LC-Smart: A Deep Learning-Based Quality Control Model for Laparoscopic Cholecystectomy

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.

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Key information

Conditions

Laparoscopic Cholecystectomy

Sex eligibility

All sexes

Study type

Observational

Primary location

Sun Yat-sen Memorial Hospital,SUn Yat-sen UNiversity

Guangzhou, Guangdong, 510220, China

Who can participate

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

Primary outcomes

the surgical time

Time frame: Nov/2023-Nov/2024

Sponsors and collaborators

Lead sponsor

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Other

Registry information

Important dates

Study start: 2024
Primary completion: 2024
Study completion: 2024
First posted: Dec 13, 2024
Registry last updated: Dec 13, 2024

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This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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Completed