ArticleDiagnostics (Basel, Switzerland)2023
Surgical Phase Duration in Robot-Assisted Partial Nephrectomy: A Surgical Data Science Exploration for Clinical Relevance.
Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Systematic analysis of evaluation metrics for deep learning-based surgical phase recognition in laparoscopic cholecystectomy.Frontiers in artificial intelligence · 2026Review
- Landmark-free automatic digital twin registration in robot-assisted partial nephrectomy using a generic end-to-end model.International journal of computer assisted radiology and surgery · 2025Article
- Surgeons versus computer vision: a comparative analysis on surgical phase recognition capabilities.International journal of computer assisted radiology and surgery · 2025Article
- Renal vascular patterns assessment before robot-assisted partial nephrectomy: a video-based correlation with hilum dissection.World journal of urology · 2025Article
- Impact of Robotic-Assisted Partial Nephrectomy with Single Layer versus Double Layer Renorrhaphy on Postoperative Renal Function.Current oncology (Toronto, Ont.) · 2024Article
Corrections and comments
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Authors and funding
18 authors.
Funding
Abstract
(1) Background: Surgical phases form the basic building blocks for surgical skill assessment, feedback, and teaching. The phase duration itself and its correlation with clinical parameters at diagnosis have not yet been investigated. Novel commercial platforms provide phase indications but have not been assessed for accuracy yet. (2) Methods: We assessed 100 robot-assisted partial nephrectomy videos for phase durations based on previously defined proficiency metrics. We developed an annotation framework and subsequently compared our annotations to an existing commercial solution (Touch Surgery, Medtronic™). We subsequently explored clinical correlations between phase durations and parameters derived from diagnosis and treatment. (3) Results: An objective and uniform phase assessment requires precise definitions derived from an iterative revision process. A comparison to a commercial solution shows large differences in definitions across phases. BMI and the duration of renal tumor identification are positively correlated, as are tumor complexity and both tumor excision and renorrhaphy duration. (4) Conclusions: The surgical phase duration can be correlated with certain clinical outcomes. Further research should investigate whether the retrieved correlations are also clinically meaningful. This requires an increase in dataset sizes and facilitation through intelligent computer vision algorithms. Commercial platforms can facilitate this dataset expansion and help unlock the full potential, provided that the phase annotation details are disclosed.
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Registered trials
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