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临床试验/NCT04903444
NCT04903444Unknown不适用

A Single-center Study on the Effectiveness and Safety of Artificial Intelligence Assisted System in Clinical Application of Endoscopic Retrograde Cholangiopancreatography

Renmin Hospital of Wuhan University1 个研究点 分布在 1 个国家目标入组 62 人开始时间: 2021年5月27日最近更新:
适应症

试验速览

阶段
不适用
入组人数
62
试验地点
1
主要终点
Procedure time

研究概览

简要总结

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.

详细描述

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.

研究设计

研究类型
Interventional
分配方式
Randomized
干预模型
Parallel
主要目的
Treatment
盲法
Double (Participant, Outcomes Assessor)

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • 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.
  • 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:
  • Able to complete MRCP in prone position;
  • 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:
  • Able to complete MRCP in prone position;
  • Patients requiring biliary drainage by ERCP due to malignant hilar biliary obstruction.

排除标准

  • 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;
  • Clinical trials
  • In addition to the criteria mentioned in the above, the clinical trial must not meet any of the following criteria:
  • Previous gastrectomy;
  • Stent replacement;
  • Pyloric or duodenal obstruction.

结局指标

主要结局

Procedure time

时间窗: During procedure

The time of performing ERCP

次要结局

  • Intersection over union of bile duct matching model:(6 month)
  • The difference in the time required to perform MRCP in different position(During procedure)
  • Intersection over Union of bile duct segmentation(A month)
  • Success rate of stent placement(During procedure)
  • Rate of adverse events(Until discharge assessed up to 14 days)
  • Fluoroscopy time(During procedure)
  • Total amount of contrast medium(During procedure)
  • The difference of the area of bile duct visualization in different position(During procedure)

研究者

申办方类型
Other
责任方
Sponsor

研究点 (1)

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