Colorectal NeoplasmsAI-COLOADRNCT07307547
Effectiveness of Artificial Intelligence-Assisted Colonoscopy for Adenoma Detection in Routine Clinical Practice : a Prospective Multicenter Randomized Trial
A study testing AI-Assisted Colonoscopy in people with Colorectal Neoplasms and Colonic Polyp, run by Zhejiang University at 1 site in China.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 40 to 74 yearsHealthy volunteers can take part
- Conditions the study is for
- Colorectal Neoplasms, Colonic Polyp, Adenoma
- What is being tested?
- AI-Assisted Colonoscopy
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 3,300 participants
- Where
- 1 siteChina
- Study dates
- Sep 2026to Dec 2028
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 40 to 74 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- 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.
Who cannot join
- 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.
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- 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.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site
The Second Affiliated Hospital, Zhejiang University School of Medicine
Hangzhou, Zhejiang, 310009
Kefeng Ding, M.D., Ph.D., +86-13906504783, dingkefeng@zju.edu.cn
About this study
Official 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
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.
Read the detailed description
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.
- Conditions
- Colorectal Neoplasms, Colonic Polyp, Adenoma, Colorectal Cancer
- Being tested
- AI-Assisted Colonoscopy
- Keywords
- Artificial Intelligence, Colonoscopy, Colorectal Cancer Screening, Adenoma Detection Rate, Deep Learning
- Medical subject headings
- Colorectal Neoplasms, Colonic Polyps, Adenoma
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-Assisted ColonoscopyDevice
High-definition colonoscopy procedure with a real-time video analyzed artificial intelligence system.
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: Device: AI-Assisted Colonoscopy |
| 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. |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: From the day of the procedure up to 14 days post-procedure.
Secondary outcomes (7)
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.
Measured: From the day of the procedure up to 14 days post-procedure.
Advanced adenoma detection rate
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.
Measured: From the day of the procedure up to 14 days post-procedure.
Serrated lesion detection rate
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.
Measured: From the day of the colonoscopy up to 14 days after the 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).
Measured: Assessed within 1 hour after completion of the colonoscopy procedure.
Proximal adenoma detection rate
The proportion of participants with at least one histologically confirmed adenoma located proximal to the splenic flexure.
Measured: From the day of the colonoscopy up to 14 days after the 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).
Measured: 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.
Measured: From the start of the procedure up to 30 days post-procedure.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Dec 2025
- Study startSep 2026 (estimated)
- Primary completionDec 2028 (estimated)
- Study completionDec 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Colorectal NeoplasmsStudies of the same condition, open and under way.
- More trials run by Zhejiang UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Screening
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Participant
- Enrolment
- 3,300 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Zhejiang University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Ding Ke-Feng, Zhejiang University
- Investigators
- Kefeng Ding, M.D., Ph.D., Study chair, Second Affiliated Hospital, Zhejiang University, School of Medicine
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07307547
- Sponsor's protocol ID
- 2025-0756
- Acronym
- AI-COLOADR
- Status last verified
- Sep 2026
- First submitted
- 14 Dec 2025
- Last updated
- 16 Sep 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 16 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official 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
- ClinicalTrials.gov ID
- NCT07307547
- Acronym / sponsor ID
- AI-COLOADR / 2025-0756
- Conditions
- Colorectal Neoplasms, Colonic Polyp, Adenoma, Colorectal Cancer
- Keywords
- Artificial Intelligence, Colonoscopy, Colorectal Cancer Screening, Adenoma Detection Rate, Deep Learning
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 3,300 participants (estimated)
- Lead sponsor
- Zhejiang UniversityUniversity, hospital or other
- Study start
- Sep 2026 (estimated)
- Primary completion
- Dec 2028 (estimated)
- Study completion
- Dec 2028 (estimated)
- First posted
- 29 Dec 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
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.
Study design
- Primary purpose
- Screening
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (participant)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Experimental: AI-Assisted Colonoscopy | Experimental | Device: AI-Assisted ColonoscopyParticipants 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. |
| 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. |
Who may qualify
- Ages
- 40 to 74 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- 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.
Key exclusion criteria (12 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-Assisted ColonoscopyHigh-definition colonoscopy procedure with a real-time video analyzed artificial intelligence system. | Device | Experimental: AI-Assisted Colonoscopy |
Primary outcome
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.
7 secondary outcomes
Mean Adenomas Per Colonoscopy (APC)
Time frame: From the day of the procedure up to 14 days post-procedure.
Advanced adenoma detection rate
Time frame: From the day of the procedure up to 14 days post-procedure.
Serrated lesion detection rate
Time frame: From the day of the colonoscopy up to 14 days after the procedure.
Patient Satisfaction Score
Time frame: Assessed within 1 hour after completion of the colonoscopy procedure.
Proximal adenoma detection rate
Time frame: From the day of the colonoscopy up to 14 days after the procedure.
Physician Satisfaction Score
Time frame: Assessed within 1 hour after completion of the colonoscopy procedure.
Incidence of Procedure-Related Adverse Events
Time frame: From the start of the procedure up to 30 days post-procedure.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 16 Sep 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Kefeng Ding, M.D., Ph.D. study chair
Second Affiliated Hospital, Zhejiang University, School of Medicine
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI-Assisted Colonoscopy in people with Colorectal Neoplasms and Colonic Polyp, run by Zhejiang University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 12 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 16 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Kefeng Ding, M.D., Ph.D. (+86-13906504783, dingkefeng@zju.edu.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Adenoma Detection Rate (ADR) (time frame: From the day of the procedure up to 14 days post-procedure.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 16 Sep 2026.