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This study presents a machine-learning approach to fully automatically quantify anatomical varus/valgus alignment from standard anteroposterior (AP) knee radiographs. A training set and separate test set of TKA patient radiographs were used, with outcomes evaluated against points-based manual and clinical surgeon measurements using ICC, MAD, and Bland-Altman analysis.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/an-ai-based-system-for-fully-automated-knee-alignment-assessment-in-standard-ap-knee-radiographs/447683/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/an-ai-based-system-for-fully-automated-knee-alignment-assessment-in-standard-ap-knee-radiographs/447683.png","ImageObject",300,407,{"name":92,"@type":93},"dabgoudw","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-30","2026-09-29",true,{"@type":102,"interactionType":103,"userInteractionCount":44},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why is automated knee alignment assessment important in knee arthroplasty?","Question",{"text":112,"@type":113},"Accurate alignment assessment is crucial for planning and evaluating knee arthroplasty. Manual methods are time-consuming and can introduce measurement errors.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does the proposed system measure varus/valgus alignment?",{"text":117,"@type":113},"The distal femur and proximal tibia/fibula are outlined using points that capture the knee joint, and the femorotibial angle is computed from these points. Varus/valgus is defined by negative/positive deviations from zero.",{"name":119,"@type":110,"acceptedAnswer":120},"How was the system performance evaluated?",{"text":121,"@type":113},"Automatic measurements were compared with points-based manual measurements and clinical measurements from an orthopaedic surgeon. Agreement was assessed using ICC, MAD, and Bland-Altman analysis, showing excellent pre-operative agreement and reduced post-operative agreement.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},447683,1790790810,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":44,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},3985747860484,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","Europe PMC unders uthManuscripts Europe M eC und Author Manuscripts  \n| Europe PMC Funders Group\u003Cbr>Author Manuscript\u003Cbr>Knee. Author manuscript; available in PMC 2026 January 06. |\n| --- |\n| Published in final edited form as:\u003Cbr>Knee. 2025 June 01; 54: 99–110. doi:10.1016/j.knee.2025.02.013 .\u003Cbr>An Al-based system for fully automated knee alignment assessment in standard AP knee radiographs ⋆\u003Cbr>Dominic Cullena,b, Peter Thompsona, David Johnsonc,d,e, Claudia Lindnera,*\u003Cbr>a Division of informatics, Imaging and Data Sciences, School of Health Sciences, The University of Manchester, United Kingdom.\u003Cbr>b Northern Care Alliance NHS Foundation Trust, Salford, United Kingdom.\u003Cbr>c Department of Trauma and Orthopaedics, Stockport NHS Foundation Trust, Stepping Hill Hospital, Stockport, United Kingdom.\u003Cbr>dSchool of Health and Society, University of Salford, United Kingdom.\u003Cbr>eSchool of Biological Sciences, The University of Manchester, United Kingdom.\u003Cbr>Abstract\u003Cbr>Background: Accurate assessment of knee alignment in pre-and post-operative radiographs is crucial for knee arthroplasty planning and evaluation. Current methods rely on manual alignment assessment, which is time-consuming and error-prone. This study proposes a machine learningbased approach to fully automatically measure anatomical varus/valgus alignment in standard anteroposterior (AP) knee radiographs.\u003Cbr>Methods: We collected a training dataset of 566 pre-operative and 457 one-year post-operative AP knee radiographs from total knee arthroplasty patients, along with a separate test set of 376 patients. The distal femur and proximal tibia/fibula were manually outlined using points to capture the knee joint. The outlines were used to develop an automatic system to locate the points.\u003Cbr>The anatomical femorotibial angle was calculated using the points, with varus/valgus defined as negative/positive deviations from zero. Fifty test images were clinically measured on two occasions by an orthopaedic surgeon. Agreement between points-based manual, automatic, and clinical measurements was assessed using intra-class correlation coefficient (ICC), mean absolute difference (MAD) and Bland-Altman analysis.\u003Cbr>This work is licensed under a BY 4.0 International license.\u003Cbr>*[Corresponding author. claudia.lindner@manchester ac.uk](Corresponding author. claudia.lindner@manchester ac.uk) (C. Lindner) .\u003Cbr>⋆This article is part of a special issue entitled: ‘AI and new technologies’ published in The Knee.\u003Cbr>CRediT authorship contribution statement\u003Cbr>Dominic Cullen: Writing – review & editing, Writing – original draft, Data curation, Conceptualization. Peter Thompson: Writing – review & editing, Data curation. David Johnson: Writing – review & editing, Methodology, Formal analysis, Data curation, Conceptualization. Claudia Lindner: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Declaration of competing interest\u003Cbr>The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Patent: “Image processing apparatus and method for fitting a deformable shape model to an image using random forest regression voting.” |\n\nEurope PMC unders uthManuscripts Europe M eC und Author Manuscripts  \nCullen et al. Page 2  \nResults: The agreement between automatic and manual measurements was excellent pre-/ post-operatively with ICC 0.98/0.96 and MAD 0.8°/0.7° . The agreement between automatic and clinical measurements was excellent pre-operatively (ICC: 0.97; MAD: 1.2°) but lacked  \nperformance post-operatively (ICC: 0.78; MAD: 1.5°) . The clinical intra-observer agreement was excellent pre-/post-operatively with ICC 0.99/0.95 and MAD 0.9°/0.8° .  \nConclusion: The developed system demonstrates high reliability in automatically measuring varus/valgus alignm","cbCaipw7LhNeMkpv","https://ap.wps.com/l/cbCaipw7LhNeMkpv","pdf",2154412,23,"English","# Abstract\n## Background\n## Methods\n## Results\n## Conclusion\n# Keywords\n# Introduction","[{\"question\":\"Why is automated knee alignment assessment important in knee arthroplasty?\",\"answer\":\"Accurate alignment assessment is crucial for planning and evaluating knee arthroplasty. Manual methods are time-consuming and can introduce measurement errors.\"},{\"question\":\"How does the proposed system measure varus/valgus alignment?\",\"answer\":\"The distal femur and proximal tibia/fibula are outlined using points that capture the knee joint, and the femorotibial angle is computed from these points. Varus/valgus is defined by negative/positive deviations from zero.\"},{\"question\":\"How was the system performance evaluated?\",\"answer\":\"Automatic measurements were compared with points-based manual measurements and clinical measurements from an orthopaedic surgeon. Agreement was assessed using ICC, MAD, and Bland-Altman analysis, showing excellent pre-operative agreement and reduced post-operative agreement.\"}]","An AI-based system for fully automated knee alignment assessment in standard AP knee radiographs | PDF",1790722186,58]