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NCT Number: NCT07307547

Effectiveness of Artificial Intelligence-Assisted Colonoscopy for Adenoma Detection in Routine Clinical Practice : a Prospective Multicenter Randomized Trial

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.

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Key information

Conditions

Colorectal Neoplasms Adenoma Colonic Diseases Colonic Polyp Colonic Polyps Colorectal Cancer Digestive System Diseases Digestive System Neoplasms Gastrointestinal Diseases Gastrointestinal Neoplasms Intestinal Diseases Intestinal Neoplasms Intestinal Polyps Neoplasms Neoplasms by Histologic Type Neoplasms by Site Neoplasms, Glandular and Epithelial Pathological Conditions, Anatomical Pathological Conditions, Signs and Symptoms Polyps Rectal Diseases

Age range

40 year–74 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

The Second Affiliated Hospital, Zhejiang University School of Medicine

Hangzhou, Zhejiang, 310009, China

Location contact

Kefeng Ding, M.D., Ph.D.

CONTACT

[email protected]

+86-13906504783

About this study

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 3300 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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age 40 to 74 years, inclusive; men and women.
  • Scheduled for elective screening, diagnostic, or surveillance colonoscopy.
  • In generally good condition, mentally competent, and willing to provide written informed consent.

Exclusion criteria

  • Known contraindication to colonoscopy or to biopsy.
  • History of colon cancer or previous colonic surgery.
  • Bowel obstruction; confirmed or highly suspected colorectal cancer; inflammatory bowel disease; or active colorectal bleeding.
  • Colorectal polyposis, including a history of familial adenomatous polyposis.
  • Pregnancy or breastfeeding.
  • Participation in another drug or medical device clinical trial within 1 month before enrollment.
  • Any other condition that, in the investigator's judgment, makes the participant unsuitable for this trial.

Withdrawal Criteria:

  • Withdrawal of consent by the participant.
  • Inadequate bowel preparation, defined as a Boston Bowel Preparation Scale (BBPS) total score below 6 or any segment score below 2.
  • Failure to reach the cecum.
  • Newly diagnosed active colitis during the procedure.

Treatment and study plan

AI-Assisted Colonoscopy

Device

High-definition colonoscopy procedure with a real-time video analyzed artificial intelligence system.

Primary outcomes

  1. Adenoma Detection Rate (ADR)

    Time frame: From the day of the procedure up to 14 days post-procedure.

    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.

Secondary outcomes

  1. Mean Adenomas Per Colonoscopy (APC)

    Time frame: From the day of the procedure up to 14 days post-procedure.

    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.

  2. Advanced adenoma detection rate

    Time frame: From the day of the procedure up to 14 days post-procedure.

    The proportion of participants with at least one histologically confirmed advanced adenoma, defined as an adenoma at least 10 mm in diameter, or with high-grade dysplasia, or with a villous component.

  3. Serrated lesion detection rate

    Time frame: From the day of the colonoscopy up to 14 days after the procedure.

    The proportion of participants with at least one histologically confirmed flat serrated lesion, including sessile serrated lesions with or without dysplasia and traditional serrated adenomas. Hyperplastic polyps are reported separately.

  4. Patient Satisfaction Score

    Time frame: Assessed within 1 hour after completion of the colonoscopy procedure.

    Assessed using a 5-point Likert scale questionnaire evaluating examination comfort and acceptance of the AI system (1=very unsatisfied, 5=very satisfied).

  5. Proximal adenoma detection rate

    Time frame: From the day of the colonoscopy up to 14 days after the procedure.

    The proportion of participants with at least one histologically confirmed adenoma located proximal to the splenic flexure.

  6. Physician Satisfaction Score

    Time frame: Assessed within 1 hour after completion of the colonoscopy procedure.

    Assessed using a 5-point Likert scale questionnaire evaluating the AI system's usability and reliability (1=very unsatisfied, 5=very satisfied).

  7. Incidence of Procedure-Related Adverse Events

    Time frame: From the start of the procedure up to 30 days post-procedure.

    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.

Study contacts

Contact information is provided by the study sponsor or research team.

Kefeng Ding, M.D., Ph.D.

CONTACT

[email protected]

+86-13906504783

Sponsors and collaborators

Lead sponsor

Zhejiang University

Other

Registry information

Official study title

A Multi-center, Randomized, Controlled Clinical Study on the Effectiveness of Artificial Intelligence-Assisted Colonoscopy in Improving the Screening of Colorectal Cancer and Precancerous Lesions in Routine Clinical Practice Across Tertiary Academic Medical Centers

Acronym: AI-COLOADR

Important dates

Study start
2026
Primary completion
2028
Study completion
2028
First posted
Dec 29, 2025
Registry last updated
Sep 16, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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