Dennis King-Hang Yee, Jonathan Patrick Ng, Cyrus Tsun-Kit Lau, Kevin Ki-Wai Ho, Gene Chi-Wai Man, Vikki Wing-Shan Chu, Tsz Lung Choi, Gloria Yan Ting Lam, Michael Tim-Yun Ong, Patrick Shu-Hang Yung
{"title":"Surgical accuracy of image-free versus image-based robotic-assisted total knee arthroplasty","authors":"Dennis King-Hang Yee, Jonathan Patrick Ng, Cyrus Tsun-Kit Lau, Kevin Ki-Wai Ho, Gene Chi-Wai Man, Vikki Wing-Shan Chu, Tsz Lung Choi, Gloria Yan Ting Lam, Michael Tim-Yun Ong, Patrick Shu-Hang Yung","doi":"10.1002/rcs.2574","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>This study investigated the accuracy in achieving proper lower limb alignment and component positions after total knee replacement (TKR) with image-free and image-based robotic-assisted TKR.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>A total of 129 patients (166 knees) suffering from end-stage knee arthritis who underwent TKA operated by robotic-assisted surgery between the years 2018 and mid-2021 were recruited. Radiological outcomes were compared between image-free and image-based robotic-assisted surgical systems.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>There were significant differences between the two robotic systems when comparing the mean planned component alignment and the mean measured alignment on radiographs, in which the image-free robotic-assisted system was more varus, whereas the image-based robotic-assisted system was more valgus for both the mean femoral and tibial component coronal alignment (<i>p</i> < 0.001). For tibial component sagittal alignment, the image-based group had a larger deviation from the planned posterior slope (<i>p</i> < 0.001).</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>Image-free and image-based robotic assisted TKR had differing accuracy in femoral and tibial alignment.</p>\n </section>\n </div>","PeriodicalId":50311,"journal":{"name":"International Journal of Medical Robotics and Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rcs.2574","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Medical Robotics and Computer Assisted Surgery","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/rcs.2574","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SURGERY","Score":null,"Total":0}
引用次数: 0
Abstract
Background
This study investigated the accuracy in achieving proper lower limb alignment and component positions after total knee replacement (TKR) with image-free and image-based robotic-assisted TKR.
Methods
A total of 129 patients (166 knees) suffering from end-stage knee arthritis who underwent TKA operated by robotic-assisted surgery between the years 2018 and mid-2021 were recruited. Radiological outcomes were compared between image-free and image-based robotic-assisted surgical systems.
Results
There were significant differences between the two robotic systems when comparing the mean planned component alignment and the mean measured alignment on radiographs, in which the image-free robotic-assisted system was more varus, whereas the image-based robotic-assisted system was more valgus for both the mean femoral and tibial component coronal alignment (p < 0.001). For tibial component sagittal alignment, the image-based group had a larger deviation from the planned posterior slope (p < 0.001).
Conclusion
Image-free and image-based robotic assisted TKR had differing accuracy in femoral and tibial alignment.
期刊介绍:
The International Journal of Medical Robotics and Computer Assisted Surgery provides a cross-disciplinary platform for presenting the latest developments in robotics and computer assisted technologies for medical applications. The journal publishes cutting-edge papers and expert reviews, complemented by commentaries, correspondence and conference highlights that stimulate discussion and exchange of ideas. Areas of interest include robotic surgery aids and systems, operative planning tools, medical imaging and visualisation, simulation and navigation, virtual reality, intuitive command and control systems, haptics and sensor technologies. In addition to research and surgical planning studies, the journal welcomes papers detailing clinical trials and applications of computer-assisted workflows and robotic systems in neurosurgery, urology, paediatric, orthopaedic, craniofacial, cardiovascular, thoraco-abdominal, musculoskeletal and visceral surgery. Articles providing critical analysis of clinical trials, assessment of the benefits and risks of the application of these technologies, commenting on ease of use, or addressing surgical education and training issues are also encouraged. The journal aims to foster a community that encompasses medical practitioners, researchers, and engineers and computer scientists developing robotic systems and computational tools in academic and commercial environments, with the intention of promoting and developing these exciting areas of medical technology.