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

NCT07158372 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 200

Last updated 2025-09-05

No results posted yet for this study

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.

Conditions

  • Cholecystectomy
  • Surgical Video Identification

Interventions

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.

Sponsors & Collaborators

  • The First Affiliated Hospital of Zhengzhou University

    collaborator OTHER

  • Capital Medical University

    collaborator OTHER

  • Beijing Anzhen Hospital

    collaborator OTHER

  • Shanghai East Hospital of Tongji University

    collaborator OTHER

  • Peking University People's Hospital

    collaborator OTHER

  • Chinese Academy of Sciences

    lead OTHER_GOV

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-08-15
Primary Completion
2026-08-15
Completion
2028-08-15

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07158372 on ClinicalTrials.gov