authors concluded that robot-assisted TKA was associated with reduced bone and soft tissue injury compared to standard jig-based techniques.
Long-term outcomes for robotic assisted TKA have not yet been defined. A prospective randomized control trial comparing robotic TKA (n=975) and conventional TKA (n=990) did not detect any differences in functional outcome scores, aseptic loosening, complications, and overall survivorship at a minimum of 10 years follow-up. The authors did not recommend robotic TKA because of the additional operating time and expense. However, this was a single-surgeon study that utilized an autonomous robotic device that is unable to quantify soft tissue balance. The work by Prof Haddad and his team has demonstrated that the ability to dynamically assess the soft tissue envelope intraoperatively when balancing the knee as well as assist in determining the functional alignment for the individual is a key feature in other robotic systems that contributes to improved clinical outcomes.[37,40]
Despite the conflicting studies, there is optimism that future research will be able to demonstrate long-term benefits of robot-assisted TKA. “Robotic surgery is still relatively new and the effects on long-term survival have not been established, however mid-term results are encouraging,” says Justin Chang.
Key points in robot-assisted TKA
- Robot-assisted TKA appears to improve component alignment and reduce bone and soft tissue injury compared to conventional TKA.
- Early outcome measures are better in the robot-assisted group.
- Long-term studies are needed to determine if differences between the groups persist.
Navigation and robot-assisted unicompartimental knee arthroplasty
The choice of UKA versus TKA for medial compartment orthopedic arthroplasty is still widely debated. “Studies have suggested that the learning curve for robotic surgery is 6 cases for UKA and 7 cases for TKA. However, it does add to the operative time,” says Justin Chang. Proponents of UKA claim improved functional outcomes, decreased complications, and improved cost-effectiveness compared with TKA.[41,42] However, critics of UKA argue that TKA should be the preference due to improved survivorship and decreased revision rates.[42,43]
While navigation in UKA has been shown to improve postoperative alignment and reduce outliers in medial UKA,[44–46] an improvement in clinical outcomes remains to be proven.[45,47] In 2009, when Lim et al compared intraoperative navigation system measurements with postoperative radiological measurements, there was poor correlation and no postoperative axial limb alignment improvements were identified in the navigated group. Using postoperative CT measurements, a similar measurement mismatch was identified by others. The additional cost and complexity of navigated UKA has led some researchers to recommend against its use while others suggest it may have utility in minimally invasive UKA due to less blood loss compared to conventionally performed UKA.
However, there is optimism that improved component position and alignment with robot-assisted UKA will lead to improved functional outcomes and long-term survivorship; this may subsequently swing the pendulum in favor of UKA for single-compartment disease. See Figure 3. In Justin Chang’s opinion, “Robotic surgery for TKA/UKA is particularly useful if there is any extraarticular deformity or previous metalwork that contraindicates or complicates the use of standard instrumentation.”
Key points in navigation and robot-assisted UKA
- Navigated UKA functional outcomes not yet proven to be superior but better component alignment reported; reduced blood loss found in minimally invasive navigated UKA compared to unnavigated.
- Robot-assisted UKA improves implant alignment and positioning.
- Short-term functional measures appear better in robot UKA compared to conventional UKA; more research is required to see if these differences persist in the long term.
- Increased infection rates in robot-assisted UKA requires further study.
Early results for robotic UKA have been promising.[50–54] Radiographic analysis from a large randomized controlled trial comparing robot-assisted UKA to conventional UKA reported significantly improved implant positioning and alignment in the robotic group. Another prospective cohort study compared robotic UKA (n=73) to conventional jig based UKA (n=73) in 146 patients. The authors reported decreased postoperative pain, reduced opioid requirements, improved early functional rehabilitation, and shorter time to discharge in the robotic group. This is likely secondary to decreased iatrogenic soft tissue injury in robotic surgery.
For robotic UKA, mid-term term results are encouraging. A study analyzing data from the Australian Orthopaedic Association National Joint Arthroplasty Registry reported decreased revision rates at three years in patients who underwent UKA with the Stryker Mako robot-assisted Resotoris UKA implant versus those who had non-robot-assisted UKA. Researchers also reported improved short-term survivorship in the Mako robot-assisted UKAs compared to all other non-robotic UKA. However, it is worth noting that increased infection rate was observed in the robot-assisted UKAs which warrants further research into this matter.
Having used both robots and navigation in TKA, UKA, and THA, Justin Chang feels that “current evidence suggests that robotic-arm assisted surgery results in faster time to discharge, better early outcomes, less pain, and decreased opioid use in UKA and TKA. While mid-term results are promising, it is too early to know if it will lead to improvements in long-term functional outcomes and survivorship.”
CAOS in THA
Optimizing component position is critical in ensuring long-term survivorship in total hip arthroplasty (THA). Suboptimal component positioning can lead to instability, impingement, and accelerated wear regardless of bearing choice. The acetabular component is most susceptible to component malpositioning despite use of external alignment guides and anatomical landmarks such as the transverse acetabular ligament.[55,56]
Numerous factors contribute to acetabular component malpositioning, such as obesity, intraoperative positioning of the pelvis, and spinopelvic morphology, which is patient-specific and may make referencing the orientation of the acetabular component challenging intraoperatively.[57–59] [See previous Insights issue on acetabular cup placement] Computer navigation and robotic-assisted surgery for THA have gained popularity in attempts to optimize implant orientation.
Additional advantages of navigation and robotic surgery include restoring optimal leg length and offset, which are known to affect PROMs and patient satisfaction. “In THA, robot-assisted surgery and computer navigation have been shown to reduce the number of outliers in acetabular component position”, notes Justin Chang.
Navigation in THA
Computer navigation is used in THA to determine the position of the femur and pelvis. This requires accurate tracking to enable the computer to recognize the position of the femur and pelvis in space and in relation to one another. Optical tracking is the most common form of tracking; this method typically uses infrared stereoscopic technology where a light source emits a signal that is reflected and captured. A downside of optical tracking is potential line-of-sight issues, where the signal is blocked by physical objects such as drapes, equipment, or assistants. Electromagnetic tracking systems avoid line-of-sight issues but have fallen out of favor due to distortion of accurate electromagnetic signal while power tools are being used.
Computer navigation can either be image-based or imageless. Image-based systems typically use preoperative CT scans to improve the accuracy of intraoperative registration. Imaging modalities including fluoroscopy and ultrasonography have also been described.[60,61] Imageless systems rely on accurate intraoperative identification of the anterior pelvic plane and attachment of a reference tracking device. Multiple anatomical landmarks are then digitized to determine the plane of the pelvis. Imageless systems are typically more cost-effective as they negate the need for preoperative imaging. See Figure 4 for an example of surface registration.
Computer navigated THA has been shown in numerous studies to improve the precision and accuracy of acetabular component positioning. In particular, navigation was associated with decreased outliers compared to freehand techniques as defined by Lewinnek’s safe zone.[63–66] However, it has been pointed out that no matter how it is done, placement in the “safe zone” does not necessarily translate into improved stability.[67–69]
One meta-analysis reported a risk reduction of 37% when navigation was used compared to conventional techniques. There is also evidence that navigation can improve acetabular component positioning in obese patients and in cases of severe hip dysplasia.[71,72] On the femoral side, navigation was shown to successfully restore offset and leg length in 95.39% and 96.04% of patients, respectively.
Despite multiple studies suggesting improved component positioning, it is unclear if this leads to decreased complications or improved functional outcomes. A retrospective study analyzing the US Medicare database of 803,732 THAs, of which 14,540 were navigated THAs, reported a decreased rate of dislocation in navigated THA (1.00% vs 1.70%; p<.001) and aseptic revision of the acetabular component (1.03% vs 1.55%; p<.001) when compared to conventional THA. However, multiple randomized controlled trials comparing navigated THA to conventional THA did not report any difference in complication rates, radiographic outcomes, or patient reported outcome measures.[63,65,66,75]
Navigation in THA summary
- Navigated THA shown to improve acetabular component positioning and restore offset and leg length compared to conventional THA.
- Decreased rates of dislocation and aseptic revision in navigated THA have been documented.
- Not clear if functional outcomes are improved.
Robot-assisted THA is rapidly gaining popularity. The additional advantages of robotic surgery compared to navigated THA includes femoral and acetabular bony preparation and definitive component implantation. Preoperative CT scans are required for accurate bony registration and tracking of the pelvis and femur intraoperatively. The most used robotic systems for THA are haptic systems, where surgeons physically steer the robotic arm via a control console. Similar to robotic systems used in TKA/UKA, instrument movement outside pre-defined boundaries triggers an alert to the surgeon.
Initial results for robotic-assisted THA have been promising. Like computer navigation, robotic-assisted THA has also been reported to improved acetabular component positioning and decrease outliers.[76–78] A 2019 prospective cohort study reported that robotic THA showed improved accuracy within Lewinnek’s safe zones compared to conventional THA (96% vs 68%, respectively; p=.02). In addition, this study found that robotic THA was associated with improved restoration of native hip center (p<.001) and combined offset (p<.001).
There is also evidence that robot-assisted THA may lead to decreased early dislocation rates. A 2017 retrospective study analyzing 300 THAs, including 100 robotic THAs, reported a 0% dislocation rate in the robotic arm group and a 3.0–5.0% dislocation rate in the conventional group.
As robot-assisted THA is relatively new, very few studies have reported long-term functional outcomes. However, a 2018 study comparing robotic THA to conventional THA at a mean follow-up of 14 years reported small improvements in clinical outcomes in the robot group, while neither group had failures related to stem loosening. While it is premature to draw conclusions about the advantages of robot-assisted THA, there is promise that future research may demonstrate decreased complication rates and improved PROMS.
Robot-assisted THA summary
- Robot-assisted THAs benefit from femoral and acetabular bony preparation and definitive component implantation.
- Robot-assisted THAs may have lower dislocation rates.
- More long-term outcome studies needed but slight outcome improvements in robotic THA group reported.
Orthopedic surgeons recognize that a one-size-fits-all approach is not suitable—the unique aspects of each body warrant an individualized approach when planning and executing surgeries. Patient-specific instrumentation and/or implant (PSI) use has been pursued in the quest for improved outcomes, increased implant durability, and maintained or lowered implant costs. It can be a time consuming process, up to six weeks from scans to delivery,  with numerous steps: preoperative MRI or CT images are submitted to a manufacturer, a 3D digital image is constructed and used to design and test a suitable implant in VR, then the surgeon must approve before it is 3D printed. After quality control inspections, sterilization, packaging, and shipping, it arrives at the hospital for use.
Interestingly, in 2018 Hafez et al reported on a hospital-based workflow to produce PSI (custom-made cutting guides), noting that “the majority of developing countries are deprived from the privilege of using [PSI].” They were able to produce these PSI for bilateral TKA in an average of 3 to 5 days from imaging to finished product.
Every new technology requires time to determine if it is a safe and suitable option as well as accumulate evidence of advantages over conventional/traditional approaches. Compared with traditional TKA, one hospital reported a net savings of $736 per TKA with PSI, realized through shorter surgical times, lowered operating room (OR) turnover time, and fewer instrument trays: these savings offset the higher costs of preoperative imaging needed to produce the PSI.
However, ideas about potential benefits of PSI have not yet aligned with demonstrated functional outcome improvement or cost savings. Schwartzkopf et al concluded that using PSI was “associated with decreased estimated blood loss, decreased length of stay, decreased range of motion, and no discernible difference in surgical or tourniquet time…all of which are unlikely to be clinically significant.” Indeed, when compared with traditional implants, a survey of 15,000 orthopedic health professionals conducted in 2014 indicated that only 47% saw a benefit of PSI.
Customized tibial cutting guides in UKA may have been shown to assist in a obtaining a better coronal orientation of the tibial component, but decreased accuracy in setting optimal tray rotation and slope was also noted. While early results show accurate positioning with PSI, there are added costs and undetermined impact on clinical outcomes.
PSI in TKA: Cutting jig inaccuracies
There is considerable variation in implant positioning using standard instrumentation (SI) in TKA. It is commonly accepted that malalignment (>3 degrees) in the coronal plane leads to increased revision rates. It has been shown that using SI in TKA can result in more than 3 degrees of malalignment in as many as 30% of the cases.[88–90] Despite the strong push to use PSI over the last decade, evidence suggests that it is not the holy grail and should be used with caution.
Recently, there has been a decline in PSI use partly due to inaccuracies of the cutting jigs. In an 2017 article examining the advantages and pitfalls of PSI, based on the authors experience with PSI in TKA, they wrote that, “Some manufacturer's PSI tibial jig inaccuracy can range between 60% to an appalling 70%. The femoral jig usually has a higher degree of accuracy. The authors strongly recommend that the surgeon pays utmost attention to the tibial jig and the cut position.”
A recent meta-analysis concluded no significant difference between PSI and SI in TKA except in some improvement in the alignment of the femoral component. Others have suggested against the wide use of PSI in TKA. Overall the current evidence does not demonstrate either precise alignment[95–97] or superior clinical outcomes in the use of PSI.[95,98–100]
3D printed PSI and high tibial osteotomy
Relatively newly available are personalized implant components. The use of a PSI, in this case custom manufactured (3D printed) knee implants for TKA, was shown to reduce blood loss and length of hospital stay without impacting surgical or tourniquet time compared to conventionally performed procedures.
High tibial osteotomy (HTO) in young patients with isolated medial osteoarthritis has had good outcomes in delaying TKA. The rapid advances in 3D printing has allowed 3D printing of PSI for HTO. This technique has the additional benefit of aiding the surgeon in planning and performing corrective multiplanar osteotomies with more accuracy. So far, early results are encouraging and with time it may become widely used.
CAOS economic considerations
Whether intended for use in an OR or in a living room, all technology and machinery carry costs in addition to purchase price. For CAOS systems, maintenance, software updates, specific sterilization protocols, and training costs should factor into purchasing decisions. Some advanced robotic CAOS systems may also require reinforced OR floors to bear their weight safely.
A 2019 study reported that navigated TKAs were associated with higher hospital charges but robot-assisted TKAs were not. However, Kayani et al decreased inpatient stay by 30 hours in robot-assisted TKAs. Cost considerations are sensitive to variation in CAOS system costs, accuracy, and probability of revisions. There is just not enough data to rule conclusively for or against purchasing one of these systems. It is worth noting that US hospitals were more likely to have a robotic CAOS system if they were in competition with another hospital in their region.
Considerations before a CAOS purchase
Malham et al offered a list of guidelines for institutions considering the purchase of assistive technologies to be used in spinal fusion. However, many of their recommendations are general to CAS systems and therefore applicable to orthopedics. Preference to open platform systems is encouraged as these provide access to all software and hardware no matter what implant a surgeon chooses. In addition, imaging systems (eg, CT scanners, fluoroscopy) that have the highest degree of compatibility with as many navigation and robot platforms as possible to provide flexibility in future purchasing options should be purchased.
CAOS systems for use in hips and knees[105–112]
There are several products on the market that are specifically designed for hips and knees. Availability is dependent on where you are situated as approvals for use differs from country to country. Table 1 is a non-exhaustive selection of some of the products and a description of selected capabilities.
Table 1. A brief summary of selected CAOS systems currently used in orthopedics for navigation and robot-assisted hip and knee surgery.
Intellijoint KNEE™ is a surgeon-controlled navigation system that provides real-time measurements of surgical cutting guides during TKA. Measurements of varus/valgus, femoral flexion and tibial slope angles, and resection depth help align cutting guides in the sagittal and coronal planes. Supports a femur-or tibia-first workflow and is compatible with any major implant vendor. Does not require preoperative imaging or pins outside the incision.
Intellijoint HIP® is a surgeon-controlled, imageless navigation tool for THA that provides real-time, intraoperative measurements to facilitate implant alignment for accurate cup position, leg length, and offset. Is compatible with any major implant vendor and suitable for primary and revision THA with any standard surgical approach (direct anterior, lateral, posterior).
JointPoint™ is templating software that is used on a tablet computer. It offers preoperative digital templating for hips and knees as well as intraoperative analysis of offset and leg length, cup position, intertrochanteric fracture reduction and tip apex. It intended to decrease surgical time and fluoroscopy use.(
The Mako robotic surgical arm system combines 3D CT image-based planning with haptic feedback robotic technology. Digital planning is translated into a customized procedure as the robot provides feedback to the surgeon when they approach pre-determined boundaries to help maintain accuracy. Surgeons are guided through their plans for partial KA, TKA, and THA. It is only compatible with proprietary implants (RESTORIS).
NAVIO Surgical System
This semi-active, imageless navigation system has evolved over time from its initial use in UKA to include TKA and patellofemoral joint (PFJ) arthroplasty. Combines a planning software application with a lightweight robotic handheld tool for accurate bone preparation.
ROSA® Knee System
Surgeons have the option to use 2D x-ray or 3D bone modeling software for TKA surgical planning. The ROSA system is a closed platform (compatible with Zimmer’s Persona®, Vanguard®, and NexGen® implants), that combines the planning software with an autonomous robot that precisely places the cutting jigs on the patient.
As the first CAS used in orthopedic surgery, this active, autonomous robot (formerly Robodoc) has been used in TKA since 2000. It is a CT image-based, open platform robotic milling system for reproducing accurate component placement and the hip-knee-ankle mechanical axis. It combines image-based preoperative planning software with a robotic operative tool for THA and TKA.
While the use of CAOS systems in TKA, UKA, and THA has been shown to have both pros and cons, the general consensus is that more time and more well-designed studies are need to determine if the benefits of surgical accuracy translate into improved patient outcomes over the long term. Until this can be definitively proven or disproven, it is fair to say that the jury is still out.
However, Justin Chang points out that CAOS systems, particularly robots, “are very useful for research as alignment targets are accurate and precise, allowing for comparison between different alignment techniques. We are currently conducting a randomized controlled trial using robotic-arm assisted technology to compare mechanical and functional alignment for TKA.”
Part 3 of this article series looks ahead at what the future of CAOS could hold—will THAs and TKAs even need a human surgeon? Learn more about the direction researchers are taking CAOS development.
This series of articles was created with the support of the following specialists (in alphabetical order):
1. Price AJ, Alvand A, Troelsen A, et al.Knee replacement. Lancet. 2018 Nov 3;392(10158):1672–1682.
2. Kayani B, Pietrzak J, Hossain FS, et al. Prevention of limb length discrepancy in total hip arthroplasty. Br J Hosp Med (Lond). 2017 Jul 2;78(7):385–390.
3. Antonios JK, Korber S, Sivasundaram L, et al. Trends in computer navigation and robotic assistance for total knee arthroplasty in the United States: an analysis of patient and hospital factors. Arthroplast Today. 2019 Mar;5(1):88–95.
4. Boylan M, Suchman K, Vigdorchik J, et al. Technology-Assisted Hip and Knee Arthroplasties: An Analysis of Utilization Trends. J Arthroplasty. 2018 Apr;33(4):1019–1023.
5. de Steiger RN, Liu YL, Graves SE. Computer navigation for total knee arthroplasty reduces revision rate for patients less than sixty-five years of age. J Bone Joint Surg Am. 2015 Apr 15;97(8):635–642.
6. Hsiue PP, Chen CJ, Villalpando C, et al. Trends and patient factors associated with technology-assisted total hip arthroplasty in the United States from 2005 to 2014. Arthroplast Today. 2020 Mar;6(1):112–117 e111.
7. Loganath K, Adamson PD, Moss AJ. 'See one, do one, teach one': finding your mentor in academic medicine. Future Sci OA. 2019 May 3;5(4):Fso385.
8. Akhtar K, Sugand K, Sperrin M, et al. Training safer orthopedic surgeons. Construct validation of a virtual-reality simulator for hip fracture surgery. Acta Orthop. 2015 86(5):616–621.
9. Fritz T, Stachel N, Braun BJ. Evidence in surgical training—a review. Innov Surg Sci. 2019 Mar;4(1):7–13.
10. Kazarian GS, Lawrie CM, Barrack TN, et al. The Impact of Surgeon Volume and Training Status on Implant Alignment in Total Knee Arthroplasty. J Bone Joint Surg Am. 2019 Oct 2;101(19):1713–1723.
11. Casali MB, Blandino A, Del Sordo S, et al. Alleged malpractice in orthopaedics. Analysis of a series of medmal insurance claims. J Orthop Traumatol. 2018 Jul 27;19(1):7.
12. Harrison WD, Narayan B, Newton AW, et al. Litigation costs of wrong-site surgery and other non-technical errors in orthopaedic operating theatres. Ann R Coll Surg Engl. 2015 Nov;97(8):592–597.
13. Mouton J, Gauthé R, Ould-Slimane M, et al. Litigation in orthopedic surgery: What can we do to prevent it? Systematic analysis of 126 legal actions involving four university hospitals in France. Orthop Traumatol Surg Res. 2018 Feb;104(1):5–9.
14. St Pierre P. Editorial Commentary: Proficiency-Based Training: Are We Ready for a New Way to Train and Test Orthopaedic Surgeons? Arthroscopy. 2018 Jul;34(7):2199–2200.
15. Verhey JT, Haglin JM, Verhey EM, et al. Virtual, augmented, and mixed reality applications in orthopedic surgery. Int J Med Robot. 2020 Apr;16(2):e2067.
16. Keith K, Hansen DM, Johannessen MA. Perceived Value of a Skills Laboratory With Virtual Reality Simulator Training in Arthroscopy: A Survey of Orthopedic Surgery Residents. J Am Osteopath Assoc. 2018 Oct 1;118(10):667–672.
17. Shi J, Hou Y, Lin Y, et al. Role of Visuohaptic Surgical Training Simulator in Resident Education of Orthopedic Surgery. World Neurosurg. 2018 Mar;111:e98–e104.
18. Cecil J, Gupta A, Pirela-Cruz M. An advanced simulator for orthopedic surgical training. Int J Comput Assist Radiol Surg. 2018 Feb;13(2):305–319.
19. Pedersen P, Palm H, Ringsted C, et al. Virtual-reality simulation to assess performance in hip fracture surgery. Acta Orthop. 2014 Aug;85(4):403–407.
20. Kahlenberg CA, Nwachukwu BU, McLawhorn AS, et al. Patient Satisfaction After Total Knee Replacement: A Systematic Review. Hss j. 2018 Jul;14(2):192–201.
21. Noble PC, Conditt MA, Cook KF, et al. The John Insall Award: Patient expectations affect satisfaction with total knee arthroplasty. Clin Orthop Relat Res. 2006 Nov;452:35–43.
22. Milner CE. Is gait normal after total knee arthroplasty? Systematic review of the literature. J Orthop Sci. 2009 Jan;14(1):114–120.
23. Bourne RB, Chesworth BM, Davis AM, et al. Patient satisfaction after total knee arthroplasty: who is satisfied and who is not? Clin Orthop Relat Res. 2010 Jan;468(1):57–63.
24. Haddad FS, Horriat S. Robotic and other enhanced technologies: are we prepared for such innovation? Bone Joint J. 2019 Dec;101-b(12):1469–1471.
25. Gholson JJ, Duchman KR, Otero JE, et al. Computer Navigated Total Knee Arthroplasty: Rates of Adoption and Early Complications. J Arthroplasty. 2017 Jul;32(7):2113–2119.
26. Confalonieri N, Chemello C, Cerveri P, et al. Is computer-assisted total knee replacement for beginners or experts? Prospective study among three groups of patients treated by surgeons with different levels of experience. J Orthop Traumatol. 2012 Dec;13(4):203–210.
27. Spencer JM, Chauhan SK, Sloan K, et al. Computer navigation versus conventional total knee replacement: no difference in functional results at two years. J Bone Joint Surg Br. 2007 Apr;89(4):477–480.
28. Harvie P, Sloan K, Beaver RJ. Computer navigation vs conventional total knee arthroplasty: five-year functional results of a prospective randomized trial. J Arthroplasty. 2012 May;27(5):667–672.e661.
29. Hsu RW, Hsu WH, Shen WJ, et al. Comparison of computer-assisted navigation and conventional instrumentation for bilateral total knee arthroplasty: The outcomes at mid-term follow-up. Medicine (Baltimore). 2019 Nov;98(47):e18083.
30. Kim YH, Park JW, Kim JS. Computer-navigated versus conventional total knee arthroplasty a prospective randomized trial. J Bone Joint Surg Am. 2012 Nov 21;94(22):2017–2024.
31. Kim YH, Park JW, Kim JS. The Clinical Outcome of Computer-Navigated Compared with Conventional Knee Arthroplasty in the Same Patients: A Prospective, Randomized, Double-Blind, Long-Term Study. J Bone Joint Surg Am. 2017 Jun 21;99(12):989–996.
32. Kim YH, Park JW, Kim JS. 2017 Chitranjan S. Ranawat Award: Does Computer Navigation in Knee Arthroplasty Improve Functional Outcomes in Young Patients? A Randomized Study. Clin Orthop Relat Res. 2018 Jan;476(1):6–15.
33. Kuo SJ, Hsu HC, Wang CJ, et al. Effects of computer-assisted navigation versus conventional total knee arthroplasty on the levels of inflammation markers: A prospective study. PLoS One. 2018 13(5):e0197097.
34. Kayani B, Haddad FS. Robotic total knee arthroplasty: clinical outcomes and directions for future research. Bone Joint Res. 2019 Oct;8(10):438–442.
35. Song EK, Seon JK, Yim JH, et al. Robotic-assisted TKA reduces postoperative alignment outliers and improves gap balance compared to conventional TKA. Clin Orthop Relat Res. 2013 Jan;471(1):118–126.
36. Marchand RC, Sodhi N, Khlopas A, et al. Patient Satisfaction Outcomes after Robotic Arm-Assisted Total Knee Arthroplasty: A Short-Term Evaluation. J Knee Surg. 2017 Nov;30(9):849–853.
37. Kayani B, Konan S, Tahmassebi J, et al. Robotic-arm assisted total knee arthroplasty is associated with improved early functional recovery and reduced time to hospital discharge compared with conventional jig-based total knee arthroplasty: a prospective cohort study. Bone Joint J. 2018 Jul;100-b(7):930–937.
38. Kayani B, Konan S, Pietrzak JRT, et al. Iatrogenic Bone and Soft Tissue Trauma in Robotic-Arm Assisted Total Knee Arthroplasty Compared With Conventional Jig-Based Total Knee Arthroplasty: A Prospective Cohort Study and Validation of a New Classification System. J Arthroplasty. 2018 Aug;33(8):2496–2501.
39. Kim YH, Yoon SH, Park JW. Does Robotic-assisted TKA Result in Better Outcome Scores or Long-Term Survivorship Than Conventional TKA? A Randomized, Controlled Trial. Clin Orthop Relat Res. 2020 Feb;478(2):266–275.
40. Oussedik S, Abdel MP, Victor J, et al. Alignment in total knee arthroplasty. Bone Joint J. 2020 Mar;102-b(3):276–279.
41. Beard DJ, Davies LJ, Cook JA, et al. The clinical and cost-effectiveness of total versus partial knee replacement in patients with medial compartment osteoarthritis (TOPKAT): 5-year outcomes of a randomised controlled trial. Lancet. 2019 Aug 31;394(10200):746–756.
42. Wilson HA, Middleton R, Abram SGF, et al. Patient relevant outcomes of unicompartmental versus total knee replacement: systematic review and meta-analysis. Bmj. 2019 Feb 21;364:l352.
43. Evans JT, Walker RW, Evans JP, et al. How long does a knee replacement last? A systematic review and meta-analysis of case series and national registry reports with more than 15 years of follow-up. Lancet. 2019 Feb 16;393(10172):655–663.
44. Ma B, Rudan J, Chakravertty R, et al. Computer-assisted FluoroGuide navigation of unicompartmental knee arthroplasty. Can J Surg. 2009 Oct;52(5):379–385.
45. Konyves A, Willis-Owen CA, Spriggins AJ. The long-term benefit of computer-assisted surgical navigation in unicompartmental knee arthroplasty. J Orthop Surg Res. 2010 Dec 31;5:94.
46. Seon JK, Song EK, Park SJ, et al. Comparison of minimally invasive unicompartmental knee arthroplasty with or without a navigation system. J Arthroplasty. 2009 Apr;24(3):351–357.
47. Zhang Z, Zhu W, Zhu L, et al. Superior alignment but no difference in clinical outcome after minimally invasive computer-assisted unicompartmental knee arthroplasty (MICA-UKA). Knee Surg Sports Traumatol Arthrosc. 2016 Nov;24(11):3419–3424.
48. Lim MH, Tallay A, Bartlett J. Comparative study of the use of computer assisted navigation system for axial correction in medial unicompartmental knee arthroplasty. Knee Surg Sports Traumatol Arthrosc. 2009 Apr;17(4):341–346.
49. Dahabreh Z, Scholes CJ, Giuffre B, et al. Lack of agreement between computer navigation and post-operative 2-dimensional computed tomography (CT) measurements for component and limb alignment in total knee arthroplasty (TKA). Knee. 2016 Jan;23(1):137–143.
50. Kayani B, Konan S, Tahmassebi J, et al. An assessment of early functional rehabilitation and hospital discharge in conventional versus robotic-arm assisted unicompartmental knee arthroplasty: a prospective cohort study. Bone Joint J. 2019 Jan;101-b(1):24–33.
51. Bell SW, Anthony I, Jones B, et al. Improved Accuracy of Component Positioning with Robotic-Assisted Unicompartmental Knee Arthroplasty: Data from a Prospective, Randomized Controlled Study. J Bone Joint Surg Am. 2016 Apr 20;98(8):627–635.
52. Burger JA, Kleeblad LJ, Laas N, et al. Mid-term survivorship and patient-reported outcomes of robotic-arm assisted partial knee arthroplasty. Bone Joint J. 2020 Jan;102-b(1):108–116.
53. St Mart JP, de Steiger RN, Cuthbert A, et al. The three-year survivorship of robotically assisted versus non-robotically assisted unicompartmental knee arthroplasty. Bone Joint J. 2020 Mar;102-b(3):319–328.
54. Citak M, Suero EM, Citak M, et al. Unicompartmental knee arthroplasty: is robotic technology more accurate than conventional technique? Knee. 2013 Aug;20(4):268–271.
55. Padgett DE, Hendrix SL, Mologne TS, et al. Effectiveness of an acetabular positioning device in primary total hip arthroplasty. Hss j. 2005 Sep;1(1):64–67.
56. Digioia AM, 3rd, Jaramaz B, Plakseychuk AY, et al. Comparison of a mechanical acetabular alignment guide with computer placement of the socket. J Arthroplasty. 2002 Apr;17(3):359–364.
57. Stefl M, Lundergan W, Heckmann N, et al. Spinopelvic mobility and acetabular component position for total hip arthroplasty. Bone Joint J. 2017 Jan;99-b(1 Supple A):37–45.
58. Eftekhary N, Shimmin A, Lazennec JY, et al. A systematic approach to the hip-spine relationship and its applications to total hip arthroplasty. Bone Joint J. 2019 Jul;101-b(7):808–816.
59. Grammatopoulos G, Gofton W, Cochran M, et al. Pelvic positioning in the supine position leads to more consistent orientation of the acetabular component after total hip arthroplasty. Bone Joint J. 2018 Oct;100-b(10):1280–1288.
60. Parratte S, Kilian P, Pauly V, et al. The use of ultrasound in acquisition of the anterior pelvic plane in computer-assisted total hip replacement: a cadaver study. J Bone Joint Surg Br. 2008 Feb;90(2):258–263.
61. Hasart O, Perka C, Tohtz S. Comparison between pointer-based and ultrasound-based navigation technique in THA using a minimally invasive approach. Orthopedics. 2008 Oct;31(10 Suppl 1).
62. Saragaglia D, Rubens-Duval B, Gaillot J, et al. Total knee arthroplasties from the origin to navigation: history, rationale, indications. Int Orthop. 2019 Mar;43(3):597–604.
63. Kamenaga T, Hayashi S, Hashimoto S, et al. Accuracy of cup orientation and learning curve of the accelerometer-based portable navigation system for total hip arthroplasty in the supine position. J Orthop Surg (Hong Kong). 2019 May–Aug;27(2):2309499019848871.
64. Lass R, Kubista B, Olischar B, et al. Total hip arthroplasty using imageless computer-assisted hip navigation: a prospective randomized study. J Arthroplasty. 2014 Apr;29(4):786–791.
65. Parratte S, Argenson JN. Validation and usefulness of a computer-assisted cup-positioning system in total hip arthroplasty. A prospective, randomized, controlled study. J Bone Joint Surg Am. 2007 Mar;89(3):494–499.
66. Parratte S, Ollivier M, Lunebourg A, et al. No Benefit After THA Performed With Computer-assisted Cup Placement: 10-year Results of a Randomized Controlled Study. Clin Orthop Relat Res. 2016 Oct;474(10):2085–2093.
67. Abdel MP, von Roth P, Jennings MT, et al. What Safe Zone? The Vast Majority of Dislocated THAs Are Within the Lewinnek Safe Zone for Acetabular Component Position. Clin Orthop Relat Res. 2016 Feb;474(2):386–391.
68. Tezuka T, Heckmann ND, Bodner RJ, et al. Functional Safe Zone Is Superior to the Lewinnek Safe Zone for Total Hip Arthroplasty: Why the Lewinnek Safe Zone Is Not Always Predictive of Stability. J Arthroplasty. 2019 Jan;34(1):3–8.
69. Dorr LD, Callaghan JJ. Death of the Lewinnek "Safe Zone". J Arthroplasty. 2019 Jan;34(1):1–2.
70. Beckmann J, Stengel D, Tingart M, et al. Navigated cup implantation in hip arthroplasty. Acta Orthop. 2009 Oct;80(5):538–544.
71. Buller LT, McLawhorn AS, Romero JA, et al. Accuracy and Precision of Acetabular Component Placement With Imageless Navigation in Obese Patients. J Arthroplasty. 2019 Apr;34(4):693–699.
72. Ueoka K, Kabata T, Kajino Y, et al. The Accuracy of the Computed Tomography-Based Navigation System in Total Hip Arthroplasty Is Comparable With Crowe Type IV and Crowe Type I Dysplasia: A Case-Control Study. J Arthroplasty. 2019 Nov;34(11):2686–2691.
73. Ellapparadja P, Mahajan V, Deakin AH, et al. Reproduction of Hip Offset and Leg Length in Navigated Total Hip Arthroplasty: How Accurate Are We? J Arthroplasty. 2015 Jun;30(6):1002–1007.
74. Bohl DD, Nolte MT, Ong K, et al. Computer-Assisted Navigation Is Associated with Reductions in the Rates of Dislocation and Acetabular Component Revision Following Primary Total Hip Arthroplasty. J Bone Joint Surg Am. 2019 Feb 6;101(3):250–256.
75. Renkawitz T, Weber M, Springorum HR, et al. Impingement-free range of movement, acetabular component cover and early clinical results comparing 'femur-first' navigation and 'conventional' minimally invasive total hip arthroplasty: a randomised controlled trial. Bone Joint J. 2015 Jul;97-b(7):890–898.
76. Illgen R, Bukowski B, Abiola R, et al. Robotic-Assisted Total Hip Arthroplasty: Outcomes at Minimum Two-Year Follow-Up. Surg Technol Int. 2017 July;25(30):365–372.
77. Tsai TY, Dimitriou D, Li JS, et al. Does haptic robot-assisted total hip arthroplasty better restore native acetabular and femoral anatomy? Int J Med Robot. 2016 Jun;12(2):288–295.
78. Kayani B, Konan S, Thakrar RR, et al. Assuring the long-term total joint arthroplasty: a triad of variables. Bone Joint J. 2019 Jan;101-b(1_Supple_A):11–18.
79. Bargar WL, Parise CA, Hankins A, et al. Fourteen Year Follow-Up of Randomized Clinical Trials of Active Robotic-Assisted Total Hip Arthroplasty. J Arthroplasty. 2018 Mar;33(3):810–814.
80. Haglin JM, Eltorai AE, Gil JA, et al. Patient-Specific Orthopaedic Implants. Orthop Surg. 2016 Nov;8(4):417–424.
81. Hafez MA, Hamza H, Nabeel A. Hospital-based Patient-specific Templates for Total Knee Arthroplasty: A Proof of Concept Clinical Study. Tech Orthop. 2018 Dec;33(4):258–263.
82. DeHaan AM, Adams JR, DeHart ML, et al. Patient-specific versus conventional instrumentation for total knee arthroplasty: peri-operative and cost differences. J Arthroplasty. 2014 Nov;29(11):2065–2069.
83. Sadoghi P. Current concepts in total knee arthroplasty: Patient specific instrumentation. World J Orthop. 2015 Jul 18;6(6):446–448.
84. Schwarzkopf R, Brodsky M, Garcia GA, et al. Surgical and Functional Outcomes in Patients Undergoing Total Knee Replacement With Patient-Specific Implants Compared With "Off-the-Shelf" Implants. Orthop J Sports Med. 2015 Jul;3(7):2325967115590379.
85. PRWeb. Customized Joint Implants Popular Among Orthopedic Surgeons: Clinical Efficacy Important Internationally. http://www.prweb.com/releases/2015/02/prweb12509081.htm. Published 2015. Accessed April 29, 2020.
86. Heyse TJ, Lipman JD, Imhauser CW, et al. Accuracy of Individualized Custom Tibial Cutting Guides in UKA. Hss j. 2014 Oct;10(3):260–265.
87. Henckel J, Holme TJ, Radford W, et al. 3D-printed Patient-specific Guides for Hip Arthroplasty. J Am Acad Orthop Surg. 2018 Aug 15;26(16):e342–e348.
88. Petersen TL, Engh GA. Radiographic assessment of knee alignment after total knee arthroplasty. J Arthroplasty. 1988 3(1):67–72.
89. Mahaluxmivala J, Bankes MJ, Nicolai P, et al. The effect of surgeon experience on component positioning in 673 Press Fit Condylar posterior cruciate-sacrificing total knee arthroplasties. J Arthroplasty. 2001 Aug;16(5):635–640.
90. Mielke RK, Clemens U, Jens JH, et al. [Navigation in knee endoprosthesis implantation--preliminary experiences and prospective comparative study with conventional implantation technique]. Z Orthop Ihre Grenzgeb. 2001 Mar–Apr;139(2):109–116.
91. Clarke G, Wood D. Robotics in arthroplasty: where are we today? Bone Joint 360. 2015 4(5):2–7.
92. Hafez MA, Moholkar K. Patient-specific instruments: advantages and pitfalls. Sicot j. 2017 3:66.
93. Gong S, Xu W, Wang R, et al. Patient-specific instrumentation improved axial alignment of the femoral component, operative time and perioperative blood loss after total knee arthroplasty. Knee Surg Sports Traumatol Arthrosc. 2019 Apr;27(4):1083–1095.
94. Lachiewicz P. Patient specific instruments: Overpromised, underdelivered – affirms. Orthopaedic Proceedings.96-B. https://online.boneandjoint.org.uk/doi/abs/10.1302/1358-992X.96BSUPP_8.CCJR2013-072. Published February 21, 2018. Accessed April 6, 2020.
95. Nam D, Park A, Stambough JB, et al. The Mark Coventry Award: Custom Cutting Guides Do Not Improve Total Knee Arthroplasty Clinical Outcomes at 2 Years Followup. Clin Orthop Relat Res. 2016 Jan;474(1):40–46.
96. Mannan A, Smith TO, Sagar C, et al. No demonstrable benefit for coronal alignment outcomes in PSI knee arthroplasty: A systematic review and meta-analysis. Orthop Traumatol Surg Res. 2015 Jun;101(4):461–468.
97. Sassoon A, Nam D, Nunley R, et al. Systematic review of patient-specific instrumentation in total knee arthroplasty: new but not improved. Clin Orthop Relat Res. 2015 Jan;473(1):151–158.
98. Yan CH, Chiu KY, Ng FY, et al. Comparison between patient-specific instruments and conventional instruments and computer navigation in total knee arthroplasty: a randomized controlled trial. Knee Surg Sports Traumatol Arthrosc. 2015 Dec;23(12):3637–3645.
99. Goyal T, Tripathy SK. Does Patient-Specific Instrumentations Improve Short-Term Functional Outcomes After Total Knee Arthroplasty? A Systematic Review and Meta-Analysis. J Arthroplasty. 2016 Oct;31(10):2173–2180.
100. Huijbregts HJ, Khan RJ, Sorensen E, et al. Patient-specific instrumentation does not improve radiographic alignment or clinical outcomes after total knee arthroplasty. Acta Orthop. 2016 Aug;87(4):386–394.
101. Jones GG, Jaere M, Clarke S, et al. 3D printing and high tibial osteotomy. EFORT Open Rev. 2018 May;3(5):254–259.
102. Novak EJ, Silverstein MD, Bozic KJ. The cost-effectiveness of computer-assisted navigation in total knee arthroplasty. J Bone Joint Surg Am. 2007 Nov;89(11):2389–2397.
103. Wright JD, Tergas AI, Hou JY, et al. Effect of Regional Hospital Competition and Hospital Financial Status on the Use of Robotic-Assisted Surgery. JAMA Surg. 2016 Jul 1;151(7):612–620.
104. Malham GM, Wells-Quinn T. What should my hospital buy next? Guidelines for the acquisition and application of imaging, navigation, and robotics for spine surgery. J Spine Surg. 2019 Mar;5(1):155–165.
105. Allen M, Jacofsky D. Evolution of Robotics in Arthroplasty. In: Lonner JH, ed. Robotics in Knee and Hip Arthroplasty: Current Concepts, Techniques and Emerging Uses. Springer Nature Switzerland; 2019:13-25.
106. Aldinger G, Fischer A, Kurtz B. Computer-aided manufacture of individual endoprostheses. Preliminary communication. Arch Orthop Trauma Surg. 1983 102(1):31–35.
107. Börner M, Wiesel U, Ditzen W. Clinical Experiences with ROBODOC and the Duracon Total Knee. In: JB S, WH K, RG H, eds. Navigation and Robotics in Total Joint and Spine Surgery. Heidelberg, Germany: Springer; 2004:362–366.
108. Jakopec M, Harris SJ, Rodriguez y Baena F, et al. The first clinical application of a "hands-on" robotic knee surgery system. Comput Aided Surg. 2001 6(6):329–339.
109. Roche M. Robotic-assisted unicompartmental knee arthroplasty: the MAKO experience. Orthop Clin North Am. 2015 Jan;46(1):125–131.
110. Lonner JH. Robotically Assisted Unicompartmental Knee Arthroplasty with a Handheld Image-Free Sculpting Tool. Orthop Clin North Am. 2016 Jan;47(1):29–40.
111. Mazoochian F, Pellengahr C, Huber A, et al. Low accuracy of stem implantation in THR using the CASPAR-system: anteversion measurements in 10 hips. Acta Orthop Scand. 2004 Jun;75(3):261–264.
112. Liow MHL, Chin PL, Pang HN, et al. THINK surgical TSolution-One(®) (Robodoc) total knee arthroplasty. Sicot J. 2017 3:63.