Colorectal Neoplasms Clinical Trial
Official title:
Adenoma Detection Rate Using Artificial Intelligence System in China
The primary aim of this study is
- to explore the usefulness of Artificial Intelligence system in colonoscopy on adenoma
detection rate (ADR). Other aims include to explore the data below when Artificial
Intelligence is used.
Mean adenomas detected per procedure, MAP Proximal Adenoma detection rate, pADR Polyp
detection rate, PDR Proximal polyp detection rate, pPDR Mean polyps detected per procedure,
MPP Withdrawal time, WT Cecal intubation rate, CIR Cecal intubation time, CIT
Colorectal cancer is common in China. Most colorectal cancers happen when an adenoma becomes
cancerous. Doctors use colonoscopy to look inside the colon and rectum and find adenomas and
remove them. Removing adenomas is known to reduce the chances of a person developing
colorectal cancers. The ability of colonoscopists finding adenomas varies, and there is a lot
of researches into how to improve "adenoma detection rates".
A new AI system, called the CSK endoscopic diagnosis and treatment system has been designed
to improve the rate of polyp detection at colonoscopy. Previous tests have shown that there
is a significant improvement in detection of adenomas when the system is used. This study
will randomize patients coming for colonoscopy to have their procedure performed as usual or
as an AI-assisted colonoscopy. The investigators will record polyp and adenoma detection
rates, duration of procedure, participant comfort levels, and complications. All patients
referred for colonoscopy will be invited in 4 centers, recruiting a total of 800
participants.
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