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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Experimental: AI-Assisted Colonoscopy | Experimental | Participants will undergo a high-definition colonoscopy procedure where a real-time artificial intelligence system analyzes the video feed to assist the endoscopist in identifying and highlighting suspicious lesions. |
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| Control: Conventional Colonoscopy | No Intervention | Participants will undergo a standard high-definition colonoscopy procedure performed by a qualified endoscopist without the assistance of the artificial intelligence system. The AI software will not be active during these procedures. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AI-Assisted Colonoscopy | Device | High-definition colonoscopy procedure with a real-time video analyzed artificial intelligence system. |
|
| Measure | Description | Time Frame |
|---|---|---|
| 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. | From the day of the procedure up to 14 days post-procedure. |
| Measure | Description | Time Frame |
|---|---|---|
| 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. | From the day of the procedure up to 14 days post-procedure. |
| Advanced Adenoma and Sessile Serrated Adenoma/Polyp (SSA/P) Detection Rate |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Kefeng Ding, M.D., Ph.D. | Contact | +86-13906504783 | dingkefeng@zju.edu.cn |
| Name | Affiliation | Role |
|---|---|---|
| Kefeng Ding, M.D., Ph.D. | Second Affiliated Hospital, School of Medicine, Zhejiang University | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| The Second Affiliated Hospital, Zhejiang University School of Medicine | Hangzhou | Zhejiang | 310009 | China |
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| ID | Term |
|---|---|
| D015179 | Colorectal Neoplasms |
| D003111 | Colonic Polyps |
| D000236 | Adenoma |
| ID | Term |
|---|---|
| D007414 | Intestinal Neoplasms |
| D005770 | Gastrointestinal Neoplasms |
| D004067 | Digestive System Neoplasms |
| D009371 | Neoplasms by Site |
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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. |
| 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). | 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). | 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. | From the start of the procedure up to 30 days post-procedure. |
| D009369 | Neoplasms |
| D004066 | Digestive System Diseases |
| D005767 | Gastrointestinal Diseases |
| D003108 | Colonic Diseases |
| D007410 | Intestinal Diseases |
| D012002 | Rectal Diseases |
| D007417 | Intestinal Polyps |
| D011127 | Polyps |
| D020763 | Pathological Conditions, Anatomical |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D009375 | Neoplasms, Glandular and Epithelial |
| D009370 | Neoplasms by Histologic Type |