Accuracy of a New Robotic System for Assisting in Total Knee Arthroplasty: A Cadaveric Study

Accuracy of a New Robotic System for Assisting in Total Knee Arthroplasty: A Cadaveric Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Accuracy of a New Robotic System for Assisting in Total Knee Arthroplasty: A Cadaveric Study Jiafeng Yi, Zhisen Gao, Yijian Huang, Yubo Liu, Yiling Zhang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4102446/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Robot-assisted total knee arthroplasty (TKA) has been shown to facilitate high-precision bone resection, an important goal in TKA. The aim of this cadaveric study was to analyse the accuracy of the target angle and bone resection thickness of a recently introduced robotic TKA system. Methods This study used 4 frozen cadaveric specimens (8 knees), 2 different implant designs (Johnson & Johnson and ICON), navigation, and a robotic system (ROPA TKA system, Longwood Valley MedTech). The 4 surgeons participating in this study were trained and familiar with the basic principles and operating procedures of this system. The angle of the bone cuts performed using the robotic system was compared with the target angles from the intraoperative plan. For each bone cut, the resection thickness was recorded and compared with the planned resection thickness. Results The mean angular difference for all specimens was less than 1°, and the standard deviation was less than 2°. The mean difference between the planned and measured angles was close to 0 and not significantly different from 0 except for the difference in the frontal tibial component angle, which was 0.88°. The mean difference in the hip-knee-ankle axis angle was -0.21°±1.06°. The mean bone resection difference for all specimens was less than 1 mm, and the standard deviation was less than 0.5 mm. Conclusions The results of our cadaveric experimental study show that surgeons using this new surgical robot in TKA can perform highly accurate bone cuts and achieve planned angles and resection thicknesses. Total knee arthroplasty Bone resection Robotic surgery Accuracy Cadaveric study. Figures Figure 1 Figure 2 Introduction Osteoarthritis is one of the most common joint diseases among elderly people. With the growing ageing population in China, the demand for total knee arthroplasty (TKA), a classic procedure for the treatment of terminal osteoarthritis, is bound to increase annually[1]. Despite the great improvements in prosthetic design, surgical instruments, surgical techniques and postoperative rehabilitation in recent years, there is still an unsatisfactory outcome rate of 10–20% after conventional TKA due to errors in surgical planning, poor prosthetics positioning, and inaccurate force line recovery[2]. Recent clinical studies have shown that robot-assisted TKA can improve the accuracy of intraoperative osteotomy and postoperative prosthetic positioning and thus restore the postoperative force line[3]. In recent years, with the continuous development of robotics and navigation technology, orthopaedic surgery robots have become increasingly accepted by the public. They have been introduced to reduce the number of alignment outliers and soft tissue damage and improve the accuracy of osteotomy in TKA[4]. Currently, the domestic application of orthopaedic surgical robots in China is still at an early stage. The most widely used robotic system in the domestic market is the MAKO robotic system, which is based on a semiactive closed platform from Stryker Corporation in the U.S. The FDA approved MAKO for TKA in 2008 and approved it for total hip arthroplasty (THA) in 2010[5]. In TKA, studies have shown that MAKO offers greater accuracy and reproducibility in prosthetic position planning, osteotomy volume control, gap balancing, and lower limb force line restoration[6, 7]. However, the higher economic costs and time-consuming data transfers associated with the MAKO robot limit its use, particularly in developing areas[8]. In recent years, China's domestic robots have also developed rapidly. The Bone Sheng Yuanhua Total Knee Replacement Assistive System (Yuanhua Robotics, Perception & AI Technologies Ltd., China), HURWA Knee Replacement Surgery Robotic System (Beijing HURWA Robotics Technology Co., Ltd.), and “SkyWalker” robotic system (MicroPort, China) have been verified through animal and cadaveric experiments, as well as multicentre randomized controlled trials completed at several large clinical centres. Therefore, these domestic robotic systems have promising prospects for application in TKA. The ROPA TKA system (Longwood Valley MedTech) is a robotic system in early development with mature technology that can be used to assist in TKA in China. In preliminary work, the accuracy and stability of the ROPA TKA system have been verified with a large amount of data[9]. The system is based on patients’ lower limb computed tomography (CT) data processed in an artificial intelligence-based surgical planning program[10], which has been used in 34 provinces and cities and more than 600 tertiary hospitals across China, providing approximately 10,000 cases of artificial intelligence-planned results. Additionally, the interface of the ROPA TKA system is friendly and does not necessitate planning by engineers, thus reducing both the planning process and related cost. Finally, the surgical program planning process is efficient, and CT data can be directly imported and to generate a planned program for the robot, which is convenient and efficient. The purpose of this study was to determine the osteotomy accuracy of this newly designed robotic system for assisting in TKA. Therefore, the accuracy of the following measurements was analysed relative to the target values in cadaveric experiments, as measured using a validated computer-assisted navigation system: the hip-knee-ankle axis (HKA) angle, coronal frontal femoral component (FFC) angle, frontal tibial component (FTC) angle, femoral valgus angle and posterior tibial slope (PTS). After each osteotomy, i.e., of the proximal tibial plateau, anterior and posterior condyles, and distal femur, the thickness of the cut was measured using a validated calliper. Materials and Methods Experimental specimens and main materials and instruments The bilateral lower extremities of four adult cadaveric specimens (8 knees) with intact hip, knee, and ankle joints were used in this study. The knee implants used were sourced from Johnson & Johnson and ICON. The osteotomy plan was created according to the preoperative software of the ROPA TKA system, and the implant prosthesis was installed after the robot-assisted osteotomy procedure was completed. The four surgeons participating in this study were knee arthroplasty specialists and familiar with the basic principles and operating procedures of the ROPA TKA system. To standardize the protocol, the target HKA angle was 180°, with 90° for both the tibial and femoral coronal angles. The femoral valgus angle was preoperatively set to 6°. Then compared with those of the bone cuts performed using the robotic system. For each bone cut, the resection thickness was measured with a calliper 3 times by 2 different observers and compared with the planned resection value[11]. Structure and working principle of the ROPA TKA robot The ROPA TKA system consists of three parts: the navigator, the robotic arm vehicle and the main control trolley. In the experimental process, the navigator recognizes and tracks the optical tracer and provides real-time feedback regarding the positions of the power tool and the surgical area to the main control trolley. The main control trolley is embedded in the software of the ROPA TKA system, which can complete the preoperative planning and merge the real-time data of the robotic arm trolley and navigator to execute intraoperative navigation algorithms. The end of the robotic arm trolley is connected to a power tool, and based on the navigational information, it recognizes the safe area for bone cutting. Based on the navigational information, the safe zone for osteotomy is identified, and the power and activity range of the power tool are restricted to prevent excessive osteotomy or accidental damage to the ligaments and other soft tissues around the knee joint, thus assisting the operator in completing precise and safe osteotomy operations. Robotic procedure A 3D CT scan of each experimental cadaver was performed before the beginning of the experiment, and the obtained data were imported into the preoperative planning software of the ROPA TKA system in DICOM format. Then, CT segmentation and 3D reconstruction were performed to obtain a 3D model of the femur and tibia of the cadaver. Subsequently, osteotomy program planning was performed, including the angle and thickness of the osteotomies of the distal femur, anterior and posterior condyles and tibia, as well as the types of femoral and tibial prosthetic implants. Experimental procedure: The surgeon performed preoperative planning with specialized software to determine the ideal resection thickness and angle for a balanced and well-aligned TKA procedure (Fig. 1 ). All cadaveric knee replacements were performed using the medial approach. The cadaveric specimen was fixed on the experimental table, and the skin and subcutaneous tissues were incised sequentially to fully reveal the distal femur, the anterior condyle and the tibial plateau. Two rigid body trackers were placed on each cadaveric knee, one on the femur and one on the tibia, to align the robot after the robot was calibrated (Fig. 2 ). The ROPA TKA system can display the relative positions of the femur and tibia as well as the osteotomy flexion and extension gaps in real time, at which point the surgeon can confirm the adjustment of the osteotomy parameters according to the soft tissue condition of the specimen. All planned angle and resection thickness values were recorded. The osteotomy robot was then used to perform the distal femoral cut first, followed by the tibial cut. During the osteotomy process, the ROPA TKA system automatically adjusts the position of the osteotomy saw blade to align it with the current osteotomy plane and limits the ability of the operator to complete the osteotomy operation within the current plane. To ensure the accuracy of the osteotomy and to protect important tissues such as the lateral collateral ligaments and blood vessels, the ROPA TKA system has a set safety limit: when the system detects that the osteotomy volume has exceeded the planned value by 1 mm or that the tip of the saw blade has touched the safety boundary of the current osteotomy, the pendulum saw will automatically stop and not continue the osteotomy. The surgeon will have to adjust the attitude of the pendulum saw to return it to the safe range before continuing the osteotomy operation. After the osteotomy was completed, the prosthetic trial mould was fitted. The prosthesis was fitted after the accuracy was confirmed, and the femoral and tibial tracers and fixation nails were then removed. Finally, the incision was closed. Measurement of angle and resection thickness After each cut with the ROPA TKA system, the thickness of the resected bone was measured using the dial calliper. Each cut was measured 3 times by 2 different independent observers. For each cadaver, the thickness of the cuts of the distal femur, anterior and posterior femoral condyles and proximal tibia was measured. To verify the accuracy of the prosthetic position, each specimen was examined by X-ray. The cadaveric specimen was placed in the lying position, with both lower limbs straightened, internally rotated by 15°, and the patella facing anteriorly. The joint position of the cadaveric specimen was fixed with sponge pads. Orthopantomographs of the hip, knee, and ankle joints were taken, and the DICOM files of the three radiographs were exported and merged to form a full-length radiograph of the lower limbs. Then, the image was imported into Image-Pro software, which was used to measure the postoperative HKA angle, FFC angle, FTC angle, and PTS. To ensure measurement accuracy and reduce measurement error, two nonparticipating orthopaedic surgeons with rich measurement experience obtained the measurements, and if the difference between two measurements was too large (≥ 0.5°), a third nonparticipating orthopaedic surgeon obtained the measurement, and the final result was taken as the mean of the two similar measurements. Statistical analysis Data were analysed using SPSS version 26 (IBM, Armonk, NY, USA). After the normality of data was checked, descriptive statistics (mean, standard deviation and extreme deviation) were calculated. Continuous data are expressed as the mean and standard deviation. The proportion of differences within ± 1° and ± 2° was calculated for alignment values. Similarly, the proportion of differences within ± 1 mm and ± 2 mm was calculated for resection thicknesses. Differences between the target and measured values were analysed by paired t test. P < 0.05 was considered to indicate statistical significance. Results For all 8 specimens, the differences between the target and measured angles were found to follow a normal distribution, as shown in Table 1 . In all cases, the mean difference was less than 1°, and the standard deviation was less than 2°. The mean difference between the planned and measured angles was close to 0 for all specimens and not significantly different from 0 except for the difference in the FTC angle, which was 0.88°. Similarly, all resection measurements are displayed in Table 2 . For all specimens, the mean difference was less than 1 mm, and the standard deviation was less than 0.5 mm. For all measurements, the mean difference between the planned and measured resection thicknesses was not significantly different from 0. Table 1 Difference Between Planned Angles and Measured Angles Angles Mean ± SD P Value Range (°) % Within 2° % Within 1° 99% PI HKA -0.21 ± 1.06 0.612 -1.8,1.1 100 62.5 -1.61, 1.19 FVA 0.28 ± 0.33 0.066 -0.3,0.8 100 100 -0.17, 0.72 FFC 0.6 ± 0.75 0.072 -1.1,1.3 100 50 -0.39, 1.59 FTC 0.88 ± 0.64 0.009 0.2,1.9 100 62.5 0.03,1.72 PTS 0.03 ± 0.29 0.829 -0.5,0.6 100 100 -0.36, 0.41 Table 2 Difference Between Planned Bone Resections and Bone Resections Measured With the Caliper Parameters Mean ± SD P Value Range (mm) % Within 2 mm % Within 1 mm 99% PI Distal femoral -0.05 ± 0.13 0.35 -0.4,0 100.00 100.00 -0.23, 0.13 Anterior femoral condyle 0.08 ± 0.45 0.67 -0.8,0.8 100.00 100.00 -0.52, 0.67 Posterior femoral condyle 0.08 ± 0.26 0.47 -0.2,0.5 100.00 100.00 -0.27, 0.42 Proximal tibial -0.05 ± 0.3 0.68 -0.5,0.5 100.00 100.00 -0.45, 0.35 Discussion The hypothesis for this study was that this newly designed robotic system (ROPA TKA system) would achieve high accuracy, with an average error within 1° for angular values and within 1 mm for resection thickness values. The results showed that the cuts performed with the ROPA TKA system were very accurate relative to the planned values. Regarding the resection angle, no significant differences were observed between the planned and measured values, except for a mean difference of 0.88° in the FTC angle. All angle error were within 1° of each other, with no significant differences. The mean difference in the HKA angle was calculated to be -0.21°± 1.06°. Compared with traditional surgery, surgery with orthopaedic robots can effectively improve surgical precision and assist doctors in bone cutting. Song et al. conducted a prospective randomized study of 50 conventional manual TKA versus 50 robotic TKA procedures and reported improved mechanical alignment accuracy and fewer outliers greater than 3° in planned alignment with robotic TKA compared to conventional manual TKA[12]. To verify the reliability and accuracy of the ROPA TKA system, this study comprised a knee osteotomy experiment based on cadaveric lower limb specimens. The results showed that the overall operation of the ROPA TKA system was stable and that the system could assist the operator in performing osteotomies according to the preoperative plan by helping control the osteotomy thickness and angle. In this experiment, the measured HKA angle and PTS values were within ± 2° of the values in the preoperative plan. Additionally, the errors between the measured and preoperatively planned osteotomy thicknesses were within 1 mm, which meets the requirements of clinical applications. Therefore, the results of this study effectively verify the accuracy and safety of the ROPA TKA system for future clinical application. Compared with the current MAKO system, which is the mainstream robotic assistance system for TKA, the ROPA TKA system used in this study was designed and optimized according to the needs of Chinese doctors. Therefore, it offers more user-friendly interaction and is more suitable for Chinese doctors’ operations and habits. At the same time, it is very convenient for surgical planning. The surgeon can import the patient's CT data directly into the robot to plan and generate a surgical scheme, which is convenient and efficient. This study also has several limitations. First, while the purpose of the study was to assess the accuracy of osteotomy, only the lower limb force line and femoral and tibial prosthetic angles were studied, which did not allow the relevant functions of the knee joint to be assessed. Thus, further clinical research is needed. Second, full-length radiographs of the lower extremities in the standing position could not be obtained in this study due to the limitations of the study subjects; therefore, three-joint orthopantomographs obtained in the supine position were spliced instead, which affects the accuracy and reliability of the experimental results to a certain extent. A third limitation is that we used cadaveric specimens, which typically exhibit less osteoarthritis and deformity than clinical cases. Despite the large gap between clinical cases and cadaveric specimens, the ability of cadaveric specimens and clinical cases to allow the evaluation of surfaces prosthetic implantation accuracy is very similar. A fourth limitation arises from the recording performance of optical navigation systems that depend on instrumental accuracy. The gold standard for current navigation technology in similar systems is an angular accuracy of 0.4 and a dimensional accuracy of 1 mm[13]. The fifth limitation is the lack of measurements related to the rotational alignment of the implant in this study. Implant cementation and three-dimensional postoperative CT scanning were not performed to verify the rotation of the prosthesis because this would introduce a potential bias in the quality of fixation of uncemented and cemented implants, which is inconsistent with the ultimate goal of validating the accuracy of the robotic system for osteotomy. Conclusion The ROPA TKA system can assist the operator in planning accurate osteotomies and realizing the planned prosthetic placement position and angulation, which is a favourable adjunct to TKA. Further in vivo studies are needed before further clinical application, first, to investigate whether the accuracy observed in this cadaveric study can be replicated in clinical studies, and second, to investigate other potential advantages of the system, such as time savings, optimization of implant positioning and improvements in patient-reported outcomes. Statements and Declarations Funding: Beijing Municipal Science and Technology Commission, Adminitrative Commission of Zhongguancun Science Park Fund (Z221100003522014). National Natural Science Foundation of China (U22A20355) Key Technologies Research and Development Program (2021YFC2401303) Statement of data availability The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Ethics Approval This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Chinese PLA General Hospital.” Consent to participate Informed consent was obtained from all individual participants included in the study. Author contributions: Manuscript preparation: Jiafeng Yi, Zhisen Gao, Yijian Huang, Yubo Liu, Yiling Zhang and Wei Chai. Data collection: Jiafeng Yi. Data interpretation: Jiafeng Yi, Zhisen Gao, Yijian Huang and Yubo Liu. Hypothesis generation: Yiling Zhang and Wei Chai. Statistical analysis: Yijian Huang. References Panjwani TR, Mullaji A, Doshi K, Thakur H. Comparison of functional outcomes of computer-assisted vs conventional total knee arthroplasty: A systematic review and meta-analysis of high-quality, prospective studies. J Arthroplasty 2019;34:3:586-93 https://doi.org/10.1016/j.arth.2018.11.028. Goh GS, Liow MHL, Bin Abd Razak HR, Tay DK, Lo NN, Yeo SJ. Patient-reported outcomes, quality of life, and satisfaction rates in young patients aged 50 years or younger after total knee arthroplasty. J Arthroplasty 2017;32:2:419-25 https://doi.org/10.1016/j.arth.2016.07.043. Liow MH, Xia Z, Wong MK, Tay KJ, Yeo SJ, Chin PL. Robot-assisted total knee arthroplasty accurately restores the joint line and mechanical axis. A prospective randomised study. J Arthroplasty 2014;29:12:2373-7 https://doi.org/10.1016/j.arth.2013.12.010. Ren Y, Cao S, Wu J, Weng X, Feng B. Efficacy and reliability of active robotic-assisted total knee arthroplasty compared with conventional total knee arthroplasty: A systematic review and meta-analysis. Postgrad Med J 2019;95:1121:125-33 https://doi.org/10.1136/postgradmedj-2018-136190. Subramanian P, Wainwright TW, Bahadori S, Middleton RG. A review of the evolution of robotic-assisted total hip arthroplasty. Hip Int 2019;29:3:232-8 https://doi.org/10.1177/1120700019828286. Deckey DG, Rosenow CS, Verhey JT, Brinkman JC, Mayfield CK, Clarke HD et al. Robotic-assisted total knee arthroplasty improves accuracy and precision compared to conventional techniques. Bone Joint J 2021;103-b:6 Supple A:74-80 https://doi.org/10.1302/0301-620x.103b6.Bjj-2020-2003.R1. Kayani B, Tahmassebi J, Ayuob A, Konan S, Oussedik S, Haddad FS. A prospective randomized controlled trial comparing the systemic inflammatory response in conventional jig-based total knee arthroplasty versus robotic-arm assisted total knee arthroplasty. Bone Joint J 2021;103-b:1:113-22 https://doi.org/10.1302/0301-620x.103b1.Bjj-2020-0602.R2. Ezeokoli EU, John J, Gupta R, Jawad A, Cavinatto L. Index surgery and ninety day re-operation cost comparison of robotic-assisted versus manual total knee arthroplasty. Int Orthop 2023;47:2:359-64 https://doi.org/10.1007/s00264-022-05674-w. Wu D, Zhi X, Liu X, Zhang Y, Chai W. Utility of a novel integrated deep convolutional neural network for the segmentation of hip joint from computed tomography images in the preoperative planning of total hip arthroplasty. J Orthop Surg Res 2022;17:1:164 https://doi.org/10.1186/s13018-022-02932-w. Huo J, Huang G, Han D, Wang X, Bu Y, Chen Y et al. Value of 3d preoperative planning for primary total hip arthroplasty based on artificial intelligence technology. J Orthop Surg Res 2021;16:1:156 https://doi.org/10.1186/s13018-021-02294-9. Biant LC, Yeoh K, Walker PM, Bruce WJ, Walsh WR. The accuracy of bone resections made during computer navigated total knee replacement. Do we resect what the computer plans we resect? Knee 2008;15:3:238-41 https://doi.org/10.1016/j.knee.2008.01.012. Song EK, Seon JK, Yim JH, Netravali NA, Bargar WL. Robotic-assisted tka reduces postoperative alignment outliers and improves gap balance compared to conventional tka. Clin Orthop Relat Res 2013;471:1:118-26 https://doi.org/10.1007/s11999-012-2407-3. Lustig S, Fleury C, Goy D, Neyret P, Donell ST. The accuracy of acquisition of an imageless computer-assisted system and its implication for knee arthroplasty. Knee 2011;18:1:15-20 https://doi.org/10.1016/j.knee.2009.12.010. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 28 Mar, 2024 Reviews received at journal 17 Mar, 2024 Reviewers agreed at journal 17 Mar, 2024 Reviewers agreed at journal 15 Mar, 2024 Reviewers agreed at journal 15 Mar, 2024 Reviewers invited by journal 15 Mar, 2024 Editor assigned by journal 15 Mar, 2024 Submission checks completed at journal 15 Mar, 2024 First submitted to journal 14 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4102446","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":280560095,"identity":"c41d72f6-6e9e-42aa-a3d3-146b360c2056","order_by":0,"name":"Jiafeng Yi","email":"","orcid":"","institution":"Nankai University","correspondingAuthor":false,"prefix":"","firstName":"Jiafeng","middleName":"","lastName":"Yi","suffix":""},{"id":280560097,"identity":"8221f825-00f4-494f-9490-618e45a5a67f","order_by":1,"name":"Zhisen Gao","email":"","orcid":"","institution":"The Fourth Medical Center of Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zhisen","middleName":"","lastName":"Gao","suffix":""},{"id":280560100,"identity":"92d4b0ce-0524-40da-9a1c-dfc64f95695d","order_by":2,"name":"Yijian Huang","email":"","orcid":"","institution":"Medical School of Chinese PLA","correspondingAuthor":false,"prefix":"","firstName":"Yijian","middleName":"","lastName":"Huang","suffix":""},{"id":280560102,"identity":"050d9e3d-74df-48aa-838d-7e4b63464aad","order_by":3,"name":"Yubo Liu","email":"","orcid":"","institution":"Nankai University","correspondingAuthor":false,"prefix":"","firstName":"Yubo","middleName":"","lastName":"Liu","suffix":""},{"id":280560104,"identity":"003e4421-99aa-4aee-ae23-1d2b79da3da8","order_by":4,"name":"Yiling Zhang","email":"","orcid":"","institution":"Longwood Valley Medical Technology Co. 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Once the cutting jig is set and fixed in the correct position, the surgeon performs the cuts.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4102446/v1/44a359ba288904d21174e913.png"},{"id":53006139,"identity":"f4f13c8b-0cae-4cd1-bc52-5cd19d428f9d","added_by":"auto","created_at":"2024-03-19 15:06:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1699739,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4102446/v1/d3086d04-da23-431a-bcc7-b50eba333721.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Accuracy of a New Robotic System for Assisting in Total Knee Arthroplasty: A Cadaveric Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOsteoarthritis is one of the most common joint diseases among elderly people. With the growing ageing population in China, the demand for total knee arthroplasty (TKA), a classic procedure for the treatment of terminal osteoarthritis, is bound to increase annually[1]. Despite the great improvements in prosthetic design, surgical instruments, surgical techniques and postoperative rehabilitation in recent years, there is still an unsatisfactory outcome rate of 10\u0026ndash;20% after conventional TKA due to errors in surgical planning, poor prosthetics positioning, and inaccurate force line recovery[2]. Recent clinical studies have shown that robot-assisted TKA can improve the accuracy of intraoperative osteotomy and postoperative prosthetic positioning and thus restore the postoperative force line[3].\u003c/p\u003e \u003cp\u003eIn recent years, with the continuous development of robotics and navigation technology, orthopaedic surgery robots have become increasingly accepted by the public. They have been introduced to reduce the number of alignment outliers and soft tissue damage and improve the accuracy of osteotomy in TKA[4].\u003c/p\u003e \u003cp\u003eCurrently, the domestic application of orthopaedic surgical robots in China is still at an early stage. The most widely used robotic system in the domestic market is the MAKO robotic system, which is based on a semiactive closed platform from Stryker Corporation in the U.S. The FDA approved MAKO for TKA in 2008 and approved it for total hip arthroplasty (THA) in 2010[5]. In TKA, studies have shown that MAKO offers greater accuracy and reproducibility in prosthetic position planning, osteotomy volume control, gap balancing, and lower limb force line restoration[6, 7]. However, the higher economic costs and time-consuming data transfers associated with the MAKO robot limit its use, particularly in developing areas[8].\u003c/p\u003e \u003cp\u003eIn recent years, China's domestic robots have also developed rapidly. The Bone Sheng Yuanhua Total Knee Replacement Assistive System (Yuanhua Robotics, Perception \u0026amp; AI Technologies Ltd., China), HURWA Knee Replacement Surgery Robotic System (Beijing HURWA Robotics Technology Co., Ltd.), and \u0026ldquo;SkyWalker\u0026rdquo; robotic system (MicroPort, China) have been verified through animal and cadaveric experiments, as well as multicentre randomized controlled trials completed at several large clinical centres. Therefore, these domestic robotic systems have promising prospects for application in TKA.\u003c/p\u003e \u003cp\u003eThe ROPA TKA system (Longwood Valley MedTech) is a robotic system in early development with mature technology that can be used to assist in TKA in China. In preliminary work, the accuracy and stability of the ROPA TKA system have been verified with a large amount of data[9]. The system is based on patients\u0026rsquo; lower limb computed tomography (CT) data processed in an artificial intelligence-based surgical planning program[10], which has been used in 34 provinces and cities and more than 600 tertiary hospitals across China, providing approximately 10,000 cases of artificial intelligence-planned results. Additionally, the interface of the ROPA TKA system is friendly and does not necessitate planning by engineers, thus reducing both the planning process and related cost. Finally, the surgical program planning process is efficient, and CT data can be directly imported and to generate a planned program for the robot, which is convenient and efficient.\u003c/p\u003e \u003cp\u003eThe purpose of this study was to determine the osteotomy accuracy of this newly designed robotic system for assisting in TKA. Therefore, the accuracy of the following measurements was analysed relative to the target values in cadaveric experiments, as measured using a validated computer-assisted navigation system: the hip-knee-ankle axis (HKA) angle, coronal frontal femoral component (FFC) angle, frontal tibial component (FTC) angle, femoral valgus angle and posterior tibial slope (PTS). After each osteotomy, i.e., of the proximal tibial plateau, anterior and posterior condyles, and distal femur, the thickness of the cut was measured using a validated calliper.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eExperimental specimens and main materials and instruments\u003c/h2\u003e \u003cp\u003eThe bilateral lower extremities of four adult cadaveric specimens (8 knees) with intact hip, knee, and ankle joints were used in this study. The knee implants used were sourced from Johnson \u0026amp; Johnson and ICON. The osteotomy plan was created according to the preoperative software of the ROPA TKA system, and the implant prosthesis was installed after the robot-assisted osteotomy procedure was completed. The four surgeons participating in this study were knee arthroplasty specialists and familiar with the basic principles and operating procedures of the ROPA TKA system. To standardize the protocol, the target HKA angle was 180\u0026deg;, with 90\u0026deg; for both the tibial and femoral coronal angles. The femoral valgus angle was preoperatively set to 6\u0026deg;. Then compared with those of the bone cuts performed using the robotic system. For each bone cut, the resection thickness was measured with a calliper 3 times by 2 different observers and compared with the planned resection value[11].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStructure and working principle of the ROPA TKA robot\u003c/h2\u003e \u003cp\u003eThe ROPA TKA system consists of three parts: the navigator, the robotic arm vehicle and the main control trolley. In the experimental process, the navigator recognizes and tracks the optical tracer and provides real-time feedback regarding the positions of the power tool and the surgical area to the main control trolley. The main control trolley is embedded in the software of the ROPA TKA system, which can complete the preoperative planning and merge the real-time data of the robotic arm trolley and navigator to execute intraoperative navigation algorithms. The end of the robotic arm trolley is connected to a power tool, and based on the navigational information, it recognizes the safe area for bone cutting. Based on the navigational information, the safe zone for osteotomy is identified, and the power and activity range of the power tool are restricted to prevent excessive osteotomy or accidental damage to the ligaments and other soft tissues around the knee joint, thus assisting the operator in completing precise and safe osteotomy operations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eRobotic procedure\u003c/h2\u003e \u003cp\u003eA 3D CT scan of each experimental cadaver was performed before the beginning of the experiment, and the obtained data were imported into the preoperative planning software of the ROPA TKA system in DICOM format. Then, CT segmentation and 3D reconstruction were performed to obtain a 3D model of the femur and tibia of the cadaver. Subsequently, osteotomy program planning was performed, including the angle and thickness of the osteotomies of the distal femur, anterior and posterior condyles and tibia, as well as the types of femoral and tibial prosthetic implants.\u003c/p\u003e \u003cp\u003eExperimental procedure: The surgeon performed preoperative planning with specialized software to determine the ideal resection thickness and angle for a balanced and well-aligned TKA procedure (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All cadaveric knee replacements were performed using the medial approach. The cadaveric specimen was fixed on the experimental table, and the skin and subcutaneous tissues were incised sequentially to fully reveal the distal femur, the anterior condyle and the tibial plateau. Two rigid body trackers were placed on each cadaveric knee, one on the femur and one on the tibia, to align the robot after the robot was calibrated (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The ROPA TKA system can display the relative positions of the femur and tibia as well as the osteotomy flexion and extension gaps in real time, at which point the surgeon can confirm the adjustment of the osteotomy parameters according to the soft tissue condition of the specimen. All planned angle and resection thickness values were recorded. The osteotomy robot was then used to perform the distal femoral cut first, followed by the tibial cut.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDuring the osteotomy process, the ROPA TKA system automatically adjusts the position of the osteotomy saw blade to align it with the current osteotomy plane and limits the ability of the operator to complete the osteotomy operation within the current plane. To ensure the accuracy of the osteotomy and to protect important tissues such as the lateral collateral ligaments and blood vessels, the ROPA TKA system has a set safety limit: when the system detects that the osteotomy volume has exceeded the planned value by 1 mm or that the tip of the saw blade has touched the safety boundary of the current osteotomy, the pendulum saw will automatically stop and not continue the osteotomy. The surgeon will have to adjust the attitude of the pendulum saw to return it to the safe range before continuing the osteotomy operation. After the osteotomy was completed, the prosthetic trial mould was fitted. The prosthesis was fitted after the accuracy was confirmed, and the femoral and tibial tracers and fixation nails were then removed. Finally, the incision was closed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement of angle and resection thickness\u003c/h2\u003e \u003cp\u003eAfter each cut with the ROPA TKA system, the thickness of the resected bone was measured using the dial calliper. Each cut was measured 3 times by 2 different independent observers. For each cadaver, the thickness of the cuts of the distal femur, anterior and posterior femoral condyles and proximal tibia was measured.\u003c/p\u003e \u003cp\u003eTo verify the accuracy of the prosthetic position, each specimen was examined by X-ray. The cadaveric specimen was placed in the lying position, with both lower limbs straightened, internally rotated by 15\u0026deg;, and the patella facing anteriorly. The joint position of the cadaveric specimen was fixed with sponge pads. Orthopantomographs of the hip, knee, and ankle joints were taken, and the DICOM files of the three radiographs were exported and merged to form a full-length radiograph of the lower limbs. Then, the image was imported into Image-Pro software, which was used to measure the postoperative HKA angle, FFC angle, FTC angle, and PTS. To ensure measurement accuracy and reduce measurement error, two nonparticipating orthopaedic surgeons with rich measurement experience obtained the measurements, and if the difference between two measurements was too large (\u0026ge;\u0026thinsp;0.5\u0026deg;), a third nonparticipating orthopaedic surgeon obtained the measurement, and the final result was taken as the mean of the two similar measurements.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData were analysed using SPSS version 26 (IBM, Armonk, NY, USA). After the normality of data was checked, descriptive statistics (mean, standard deviation and extreme deviation) were calculated. Continuous data are expressed as the mean and standard deviation. The proportion of differences within \u0026plusmn;\u0026thinsp;1\u0026deg; and \u0026plusmn;\u0026thinsp;2\u0026deg; was calculated for alignment values. Similarly, the proportion of differences within \u0026plusmn;\u0026thinsp;1 mm and \u0026plusmn;\u0026thinsp;2 mm was calculated for resection thicknesses. Differences between the target and measured values were analysed by paired t test. P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to indicate statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eFor all 8 specimens, the differences between the target and measured angles were found to follow a normal distribution, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In all cases, the mean difference was less than 1\u0026deg;, and the standard deviation was less than 2\u0026deg;. The mean difference between the planned and measured angles was close to 0 for all specimens and not significantly different from 0 except for the difference in the FTC angle, which was 0.88\u0026deg;. Similarly, all resection measurements are displayed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. For all specimens, the mean difference was less than 1 mm, and the standard deviation was less than 0.5 mm. For all measurements, the mean difference between the planned and measured resection thicknesses was not significantly different from 0.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifference Between Planned Angles and Measured Angles\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAngles\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRange (\u0026deg;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e% Within 2\u0026deg;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e% Within 1\u0026deg;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e99% PI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHKA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.8,1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e62.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.61, 1.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.3,0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.17, 0.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFFC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.1,1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.39, 1.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2,1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e62.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.03,1.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePTS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.5,0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.36, 0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifference Between Planned Bone Resections and Bone Resections Measured With the Caliper\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRange (mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e% Within 2 mm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e% Within 1 mm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e99% PI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistal femoral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.4,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.23, 0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnterior femoral condyle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.8,0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.52, 0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePosterior femoral condyle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.2,0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.27, 0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProximal tibial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.5,0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.45, 0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe hypothesis for this study was that this newly designed robotic system (ROPA TKA system) would achieve high accuracy, with an average error within 1\u0026deg; for angular values and within 1 mm for resection thickness values. The results showed that the cuts performed with the ROPA TKA system were very accurate relative to the planned values. Regarding the resection angle, no significant differences were observed between the planned and measured values, except for a mean difference of 0.88\u0026deg; in the FTC angle. All angle error were within 1\u0026deg; of each other, with no significant differences. The mean difference in the HKA angle was calculated to be -0.21\u0026deg;\u0026plusmn; 1.06\u0026deg;.\u003c/p\u003e \u003cp\u003eCompared with traditional surgery, surgery with orthopaedic robots can effectively improve surgical precision and assist doctors in bone cutting. Song et al. conducted a prospective randomized study of 50 conventional manual TKA versus 50 robotic TKA procedures and reported improved mechanical alignment accuracy and fewer outliers greater than 3\u0026deg; in planned alignment with robotic TKA compared to conventional manual TKA[12]. To verify the reliability and accuracy of the ROPA TKA system, this study comprised a knee osteotomy experiment based on cadaveric lower limb specimens. The results showed that the overall operation of the ROPA TKA system was stable and that the system could assist the operator in performing osteotomies according to the preoperative plan by helping control the osteotomy thickness and angle. In this experiment, the measured HKA angle and PTS values were within \u0026plusmn;\u0026thinsp;2\u0026deg; of the values in the preoperative plan. Additionally, the errors between the measured and preoperatively planned osteotomy thicknesses were within 1 mm, which meets the requirements of clinical applications. Therefore, the results of this study effectively verify the accuracy and safety of the ROPA TKA system for future clinical application.\u003c/p\u003e \u003cp\u003eCompared with the current MAKO system, which is the mainstream robotic assistance system for TKA, the ROPA TKA system used in this study was designed and optimized according to the needs of Chinese doctors. Therefore, it offers more user-friendly interaction and is more suitable for Chinese doctors\u0026rsquo; operations and habits. At the same time, it is very convenient for surgical planning. The surgeon can import the patient's CT data directly into the robot to plan and generate a surgical scheme, which is convenient and efficient.\u003c/p\u003e \u003cp\u003eThis study also has several limitations. First, while the purpose of the study was to assess the accuracy of osteotomy, only the lower limb force line and femoral and tibial prosthetic angles were studied, which did not allow the relevant functions of the knee joint to be assessed. Thus, further clinical research is needed.\u003c/p\u003e \u003cp\u003eSecond, full-length radiographs of the lower extremities in the standing position could not be obtained in this study due to the limitations of the study subjects; therefore, three-joint orthopantomographs obtained in the supine position were spliced instead, which affects the accuracy and reliability of the experimental results to a certain extent.\u003c/p\u003e \u003cp\u003eA third limitation is that we used cadaveric specimens, which typically exhibit less osteoarthritis and deformity than clinical cases. Despite the large gap between clinical cases and cadaveric specimens, the ability of cadaveric specimens and clinical cases to allow the evaluation of surfaces prosthetic implantation accuracy is very similar.\u003c/p\u003e \u003cp\u003eA fourth limitation arises from the recording performance of optical navigation systems that depend on instrumental accuracy. The gold standard for current navigation technology in similar systems is an angular accuracy of 0.4 and a dimensional accuracy of 1 mm[13].\u003c/p\u003e \u003cp\u003eThe fifth limitation is the lack of measurements related to the rotational alignment of the implant in this study. Implant cementation and three-dimensional postoperative CT scanning were not performed to verify the rotation of the prosthesis because this would introduce a potential bias in the quality of fixation of uncemented and cemented implants, which is inconsistent with the ultimate goal of validating the accuracy of the robotic system for osteotomy.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe ROPA TKA system can assist the operator in planning accurate osteotomies and realizing the planned prosthetic placement position and angulation, which is a favourable adjunct to TKA. Further in vivo studies are needed before further clinical application, first, to investigate whether the accuracy observed in this cadaveric study can be replicated in clinical studies, and second, to investigate other potential advantages of the system, such as time savings, optimization of implant positioning and improvements in patient-reported outcomes.\u0026nbsp;\u003c/p\u003e"},{"header":"Statements and Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eBeijing Municipal Science and Technology Commission, Adminitrative Commission of Zhongguancun Science Park Fund\u0026nbsp;(Z221100003522014).\u003c/li\u003e\n \u003cli\u003eNational Natural Science Foundation of China (U22A20355)\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eKey Technologies Research and Development Program (2021YFC2401303)\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eStatement of data availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Chinese PLA General Hospital.”\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eManuscript preparation:\u0026nbsp;Jiafeng Yi,\u0026nbsp;Zhisen Gao,\u0026nbsp;Yijian Huang,\u0026nbsp;Yubo Liu,\u0026nbsp;Yiling Zhang\u0026nbsp;and Wei Chai.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData collection:\u0026nbsp;Jiafeng Yi.\u003c/p\u003e\n\u003cp\u003eData interpretation:\u0026nbsp;Jiafeng Yi,\u0026nbsp;Zhisen Gao, Yijian Huang\u0026nbsp;and\u0026nbsp;Yubo Liu.\u003c/p\u003e\n\u003cp\u003eHypothesis generation:\u0026nbsp;Yiling Zhang\u0026nbsp;and Wei Chai.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStatistical analysis:\u0026nbsp;Yijian Huang.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003ePanjwani TR, Mullaji A, Doshi K, Thakur H. Comparison of functional outcomes of computer-assisted vs conventional total knee arthroplasty: A systematic review and meta-analysis of high-quality, prospective studies. J Arthroplasty 2019;34:3:586-93 https://doi.org/10.1016/j.arth.2018.11.028.\u003c/li\u003e\n \u003cli\u003eGoh GS, Liow MHL, Bin Abd Razak HR, Tay DK, Lo NN, Yeo SJ. Patient-reported outcomes, quality of life, and satisfaction rates in young patients aged 50 years or younger after total knee arthroplasty. J Arthroplasty 2017;32:2:419-25 https://doi.org/10.1016/j.arth.2016.07.043.\u003c/li\u003e\n \u003cli\u003eLiow MH, Xia Z, Wong MK, Tay KJ, Yeo SJ, Chin PL. Robot-assisted total knee arthroplasty accurately restores the joint line and mechanical axis. A prospective randomised study. J Arthroplasty 2014;29:12:2373-7 https://doi.org/10.1016/j.arth.2013.12.010.\u003c/li\u003e\n \u003cli\u003eRen Y, Cao S, Wu J, Weng X, Feng B. Efficacy and reliability of active robotic-assisted total knee arthroplasty compared with conventional total knee arthroplasty: A systematic review and meta-analysis. Postgrad Med J 2019;95:1121:125-33 https://doi.org/10.1136/postgradmedj-2018-136190.\u003c/li\u003e\n \u003cli\u003eSubramanian P, Wainwright TW, Bahadori S, Middleton RG. A review of the evolution of robotic-assisted total hip arthroplasty. Hip Int 2019;29:3:232-8 https://doi.org/10.1177/1120700019828286.\u003c/li\u003e\n \u003cli\u003eDeckey DG, Rosenow CS, Verhey JT, Brinkman JC, Mayfield CK, Clarke HD et al. Robotic-assisted total knee arthroplasty improves accuracy and precision compared to conventional techniques. Bone Joint J 2021;103-b:6 Supple A:74-80 https://doi.org/10.1302/0301-620x.103b6.Bjj-2020-2003.R1.\u003c/li\u003e\n \u003cli\u003eKayani B, Tahmassebi J, Ayuob A, Konan S, Oussedik S, Haddad FS. A prospective randomized controlled trial comparing the systemic inflammatory response in conventional jig-based total knee arthroplasty versus robotic-arm assisted total knee arthroplasty. Bone Joint J 2021;103-b:1:113-22 https://doi.org/10.1302/0301-620x.103b1.Bjj-2020-0602.R2.\u003c/li\u003e\n \u003cli\u003eEzeokoli EU, John J, Gupta R, Jawad A, Cavinatto L. Index surgery and ninety day re-operation cost comparison of robotic-assisted versus manual total knee arthroplasty. Int Orthop 2023;47:2:359-64 https://doi.org/10.1007/s00264-022-05674-w.\u003c/li\u003e\n \u003cli\u003eWu D, Zhi X, Liu X, Zhang Y, Chai W. Utility of a novel integrated deep convolutional neural network for the segmentation of hip joint from computed tomography images in the preoperative planning of total hip arthroplasty. J Orthop Surg Res 2022;17:1:164 https://doi.org/10.1186/s13018-022-02932-w.\u003c/li\u003e\n \u003cli\u003eHuo J, Huang G, Han D, Wang X, Bu Y, Chen Y et al. Value of 3d preoperative planning for primary total hip arthroplasty based on artificial intelligence technology. J Orthop Surg Res 2021;16:1:156 https://doi.org/10.1186/s13018-021-02294-9.\u003c/li\u003e\n \u003cli\u003eBiant LC, Yeoh K, Walker PM, Bruce WJ, Walsh WR. The accuracy of bone resections made during computer navigated total knee replacement. Do we resect what the computer plans we resect? Knee 2008;15:3:238-41 https://doi.org/10.1016/j.knee.2008.01.012.\u003c/li\u003e\n \u003cli\u003eSong EK, Seon JK, Yim JH, Netravali NA, Bargar WL. Robotic-assisted tka reduces postoperative alignment outliers and improves gap balance compared to conventional tka. Clin Orthop Relat Res 2013;471:1:118-26 https://doi.org/10.1007/s11999-012-2407-3.\u003c/li\u003e\n \u003cli\u003eLustig S, Fleury C, Goy D, Neyret P, Donell ST. The accuracy of acquisition of an imageless computer-assisted system and its implication for knee arthroplasty. Knee 2011;18:1:15-20 https://doi.org/10.1016/j.knee.2009.12.010.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-orthopaedic-surgery-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"josr","sideBox":"Learn more about [Journal of Orthopaedic Surgery and Research](http://josr-online.biomedcentral.com)","snPcode":"13018","submissionUrl":"https://submission.nature.com/new-submission/13018/3","title":"Journal of Orthopaedic Surgery and Research","twitterHandle":"@MSKmedBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Total knee arthroplasty, Bone resection, Robotic surgery, Accuracy, Cadaveric study.","lastPublishedDoi":"10.21203/rs.3.rs-4102446/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4102446/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRobot-assisted total knee arthroplasty (TKA) has been shown to facilitate high-precision bone resection, an important goal in TKA. The aim of this cadaveric study was to analyse the accuracy of the target angle and bone resection thickness of a recently introduced robotic TKA system.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study used 4 frozen cadaveric specimens (8 knees), 2 different implant designs (Johnson \u0026amp; Johnson and ICON), navigation, and a robotic system (ROPA TKA system, Longwood Valley MedTech). The 4 surgeons participating in this study were trained and familiar with the basic principles and operating procedures of this system. The angle of the bone cuts performed using the robotic system was compared with the target angles from the intraoperative plan. For each bone cut, the resection thickness was recorded and compared with the planned resection thickness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mean angular difference for all specimens was less than 1°, and the standard deviation was less than 2°. The mean difference between the planned and measured angles was close to 0 and not significantly different from 0 except for the difference in the frontal tibial component angle, which was 0.88°. The mean difference in the hip-knee-ankle axis angle was -0.21°±1.06°. The mean bone resection difference for all specimens was less than 1 mm, and the standard deviation was less than 0.5 mm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of our cadaveric experimental study show that surgeons using this new surgical robot in TKA can perform highly accurate bone cuts and achieve planned angles and resection thicknesses.\u003c/p\u003e","manuscriptTitle":"Accuracy of a New Robotic System for Assisting in Total Knee Arthroplasty: A Cadaveric Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-19 14:58:38","doi":"10.21203/rs.3.rs-4102446/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-03-29T01:57:05+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-03-17T05:07:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"818e5387-079d-47ad-ab0c-ba53b47fb9c1","date":"2024-03-17T04:56:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4849a1c4-28d8-4f31-9b91-ca0761d8a36a","date":"2024-03-15T13:16:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1870c27a-42e6-4bf0-8340-0abe84e12244","date":"2024-03-15T13:02:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-15T12:52:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-15T12:01:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-15T04:19:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Orthopaedic Surgery and Research","date":"2024-03-14T16:45:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-orthopaedic-surgery-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"josr","sideBox":"Learn more about [Journal of Orthopaedic Surgery and Research](http://josr-online.biomedcentral.com)","snPcode":"13018","submissionUrl":"https://submission.nature.com/new-submission/13018/3","title":"Journal of Orthopaedic Surgery and Research","twitterHandle":"@MSKmedBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fc6e41ac-5a7d-4f58-b32b-c79de280e5b7","owner":[],"postedDate":"March 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-05-07T23:09:42+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-19 14:58:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4102446","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4102446","identity":"rs-4102446","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}