ArticleSurgical endoscopy2023
Proposal and multicentric validation of a laparoscopic Roux-en-Y gastric bypass surgery ontology.
Article in Surgical endoscopy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- A Standardized Temporal Segmentation Framework and Annotation Resource Library in Robotic Surgery.Mayo Clinic proceedings. Digital health · 2025Article
- Robotic bariatric surgery: the Italian point of view to go beyond.Updates in surgery · 2025Article
- Semantic web-based ontology: a comprehensive framework for cardiovascular knowledge representation.BMC cardiovascular disorders · 2025Article
- Analyzing the impact of surgical technique on intraoperative adverse events in laparoscopic Roux-en-Y gastric bypass surgery by video-based assessment.Surgical endoscopy · 2025Article
- Challenges in multi-centric generalization: phase and step recognition in Roux-en-Y gastric bypass surgery.International journal of computer assisted radiology and surgery · 2024Article
- Surgical Phase Duration in Robot-Assisted Partial Nephrectomy: A Surgical Data Science Exploration for Clinical Relevance.Diagnostics (Basel, Switzerland) · 2023Article
- Preserving privacy in surgical video analysis using a deep learning classifier to identify out-of-body scenes in endoscopic videos.Scientific reports · 2023Article
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Abstract
backgroundPhase and step annotation in surgical videos is a prerequisite for surgical scene understanding and for downstream tasks like intraoperative feedback or assistance. However, most ontologies are applied on small monocentric datasets and lack external validation. To overcome these limitations an ontology for phases and steps of laparoscopic Roux-en-Y gastric bypass (LRYGB) is proposed and validated on a multicentric dataset in terms of inter- and intra-rater reliability (inter-/intra-RR).
methodsThe proposed LRYGB ontology consists of 12 phase and 46 step definitions that are hierarchically structured. Two board certified surgeons (raters) with > 10 years of clinical experience applied the proposed ontology on two datasets: (1) StraBypass40 consists of 40 LRYGB videos from Nouvel Hôpital Civil, Strasbourg, France and (2) BernBypass70 consists of 70 LRYGB videos from Inselspital, Bern University Hospital, Bern, Switzerland. To assess inter-RR the two raters' annotations of ten randomly chosen videos from StraBypass40 and BernBypass70 each, were compared. To assess intra-RR ten randomly chosen videos were annotated twice by the same rater and annotations were compared. Inter-RR was calculated using Cohen's kappa. Additionally, for inter- and intra-RR accuracy, precision, recall, F1-score, and application dependent metrics were applied.
resultsThe mean ± SD video duration was 108 ± 33 min and 75 ± 21 min in StraBypass40 and BernBypass70, respectively. The proposed ontology shows an inter-RR of 96.8 ± 2.7% for phases and 85.4 ± 6.0% for steps on StraBypass40 and 94.9 ± 5.8% for phases and 76.1 ± 13.9% for steps on BernBypass70. The overall Cohen's kappa of inter-RR was 95.9 ± 4.3% for phases and 80.8 ± 10.0% for steps. Intra-RR showed an accuracy of 98.4 ± 1.1% for phases and 88.1 ± 8.1% for steps.
conclusionThe proposed ontology shows an excellent inter- and intra-RR and should therefore be implemented routinely in phase and step annotation of LRYGB.
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