Clinical Research on a Novel Deep-learning Based System in Pancreatic Endoscopic Ultrasound Scanning

Not Applicable

Recruiting

• Conditions: Pancreatic Disease
• Interventions: Device: artificial intelligence system

• Registration Number: NCT05792267
• Lead Sponsor: The Third Xiangya Hospital of Central South University

Brief Summary

The goal of this clinical trial is to develop and verify the auxiliary role of the artificial intelligence system in pancreatic ultrasound endoscopic scanning.The main questions it aims to answer are as follows: 1.The comparison of the image recognition accuracy between the artificial intelligence system and the ultrasound endoscopist; 2. Whether the artificial intelligence system can improve the efficiency of the pancreatic scanning for the ultrasound endoscopist. Participants will undergo pancreatic EUS with or without the assistance of the artificial intelligence system.

Detailed Description

In this study, pancreatic endoscopic ultrasound scanning videos and images will be collected. First of all, an artificial intelligence system based on deep learning for the navigation and quality control of pancreatic endoscopic ultrasonography will be established. Secondly, the artificial intelligence system will be used to identify the site and anatomical structure of the pancreatic ultrasound endoscopy, and the results of the artificial intelligence system's station recognition will be compared with the results of the endoscopist's station recognition. Finally, the completeness of standard sites and scanning time of endoscopic-assisted and non-assisted AI systems were compared.

Study Timeline

• Study Start: 2021-01-01
• Study First Submitted: 2023-03-17
• Study First Submitted QC: 2023-03-29
• Study First Posted: 2023-03-31
• Primary Completion: 2024-06-30
• Status Verified: 2024-11
• Last Update Submitted: 2025-02-07
• Last Update Posted: 2025-02-12
• Study Completion: 2025-06-30

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 200

Inclusion Criteria

• 1. Age ≥18 years old, <80 years old 2.Patients who need endoscopic ultrasonography of pancreas; 3. Agree to participate in this study and sign the informed consent form.

Exclusion Criteria

• Subjects who meet any of the following criteria cannot be selected for this trial:

First. The patient's physical condition does not meet the requirements of conventional endoscopic ultrasonography:

1. Poor physical condition, including hemoglobin ≤8.0g/dl, severe cardiopulmonary insufficiency, etc.
2. Anesthesia assessment failed
3. Pregnancy or breastfeeding
4. In the acute stage of chemical and corrosive injury, it is very easy to cause perforation
5. Recent acute coronary syndrome or clinically unstable ischemic heart attack
6. Heart disease patients with right-to-left shunt, patients with severe pulmonary hypertension (pulmonary artery pressure> 90mmHg),patients with uncontrolled systemic hypertension and patients with adult respiratory distress syndrome.

Second. Disagree to participate in this study.

Third. There are other problems that do not meet the requirements of this research or that affect the results of the research:

1. Pancreatic disease has undergone surgery or radiotherapy and chemotherapy beforehand;
2. Mental illness, drug addiction, inability to express themselves or other diseases that may affect follow-up.

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Arm && Interventions

Group	Intervention	Description
AI-assisted group	artificial intelligence system	Subjects will undergo EUS examination with the assistance of artificial intelligence(AI) system.

Primary Outcome Measures

Name	Time	Method
Accuracy	2 year	The number of correctly classified images divided by the total number of images.
The completeness for standard station scanning	2 year	This was calculated as the number of stations successfully scanned divided by the total number of stations that should have been scanned.

Secondary Outcome Measures

Name	Time	Method
The completeness of anatomical landmarks	2 year	It calculated as the number of anatomical structures successfully scanned divided by the total number of structures that should have been scanned.
The completeness for standard stations and anatomical landmarks per individual	2 year	The completeness of stations and anatomic landmarks of biliopancreatic endoscopic ultrasonography by different endoscopists in the AI system assisted group and the control group were compared.
Cohen's kappa coefficient.	2 year	This data is to evaluate the agreement between the model and the endoscopists.
Operation time	2 year	In addition to puncture, elastography, and enhanced ultrasound to observe the lesion or treatment, it is also used to observe the time of biliopancreatic system.

Trial Locations

Locations (1)

The Third Xiangya Hospital of Central South University; 🇨🇳 Changsha, Hunan, China