Trial reportSurgical endoscopy2023
An intraoperative artificial intelligence system identifying anatomical landmarks for laparoscopic cholecystectomy: a prospective clinical feasibility trial (J-SUMMIT-C-01).
Trial report in Surgical endoscopy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.
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The trial behind it
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
25 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Detection of anatomic landmarks during laparoscopic cholecystectomy with the use of artificial intelligence-a systematic review of the literature.Updates in surgery · 2026Pooled it
- Systematic review on the use of artificial intelligence to identify anatomical structures during laparoscopic cholecystectomy: a tool towards the future.Langenbeck's archives of surgery · 2025Pooled it
- First-in-human evaluation of real-time pixel-level AI-assisted anatomical segmentation in neurosurgery: pituitary surgery as an exemplar.Pituitary · 2026Article
- AI-based smoke removal in robotic urooncologic surgery: a clinical pilot study.Journal of robotic surgery · 2026Article
- Artificial Intelligence for Automated Recognition of Hepatocystic Anatomy During Laparoscopic Cholecystectomy: Current Evidence, Clinical Readiness, and Future Directions.Medicina (Kaunas, Lithuania) · 2026Review
- Application of deep learning for surgical decision support during single-incision laparoscopic cholecystectomy.Surgical endoscopy · 2026Article
- Deep learning-based real-time intraoperative detection of thoracic duct.Journal of thoracic disease · 2026Article
- Artificial intelligence in emergency surgery: a scoping review within the artificial intelligence in emergency and trauma surgery (ARIES) project.World journal of emergency surgery : WJES · 2026Article
- Exploring the Impact of an Artificial Intelligence-Based Intraoperative Image Navigation System in Laparoscopic Surgery on Clinical Outcomes: A Protocol for a Multicenter Randomized Controlled Trial.European surgical research. Europaische chirurgische Forschung. Recherches chirurgicales europeennes · 2026Article
- An artificial intelligence-based image recognition model using indocyanine green cholangiography to identify the hepatocystic triangle during minimally‑invasive cholecystectomy.Wideochirurgia i inne techniki maloinwazyjne = Videosurgery and other miniinvasive techniques · 2025Article
- Artificial Intelligence in Gastrointestinal Surgery: A Systematic Review of Its Role in Laparoscopic and Robotic Surgery.Journal of personalized medicine · 2025Review
- Artificial intelligence-supported system of surgical anatomy recognition may facilitate the understanding of gastrointestinal surgery for medical students.Surgical endoscopy · 2025Article
- Deep learning HRNet FCN for blood vessel identification in laparoscopic pancreatic surgery.NPJ digital medicine · 2025Article
- Development of an artificial intelligence system to indicate intraoperative findings of scarring in laparoscopic cholecystectomy for cholecystitis.Surgical endoscopy · 2025Article
- AI-based visualization of loose connective tissue as a dissectable layer in gastrointestinal surgery.Scientific reports · 2025Article
- Vision techniques for anatomical structures in laparoscopic surgery: a comprehensive review.Frontiers in surgery · 2025Review
- Artificial Intelligence (AI) Competency and Educational Needs: Results of an AI Survey of Members of the European Society of Pediatric Endoscopic Surgeons (ESPES).Children (Basel, Switzerland) · 2024Article
- Artificial intelligence for surgical safety during laparoscopic gastrectomy for gastric cancer: Indication of anatomical landmarks related to postoperative pancreatic fistula using deep learning.Surgical endoscopy · 2024Article
- Artificial intelligence applied to laparoscopic cholecystectomy: what is the next step? A narrative review.Updates in surgery · 2024Review
- Article
Corrections and comments
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWe have implemented Smart Endoscopic Surgery (SES), a surgical system that uses artificial intelligence (AI) to detect the anatomical landmarks that expert surgeons base on to perform certain surgical maneuvers. No report has verified the use of AI-based support systems for surgery in clinical practice, and no evaluation method has been established. To evaluate the detection performance of SES, we have developed and established a new evaluation method by conducting a clinical feasibility trial.
methodsA single-center prospective clinical feasibility trial was conducted on 10 cases of LC performed at Oita University hospital. Subsequently, an external evaluation committee (EEC) evaluated the AI detection accuracy for each landmark using five-grade rubric evaluation and DICE coefficient. We defined LM-CBD as the expert surgeon's "judge" of the cystic bile duct in endoscopic images.
resultsThe average detection accuracy on the rubric by the EEC was 4.2 ± 0.8 for the LM-CBD. The DICE coefficient between the AI detection area of the LM-CBD and the EEC members' evaluation was similar to the mean value of the DICE coefficient between the EEC members. The DICE coefficient was high score for the case that was highly evaluated by the EEC on a five-grade scale.
conclusionThis is the first feasible clinical trial of an AI system designed for intraoperative use and to evaluate the AI system using an EEC. In the future, this concept of evaluation for the AI system would contribute to the development of new AI navigation systems for surgery.
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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.