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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT04903444
Other study ID # EA-19-003-22
Secondary ID
Status Recruiting
Phase N/A
First received
Last updated
Start date May 27, 2021
Est. completion date July 1, 2022

Study information

Verified date May 2021
Source Renmin Hospital of Wuhan University
Contact Honggang Yu, Doctor
Phone +862788041911
Email whdxrmyy@126.com
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial Summary

In this study, the investigators proposed an artificial intelligence-based biliary stricture navigation system in MRCP-based ERCP, which can instruct the direction of guide wire and the position of stent placement in real time.


Description:

585/5000 Biliary stricture can be divided into benign biliary stricture and malignant biliary stricture, and malignant hilar biliary obstruction is the one of the common cause. Since there is no specific early screening method for malignant hilar biliary obstruction at present and most patients have no obvious clinical symptoms in the early stage, most patients are already in the advanced stage when they are first diagnosed. Advanced malignant hilar biliary obstruction cannot undergo resection surgery, whose first choice for the treatment is palliative endoscopic biliary drainage.Biliary drainage can relieve jaundice, pruritus and other symptoms due to cholestasis. However,before the narrow segment was placed the stent, the contrast agent could not pass through the narrow segment and the bile duct above the narrow segment could not be seen.So it was difficult for doctors to determine the direction of the guide wire and the position of the stent. In addition, indiscriminate application of the contrast agent may cause outflow obstruction leading to infection. However, there is no relevant research to solve these problems. MRCP is the preferred examination method of pancreatic and bile duct diseases. Therefore, MRCP should be routinely performed before patients are treated with ERCP. At present, MRCP is in supine position, and ERCP is in prone position. Different positions lead to differences in the morphology of MRCP and the bile duct on ERCP.So preoperative MRCP in supine position has limited role in advising physicians on the morphology of the bile duct. Therefore, MRCP in the prone position is more favorable for endoscopists to perform ERCP . In recent years, deep learning algorithms have been continuously developed and increasingly mature.They have been gradually applied to the medical field. Computer vision is a science that studies how to make machines "see". Through deep learning, camera and computer can replace human eyes to carry out machine vision such as target recognition, tracking and measurement.Interdisciplinary cooperation in the field of medical imaging and computer vision is also one of the research hotspots in recent years. At present, it is mainly applied to the automatic identification and detection of lesions and quality control, and has achieved good results. It can assist doctors to find lesions, make disease diagnosis and standardize doctors' operations, so as to improve the quality of doctors' operations.With mature technical support, it has a good prospect and application value to develop endoscopic operating system for lesion detection and quality control based on artificial intelligence methods such as deep learning. In this study, the investigators proposed an artificial Intelligence-based Biliary Stricture Navigation System in MRCP-based ERCP, which can instruct the direction of guide wire and the position of stent placement in real time.


Recruitment information / eligibility

Status Recruiting
Enrollment 62
Est. completion date July 1, 2022
Est. primary completion date June 1, 2022
Accepts healthy volunteers No
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria: 1. Bile duct segmentation model 1) Male or female aged 18 or above; 2) Who needs ERCP,MRCP and its related tests are needed to further define the characteristics of digestive tract diseases; 3)The images of MRCP and ERCP are clear; 4) Able to read, understand and sign informed consent; 5) The investigator believes that the subject can understand the process of the clinical study and is willing and able to complete all the study procedures and follow-up visits and cooperate with the study procedures. 2. Bile duct matching model In addition to the criteria mentioned in the bile duct segmentation model, the bile duct matching model should also meet the following criteria: 1. Able to complete MRCP in prone position; 2. Bile ducts are almost completely visible in MRCP and ERCP. (3) Clinical trials In addition to the criteria mentioned in the bile duct segmentation model, the clinical trials should also meet the following criteria: 1. Able to complete MRCP in prone position; 2. Patients requiring biliary drainage by ERCP due to malignant hilar biliary obstruction. Exclusion Criteria: 1. Bile duct segmentation model and bile duct matching model 1)Has participated in other clinical trials, signed the informed consent and was in the follow-up period of other clinical trials; 2) Drug or alcohol abuse or psychological disorder in the last 5 years; 3) Patients in pregnancy or lactation; 4) The investigator considers that the subjects were not suitable for MRCP, ERCP and related tests; 5)A high-risk diseases or other special conditions that the investigator considers inappropriate for the subject to participate in a clinical trial; 2. Clinical trials In addition to the criteria mentioned in the above, the clinical trial must not meet any of the following criteria: 1. Previous gastrectomy; 2. Stent replacement; 3. Pyloric or duodenal obstruction.

Study Design


Related Conditions & MeSH terms


Intervention

Device:
Artificial intelligence assistant system
The endoscopists in the experimental group will be assisted by AI system, which can instruct the direction of guide wire and the position of stent placement in real time. The system is an non-invasive AI system .

Locations

Country Name City State
China Renmin hospital of Wuhan University Wuhan Hubei

Sponsors (1)

Lead Sponsor Collaborator
Renmin Hospital of Wuhan University

Country where clinical trial is conducted

China, 

Outcome

Type Measure Description Time frame Safety issue
Primary Procedure time The time of performing ERCP During procedure
Secondary Intersection over Union of bile duct segmentation Intersection over Union of bile ducts predicted by artificial intelligence devices and actual bile ducts A month
Secondary Intersection over union of bile duct matching model: Intersection over Union of the bile ducts generated by the AI device and the actual bile ducts in ERCP 6 month
Secondary Success rate of stent placement The number of successful patients is the numerator, and the total number of patients with stent placement is the denominator. During procedure
Secondary Rate of adverse events The number of patients who experienced adverse events was numerator, and the total number of patients undergoing stent placement was denominator. Until discharge assessed up to 14 days
Secondary Fluoroscopy time The sum of the total X ray fluoroscopy time during the whole procedure. During procedure
Secondary Total amount of contrast medium Total amount of contrast medium during the whole procedure. During procedure
Secondary The difference of the area of bile duct visualization in different position The area of bile duct visualization of MRCP in different position During procedure
Secondary The difference in the time required to perform MRCP in different position The difference in the time required to perform MRCP in different position During procedure
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