Busisiwe Mlambo MD , Mallory Shields PhD , Simon Bach MD , Armin Bauer PhD , Andrew Hung MD , Omar Yusef Kudsi MD , Felix Neis MD , John Lazar MD , Daniel Oh MD , Robert Perez MD , Seth Rosen MD , Naeem Soomro MD , Michael Stany MD , Mark Tousignant MD , Christian Wagner MD , Ken Whaler MS , Lilia Purvis MS , Benjamin Mueller BS , Sadia Yousaf MD , Casey Troxler BS , Anthony Jarc PhD
{"title":"A Standardized Temporal Segmentation Framework and Annotation Resource Library in Robotic Surgery","authors":"Busisiwe Mlambo MD , Mallory Shields PhD , Simon Bach MD , Armin Bauer PhD , Andrew Hung MD , Omar Yusef Kudsi MD , Felix Neis MD , John Lazar MD , Daniel Oh MD , Robert Perez MD , Seth Rosen MD , Naeem Soomro MD , Michael Stany MD , Mark Tousignant MD , Christian Wagner MD , Ken Whaler MS , Lilia Purvis MS , Benjamin Mueller BS , Sadia Yousaf MD , Casey Troxler BS , Anthony Jarc PhD","doi":"10.1016/j.mcpdig.2025.100257","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><div>To develop and share the first clinical temporal annotation guide library for 10 robotic procedures accompanied with a standardized ontology framework for surgical video annotation.</div></div><div><h3>Patients and Methods</h3><div>A standardized temporal annotation framework of surgical videos paired with consistent, procedure-specific annotation guides is critical to enable comparisons of surgical insights and facilitate large-scale insights for exceptional surgical practice. Existing ontologies and guidance not only provide foundational frameworks but also provide limited scalability in clinical settings. Building on these, we developed a temporal annotation framework with nested surgical phases, steps, tasks, and subtasks. Procedure-specific annotation resource guides consistent with this framework that define each surgical segment with formulaic start and stop parameters and surgical objectives were iteratively created across 7 years (January 1, 2018, to January 1, 2025) through global research collaborations with surgeon researchers and industry scientists.</div></div><div><h3>Results</h3><div>We provide the first resource library of annotation guides for 10 common robotic procedures consistent with our proposed temporal annotation framework, enabling consistent annotations for clinicians and large-scale data comparisons with computer-readable examples. These have been used in over 13,000 annotated surgical cases globally, demonstrating reproducibility and broad applicability.</div></div><div><h3>Conclusion</h3><div>This resource library and accompanying ontology framework provide critical structure for standardized temporal segmentation in robotic surgery. This framework has been applied globally in private studies examining surgical objective performance metrics, surgical education, workflow characterization, outcome prediction, algorithms for surgical activity recognition, and more. Adoption of these resources will unify clinical, academic, and industry efforts, ultimately catalyzing transformational advancements in surgical practice.</div></div>","PeriodicalId":74127,"journal":{"name":"Mayo Clinic Proceedings. Digital health","volume":"3 4","pages":"Article 100257"},"PeriodicalIF":0.0000,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mayo Clinic Proceedings. Digital health","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949761225000641","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Objective
To develop and share the first clinical temporal annotation guide library for 10 robotic procedures accompanied with a standardized ontology framework for surgical video annotation.
Patients and Methods
A standardized temporal annotation framework of surgical videos paired with consistent, procedure-specific annotation guides is critical to enable comparisons of surgical insights and facilitate large-scale insights for exceptional surgical practice. Existing ontologies and guidance not only provide foundational frameworks but also provide limited scalability in clinical settings. Building on these, we developed a temporal annotation framework with nested surgical phases, steps, tasks, and subtasks. Procedure-specific annotation resource guides consistent with this framework that define each surgical segment with formulaic start and stop parameters and surgical objectives were iteratively created across 7 years (January 1, 2018, to January 1, 2025) through global research collaborations with surgeon researchers and industry scientists.
Results
We provide the first resource library of annotation guides for 10 common robotic procedures consistent with our proposed temporal annotation framework, enabling consistent annotations for clinicians and large-scale data comparisons with computer-readable examples. These have been used in over 13,000 annotated surgical cases globally, demonstrating reproducibility and broad applicability.
Conclusion
This resource library and accompanying ontology framework provide critical structure for standardized temporal segmentation in robotic surgery. This framework has been applied globally in private studies examining surgical objective performance metrics, surgical education, workflow characterization, outcome prediction, algorithms for surgical activity recognition, and more. Adoption of these resources will unify clinical, academic, and industry efforts, ultimately catalyzing transformational advancements in surgical practice.