This study is a multi-center, randomized controlled trial designed to evaluate whether an artificial intelligence (AI) system can assist endoscopists to improve the detection rate of colorectal adenomas and cancers during colonoscopy compared to standard colonoscopy. Early screening and diagnosis are key to reducing the burden of colorectal cancer, but current colonoscopy has limitations, including the risk of missed lesions. This trial aims to determine if AI can enhance screening quality and diagnostic accuracy.
Colorectal cancer (CRC) screening is crucial for early detection and reducing mortality, yet current colonoscopy techniques face challenges such as variable adenoma detection rates (ADR) and the risk of missed diagnoses for subtle lesions. This study is a prospective, multi-center, parallel-group, randomized controlled trial aiming to validate the clinical value of an AI-assisted diagnostic system in improving screening quality. A total of 3342 participants will be randomized in a 1:1 ratio to undergo either AI-assisted colonoscopy (Experimental Group) or conventional high-definition colonoscopy (Control Group). The primary objective is to compare the ADR between the two groups. Secondary objectives include assessing the detection rate of advanced or specific types of polyps, the mean number of adenomas per procedure, and the impact of the AI system on both patient and physician satisfaction. The study will provide high-quality evidence for the standardized application of AI technology in CRC screening, with the ultimate goal of reducing the incidence and mortality of colorectal cancer.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
SCREENING
Masking
NONE
Enrollment
3,342
High-definition colonoscopy procedure with a real-time video analyzed artificial intelligence system.
The Second Affiliated Hospital, Zhejiang University School of Medicine
Hangzhou, Zhejiang, China
Adenoma Detection Rate (ADR)
The proportion of participants with at least one histologically confirmed colorectal adenoma or adenocarcinoma. Detection and specimen collection occur during the colonoscopy, with final confirmation based on pathology reports.
Time frame: From the day of the procedure up to 14 days post-procedure.
Mean Adenomas Per Colonoscopy (APC)
The mean number of histologically confirmed adenomas detected per participant. The number of polyps is counted during the procedure, but confirmation of adenoma status depends on pathology.
Time frame: From the day of the procedure up to 14 days post-procedure.
Advanced Adenoma and Sessile Serrated Adenoma/Polyp (SSA/P) Detection Rate
The proportion of participants with at least one histologically confirmed advanced adenoma (defined as ≥10mm, or with high-grade dysplasia or villous components) or SSA/P.
Time frame: From the day of the procedure up to 14 days post-procedure.
Patient Satisfaction Score
Assessed using a 5-point Likert scale questionnaire evaluating examination comfort and acceptance of the AI system (1=very unsatisfied, 5=very satisfied).
Time frame: Assessed within 1 hour after completion of the colonoscopy procedure.
Physician Satisfaction Score
Assessed using a 5-point Likert scale questionnaire evaluating the AI system's usability and reliability (1=very unsatisfied, 5=very satisfied).
Time frame: Assessed within 1 hour after completion of the colonoscopy procedure.
Incidence of Procedure-Related Adverse Events
The number and type of adverse events (AEs) and serious adverse events (SAEs), including but not limited to perforation, significant bleeding, and infection, are recorded.
Time frame: From the start of the procedure up to 30 days post-procedure.
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.