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HIPAA Compliant
ISO 27001 Certified

Actively Recruiting

Phase Not Applicable
Age: 40Years - 80Years
All Genders
Healthy Volunteers
ID07127471

Comparing AI-Assisted Water Exchange Colonoscopy With and Without Linked-Color Imaging to Detect Important Colon Lesions in Adults Aged 40 to 80

Led by Evergreen General Hospital, Taiwan · Updated on 2025-11-20

1090

Participants Needed

4

Research Sites

13 weeks

Total Duration

AI-Summary

What this Trial Is About

Researchers are investigating the detection rates of clinically significant serrated lesions CSSL in people undergoing colonoscopy using water exchange WE combined with artificial intelligence AI-based computer-aided detection CADe. The study compares two methods one using CADe alone and another adding linked-color imaging LCI to CADe during WE colonoscopy. The goal is to determine if LCI improves the detection of CSSL during screening, surveillance, diagnostic colonoscopy, or after positive stool test results. This trial involves two groups one uses standard high-definition colonoscopy with CADe assistance during the withdrawal phase, and the other adds LCI imaging to enhance lesion visualization. Both groups use water instead of air to insert the colonoscope, with water infusion and suction to expand the colon and clean the view. The study is randomized and unblinded, with procedures performed by experienced endoscopists using the ELUXEO 7000 system. The trial is planned to run for two years across multiple international centers. Participants aged 40 to 80 at average risk for colorectal cancer will undergo colonoscopy and have CSSL detection rates recorded using pathology reports released about one week after the procedure. The study also measures detection rates of other lesion types and adenomas. Sedation options vary, and procedures follow consistent techniques. Safety and effectiveness of lesion detection are monitored closely during the study period ending in July 2027.

CONDITIONS

Brief Title

Computer-Aided Water Exchange Colonoscopy With and Without Linked-Color Imaging for Detection of Clinically Significant Serrated Lesions

Research Team

C

Chi-Liang Cheng, MD

R

Rungsun Rerknimitr, MD

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