NCT07158372

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

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 200 (estimated)
• Sponsor: Chinese Academy of Sciences · Other Government
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

Laparoscopic cholecystectomy is a common surgical procedure, but it carries the potential for bile duct injury and other surgical risks. To provide visual assistance to surgeons during surgery and mitigate these risks, this research project aims to develop a real-time object recognition algorithm based on deep learning technology. This algorithm will label key anatomical structures in laparoscopic cholecystectomy videos, providing surgeons with immediate information on dangerous and safe areas.

Detailed description

Laparoscopic cholecystectomy is a common surgical procedure, but it carries the potential for bile duct injury and other surgical risks. To provide visual assistance to surgeons during surgery and mitigate these risks, this research project aims to develop a real-time object recognition algorithm based on deep learning technology. This algorithm will label key anatomical structures in laparoscopic cholecystectomy videos, providing surgeons with immediate information on dangerous and safe areas.

Conditions

• Cholecystectomy
• Surgical Video Identification

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	AI-assisted Intraoperative Anatomy Analysis	This is a prospective study on patients aged 18 years or more diagnosed with laparoscopic cholecystectomy. We will collect information such as laparoscopic cholecystectomy videos and procedure type, excluding patients who did not undergo surgery at the original hospital or whose videos were blurry.

Timeline

• Start date: 2025-08-15
• Primary completion: 2026-08-15
• Completion: 2028-08-15
• First posted: 2025-09-05
• Last updated: 2025-09-05

Locations

5 sites across 1 country: China