Real-time AI labeling of critical anatomy during laparoscopic gallbladder removal
Official title: Research on Identifying Critical Surgical Anatomy in Cholecystectomy Videos Based on Deep Learning
Run by Chinese Academy of Sciences · NCT07158372 · Data updated 2026-11-12
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 type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 200 (estimated) |
| Sponsor | Chinese Academy of Sciences Government |
| Locations | 5 sites (Zhengzhou, Henan and 4 other locations) |
| Status | Recruiting |
| Started | August 15, 2025 |
| Main results expected | August 15, 2026 |
| Study ends | August 15, 2028 |
| Registry record updated | September 5, 2025 |
| Trial ID | NCT07158372 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a 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.
✕Probably 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.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
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.
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 gone: 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.
Who can join: the full rules
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 it's running
-
The First Affiliated Hospital of Zhengzhou University
Zhengzhou, Henan, China Recruiting -
Beijing Anzhen Hospital, Capital Medical University
Beijing, China Recruiting -
Beijing Luhe Hospital, Capital Medical University
Beijing, China Recruiting -
Peking university people's hospital
Beijing, China Recruiting -
Shanghai East Hospital of Tongji University
Shanghai, China Recruiting
Study contacts
- Study coordinator: Di Dong, Ph.D
- Email: di.dong@ia.ac.cn
- Phone: +86 010-82618465
Similar studies
Other studies for the same condition or treatment. Recruiting studies are listed first.
-
PEG bowel preparation effects on gut microbes after gallbladder removal
This study tests whether PEG-based colonoscopy prep causes larger or longer-lasting changes to gut microbes in adults who have had their gallbladder removed compared with people who still have their gallbladder.
-
Comparing laparoscopic ultrasound and fluorescence imaging with indocyanine green to map bile ducts during difficult laparoscopic gallbladder removal
This will try two imaging methods—laparoscopic ultrasound and fluorescence cholangiography with indocyanine green—in adults having technically difficult laparoscopic gallbladder removal to see which shows the bile duct anatomy best.
-
Robotic versus laparoscopic gallbladder removal for benign gallbladder disease
This trial will test whether robotic gallbladder removal is as safe as standard laparoscopic surgery for adults who need their gallbladder removed for benign disease.
-
How genetic differences affect nalbuphine pain relief after abdominal or pelvic surgery
We will test whether genetic differences change how well nalbuphine relieves pain after abdominal or pelvic surgery in adults.
-
Stanford program to advance robotic surgery for children and adolescents
This program will try the da Vinci Xi surgical robot in children and adolescents (ages 6–21, ≥15 kg) to see if it is safe and works well for procedures like sleeve gastrectomy, cholecystectomy, splenectomy, hysterectomy, and operations for endometriosis.
-
Subcostal TAP Block and EEG Changes During Laparoscopic Gallbladder Surgery
This observational study tests whether adding a subcostal TAP block to standard IV opioid therapy affects intraoperative brain activity measures and pain needs in adults undergoing laparoscopic cholecystectomy.
How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.