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NCT Number: NCT05792280

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

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.

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Key information

Conditions

Mediastinum Disease Mediastinal Diseases Respiratory Tract Diseases Thoracic Diseases

Age range

18 year–80 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • 1. Age ≥18 years old, <80 years old 2.Patients who need endoscopic ultrasonography; 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:

  • Poor physical condition, including hemoglobin ≤8.0g/dl, severe cardiopulmonary insufficiency, etc.
  • Anesthesia assessment failed
  • Pregnancy or breastfeeding
  • In the acute stage of chemical and corrosive injury, it is very easy to cause perforation
  • Recent acute coronary syndrome or clinically unstable ischemic heart attack
  • 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:

  • Mediastinal lesions have previously undergone surgery or radiotherapy and chemotherapy;
  • Mental illness, drug addiction, inability to express themselves or other diseases that may affect follow-up.

Treatment and study plan

AI system

Device

Patients will undergo EUS examination with the assistance of AI system.

Primary outcomes

  1. Accuracy

    Time frame: 1 year

    The number of correctly classified images divided by the total number of images.

  2. The completeness for standard station scanning

    Time frame: Until the end of the study

    This was calculated as the number of stations successfully scanned divided by the total number of stations that should have been scanned.

Secondary outcomes

  1. Cohen's kappa coefficient

    Time frame: 1 year

    This data is to evaluate the agreement between the model and the endoscopists.

  2. The completeness for standard stations and anatomical landmarks per individual

    Time frame: Until the end of the study

    The completeness of stations and anatomic landmarks of endoscopic ultrasonography by different endoscopists in the AI system assisted group and the control group were compared.

  3. The completeness of anatomical landmarks

    Time frame: Until the end of the study

    It calculated as the number of anatomical structures successfully scanned divided by the total number of structures that should have been scanned

  4. Operation time

    Time frame: Until the end of the study

    In addition to puncture, elastography, and ultrasound enhancement to observe the lesion or treatment, it can also be used to observe the time of the mediastinum.

  5. The incidence of adverse events

    Time frame: Until the end of the study

    The incidence of adverse events in both groups during the entire research process.

Study contacts

Contact information is provided by the study sponsor or research team.

Shiqin Huang, MD

CONTACT

[email protected]

+8618308312098

Xiaoyan Wang, Doctor

CONTACT

[email protected]

+8613974889301

Sponsors and collaborators

Lead sponsor

The Third Xiangya Hospital of Central South University

Other

Registry information

Official study title

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

Important dates

Study start
2021
Primary completion
2025
Study completion
2025
First posted
Mar 31, 2023
Registry last updated
Mar 13, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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