Real-time AI labeling of critical anatomy during laparoscopic gallbladder removal

Research on Identifying Critical Surgical Anatomy in Cholecystectomy Videos Based on Deep Learning

Observational Chinese Academy of Sciences · NCT07158372

This project will try a real-time AI algorithm to label key anatomical structures in laparoscopic cholecystectomy videos to help surgeons avoid bile duct injuries.

Quick facts

Study typeObservational
Enrollment200 (estimated)
Ages18 Years and up
SexAll
SponsorChinese Academy of Sciences Government
Locations5 sites (Zhengzhou, Henan and 4 other locations)
Trial IDNCT07158372 on ClinicalTrials.gov

What this trial studies

This observational project collects high-quality laparoscopic cholecystectomy videos from several participating hospitals and uses them to train a deep-learning object recognition algorithm. The model is trained to identify and label key anatomical structures in video frames and to highlight areas considered dangerous or safe during dissection. Blurry or out-of-hospital videos are excluded to preserve data quality, and annotated frames are used for model validation. The goal is to produce real-time visual guidance that can be integrated into the operating room workflow for further clinical testing.

Who should consider this trial

Good fit: Adults aged 18 or older who are scheduled for laparoscopic cholecystectomy at one of the participating hospitals and whose operations are recorded with clear intraoperative video are the intended data sources.

Not a fit: Patients who undergo open cholecystectomy, have surgery performed outside the participating centers, or whose intraoperative videos are too blurry will likely not benefit from this project.

Why it matters

Potential benefit: If successful, the algorithm could give surgeons immediate visual warnings during gallbladder removal, potentially reducing bile duct injuries and other complications.

How similar studies have performed: Similar deep-learning approaches for surgical phase recognition and anatomy segmentation have shown promising early results in research settings but are not yet widely adopted in routine clinical practice.

Eligibility criteria

Show full inclusion / exclusion criteria
Inclusion Criteria:

* Patients aged 18 or above who are diagnosed by a doctor as needing laparoscopic cholecystectomy

Exclusion Criteria:

* Patients who did not undergo surgery at the original hospital and those whose videos were blurry were excluded.

Where this trial is running

Zhengzhou, Henan and 4 other locations

Study contacts

How to participate

  1. Review the eligibility criteria above with your treating physician.
  2. Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
  3. Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions CholecystectomySurgical Video IdentificationDeep LearningArtificial Intelligence
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.