Adenoma Detection Rate Using AI System in China
- Conditions
- Colorectal NeoplasmsAdenomaColonic Polyp
- Interventions
- Device: CSK AI systemDevice: Standard Colonoscopy
- Registration Number
- NCT03840590
- Lead Sponsor
- Changhai Hospital
- Brief Summary
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
- Detailed Description
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.
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 743
- All patients referred for screening, surveillance, or diagnostic colonoscopy
- All patients must be able to give informed consent
- Patients with any absolute contraindications to colonoscopy
- Patients with established or suspicion of large bowel obstruction or pseudo-obstruction
- Patients with known colon cancer or polyposis syndromes
- Patients with known colonic strictures
- Patients with known severe diverticular segments (that is likely to impede colonoscope passage)
- Patients with active colitis (ulcerative colitis, Crohn's colitis, diverticulitis, infective colitis)
- Patients lacking capacity to give informed consent
- Pregnancy
- Patients who are on clopidogrel, warfarin, or other new generation anticoagulants who have not stopped this for the procedure.
- Patients who are attending for a therapeutic procedure or assessment of a known lesion
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- PARALLEL
- Arm && Interventions
Group Intervention Description AI-assisted Colonoscopy CSK AI system Participants in this arm undergo AI-assisted colonoscopy using CSK AI system. Standard Colonoscopy Standard Colonoscopy Participants in this arm undergo standard colonoscopy.
- Primary Outcome Measures
Name Time Method Adenoma detection rate, ADR At the end of the procedure, up to 1 hour. ADR refer to the rate of adenoma detection, calculated as the proportion of subjects with at least one adenoma.
- Secondary Outcome Measures
Name Time Method Polyp detection rate, PDR At the end of the procedure, up to 1 hour. PDR refer to the rate of polyp detection, calculated as the proportion of subjects with at least one polyp.
Trial Locations
- Locations (4)
Shanghai Zhongshan Hospital
🇨🇳Shanghai, Shanghai, China
Tianjin People's Hospital
🇨🇳Tianjin, Tianjin, China
Sixth affiliated Hospital, Sun Yat-Sen University
🇨🇳Guangzhou, Guangdong, China
Tianjin Nankai Hospital
🇨🇳Tianjin, Tianjin, China