AI to improve safety during laparoscopic gallbladder removal
Evaluating the Clinical Impact of Artificial Intelligence on Safety in Laparoscopic Cholecystectomy: A Randomized Controlled Trial
PHASE3 · University Health Network, Toronto · NCT07186803
This tests whether real-time AI guidance helps surgeons perform safer laparoscopic gallbladder removals for adult patients.
Quick facts
| Phase | PHASE3 |
|---|---|
| Study type | Interventional |
| Enrollment | 70 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | University Health Network, Toronto (other) |
| Locations | 2 sites (Toronto, Ontario and 1 other locations) |
| Trial ID | NCT07186803 on ClinicalTrials.gov |
What this trial studies
Researchers will randomize 10 surgeons or fellows to perform five laparoscopic cholecystectomies each with real-time AI guidance or standard care, for a total of 50 adult patients across Toronto General and Toronto Western Hospitals. Two AI models will provide intraoperative feedback to guide safe dissection and the achievement of the Critical View of Safety, while operative recordings are collected for blinded post‑hoc review by expert surgeons. The primary outcome is the rate of achieving the Critical View of Safety, and secondary outcomes include the proportion of dissections above the line of safety, surgeon feedback, observational notes, and 30‑day postoperative chart review. The randomized controlled design compares immediate intraoperative safety milestones and surgeon behavior with and without AI support.
Who should consider this trial
Good fit: Adults (18+) scheduled for laparoscopic cholecystectomy performed by participating surgeons or fellows at the University Health Network hospitals are the ideal candidates.
Not a fit: Patients who are having open cholecystectomy, who are operated on outside the two participating hospitals, or whose surgeons do not participate in the program are unlikely to benefit from this intervention.
Why it matters
Potential benefit: If successful, AI guidance could lower the risk of bile duct injury and other complications during laparoscopic gallbladder removal.
How similar studies have performed: Early technical studies and pilot clinical reports suggest AI can recognize surgical anatomy and assist decision‑making, but randomized clinical evidence for intraoperative AI guidance remains limited.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Surgeon participants: Attending surgeons or fellows that perform laparoscopic cholecystectomy at University Health Network. * Patients participants: Adults 18 years of age and over, scheduled for laparoscopic cholecystectomy surgery. Exclusion Criteria: * Surgeon participants: Anyone who is not a surgeon or fellow at University Health Network or that does not perform laparoscopic cholecystectomies. * Patient participants: Any patient who is not having a laparoscopic cholecystectomy surgery.
Where this trial is running
Toronto, Ontario and 1 other locations
- Toronto General Hospital — Toronto, Ontario, Canada (RECRUITING)
- Toronto Western Hospital — Toronto, Ontario, Canada (RECRUITING)
Study contacts
- Study coordinator: Ariana Walji, BSc, MSc Candidate
- Email: ariana.walji@uhn.ca
- Phone: 416-603-5185
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions: Laparoscopic Cholecystectomy, artificial intelligence, laparoscopic cholecystectomy, safety, critical view of safety, line of safety