ArticleSurgical endoscopy2023
Towards automatic verification of the critical view of the myopectineal orifice with artificial intelligence.
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 21 papers.
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Who cites it
21 citing papers in PubMed, 25 citations in OpenAlex.
- A novel artificial intelligence anatomical model for landmark recognition in endolaparoscopic totally extraperitoneal inguinal hernia repair.Surgical endoscopy · 2026Article
- Artificial intelligence-based anatomical segmentation in transabdominal preperitoneal repair of groin hernia.Hernia : the journal of hernias and abdominal wall surgery · 2026Article
- Artificial intelligence in abdominal wall hernia surgery: clinical applications and translational readiness.Surgical endoscopy · 2026Review
- A proof-of-concept study of surgical-VLM for surgical support in robotic surgery: contextual benchmarking against ChatGPT-5.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2026Article
- Artificial-Intelligence-based Surgical Phase Recognition in Robot-Assisted Radical Prostatectomy and Cross-Surgeon Validation.Annals of surgical oncology · 2026Article
- Improving Intraoperative Compliance With Critical View of the Myopectineal Orifice Criteria Using the V-M Pathway During Laparoscopic Inguinal Hernia Repair.Journal of abdominal wall surgery : JAWS · 2026Article
- Assessment of AI-driven anatomical recognition in robotic gastrectomy: A multicenter retrospective analysis.Surgical endoscopy · 2025Article
- Role of Robotic Surgery and Artificial Intelligence in the Management of Abdominal Wall Hernias: A Systematic Review.Cureus · 2025Review
- Artificial Intelligence in Gastrointestinal Surgery: A Systematic Review of Its Role in Laparoscopic and Robotic Surgery.Journal of personalized medicine · 2025Review
- Article
- External Validation of an Automated Surgical Step Recognition Model for Robotic Distal Gastrectomy (RDG) Using a Multicenter Dataset.Annals of gastroenterological surgery · 2025Article
- Emerging innovation, artificial intelligence, and digital technology in esophagology.Annals of the New York Academy of Sciences · 2025Review
- Landmark display system for laparoscopic inguinal hernia repair using artificial intelligence.Surgical endoscopy · 2025Article
- Use of artificial intelligence in the analysis of digital videos of invasive surgical procedures: scoping review.BJS open · 2025Article
- Anatomical recognition of dissection layers, nerves, vas deferens, and microvessels using artificial intelligence during transabdominal preperitoneal inguinal hernia repair.Hernia : the journal of hernias and abdominal wall surgery · 2024Article
- Usefulness of an Artificial Intelligence Model in Recognizing Recurrent Laryngeal Nerves During Robot-Assisted Minimally Invasive Esophagectomy.Annals of surgical oncology · 2024Article
- ASO Author Reflections: Can Artificial Intelligence Assist in the Recognition of Recurrent Laryngeal Nerve During Robot-Assisted Minimally Invasive Esophagectomy?Annals of surgical oncology · 2024Article
- Evaluating surgical expertise with AI-based automated instrument recognition for robotic distal gastrectomy.Annals of gastroenterological surgery · 2024Article
- Real-time detection of active bleeding in laparoscopic colectomy using artificial intelligence.Surgical endoscopy · 2024Article
- Artificial intelligence and surgery.Annals of gastroenterological surgery · 2024Article
Corrections and comments
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Authors and funding
15 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVisualization of key anatomical landmarks is required during surgical Trans Abdominal Pre Peritoneal repair (TAPP) of inguinal hernia. The Critical View of the MyoPectineal Orifice (CVMPO) was proposed to ensure correct dissection. An artificial intelligence (AI) system that automatically validates the presence of key and marks during the procedure is a critical step towards automatic dissection quality assessment and video-based competency evaluation. The aim of this study was to develop an AI system that automatically recognizes the TAPP key CVMPO landmarks in hernia repair videos.
methodsSurgical videos of 160 TAPP procedures were used in this single-center study. A deep neural network-based object detector was developed to automatically recognize the pubic symphysis, direct hernia orifice, Cooper's ligament, the iliac vein, triangle of Doom, deep inguinal ring, and iliopsoas muscle. The system was trained using 130 videos, annotated and verified by two board-certified surgeons. Performance was evaluated in 30 videos of new patients excluded from the training data.
resultsPerformance was validated in 2 ways: first, single-image validation where the AI model detected landmarks in a single laparoscopic image (mean average precision (MAP) of 51.2%). The second validation is video evaluation where the model detected landmarks throughout the myopectineal orifice visual inspection phase (mean accuracy and F-score of 77.1 and 75.4% respectively). Annotation objectivity was assessed between 2 surgeons in video evaluation, showing a high agreement of 88.3%.
conclusionThis study establishes the first AI-based automated recognition of critical structures in TAPP surgical videos, and a major step towards automatic CVMPO validation with AI. Strong performance was achieved in the video evaluation. The high inter-rater agreement confirms annotation quality and task objectivity.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.