Clinical trial NCT05792267: Clinical Research on a Novel Deep-learning Based System in Pancreatic Endoscopic Ultrasound Scanning
Official title: Clinical Research on Navigation and Quality Control System of Pancreatic Ultrasound Endoscopy Based on Deep Learning
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Pancreatic Disease
Lead sponsor: The Third Xiangya Hospital of Central South University
Sponsor class: OTHER
First posted: 2023-03-31
Enrollment: 200
Sex: ALL
Minimum age (years): 18
Maximum age (years): 80
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: OTHER

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.

Eligibility criteria: 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.

Primary outcomes:
measure: Accuracy
timeFrame: 2 year
measure: The completeness for standard station scanning
timeFrame: 2 year
Secondary outcomes:
measure: Cohen's kappa coefficient.
timeFrame: 2 year
measure: The completeness of anatomical landmarks
timeFrame: 2 year
measure: The completeness for standard stations and anatomical landmarks per individual
timeFrame: 2 year
measure: Operation time
timeFrame: 2 year
Other outcomes:
Locations:
city: Changsha
country: China
facility: The Third Xiangya Hospital of Central South University
state: Hunan
Study officials:
affiliation: The Third Xiangya Hospital of Central South University
name: Xiaoyan Wang, Doctor
role: PRINCIPAL_INVESTIGATOR
References: