Effect of a Deep Learning-based Bile Duct Scanning System on the Diagnostic Accuracy of Common Bile Duct Stones During Examination by Novice Ultrasound Endoscopists

NCT05381064 | Unknown

• 1 other identifier: EA-22-004
• Study Type: interventional
• Target: 184
• Locations: 0 countries
• Sites: N/A

Brief Summary

The bile duct scanning system based on deep learning can prompt endoscopists to scan standard stations and identify bile ducts and stones in real time. The purpose of this study is to evaluate the effectiveness and safety of the proposed deep learning-based bile duct scanning system in improving the diagnostic accuracy of common bile duct stones and reducing the rate of missed gallstones during bile duct scanning by novice ultrasound endoscopists in a single-center, tandem, randomized controlled trial

Conditions

Common Bile Duct Stones

Keywords

Ultrasound Endoscopy; Common bile duct stones; artificial intelligence

Outcome Measures

Primary Outcomes (1)

• Accuracy of diagnosis of common bile duct stones in patients with low and intermediate risk by novice combined with AI-assisted and expert

  the time novice finished operation and expert finished operation

Secondary Outcomes (8)

• Sensitivity, specificity, NPV, and PPV for the diagnosis of common bile duct stones in low and intermediate risk patients

  the time novice finished operation and expert finished operation

• Detection rate of gallstone lesions

  the time novice finished operation and expert finished operation

• Missed detection rate of gallstone lesions

  the time novice finished operation and expert finished operation

• Detection rate of bile duct lesions(all bile duct lesions including gallstones)

  the time novice finished operation and expert finished operation

• Missed rate of bile duct lesion(all bile duct lesions including gallstones)

  the time novice finished operation and expert finished operation

Study Arms (2)

novices with AI-assisted system, Then experts without AI-assisted system

EXPERIMENTAL

The patient is first scanned by a novice endoscopist with the assistance of a deep learning-based bile duct scanning system during the examination, and then rescanned by a specialist without the assistance of AI.

Device: artificial intelligence assistance system

experts without AI-assisted system, Then novices with AI-assisted system

EXPERIMENTAL

The patient is first scanned by a specialist without the assistance of AI and then rescanned by a novice endoscopist with the assistance of a deep learning-based bile duct scanning system during the examination.

Device: artificial intelligence assistance system

Interventions

artificial intelligence assistance system DEVICE

A deep learning-based bile duct scanning system that can prompt endoscopists to scan standard stations, identify bile ducts and stones in real time

experts without AI-assisted system, Then novices with AI-assisted system; novices with AI-assisted system, Then experts without AI-assisted system

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Males and females aged 18 years and older who are suspected of having common bile duct stones at intermediate to low risk, where intermediate-risk patients are those with normal liver function but with abdominal ultrasound suggestive of bile duct dilatation, and low-risk patients are those with normal abdominal ultrasound and liver function but whose physicians still suspect common bile duct stones;
• Able to read, understand and sign an informed consent;
• The investigator believes that the subjects can understand the process of the clinical study, are willing and able to complete all study procedures and follow-up visits, and cooperate with the study procedures.

You may not qualify if:

• Patients at high risk of common bile duct stones. High-risk patients are those with common bile duct stones detected by abdominal ultrasound, patients with manifestations of cholangitis or hospitalized patients with a history of gallbladder stones with pain, bile duct dilatation and jaundice;
• Have drug or alcohol abuse or mental disorder in the last 5 years;
• Pregnant or lactating women;
• Altered anatomy due to previous history of upper gastrointestinal surgery;
• Patients with advanced tumors resulting in abnormal upper gastrointestinal anatomy;
• High-risk diseases or other special conditions that the investigator considers the subject unsuitable for participation in the clinical trial.

Sponsors & Collaborators

• Renmin Hospital of Wuhan University: lead

Study Officials

• Yu Honggang, Doctor

  Renmin Hospital of Wuhan University

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Yu Honggang, Doctor

CONTACT

13871281899; yuhonggang@whu.edu.cn

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: PARTICIPANT, OUTCOMES ASSESSOR
• Purpose: DIAGNOSTIC
• Intervention Model: CROSSOVER
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 13, 2022
• First Posted: May 19, 2022
• Study Start: June 1, 2022
• Primary Completion: December 1, 2023
• Study Completion: January 1, 2024
• Last Updated: May 19, 2022

Record last verified: 2022-05