NCT05792280

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

Clinical Research on Navigation and Quality Control System of Mediastinal Ultrasound Endoscopy Based on Deep Learning

• Status: Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 180 (estimated)
• Sponsor: The Third Xiangya Hospital of Central South University · Academic / Other
• Sex: All
• Age: 18 Years – 80 Years
• Healthy volunteers: Accepted

Summary

The goal of this clinical trial is to develop and verify the auxiliary role of the artificial intelligence system in mediastinal 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 integrity and efficiency of the mediastinum scanning for the ultrasound endoscopist. Participants will undergo mediastinal EUS with or without the assistance of the artificial intelligence system.

Detailed description

In this study, a total of 200 cases of mediastinal endoscopic ultrasound scanning videos will be collected. First of all, an artificial intelligence system based on deep learning for the navigation and quality control of mediastinal endoscopic ultrasonography will be established. Secondly, the artificial intelligence system will be used to identify the site and anatomical structure of the mediastinal ultrasound endoscope, 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.

Conditions

• Mediastinum Disease

Interventions

Type	Name	Description
DEVICE	AI system	Patients will undergo EUS examination with the assistance of AI system.

Timeline

• Start date: 2021-01-01
• Primary completion: 2025-03-30
• Completion: 2025-04-10
• First posted: 2023-03-31
• Last updated: 2025-03-13

Locations

1 site across 1 country: China