Research on Identifying Critical Surgical Anatomy in Cholecystectomy Videos Based on Deep Learning
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: AI-assisted Intraoperative Anatomy Analysis.
- Who it may be relevant to
- Registry conditions: Cholecystectomy, Surgical Video Identification. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Overview
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.
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.
Primary outcome measures
- Dice Similarity Coefficient [Time frame: 3 years]
- Mean Intersection over Union [Time frame: 3 years]
- Global Accuracy [Time frame: 3 years]
Secondary outcome measures (1)
- Inference Latency [Time frame: 3 years]
Eligibility 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.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Cohort
Study locations
China · 5 centers
- The First Affiliated Hospital of Zhengzhou University — Zhengzhou
- Beijing Anzhen Hospital, Capital Medical University — Beijing
- Beijing Luhe Hospital, Capital Medical University — Beijing
- Peking university people's hospital — Beijing
- Shanghai East Hospital of Tongji University — Shanghai
Identifiers
NCT: NCT07158372 · CASMI007