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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT05435872
Other study ID # JS-3594
Secondary ID
Status Recruiting
Phase N/A
First received
Last updated
Start date July 9, 2022
Est. completion date July 1, 2024

Study information

Verified date July 2022
Source Peking Union Medical College Hospital
Contact Shengyu Zhang, M.D.
Phone +8618501155701
Email pumchzsy@126.com
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial Summary

Study objective: To establish a quality control system for gastrointestinal endoscopy based on artificial intelligence technology and an auxiliary diagnosis system that can perform lesion identification, improving the detection rate of early gastrointestinal cancer while standardizing, normalizing, and homogenizing the endoscopic treatment in primary hospitals (including some of the primary hospitals, which are participating in Beijing-Tianjin-Hebei Gastrointestinal Endoscopy Medical Consortium) under Gastrointestinal Endoscopy Artificial Intelligence Cloud Platform as the hardware base. Study design: This study is a prospective, multi-center, real-world study.


Description:

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Study Design


Intervention

Device:
The Artificial intelligence Cloud Platform
The Artificial intelligence Cloud Platform would be used as the auxiliary device for endoscopists during the whole endoscopic examination to help endoscopists complete the quality control, indicate potential lesions, and aid in diagnosis.

Locations

Country Name City State
China Peking Union Medical College Hospital Beijing

Sponsors (6)

Lead Sponsor Collaborator
Peking Union Medical College Hospital Beijing Aerospace General Hospital, Beijing Fangshan District Liangxiang Hospital, Gucheng County Hospital of Hebei Province, Nanhe County Hospital of Hebei Province, People's Hospital of Beijing Daxing District

Country where clinical trial is conducted

China, 

Outcome

Type Measure Description Time frame Safety issue
Primary Diagnosis rate of early gastrointestinal cancer. The number of patients diagnosed with early gastrointestinal cancer is divided by the total number of patients undergoing digestive endoscopy of the intervention group with Artificial Intelligence Cloud Platform Auxiliary and the control group with nothing.
The Early Gastrointestinal cancer in this study is defined as ? early gastric cancer and ? progressive adenoma of the colon and serrated adenoma.
The pathology of biopsies will be referred to the official report of the pathologists in the participating centers, which shall be filled in and uploaded to the cloud platform.
two years
Secondary Indicators for Quality Control of gastroscopy The principle of quality control for gastroscopy in this part is 'no neglected area for observation in the stomach'. The artificial intelligence system can automatically identify the corresponding sites (according to the standard anatomical sites) of the photos taken under the gastroscope and mark them as green on the stomach schematic diagram. After all the sites are observed and corresponding photos are taken, the stomach schematic diagram totally turns green, which would be regarded as no blind sites. two years
Secondary Indicators for Quality Control of colonoscopy The quality control of colonoscopy is assessed with the following criteria: ? Quality of bowel preparations, which is evaluated with the Boston score; ? Withdrawal time, which should be no less than 6 minutes from the time of the first cecum image under colonoscopy to the time of the last rectum image. two years
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