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Clinical Trial Summary

Colonoscopy is clinically used as the gold standard for detection of colorectal cancer (CRC) and removal of adenomatous polyps of the colon and rectum. Evidence has shown that CRC could be prevented by colonoscopic removal of adenomatous polyps. Despite the success of colonoscopy in reducing cancer-related deaths, there exists a disappointing level of adenomas missed at colonoscopy. In recent years, emerging artificial intelligence (AI) and computer-aided detection (CADe) technology has been shown to improve ADR. Based on a meta-analysis, ADR was demonstrated to be significantly higher in the CADe groups than in the standard colonoscopy groups, representing a relative risk of 25.2%. In this study, performance of colonoscopy with or without aid of CADe will be compared in terms of quality indicators. The adenoma detection rate (ADR), which is the proportion of average-risk patients undergoing screening colonoscopy in whom an adenoma is found, is regarded as a robust measure of colonoscopy performance quality that correlates with subsequent cancer risk. Thus, ADR is taken as the primary outcome of this study. The target population includes individuals who are undergoing screening, diagnostic, or surveillance colonoscopy.


Clinical Trial Description

This multiple-site study aims to evaluate whether a computer-aided detection (CADe) device can assist in adenoma detection rate (ADR) when compared with the current standard-of-care procedure. The subject CADe device used in this study contains an artificial intelligence/machine learning (AI/ML) advanced algorithm to aid the endoscopists in detection of colonic mucosal lesions and the detected polyps will be highlighted to the endoscopists during the real-time colonoscopy procedures. This study plans to enroll subjects aged ≥ 40 years and < 80 years, who are scheduled for screening or diagnostic colonoscopy for colorectal cancer (CRC) or surveillance colonoscopy for post-polypectomy follow-up. After being evaluated with the inclusion and exclusion criteria, eligible subjects will be randomized in a 1:1 ratio to receive either the computer-aided colonoscopy (CC) or the standard colonoscopy(SC). Randomization will be stratified by gender, age, and colonoscopy indication (screening, diagnostic, or surveillance) of subjects. The resected polyps will be submitted for histologic examination by one expert pathologist at each site. If any uncertainty or doubt exists, an expert in gastrointestinal pathology will serve as the adjudicator to perform a second review and make the final decision. All of the pathologists (including the final adjudicator) who will perform the histopathologic examinations and produce the pathology assessment will be blinded to the assigned study arm of the specimens. The pathology reports of the subjects will be kept securely at each site as the source data. The primary endpoint is the ADR of the CC as compared with that of the SC. The ADR is defined as the percentage of subjects undergoing a complete colonoscopy, who have at least one histologically confirmed adenoma detected and removed. In addition, the following secondary endpoints will also be evaluated, including: Polyp detection rate (PDR), Adenomas per colonoscopy (APC), Polyps per colonoscopy (PPC), Non-neoplastic polypectomy rate (NNPR), Non-neoplastic polypectomy (NNP), Sessile serrated lesions per colonoscopy (SPC), Advanced adenomas per colonoscopy (AAPC), and withdrawal time. Signed written informed consent forms will be obtained from all participating subjects before enrollment. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT05240625
Study type Interventional
Source National Taiwan University Hospital
Contact Han-Mo Chiu, MD, PhD
Phone +886-2-23123456
Email hanmochiu@ntu.edu.tw
Status Recruiting
Phase N/A
Start date March 1, 2022
Completion date December 31, 2025

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