Status:

UNKNOWN

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

Lead Sponsor:

Renmin Hospital of Wuhan University

Conditions:

Common Bile Duct Stones

Eligibility:

All Genders

18+ years

Phase:

NA

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 eff...

Detailed Description

The incidence of gallstones has been increasing in recent years, up to 10-15% in developed countries, and is still increasing at a rate of 0.6% per year. It is estimated that common bile duct stones (...

Eligibility Criteria

Inclusion

  • 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.

Exclusion

  • 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.

Key Trial Info

Start Date :

June 1 2022

Trial Type :

INTERVENTIONAL

Allocation :

ESTIMATED

End Date :

January 1 2024

Estimated Enrollment :

184 Patients enrolled

Trial Details

Trial ID

NCT05381064

Start Date

June 1 2022

End Date

January 1 2024

Last Update

May 19 2022

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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 | DecenTrialz