Laparoscopic Cholecystectomy
Conditions
Brief summary
Objective: Critical view of safety (CVS) is a successful technique to reduce bile duct injury during laparoscopic cholecystectomy (LC). We aimed to create a deep learning-based quality control model for LC and reduce the learning curve for junior surgeons, which would automatically assess whether surgeons are CVS conscious during procedures.Methods: We retrospectively collected 308 LC videos from public datasets (Cholec80, Endoscapes) and Sun Yat-sen Memorial Hospital. Video frames were labeled using binary classification and feature optimization methods, such as black border clipping and sliding windows. Two neural networks, ResNet-50 and EfficientNetV2-S, were trained and evaluated based on F1 scores and accuracy. Additionally, We created an online CVS recognition system (LC-Smart), tested it using 171 films from two hospitals, and compared the results to two local senior doctors.
Interventions
None listed
Sponsors
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Study design
Observational model
OTHER
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Inclusion criteria
* complete video data with no missing footage; * surgical procedure identified as laparoscopic cholecystectomy; * full visibility of the surgical area in the video; * successful completion of the procedure; * absence of significant anatomical variations * video resolution no less than 720×560.
Exclusion criteria
* substantial intraoperative adhesions * a history of previous abdominal or pelvic procedures * a conversion to open surgery during the procedure * significant bleeding that obscured structural identification.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| the surgical time | Nov/2023-Nov/2024 |
Countries
China
Outcome results
None listed