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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

Primary Purpose

Common Bile Duct Stones

Status
Not yet recruiting
Phase
Not Applicable
Locations
Study Type
Interventional
Intervention
artificial intelligence assistance system
Sponsored by
Renmin Hospital of Wuhan University
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional diagnostic trial for Common Bile Duct Stones focused on measuring Ultrasound Endoscopy, Common bile duct stones, artificial intelligence

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)All SexesDoes not accept healthy volunteers

Inclusion Criteria:

  1. 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;
  2. Able to read, understand and sign an informed consent;
  3. 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 Criteria:

  1. 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;
  2. Have drug or alcohol abuse or mental disorder in the last 5 years;
  3. Pregnant or lactating women;
  4. Altered anatomy due to previous history of upper gastrointestinal surgery;
  5. Patients with advanced tumors resulting in abnormal upper gastrointestinal anatomy;
  6. High-risk diseases or other special conditions that the investigator considers the subject unsuitable for participation in the clinical trial.

Sites / Locations

    Arms of the Study

    Arm 1

    Arm 2

    Arm Type

    Experimental

    Experimental

    Arm Label

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

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

    Arm Description

    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.

    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.

    Outcomes

    Primary Outcome Measures

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

    Secondary Outcome Measures

    Sensitivity, specificity, NPV, and PPV for the diagnosis of common bile duct stones in low and intermediate risk patients
    Detection rate of gallstone lesions
    Missed detection rate of gallstone lesions
    Detection rate of bile duct lesions(all bile duct lesions including gallstones)
    Missed rate of bile duct lesion(all bile duct lesions including gallstones)
    Number of bile duct standard station scans
    scan time
    Incidence of Adverse Events

    Full Information

    First Posted
    May 13, 2022
    Last Updated
    May 18, 2022
    Sponsor
    Renmin Hospital of Wuhan University
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    1. Study Identification

    Unique Protocol Identification Number
    NCT05381064
    Brief Title
    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
    Official Title
    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: a Single-center, Tandem, Randomized Controlled Trial
    Study Type
    Interventional

    2. Study Status

    Record Verification Date
    May 2022
    Overall Recruitment Status
    Not yet recruiting
    Study Start Date
    June 1, 2022 (Anticipated)
    Primary Completion Date
    December 1, 2023 (Anticipated)
    Study Completion Date
    January 1, 2024 (Anticipated)

    3. Sponsor/Collaborators

    Responsible Party, by Official Title
    Sponsor
    Name of the Sponsor
    Renmin Hospital of Wuhan University

    4. Oversight

    Studies a U.S. FDA-regulated Drug Product
    No
    Studies a U.S. FDA-regulated Device Product
    No

    5. Study Description

    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
    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 (CBDS) are present in about 10-20% of patients with symptomatic bile duct stones. Each year, common bile duct stones lead to acute complications such as biliary obstruction, cholangitis and acute pancreatitis in a large number of patients, seriously endangering their lives and health. In addition, Diagnosis Related Group (DRG) analysis shows that each episode of common bile duct stones costs $9,000, and acute pancreatitis that progresses from common bile duct stones can result in 275,000 hospitalizations annually, incurring $2.6 billion in costs and imposing a significant economic and health burden on society. Therefore, timely diagnosis of common bile duct stones and intervention for them is crucial. Endoscopic retrograde cholangiopancreatography (ERCP) is the method of choice for the diagnosis and treatment of CBDS, and guidelines recommend stone extraction for all patients with CBDS who are physically fit enough to tolerate ERCP operations. However, ERCP is a highly demanding and risky operation with the potential for serious complications such as PEP (incidence 2.6-3.5%). How to diagnose choledocholithiasis early and accurately, achieve timely intervention to improve prognosis, and avoid unnecessary medical operations to reduce risks are the challenges we are currently trying to solve. The guidelines recommend ultrasound endoscopy (EUS) or magnetic resonance cholangiopancreatography (MRCP) to determine the presence of CBDS, depending on the local level of care, for patients in the intermediate-risk group for CBDS and for patients in the low-risk group whose physicians still have a high suspicion of CBDS. sensitivity. In addition, a cost-effectiveness analysis showed that MRCP would be the preferred test when the predicted probability of CBDS is less than 40%, while EUS is the preferred test when the predicted probability is 40%-90%. Compared to MRCP, EUS has a wide range of applicability but a steep learning curve. ASGE states that a minimum of 225 EUS operations are required to qualify, while the ESGE states that a minimum of 300 operations are required. However, this experience can only be gained at training centers that perform a large number of cases. Thus, the training of novice physicians in resource-limited areas is a huge challenge, which leaves a significant shortage of experienced ultrasound endoscopists with poor performance in the actual diagnosis of common bile duct stones, greatly limiting the popularity of ultrasound endoscopy. 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 through a single-center, tandem, randomized controlled trial

    6. Conditions and Keywords

    Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
    Common Bile Duct Stones
    Keywords
    Ultrasound Endoscopy, Common bile duct stones, artificial intelligence

    7. Study Design

    Primary Purpose
    Diagnostic
    Study Phase
    Not Applicable
    Interventional Study Model
    Crossover Assignment
    Masking
    ParticipantOutcomes Assessor
    Allocation
    Randomized
    Enrollment
    184 (Anticipated)

    8. Arms, Groups, and Interventions

    Arm Title
    novices with AI-assisted system, Then experts without AI-assisted system
    Arm Type
    Experimental
    Arm Description
    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.
    Arm Title
    experts without AI-assisted system, Then novices with AI-assisted system
    Arm Type
    Experimental
    Arm Description
    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.
    Intervention Type
    Device
    Intervention Name(s)
    artificial intelligence assistance system
    Intervention Description
    A deep learning-based bile duct scanning system that can prompt endoscopists to scan standard stations, identify bile ducts and stones in real time
    Primary Outcome Measure Information:
    Title
    Accuracy of diagnosis of common bile duct stones in patients with low and intermediate risk by novice combined with AI-assisted and expert
    Time Frame
    the time novice finished operation and expert finished operation
    Secondary Outcome Measure Information:
    Title
    Sensitivity, specificity, NPV, and PPV for the diagnosis of common bile duct stones in low and intermediate risk patients
    Time Frame
    the time novice finished operation and expert finished operation
    Title
    Detection rate of gallstone lesions
    Time Frame
    the time novice finished operation and expert finished operation
    Title
    Missed detection rate of gallstone lesions
    Time Frame
    the time novice finished operation and expert finished operation
    Title
    Detection rate of bile duct lesions(all bile duct lesions including gallstones)
    Time Frame
    the time novice finished operation and expert finished operation
    Title
    Missed rate of bile duct lesion(all bile duct lesions including gallstones)
    Time Frame
    the time novice finished operation and expert finished operation
    Title
    Number of bile duct standard station scans
    Time Frame
    the time novice finished operation and expert finished operation
    Title
    scan time
    Time Frame
    the time novice finished operation and expert finished operation
    Title
    Incidence of Adverse Events
    Time Frame
    the time novice finished operation and expert finished operation

    10. Eligibility

    Sex
    All
    Minimum Age & Unit of Time
    18 Years
    Accepts Healthy Volunteers
    No
    Eligibility Criteria
    Inclusion Criteria: 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 Criteria: 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.
    Central Contact Person:
    First Name & Middle Initial & Last Name or Official Title & Degree
    Yu Honggang, Doctor
    Phone
    13871281899
    Email
    yuhonggang@whu.edu.cn
    Overall Study Officials:
    First Name & Middle Initial & Last Name & Degree
    Yu Honggang, Doctor
    Organizational Affiliation
    Renmin Hospital of Wuhan University
    Official's Role
    Principal Investigator

    12. IPD Sharing Statement

    Learn more about this trial

    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

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