NCT04563416|Unknown
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Sponsor study identifier
observational
80
1 country
1
Study Start
July 10, 2020
Actual (reported)Primary Completion
November 30, 2020
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
Study Completion
December 30, 2020
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
Previous prospective randomized controlled study demonstrated higher accuracy rate of diagnosing early gastric cancers by Magnifying image-enhanced endoscopy than conventional white-light endoscopy. Nevertheless, it is difficult to differentiate early gastric cancer from noncancerous lesions for beginner. we developed a new computer-aided system to assist endoscopists in identifying early gastric cancers in magnifying optical enhancement images.
Registry-reported information. Elapsed time and enrollment totals alone do not measure study progress or recruitment pace.
December 30, 2020
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
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Dates and qualifiers reported by the registry. Estimated dates do not confirm that a milestone has occurred.
July 10, 2020
Actual (reported)September 22, 2020
Actual (reported)September 24, 2020
Actual (reported)November 30, 2020
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
December 30, 2020
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
the diagnosis efficiency of the computer-assist diagnosis tool
the sensitivity, specificity and accuracy of the computer-assist diagnosis tool
12 months
Consecutive patients suspected of early gastric cancer and receive optical magnifying OE endoscopy examination.
Department of Gastroenterology, Qilu Hospital, Shandong University
Jinan, Shandong, 250012, China
Ma M, Li Z, Yu T, Liu G, Ji R, Li G, Guo Z, Wang L, Qi Q, Yang X, Qu J, Wang X, Zuo X, Ren H, Li Y. Application of deep learning in the real-time diagnosis of gastric lesion based on magnifying optical enhancement videos. Front Oncol. 2022 Aug 5;12:945904. doi: 10.3389/fonc.2022.945904. eCollection 2022.
Yanqing Li, PHD
Study Principal Investigator Qilu Hospital, Shandong University
First Submitted
September 22, 2020
First Posted
September 24, 2020
Study Start
July 10, 2020
Actual (reported)Primary Completion
November 30, 2020
Estimated (date passed)Automatic Real-time Diagnosis of Gastric Mucosal Disease Using pCLE With Artificial Intelligence
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This estimate has passed. The registry has not confirmed an actual date for this milestone.
Study Completion
December 30, 2020
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
Last Updated
September 24, 2020
Record last verified: 2020-09
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Source: ClinicalTrials.gov.
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