Early Radiological Outcomes of Imageless Robotic-Assisted Total Knee Arthroplasty with VELYS®: A Comparative Study of CPAK Varus vs. Valgus Phenotypes

Early Radiological Outcomes of Imageless Robotic-Assisted Total Knee Arthroplasty with VELYS®: A Comparative Study of CPAK Varus vs. Valgus Phenotypes | 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 Early Radiological Outcomes of Imageless Robotic-Assisted Total Knee Arthroplasty with VELYS®: A Comparative Study of CPAK Varus vs. Valgus Phenotypes Vadim Benkovich, Artsiom Abialevich This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6486112/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Jun, 2025 Read the published version in Journal of Robotic Surgery → Version 1 posted 12 You are reading this latest preprint version Abstract Background: Robotic-assisted total knee arthroplasty (RATKA) offers enhanced intraoperative accuracy and real-time feedback. This study evaluates mid-term radiological outcomes of imageless RATKA in patients with mild and severe varus or valgus deformities, focusing on alignment accuracy and post-surgical outliers. Methods: A retrospective analysis was conducted on 257 patients who underwent RATKA. Demographic data, BMI, operative side, and key radiographic parameters—including pre- and postoperative hip-knee-ankle (HKA) angle, coronal alignment, joint line obliquity (MPTA + LDFA), tibial slope, and implant details—were recorded. Alignment phenotypes were classified using the CPAK system: Group 1 (varus phenotypes: CPAK I, IV, VII) and Group 2 (valgus phenotypes: CPAK III, VI, IX). Results: RATKA significantly improved alignment in both groups. In Varus Group 1 (N = 181), maximum extension improved (p < 0.001), flexion remained unchanged. JLO and HKA improved (p < 0.001). In Valgus Group 2 (N = 60), extension improved (p < 0.001) with no flexion change. Group 2 had better post-operative HKA and JLO (p < 0.001), aligning with close to CPAK 5 Neutral. Tibial resection was lower in Group 2 (7.43 ± 0.96) mm vs. (8.68 ± 1.45 mm). One tibial recut and one revision observed. Liner use favored 5 mm (80.11%) in Group 1, (90%) in Group 2. RATKA effectively optimized alignment and minimized tibial resection in valgus and varus deformities. Conclusion: Imageless RATKA provides accurate alignment correction in both varus and valgus deformities, even in severe cases. It enables minimal tibial resection and precise, balanced placement of cruciate-retaining implants, underscoring its role in optimizing modern TKA outcomes. Figures Figure 1 Figure 2 Introduction The prevalence of knee osteoarthritis and the need for effective treatments, such as total knee arthroplasty (TKA), continue to rise [1]. To further improve patient satisfaction, robotic-assisted TKA (RATKA) has emerged as a promising approach. By providing surgeons with real-time feedback and advanced imaging technology, it can lead to more accurate and personalized surgical procedures. Although there is some evidence to suggest that robotic TKA may result in better clinical outcomes, further studies are needed to validate its efficacy and cost-effectiveness [2]. Along with the correct orientation of the endoprosthesis components, which affects the service life of the components and reduces the degree of wear, it is necessary to optimize postoperative recovery and reduce the length of hospital stay, while maintaining the quality of care. Various medical advances have been focused on improving postoperative recovery and reducing the time that patients spend in the hospital following total knee replacement surgery. These advances include minimally invasive surgical techniques, improved pain management, more effective deep vein thrombosis prophylaxis, better antibiotic prophylaxis, advances in implant design and manufacturing, and more advanced rehabilitation techniques [3]. In addition, robotic-assisted technology has been utilized to improve inpatient recovery and expedite patient discharge in several types of surgical procedures, including gastrointestinal, urological, gynecological surgery, and more recently, in arthroplasty surgery over the past decade [4]. During robotic-arm assisted total knee replacement surgery, the surgeon utilizes a method of dynamic referencing to assess knee stability, alignment, and range of motion. This advanced technology enables the surgeon to make real-time adjustments to bone resection and implant positioning during the operation. By manipulating bone cuts, the surgeon can achieve the desired flexion and extension gaps without having to perform extensive soft-tissue releases. This technique is highly effective in improving the precision and accuracy of total knee replacement surgery [5,6]. At the moment, there is a large number of studies on the subject of positioning and functional results in robotic assisted UKA vs conventional UKA [7–10], which show excellent results. Now in robotic Total Knee Arthroplasty (RA-TKA) The DePuy Synthes VELYS Robotic-Assisted Solution (VRAS) represents a recent modern in robotic technology. This imageless system obviates the need for preoperative CT imaging, thereby reducing preoperative preparation time, associated costs, and patient exposure to ionizing radiation. This study aimed to evaluate the mid-term radiological outcomes of imageless robotic-assisted total knee arthroplasty (RA-TKA) using the DePuy Synthes VELYS Robotic-Assisted Solution (VRAS) in patients presenting with varus or valgus deformity alignment phenotypes. according to Coronal Plane Alignment of the Knee (CPAK) classification [11]. Materials and methods This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Assuta Medical Center No0028-25-ASMC. Additionally study was conducted retrospectively using data obtained from institutional records, and no identifiable human data were used. Therefore, informed consent was not required. The inclusion criteria were as follows: patients with primary or secondary gonarthrosis with indication of TKA, aged 30 to 85 years, both sexes. Patients with previous history of infection of operating joint or patients with current infection in joint, patients with inflammatory joint diseases, patients with active wounds on operating leg, smokers (at least 1 cigarette per day), patients with chronic alcoholism, patients with hypoalbuminemia (below 3.5 mg / dl, and anemia (hemoglobin ≤ 10 mg / dl), patients with HB1AC above 7,5, level of BMI above 40 were excluded from operation and this investigation as well. Also, 13 patients with initially normal values of so called neutral HKA (1° valgus and 2° varus ) ​​were excluded from the study groups. After exclusion of 16 patients with normal primary HKA we studied 241 patients operated in our department and evaluated in outpatient clinic. In this analysis data was collected on demographic characteristics, body mass index (BMI) and side of operation. Additionally key alignment parameters evaluated included the mechanical alignment HKA (Hip-knee-ankle angle), coronal plane alignment of the femoral and tibial components, joint line obliquity (MPTA + LDFA), tibial slope and overall limb alignment, final tibia insert size and implant type. Alignment phenotypes pre- and post-op were categorized based on the latest Coronal Plane Alignment of the Knee (CPAK) classification, enabling a detailed and nuanced analysis of individual alignment characteristics and their potential impact on surgical and radiological outcomes. Group 1 consisted of 181 patients who was diagnosed preoperative with varus phenotypes according to CPAK (I, IV, VII). In contrast, Group 2 comprised of 60 patients who was diagnosed preoperative with valgus phenotypes according to CPAK (III, VI, IX). All data pertaining to the operated knee were systematically recorded and analyzed using the ACCUBALANCE™ graph for pre-resection visualization of soft tissue balance and the PROADJUST™ planning system, facilitating a personalized approach to alignment and balance tailored to the patient’s unique soft tissue characteristics. Guidelines for perioperative protocols and postoperative anticoagulation were the same for all patients. For the purpose of anesthesia, depending on the type of operation and the choice of the anesthesiologist, general anesthesia with sevoflurane/isoflurane or spinal anesthesia with heavy marcaine 0.5% solution from 2 to 2.5 ml + sedation with propofol 2% 12–20 ml per hour. In all types of of anesthesia additional blocks such as block of adductor canal/ low femoral triangle bloc, were performed preoperatively using ultrasound control with a marcaine solution of 0.25% − 0,5% 20 ml. Access to the knee was a medial parapatellar approach with longitudinal straight midline incision, extending from a point 6 cm above the superior pole of the patella to below the level of the tibial tubercle. Re-examination of all patients was carried out planned one month after the operation and continued long-term follow up in our outpatient clinic. All data were collected in Google Tables®. Statistical processing of the obtained data was performed using the application package software programs Statistica 7.0 (StatSoft Inc., USA). Data are presented as mean and standard deviation (at normal definition) or median, 25th and 75th percentile styles (with a distribution that is different from the normal). To assess the qualitative variables used the χ2 test, Fisher’s criterion. The data obtained were considered statistically clinically significant at p < 0.05. Results Patient characteristics are described in Table 1. Percentage distribution according to the CPAK classification of studied population are described in Table 2. The distribution of individuals across all CPAK types remained different when comparing preoperative and postoperative measurements (Figs. 1 and 2). The analysis of pre-operative and post-operative parameters demonstrated significant improvements in both groups, confirming the efficacy of the intervention with RA- TKA VRAS are described in Tables 3 and 4. In Varus Group 1 (N = 181), maximum extension improved from 2.55° ± 5.47° to -1.73° ± 3.65° (p < 0.001), while maximum flexion showed no significant change (p = 0.139). Significant reductions were observed in extension and flexion gaps, and joint line obliquity improved from 173.98° ± 4.91° to 178.89° ± 2.07° (p < 0.001). The HKA angle also improved significantly (p < 0.001). In Valgus Group 2 (N = 60), maximum extension improved from 0.63° ± 6.77° to -1.78° ± 2.55° (p < 0.001), with no significant change in maximum flexion (p = 0.694). Reductions in gaps and improvements in joint line obliquity and the HKA angle were statistically significant (p < 0.001). Table 1 Patient characteristics Index Group 1 N = 181 Group 2 N = 60 P value Female/male 1.22:1 1.22:1 1.0 Right side/Left side 1.12:1 2.22:1 0.044 Age, years 70.38 ± 8.95 72.02 ± 7.23 0.154 BMI, kg/m2 30.47 ± 4.49 29.41 ± 4.06 0.09 Abbreviations: BMI, body mass index; aHKA, arithmetic hip–knee–ankle; JLO, joint line obliquity. Table 2 Percentage distribution according to the CPAK classification of studied population. CPAK Classification Patients (n = 257) CPAK I (varus and apex distal) 131 CPAK II (neutral and apex distal) 2 CPAK III (valgus and apex distal) 0 CPAK IV (varus and apex neutral) 50 CPAK V (neutral and apex neutral) 13 CPAK VI (valgus and apex neutral) 36 CPAK VII (varus and apex proximal) 0 CPAK VIII (neutral and apex proximal) 1 CPAK IX (valgus and apex proximal) 24 Table 3 Pre- Vs Post-Operative Parameters for Group 1 Parameters Pre-operative Post-operative P value Maximum Extension, ° 2.55 ± 5.47 -1.73 ± 3.65 < 0.001 Maximum Flexion, ° 127.45 ± 9.30 128.61 ± 11.57 0.139 Extension Medial Gap on Balance Graph, mm 7.11 ± 2.23 1.34 ± 1.12 < 0.001 Extension Lateral Gap on Balance Graph, mm 10.77 ± 1.75 2.35 ± 1.27 < 0.001 Extension Angle for Gaps Display on Balance Graph, ° 5.97 ± 4.87 1.14 ± 2.05 < 0.001 Joint Line Obliquity (MPTA + LDFA) Post OP, ° 173.98 ± 4.91 178.89 ± 2.07 < 0.001 Flexion Medial Gap on Balance Graph, mm 9.16 ± 2.27 1.59 ± 1.31 < 0.001 Flexion Lateral Gap on Balance Graph, mm 11.22 ± 1.85 1.72 ± 1.88 < 0.001 Flexion Angle for Gaps Display on Balance Graph, ° 88.85 ± 1.34 89.90 ± 2.88 < 0.001 HKA, ° -6.96 ± 2.96 -2.57 ± 1.43 < 0.001 Table 4 Pre- Vs Post-Operative Parameters for Group 2 Parameters Pre-operative Post-operative P value Maximum Extension, ° 0.63 ± 6.77 -1.78 ± 2.55 < 0.001 Maximum Flexion, ° 126.47 ± 7.57 126.18 ± 11.77 0.694 Extension Medial Gap on Balance Graph, mm 10.89 ± 1.16 1.83 ± 1.40 < 0.001 Extension Lateral Gap on Balance Graph, mm 6.46 ± 2.08 2.04 ± 0.96 < 0.001 Extension Angle for Gaps Display on Balance Graph, ° 3.60 ± 4.77 0.72 ± 1.38 < 0.001 Joint Line Obliquity (MPTA + LDFA) Post OP, ° 183.60 ± 4.77 180.52 ± 1.47 < 0.001 Flexion Medial Gap on Balance Graph, mm 11.94 ± 1.25 -0.54 ± 6.06 < 0.001 Flexion Lateral Gap on Balance Graph, mm 8.84 ± 2.14 0.03 ± 5.63 < 0.001 Flexion Angle for Gaps Display on Balance Graph, ° 89.97 ± 1.51 89.52 ± 1.80 < 0.001 HKA, ° 6.05 ± 2.68 0.92 ± 1.05 < 0.001 According to Table 5 post-operatively, Group 2 showed better HKA (0.92° ± 1.05°) and joint line obliquity (180.52° ± 1.47°) compared to Group 1 (p < 0.001), but both results showed normal range according to CPAK classification maximally close to neutral position (CPAK 5 Neutral). Also it should be noted that in 100% of cases was performed CR design of endoprosthesis. Notably, a tibial recut was required in only one case, and a revision surgery was performed in only one instance due to the spin-out of the mobile bearing insert. Tibial resection in Group 1 averaged 8.68 ± 1.45 mm, whereas in Group 2, it was 7.43 ± 0.96 mm. These findings suggest that this technology enables surgeons to avoid additional tibial component re-cut’s in cases of valgus and varus deformities while also minimizing the extent of tibial bone resection. Table 5 Comparison of post-operative main measures in Group 1 and 2 Index Group 1 N = 181 Group 2 N = 60 P value HKA, ° -2.57 ± 1.43 0.92 ± 1.05 < 0.001 Joint Line Obliquity (MPTA + LDFA) Post OP, ° 178.89 ± 2.07 180.52 ± 1.47 < 0.001 Final Femur Implant Size 5.41 ± 1.51 5.03 ± 1.46 0.088 Tibia Slope, ° 5.67 ± 1.01 5.61 ± 0.73 0.620 Implant Type 181 CR − 100% 60 CR − 100% 1 In Group 1, the most commonly used liner size was 5 mm, utilized in 145 cases (80.11%), followed by 6 mm in 26 cases (14.36%), 7 mm in 6 cases (3.31%), and 8 mm in 4 cases (2.20%). In Group 2, 5 mm liners were used in the majority of cases (54 cases, 90%), while 6 mm and 7 mm liners were each used in 3 cases (5%). These findings indicate a preference for smaller liner sizes in both groups Discussion Robotic-assisted total knee arthroplasty (TKA) significantly enhances surgical planning and execution by improving the precision of bony resections, optimizing soft tissue balancing, and reducing alignment outliers. These advancements align closely with the principles of the Coronal Plane Alignment of the Knee (CPAK) classification, which emphasizes individualized alignment strategies tailored to constitutional limb phenotypes, thereby promoting a more patient-specific approach to TKA. The Coronal Plane Alignment of the Knee (CPAK) classification represents a significant advancement in modern orthopedics, offering a structured framework for categorizing knee alignment phenotypes. By incorporating constitutional alignment and joint line obliquity (JLO), CPAK enables a patient-specific approach to total knee arthroplasty (TKA), challenging traditional mechanical alignment (MA) paradigms that prioritize a neutral mechanical axis for all patients. CPAK, as described by MacDessi et al. [11], classifies knees into nine phenotypes based on the arithmetic hip-knee-ankle angle (aHKA) and JLO, reflecting the natural variability of alignment in both healthy and osteoarthritic populations. This system has demonstrated predictive capabilities, with kinematic alignment (KA) achieving superior soft tissue balance in CPAK Types I, II, and IV compared to MA, particularly for phenotypes deviating from neutral alignment [11]. The role of JLO has been further emphasized by studies demonstrating its impact on restoring native knee phenotypes, with excessive restriction of JLO limiting alignment restoration [12]. Additionally, Morrisey et al. [13] proposed the inclusion of posterior tibial slope (PTS) into CPAK, identifying its influence on knee kinematics and gap balancing, further broadening CPAK's utility in addressing sagittal and coronal plane considerations. CPAK has also illuminated population-specific differences, as Harada et al. [14] and León-Muñoz et al. [15] reported variability in CPAK distributions with age, gender, and osteoarthritis progression across Japanese and Spanish cohorts, respectively, reinforcing the need for demographic-specific alignment strategies. Furthermore, Griffiths-Jones et al. [16] validated the use of aHKA as a reliable estimate of constitutional alignment in osteoarthritic knees, underscoring its relevance in surgical planning. By integrating these insights, CPAK offers a transformative approach to TKA, aligning with precision medicine principles to optimize functional outcomes through personalized surgical strategies like, as example, patient-Specific TKA with the VELYS™ robotic-assisted solution. Robotic-assisted total knee arthroplasty (RATKA) represents a significant advancement in surgical precision and reproducibility, with systems like the DePuy Synthes VELYS™ Robotic-Assisted Solution (VRAS) demonstrating superior alignment accuracy and reduced variability compared to conventional techniques. Studies have shown that RATKA significantly decreases outliers in key parameters, including hip-knee-ankle (HKA) alignment, proximal tibial angle (MPTA), and distal femoral angle (LDFA), leading to improved implant positioning and surgical consistency [17,18]. Furthermore, VRAS achieves these outcomes without the need for preoperative imaging, reducing costs and procedural complexity while maintaining comparable operating times and discharge profiles [19]. Additionally, RATKA has shown improved cementless tibial component fixation, enhancing survivorship and addressing challenges like aseptic loosening [20]. Although long-term functional outcomes may not differ significantly from manual TKA, the superior alignment accuracy and reduced variability offered by VRAS position it as a critical innovation in modern arthroplasty [21,22]. The imageless nature of VRAS, leveraging intraoperative anatomic data instead of preoperative imaging, exemplifies the next generation of robotic TKA technology. This approach not only simplifies workflow but also integrates seamlessly with advanced algorithms like XPlan.ai™ for precise surgical planning and execution [23]. As robotic TKA continues to evolve, VRAS serves as a benchmark for precision and cost-effectiveness, offering a patient-specific approach to improve outcomes in a resource-conscious healthcare landscape. Conclusion The findings of our study indicate that this advanced technology enables the achievement of optimal outcomes in addressing varus and valgus deformities of the knee joint. Specifically, it facilitates the precise placement of a maximally balanced and minimally constrained CR design, even in cases of severe deformity. This capability underscores the potential to redefine management strategies for this patient population, particularly with respect to achieving enhanced soft tissue balance in the operated knee joint. Declarations Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Competing Interests Financial interests: The authors declare they have no financial interests. Author Contributions All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by A.A and V.B. The first draft of the manuscript was written by Abialevich Artsiom. All authors read and approved the final manuscript. References Cross M, Smith E, Hoy D, Nolte S, Ackerman I, Fransen M, Bridgett L, Williams S, Guillemin F, Hill CL, Laslett LL, Jones G, Cicuttini F, Osborne R, Vos T, Buchbinder R, Woolf A, March L. 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Cite Share Download PDF Status: Published Journal Publication published 13 Jun, 2025 Read the published version in Journal of Robotic Surgery → Version 1 posted Editorial decision: Revision requested 22 May, 2025 Reviews received at journal 22 May, 2025 Reviews received at journal 22 May, 2025 Reviewers agreed at journal 20 May, 2025 Reviewers agreed at journal 19 May, 2025 Reviewers agreed at journal 19 May, 2025 Reviewers agreed at journal 19 May, 2025 Reviewers agreed at journal 19 May, 2025 Reviewers invited by journal 19 May, 2025 Editor assigned by journal 22 Apr, 2025 Submission checks completed at journal 22 Apr, 2025 First submitted to journal 19 Apr, 2025 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. 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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-6486112","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":459198744,"identity":"94fc27bc-0754-4d91-a27c-c23967100420","order_by":0,"name":"Vadim Benkovich","email":"","orcid":"","institution":"Assuta Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Vadim","middleName":"","lastName":"Benkovich","suffix":""},{"id":459198745,"identity":"103df637-d7dc-47fe-9b7a-26b52f195e94","order_by":1,"name":"Artsiom Abialevich","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIiWNgGAWjYBACxgYeNiiT+QCQkJAhRQtbAkgLDxH2wLXwGIBJghqY288ee/Czzcaen/3M51c3aix4GNgPH92A12E9eemGvW1pzJI9udusc44BHcaTlnYDr5aGHDMJ3m2H2Qxu8G4zzmEDapHgMcOvpf+NmeTfbYd57G/wPDPO+UeMlhk5ZtJAWyQMJHiYH+e2EaXlXbqx7L80A4kzaWbMuX0SPGyE/GLYn3vs4ZszwBBrP/z4c863Ojl+9sPH8GtpQLDZJMAkPuUgII/EZv5ASPUoGAWjYBSMTAAAq2BDsKqNNaoAAAAASUVORK5CYII=","orcid":"","institution":"Soroka Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Artsiom","middleName":"","lastName":"Abialevich","suffix":""}],"badges":[],"createdAt":"2025-04-19 17:38:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6486112/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6486112/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11701-025-02456-5","type":"published","date":"2025-06-13T15:57:52+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":83298776,"identity":"6f3038b3-c3a4-4adb-b1ea-112b46d5768a","added_by":"auto","created_at":"2025-05-22 14:36:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":452742,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6486112/v1/776a36c8a73f6a69fac70e48.png"},{"id":83298771,"identity":"d446c398-4aaf-49a7-925c-34ee49c7df31","added_by":"auto","created_at":"2025-05-22 14:36:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":417941,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6486112/v1/6fbea3cc7f7bbe46b43547c7.png"},{"id":84726553,"identity":"7daaf726-942b-4273-9b8c-594aa24e55a5","added_by":"auto","created_at":"2025-06-16 16:06:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1795806,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6486112/v1/3d5655d7-52f4-499c-80be-4a235e96c963.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eEarly Radiological Outcomes of Imageless Robotic-Assisted Total Knee Arthroplasty with VELYS®: A Comparative Study of CPAK Varus vs. Valgus Phenotypes\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe prevalence of knee osteoarthritis and the need for effective treatments, such as total knee arthroplasty (TKA), continue to rise [1]. To further improve patient satisfaction, robotic-assisted TKA (RATKA) has emerged as a promising approach. By providing surgeons with real-time feedback and advanced imaging technology, it can lead to more accurate and personalized surgical procedures. Although there is some evidence to suggest that robotic TKA may result in better clinical outcomes, further studies are needed to validate its efficacy and cost-effectiveness [2].\u003c/p\u003e \u003cp\u003eAlong with the correct orientation of the endoprosthesis components, which affects the service life of the components and reduces the degree of wear, it is necessary to optimize postoperative recovery and reduce the length of hospital stay, while maintaining the quality of care. Various medical advances have been focused on improving postoperative recovery and reducing the time that patients spend in the hospital following total knee replacement surgery. These advances include minimally invasive surgical techniques, improved pain management, more effective deep vein thrombosis prophylaxis, better antibiotic prophylaxis, advances in implant design and manufacturing, and more advanced rehabilitation techniques [3].\u003c/p\u003e \u003cp\u003eIn addition, robotic-assisted technology has been utilized to improve inpatient recovery and expedite patient discharge in several types of surgical procedures, including gastrointestinal, urological, gynecological surgery, and more recently, in arthroplasty surgery over the past decade [4].\u003c/p\u003e \u003cp\u003eDuring robotic-arm assisted total knee replacement surgery, the surgeon utilizes a method of dynamic referencing to assess knee stability, alignment, and range of motion. This advanced technology enables the surgeon to make real-time adjustments to bone resection and implant positioning during the operation. By manipulating bone cuts, the surgeon can achieve the desired flexion and extension gaps without having to perform extensive soft-tissue releases. This technique is highly effective in improving the precision and accuracy of total knee replacement surgery [5,6].\u003c/p\u003e \u003cp\u003eAt the moment, there is a large number of studies on the subject of positioning and functional results in robotic assisted UKA vs conventional UKA [7\u0026ndash;10], which show excellent results. Now in robotic Total Knee Arthroplasty (RA-TKA) The DePuy Synthes VELYS Robotic-Assisted Solution (VRAS) represents a recent modern in robotic technology. This imageless system obviates the need for preoperative CT imaging, thereby reducing preoperative preparation time, associated costs, and patient exposure to ionizing radiation.\u003c/p\u003e \u003cp\u003eThis study aimed to evaluate the mid-term radiological outcomes of imageless robotic-assisted total knee arthroplasty (RA-TKA) using the DePuy Synthes VELYS Robotic-Assisted Solution (VRAS) in patients presenting with varus or valgus deformity alignment phenotypes. according to Coronal Plane Alignment of the Knee (CPAK) classification [11].\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Assuta Medical Center No0028-25-ASMC. Additionally study was conducted retrospectively using data obtained from institutional records, and no identifiable human data were used. Therefore, informed consent was not required. The inclusion criteria were as follows: patients with primary or secondary gonarthrosis with indication of TKA, aged 30 to 85 years, both sexes. Patients with previous history of infection of operating joint or patients with current infection in joint, patients with inflammatory joint diseases, patients with active wounds on operating leg, smokers (at least 1 cigarette per day), patients with chronic alcoholism, patients with hypoalbuminemia (below 3.5 mg / dl, and anemia (hemoglobin\u0026thinsp;\u0026le;\u0026thinsp;10 mg / dl), patients with HB1AC above 7,5, level of BMI above 40 were excluded from operation and this investigation as well. Also, 13 patients with initially normal values of so called neutral HKA (1\u0026deg; valgus and 2\u0026deg; varus ) ​​were excluded from the study groups.\u003c/p\u003e \u003cp\u003eAfter exclusion of 16 patients with normal primary HKA we studied 241 patients operated in our department and evaluated in outpatient clinic. In this analysis data was collected on demographic characteristics, body mass index (BMI) and side of operation. Additionally key alignment parameters evaluated included the mechanical alignment HKA (Hip-knee-ankle angle), coronal plane alignment of the femoral and tibial components, joint line obliquity (MPTA\u0026thinsp;+\u0026thinsp;LDFA), tibial slope and overall limb alignment, final tibia insert size and implant type. Alignment phenotypes pre- and post-op were categorized based on the latest Coronal Plane Alignment of the Knee (CPAK) classification, enabling a detailed and nuanced analysis of individual alignment characteristics and their potential impact on surgical and radiological outcomes.\u003c/p\u003e \u003cp\u003eGroup 1 consisted of 181 patients who was diagnosed preoperative with varus phenotypes according to CPAK (I, IV, VII). In contrast, Group 2 comprised of 60 patients who was diagnosed preoperative with valgus phenotypes according to CPAK (III, VI, IX). All data pertaining to the operated knee were systematically recorded and analyzed using the ACCUBALANCE\u0026trade; graph for pre-resection visualization of soft tissue balance and the PROADJUST\u0026trade; planning system, facilitating a personalized approach to alignment and balance tailored to the patient\u0026rsquo;s unique soft tissue characteristics.\u003c/p\u003e \u003cp\u003e Guidelines for perioperative protocols and postoperative anticoagulation were the same for all patients.\u003c/p\u003e \u003cp\u003eFor the purpose of anesthesia, depending on the type of operation and the choice of the anesthesiologist, general anesthesia with sevoflurane/isoflurane or spinal anesthesia with heavy marcaine 0.5% solution from 2 to 2.5 ml\u0026thinsp;+\u0026thinsp;sedation with propofol 2% 12\u0026ndash;20 ml per hour. In all types of of anesthesia additional blocks such as block of adductor canal/ low femoral triangle bloc, were performed preoperatively using ultrasound control with a marcaine solution of 0.25% \u0026minus;\u0026thinsp;0,5% 20 ml. Access to the knee was a medial parapatellar approach with longitudinal straight midline incision, extending from a point 6 cm above the superior pole of the patella to below the level of the tibial tubercle. Re-examination of all patients was carried out planned one month after the operation and continued long-term follow up in our outpatient clinic.\u003c/p\u003e \u003cp\u003eAll data were collected in Google Tables\u0026reg;. Statistical processing of the obtained data was performed using the application package software programs Statistica 7.0 (StatSoft Inc., USA). Data are presented as mean and standard deviation (at normal definition) or median, 25th and 75th percentile styles (with a distribution that is different from the normal). To assess the qualitative variables used the χ2 test, Fisher\u0026rsquo;s criterion. The data obtained were considered statistically clinically significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003ePatient characteristics are described in Table 1. Percentage distribution according to the CPAK classification of studied population are described in Table 2. The distribution of individuals across all CPAK types remained different when comparing preoperative and postoperative measurements (Figs. 1 and 2). The analysis of pre-operative and post-operative parameters demonstrated significant improvements in both groups, confirming the efficacy of the intervention with RA- TKA VRAS are described in Tables 3 and 4. In Varus Group 1 (N = 181), maximum extension improved from 2.55° ± 5.47° to -1.73° ± 3.65° (p \u0026lt; 0.001), while maximum flexion showed no significant change (p = 0.139). Significant reductions were observed in extension and flexion gaps, and joint line obliquity improved from 173.98° ± 4.91° to 178.89° ± 2.07° (p \u0026lt; 0.001). The HKA angle also improved significantly (p \u0026lt; 0.001). In Valgus Group 2 (N = 60), maximum extension improved from 0.63° ± 6.77° to -1.78° ± 2.55° (p \u0026lt; 0.001), with no significant change in maximum flexion (p = 0.694). Reductions in gaps and improvements in joint line obliquity and the HKA angle were statistically significant (p \u0026lt; 0.001).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003ePatient characteristics\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIndex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup 1 N = 181\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup 2 N = 60\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale/male\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.22:1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.22:1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRight side/Left side\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.12:1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.22:1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e70.38 ± 8.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e72.02 ± 7.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI, kg/m2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30.47 ± 4.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29.41 ± 4.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eAbbreviations: BMI, body mass index; aHKA, arithmetic hip–knee–ankle; JLO, joint line obliquity.\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003ePercentage distribution according to the CPAK classification of studied population.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"2\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCPAK Classification\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePatients (n = 257)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCPAK I (varus and apex distal)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCPAK II (neutral and apex distal)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCPAK III (valgus and apex distal)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCPAK IV (varus and apex neutral)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCPAK V (neutral and apex neutral)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCPAK VI (valgus and apex neutral)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCPAK VII (varus and apex proximal)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCPAK VIII (neutral and apex proximal)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCPAK IX (valgus and apex proximal)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003ePre- Vs Post-Operative Parameters for Group 1\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePre-operative\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePost-operative\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaximum Extension, °\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.55 ± 5.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.73 ± 3.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaximum Flexion, °\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e127.45 ± 9.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e128.61 ± 11.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.139\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eExtension Medial Gap on Balance Graph, mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.11 ± 2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.34 ± 1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eExtension Lateral Gap on Balance Graph, mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.77 ± 1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.35 ± 1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eExtension Angle for Gaps Display on Balance Graph, °\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.97 ± 4.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.14 ± 2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eJoint Line Obliquity (MPTA + LDFA) Post OP, °\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e173.98 ± 4.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e178.89 ± 2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFlexion Medial Gap on Balance Graph, mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.16 ± 2.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.59 ± 1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFlexion Lateral Gap on Balance Graph, mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.22 ± 1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.72 ± 1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFlexion Angle for Gaps Display on Balance Graph, °\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88.85 ± 1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89.90 ± 2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHKA, °\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-6.96 ± 2.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.57 ± 1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003ePre- Vs Post-Operative Parameters for Group 2\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePre-operative\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePost-operative\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaximum Extension, °\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.63 ± 6.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.78 ± 2.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaximum Flexion, °\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e126.47 ± 7.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e126.18 ± 11.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.694\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eExtension Medial Gap on Balance Graph, mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.89 ± 1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.83 ± 1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eExtension Lateral Gap on Balance Graph, mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.46 ± 2.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.04 ± 0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eExtension Angle for Gaps Display on Balance Graph, °\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.60 ± 4.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.72 ± 1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eJoint Line Obliquity (MPTA + LDFA) Post OP, °\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e183.60 ± 4.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e180.52 ± 1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFlexion Medial Gap on Balance Graph, mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.94 ± 1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.54 ± 6.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFlexion Lateral Gap on Balance Graph, mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.84 ± 2.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.03 ± 5.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFlexion Angle for Gaps Display on Balance Graph, °\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89.97 ± 1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89.52 ± 1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHKA, °\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.05 ± 2.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.92 ± 1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAccording to Table 5 post-operatively, Group 2 showed better HKA (0.92° ± 1.05°) and joint line obliquity (180.52° ± 1.47°) compared to Group 1 (p \u0026lt; 0.001), but both results showed normal range according to CPAK classification maximally close to neutral position (CPAK 5 Neutral). Also it should be noted that in 100% of cases was performed CR design of endoprosthesis. Notably, a tibial recut was required in only one case, and a revision surgery was performed in only one instance due to the spin-out of the mobile bearing insert. Tibial resection in Group 1 averaged 8.68 ± 1.45 mm, whereas in Group 2, it was 7.43 ± 0.96 mm. These findings suggest that this technology enables surgeons to avoid additional tibial component re-cut’s in cases of valgus and varus deformities while also minimizing the extent of tibial bone resection.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 5\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eComparison of post-operative main measures in Group 1 and 2\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIndex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup 1 N = 181\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup 2 N = 60\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHKA, °\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.57 ± 1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.92 ± 1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eJoint Line Obliquity (MPTA + LDFA) Post OP, °\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e178.89 ± 2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e180.52 ± 1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFinal Femur Implant Size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.41 ± 1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.03 ± 1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTibia Slope, °\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.67 ± 1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.61 ± 0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.620\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eImplant Type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e181 CR − 100%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60 CR − 100%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eIn Group 1, the most commonly used liner size was 5 mm, utilized in 145 cases (80.11%), followed by 6 mm in 26 cases (14.36%), 7 mm in 6 cases (3.31%), and 8 mm in 4 cases (2.20%). In Group 2, 5 mm liners were used in the majority of cases (54 cases, 90%), while 6 mm and 7 mm liners were each used in 3 cases (5%). These findings indicate a preference for smaller liner sizes in both groups\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eRobotic-assisted total knee arthroplasty (TKA) significantly enhances surgical planning and execution by improving the precision of bony resections, optimizing soft tissue balancing, and reducing alignment outliers. These advancements align closely with the principles of the Coronal Plane Alignment of the Knee (CPAK) classification, which emphasizes individualized alignment strategies tailored to constitutional limb phenotypes, thereby promoting a more patient-specific approach to TKA.\u003c/p\u003e \u003cp\u003eThe Coronal Plane Alignment of the Knee (CPAK) classification represents a significant advancement in modern orthopedics, offering a structured framework for categorizing knee alignment phenotypes. By incorporating constitutional alignment and joint line obliquity (JLO), CPAK enables a patient-specific approach to total knee arthroplasty (TKA), challenging traditional mechanical alignment (MA) paradigms that prioritize a neutral mechanical axis for all patients. CPAK, as described by MacDessi et al. [11], classifies knees into nine phenotypes based on the arithmetic hip-knee-ankle angle (aHKA) and JLO, reflecting the natural variability of alignment in both healthy and osteoarthritic populations. This system has demonstrated predictive capabilities, with kinematic alignment (KA) achieving superior soft tissue balance in CPAK Types I, II, and IV compared to MA, particularly for phenotypes deviating from neutral alignment [11].\u003c/p\u003e \u003cp\u003eThe role of JLO has been further emphasized by studies demonstrating its impact on restoring native knee phenotypes, with excessive restriction of JLO limiting alignment restoration [12]. Additionally, Morrisey et al. [13] proposed the inclusion of posterior tibial slope (PTS) into CPAK, identifying its influence on knee kinematics and gap balancing, further broadening CPAK's utility in addressing sagittal and coronal plane considerations. CPAK has also illuminated population-specific differences, as Harada et al. [14] and Le\u0026oacute;n-Mu\u0026ntilde;oz et al. [15] reported variability in CPAK distributions with age, gender, and osteoarthritis progression across Japanese and Spanish cohorts, respectively, reinforcing the need for demographic-specific alignment strategies.\u003c/p\u003e \u003cp\u003eFurthermore, Griffiths-Jones et al. [16] validated the use of aHKA as a reliable estimate of constitutional alignment in osteoarthritic knees, underscoring its relevance in surgical planning. By integrating these insights, CPAK offers a transformative approach to TKA, aligning with precision medicine principles to optimize functional outcomes through personalized surgical strategies like, as example, patient-Specific TKA with the VELYS\u0026trade; robotic-assisted solution.\u003c/p\u003e \u003cp\u003eRobotic-assisted total knee arthroplasty (RATKA) represents a significant advancement in surgical precision and reproducibility, with systems like the DePuy Synthes VELYS\u0026trade; Robotic-Assisted Solution (VRAS) demonstrating superior alignment accuracy and reduced variability compared to conventional techniques. Studies have shown that RATKA significantly decreases outliers in key parameters, including hip-knee-ankle (HKA) alignment, proximal tibial angle (MPTA), and distal femoral angle (LDFA), leading to improved implant positioning and surgical consistency [17,18]. Furthermore, VRAS achieves these outcomes without the need for preoperative imaging, reducing costs and procedural complexity while maintaining comparable operating times and discharge profiles [19].\u003c/p\u003e \u003cp\u003eAdditionally, RATKA has shown improved cementless tibial component fixation, enhancing survivorship and addressing challenges like aseptic loosening [20]. Although long-term functional outcomes may not differ significantly from manual TKA, the superior alignment accuracy and reduced variability offered by VRAS position it as a critical innovation in modern arthroplasty [21,22].\u003c/p\u003e \u003cp\u003eThe imageless nature of VRAS, leveraging intraoperative anatomic data instead of preoperative imaging, exemplifies the next generation of robotic TKA technology. This approach not only simplifies workflow but also integrates seamlessly with advanced algorithms like XPlan.ai\u0026trade; for precise surgical planning and execution [23].\u003c/p\u003e \u003cp\u003eAs robotic TKA continues to evolve, VRAS serves as a benchmark for precision and cost-effectiveness, offering a patient-specific approach to improve outcomes in a resource-conscious healthcare landscape.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe findings of our study indicate that this advanced technology enables the achievement of optimal outcomes in addressing varus and valgus deformities of the knee joint. Specifically, it facilitates the precise placement of a maximally balanced and minimally constrained CR design, even in cases of severe deformity. This capability underscores the potential to redefine management strategies for this patient population, particularly with respect to achieving enhanced soft tissue balance in the operated knee joint.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFinancial interests: The authors declare they have no financial interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by A.A and V.B. The first draft of the manuscript was written by Abialevich Artsiom. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCross M, Smith E, Hoy D, Nolte S, Ackerman I, Fransen M, Bridgett L, Williams S, Guillemin F, Hill CL, Laslett LL, Jones G, Cicuttini F, Osborne R, Vos T, Buchbinder R, Woolf A, March L. The global burden of hip and knee osteoarthritis: estimates from the global burden of disease 2010 study. Ann Rheum Dis. 2014 Jul;73(7):1323-30. doi: 10.1136/annrheumdis-2013-204763. Epub 2014 Feb 19. PMID: 24553908.\u003c/li\u003e\n\u003cli\u003eKayani B, Konan S, Tahmassebi J, Pietrzak JRT, Haddad FS. 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. doi: 10.1302/0301-620X.100B7.BJJ-2017-1449.R1. PMID: 29954217; PMCID: PMC6413767.\u003c/li\u003e\n\u003cli\u003eEl Bitar YF, Illingworth KD, Scaife S, Horberg JV, Saleh KJ. Hospital Length of Stay following Primary Total Knee Arthroplasty: Data from the Nationwide Inpatient Sample Database. J Arthroplasty 2015;30:1710\u0026ndash;1715.\u003c/li\u003e\n\u003cli\u003eGourin CG, Terris DJHistory of Robotic Surgery. In: Faust RA, ed. Robotics in Surgery: History, Current and Future Applications.New York (NY): Nova Science Publishers, Inc., 2007:3-12.\u003c/li\u003e\n\u003cli\u003eConditt MA, Roche MW. Minimally invasive robotic-arm-guided unicompartmental knee arthroplasty. J Bone Joint Surg [Am] 2009;91-A (Suppl 1):63\u0026ndash;68\u003c/li\u003e\n\u003cli\u003eDunbar NJ, Roche MW, Park BH, et al. Accuracy of dynamic tactile-guided unicompartmental knee arthroplasty. J Arthroplasty 2012;27:803\u0026ndash;808.\u003c/li\u003e\n\u003cli\u003eLonner JH, John TK, Conditt MA. Robotic arm-assisted UKA improves tibial component alignment: a pilot study. Clin Orthop Relat Res. 2010;468:141\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eCitak M, Suero EM, Citak M, Dunbar NJ, Branch SH, Conditt MA, et al. Unicompartmental knee arthroplasty: is robotic technology more accurate than conventional technique? Knee. 2013;20:268\u0026ndash;71. \u003c/li\u003e\n\u003cli\u003eCobb J, Henckel J, Gomes P, Harris S, Jakopec M, Rodriguez F, et al. Hands-on robotic unicompartmental knee replacement: a prospective, randomised controlled study of the acrobot system. J Bone Joint Surg Br. 2006;88:188\u0026ndash;97.\u003c/li\u003e\n\u003cli\u003ePlate JF, Mofidi A, Mannava S, Smith BP, Lang JE, Poehling GG, et al. Achieving accurate ligament balancing using robotic-assisted unicompartmental knee arthroplasty. Adv Orthop. 2013;2013:837167.\u003c/li\u003e\n\u003cli\u003eMacDessi SJ, Griffiths-Jones W, Harris IA, Bellemans J, Chen DB. Coronal Plane Alignment of the Knee (CPAK) classification. Bone Joint J. 2021 Feb;103-B(2):329-337. doi: 10.1302/0301-620X.103B2.BJJ-2020-1050.R1. PMID: 33517740; PMCID: PMC7954147.\u003c/li\u003e\n\u003cli\u003eMacDessi SJ, Allom RJ, Griffiths-Jones W, Chen DB, Wood JA, Bellemans J. The importance of joint line obliquity: a radiological analysis of restricted boundaries in normal knee phenotypes to inform surgical decision making in kinematically aligned total knee arthroplasty. Knee Surg Sports Traumatol Arthrosc. 2022 Sep;30(9):2931-2940. doi: 10.1007/s00167-022-06872-0. Epub 2022 Jan 24. PMID: 35075509.\u003c/li\u003e\n\u003cli\u003eMorrisey Z, Cruse J, Barra M, Carroll T, Drinkwater C. Posterior tibial slope considered as an important addition to the CPAK classification system. J Orthop. 2024 Jan 14;51:54-59. doi: 10.1016/j.jor.2024.01.008. PMID: 38304145; PMCID: PMC10828574.\u003c/li\u003e\n\u003cli\u003eHarada K, Mori Y, Kamimura M, Aki T, Koyama T, Aizawa T. Impact of Aging and Knee Osteoarthritis on Lower Limb Alignment and CPAK Classification: Gender Differences in a Japanese Cohort. J Clin Med. 2024 Oct 19;13(20):6250. doi: 10.3390/jcm13206250. PMID: 39458201; PMCID: PMC11508215.\u003c/li\u003e\n\u003cli\u003eLe\u0026oacute;n-Mu\u0026ntilde;oz VJ, Hurtado-Avil\u0026eacute;s J, L\u0026oacute;pez-L\u0026oacute;pez M, Santonja-Medina F, Moya-Angeler J. The Distribution of Coronal Plane Alignment of the Knee Classification in a Sample of Spanish Southeast Osteoarthritic Population: A Retrospective Cross-Sectional Observational Study. Medicina (Kaunas). 2024 Oct 2;60(10):1612. doi: 10.3390/medicina60101612. PMID: 39459399; PMCID: PMC11509655.\u003c/li\u003e\n\u003cli\u003eGriffiths-Jones W, Chen DB, Harris IA, Bellemans J, MacDessi SJ. Arithmetic hip-knee-ankle angle (aHKA): An algorithm for estimating constitutional lower limb alignment in the arthritic patient population. Bone Jt Open. 2021 May;2(5):351-358. doi: 10.1302/2633-1462.25.BJO-2021-0028.R1. PMID: 34042492; PMCID: PMC8168548.\u003c/li\u003e\n\u003cli\u003eRajasekaran S, Soundarrajan D, Singh R, Shiferaw BA, Rajasekaran RB, Dhanasekararaja P, Rajkumar N. Comparison of imageless robotic assisted total knee arthroplasty and conventional total knee arthroplasty: early clinical and radiological outcomes of 200 knees. J Robot Surg. 2024 Apr 2;18(1):151. doi: 10.1007/s11701-024-01905-x. Erratum in: J Robot Surg. 2024 Jun 15;18(1):252. doi: 10.1007/s11701-024-02004-7. PMID: 38564044.\u003c/li\u003e\n\u003cli\u003eDoan GW, Courtis RP, Wyss JG, Green EW, Clary CW. Image-Free Robotic-Assisted Total Knee Arthroplasty Improves Implant Alignment Accuracy: A Cadaveric Study. J Arthroplasty. 2022 Apr;37(4):795-801. doi: 10.1016/j.arth.2021.12.035. Epub 2022 Jan 1. PMID: 34979253.\u003c/li\u003e\n\u003cli\u003eHuang P, Cross M, Gupta A, Intwala D, Ruppenkamp J, Hoeffel D. Early Clinical and Economic Outcomes for the VELYS Robotic-Assisted Solution Compared with Manual Instrumentation for Total Knee Arthroplasty. J Knee Surg. 2024 Oct;37(12):864-872. doi: 10.1055/a-2343-2444. Epub 2024 Jun 12. PMID: 38866046; PMCID: PMC11405097.\u003c/li\u003e\n\u003cli\u003eWoelfle CA, Geller JA, Neuwirth AL, Sarpong NO, Shah RP, John Cooper H. Robotic assistance improves success of cementless component fixation in one total knee arthroplasty system. Knee. 2024 Oct 12;51:240-248. doi: 10.1016/j.knee.2024.09.012. Epub ahead of print. PMID: 39396419.\u003c/li\u003e\n\u003cli\u003eRajgopal A, Sundararajan SS, Aggarwal K, Kumar S, Singh G. Robotic Assisted TKA achieves adjusted mechanical alignment targets more consistently compared to manual TKA without improving outcomes. J Exp Orthop. 2024 Sep 2;11(3):e70008. doi: 10.1002/jeo2.70008. PMID: 39224750; PMCID: PMC11366966.\u003c/li\u003e\n\u003cli\u003eBensa A, Sangiorgio A, Deabate L, Illuminati A, Pompa B, Filardo G. Robotic-assisted mechanically aligned total knee arthroplasty does not lead to better clinical and radiological outcomes when compared to conventional TKA: a systematic review and meta-analysis of randomized controlled trials. Knee Surg Sports Traumatol Arthrosc. 2023 Nov;31(11):4680-4691. doi: 10.1007/s00167-023-07458-0. Epub 2023 Jun 3. PMID: 37270464.\u003c/li\u003e\n\u003cli\u003eFactor S, Gurel R, Dan D, Benkovich G, Sagi A, Abialevich A, Benkovich V. Validating a Novel 2D to 3D Knee Reconstruction Method on Preoperative Total Knee Arthroplasty Patient Anatomies. J Clin Med. 2024 Feb 22;13(5):1255. doi: 10.3390/jcm13051255. PMID: 38592666; PMCID: PMC10931545.\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-robotic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jors","sideBox":"Learn more about [Journal of Robotic Surgery](http://link.springer.com/journal/11701)","snPcode":"11701","submissionUrl":"https://submission.nature.com/new-submission/11701/3","title":"Journal of Robotic Surgery","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6486112/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6486112/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Robotic-assisted total knee arthroplasty (RATKA) offers enhanced intraoperative accuracy and real-time feedback. This study evaluates mid-term radiological outcomes of imageless RATKA in patients with mild and severe varus or valgus deformities, focusing on alignment accuracy and post-surgical outliers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMethods: A retrospective analysis was conducted on 257 patients who underwent RATKA. Demographic data, BMI, operative side, and key radiographic parameters—including pre- and postoperative hip-knee-ankle (HKA) angle, coronal alignment, joint line obliquity (MPTA + LDFA), tibial slope, and implant details—were recorded. Alignment phenotypes were classified using the CPAK system: Group 1 (varus phenotypes: CPAK I, IV, VII) and Group 2 (valgus phenotypes: CPAK III, VI, IX).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults: RATKA significantly improved alignment in both groups. In Varus Group 1 (N = 181), maximum extension improved (p \u0026lt; 0.001), flexion remained unchanged. JLO and HKA improved (p \u0026lt; 0.001). In Valgus Group 2 (N = 60), extension improved (p \u0026lt; 0.001) with no flexion change. Group 2 had better post-operative HKA and JLO (p \u0026lt; 0.001), aligning with close to CPAK 5 Neutral. Tibial resection was lower in Group 2 (7.43 ± 0.96) mm vs. (8.68 ± 1.45 mm). One tibial recut and one revision observed. Liner use favored 5 mm (80.11%) in Group 1, (90%) in Group 2. RATKA effectively optimized alignment and minimized tibial resection in valgus and varus deformities.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConclusion: Imageless RATKA provides accurate alignment correction in both varus and valgus deformities, even in severe cases. It enables minimal tibial resection and precise, balanced placement of cruciate-retaining implants, underscoring its role in optimizing modern TKA outcomes.\u003c/p\u003e","manuscriptTitle":"Early Radiological Outcomes of Imageless Robotic-Assisted Total Knee Arthroplasty with VELYS®: A Comparative Study of CPAK Varus vs. Valgus Phenotypes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-22 14:36:32","doi":"10.21203/rs.3.rs-6486112/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-22T20:38:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-22T12:12:07+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-22T07:37:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"8924056835555617618067175349222858456","date":"2025-05-20T08:42:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"168986197580435339824676289796969596122","date":"2025-05-20T01:18:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"13918474680079506805915941380573373599","date":"2025-05-19T23:41:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"281831110502987027265151920664171017975","date":"2025-05-19T21:15:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"90745279384125917739740172058377982790","date":"2025-05-19T15:33:24+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-19T15:13:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-23T00:25:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-22T05:17:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Robotic Surgery","date":"2025-04-19T17:34:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-robotic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jors","sideBox":"Learn more about [Journal of Robotic Surgery](http://link.springer.com/journal/11701)","snPcode":"11701","submissionUrl":"https://submission.nature.com/new-submission/11701/3","title":"Journal of Robotic Surgery","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"412735f6-9615-4270-98e9-d53e0e4ba20d","owner":[],"postedDate":"May 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-06-16T16:02:17+00:00","versionOfRecord":{"articleIdentity":"rs-6486112","link":"https://doi.org/10.1007/s11701-025-02456-5","journal":{"identity":"journal-of-robotic-surgery","isVorOnly":false,"title":"Journal of Robotic Surgery"},"publishedOn":"2025-06-13 15:57:52","publishedOnDateReadable":"June 13th, 2025"},"versionCreatedAt":"2025-05-22 14:36:32","video":"","vorDoi":"10.1007/s11701-025-02456-5","vorDoiUrl":"https://doi.org/10.1007/s11701-025-02456-5","workflowStages":[]},"version":"v1","identity":"rs-6486112","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6486112","identity":"rs-6486112","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}