Screening ColonoscopyNCT04422548
Does AI-assisted Colonoscopy Improve Adenoma Detection in Screening Colonoscopy?
A study testing AI-assisted Colonoscopy and Standard Colonoscopy in people with Screening Colonoscopy, run by Chinese University of Hong Kong at 1 site in Hong Kong.
Trial summary
To date, there is a lack of large-scale randomized controlled study using AI assistance in the detection of polyps/adenoma in a screening population. The correlation of fecal occult blood test (FIT or FOBT) and the advantage of AI-assisted colonoscopy has not been investigated. Read more about this study
- Who is it for?
- Ages 45 to 75 yearsHealthy volunteers can take part
- Conditions the study is for
- Screening Colonoscopy
- What is being tested?
- AI-assisted Colonoscopy and Standard Colonoscopy
- Type of treatment
- Surgery or procedure
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 2,994 participants
- Where
- 1 siteHong Kong
- Study dates
- 28 Nov 2019to 27 Nov 2020
- Phase
- Interventional
- Are there results?
- None posted in the registry
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 45 to 75 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Patients receiving colonoscopy screening
- Patients aged 45-75 years
- Both patients who have or have not done a FIT test and both FIT +ve and FIT -ve subjects
Who cannot join
- Patients who have symptom(s) suggestive of colorectal diseases
- Patients who have a history of inflammatory bowel disease, colorectal cancer or polyposis syndrome (anaemia, bloody stool, tenesmus and obstructive symptoms)
- Patients who had colonoscopy or other investigation of colon and rectum in the past 10 years
- Patients who had surgery for colorectal diseases
- Patients who cannot tolerate bowel preparation or have suboptimal bowel preparations (Boston Bowel Preparation Scale)
- Cannot reach caecum
- Patients who are incompetent in giving informed consent
Trial locations and contacts
1 site in 1 country.
Hong Kong1 site, 1 recruiting
- Recruiting
Prince of Wales Hospital
Hong Kong
Ming Yeung HO, 26371398, andrewho@cuhk.edu.hk
About this study
Official title: Does AI-assisted Colonoscopy Improve Adenoma Detection in Screening Colonoscopy? A Multi-center Randomized Controlled
To date, there is a lack of large-scale randomized controlled study using AI assistance in the detection of polyps/adenoma in a screening population. The correlation of fecal occult blood test (FIT or FOBT) and the advantage of AI-assisted colonoscopy has not been investigated. There is also a lack of information of the benefit of AI-assisted colonoscopy in experienced colonoscopist versus trainee/resident.
Read the detailed description
There are several studies showing that AI-assisted colonoscopy can help in identifying and characterizing polyps found on colonoscopy.
- Byrne et al demonstrated that their AI model for real-time assessment of endoscopic video images of colorectal polyp can differentiate between hyperplastic diminutive polyps vs adenomatous polyps with sensitivity of 98% and specificity of 83% (Byrne et al. GUT 2019)
- Urban et al designed and trained deep CNNs to detect polyps in archived video with a ROC curve of 0.991 and accuracy of 96.4%. The total number of polyps identified is significantly higher but mainly in the small (1-3mm and 4-6mm polyps) (Urban et al. Gastroenterol 2018)
- Wang et al conducted an open, non-blinded trial consecutive patients (n=1058) prospectively randomized to undergo diagnostic colonoscopy with or without AI assistance. They found that AI system increased ADR from 20.3% to 29.1% and the mean number of adenomas per patients from 0.31 to 0.53. This was due to a higher number of diminutive polyps found while there was no statistic difference in larger adenoma. (Wang et al. GUT 2019). In this study, they excluded patients with IBD, CRC and colorectal surgery. The patients presented with symptoms to hospital for investigation.
To date, there is a lack of large-scale randomized controlled study using AI assistance in the detection of polyps/adenoma in a screening population. The correlation of fecal occult blood test (FIT or FOBT) and the advantage of AI-assisted colonoscopy has not been investigated. There is also a lack of information of the benefit of AI-assisted colonoscopy in experienced colonoscopist versus trainee/resident.
- Conditions
- Screening Colonoscopy
- Being tested
- AI-assisted Colonoscopy, Standard Colonoscopy
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-assisted ColonoscopyProcedure or surgery
This is a multi-center prospective randomized controlled study comparing real-time AI-assisted colonoscopy versus standard colonoscopy in a real-life setting.
Standard ColonoscopyProcedure or surgery
Standard Colonoscopy
| Study group | Role | What they receive |
|---|---|---|
| AI-assisted Group | Active comparator | Not described Receives: Procedure: AI-assisted Colonoscopy |
| Standard | Active comparator | Not described Receives: Procedure: Standard Colonoscopy |
What is being measured
The primary outcome is the main question the study is designed to answer.
Per-patient ADR in each group
For the AI-Assisted group, it is defined as the number of patients with at least 1 adenoma identified in the colon divided by the total number of patients in the AI-Assisted group.
Measured: 12 months
Per-patient ADR in each group
For the Standard group, it is defined as the number of patients with at least 1 adenoma identified in the colon divided by the total number of patients in the Standard group.
Measured: 12 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Jun 2020
- Study start28 Nov 2019
- Primary completion27 Nov 2020 (estimated)
- Study completion27 Nov 2020 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Screening ColonoscopyStudies of the same condition, open and under way.
- More trials run by Chinese University of Hong KongThe 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
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Participant
- Enrolment
- 2,994 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Chinese University of Hong Kong
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Joseph JY SUNG, Chinese University of Hong Kong
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04422548
- Sponsor's protocol ID
- AI-CLN Study_Protocol
- Status last verified
- Jul 2020
- First submitted
- 5 Jun 2020
- Last updated
- 16 Jul 2020
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Xu H, Tang RSY, Lam TYT, Zhao G, Lau JYW, Liu Y, Wu Q, Rong L, Xu W, Li X, Wong SH, Cai S, Wang J, Liu G, Ma T, Liang X, Mak JWY, Xu H, Yuan P, Cao T, Li F, Ye Z, Shutian Z, Sung JJY. Artificial Intelligence-Assisted Colonoscopy for Colorectal Cancer Screening: A Multicenter Randomized Controlled Trial. Clin Gastroenterol Hepatol. 2023 Feb;21(2):337-346.e3. doi: 10.1016/j.cgh.2022.07.006. Epub 2022 Jul 19.
PubMed 35863686
Study at a glance
From the registry record, last updated by the sponsor on 16 Jul 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Does AI-assisted Colonoscopy Improve Adenoma Detection in Screening Colonoscopy? A Multi-center Randomized Controlled
- ClinicalTrials.gov ID
- NCT04422548
- Acronym / sponsor ID
- AI-CLN Study_Protocol
- Conditions
- Screening Colonoscopy
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 2,994 participants (estimated)
- Lead sponsor
- Chinese University of Hong KongUniversity, hospital or other
- Study start
- 28 Nov 2019 (actual)
- Primary completion
- 27 Nov 2020 (estimated)
- Study completion
- 27 Nov 2020 (estimated)
- First posted
- 9 Jun 2020 (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.
To date, there is a lack of large-scale randomized controlled study using AI assistance in the detection of polyps/adenoma in a screening population. The correlation of fecal occult blood test (FIT or FOBT) and the advantage of AI-assisted colonoscopy has not been investigated. There is also a lack of information of the benefit of AI-assisted colonoscopy in experienced colonoscopist versus trainee/resident.
Detailed description
There are several studies showing that AI-assisted colonoscopy can help in identifying and characterizing polyps found on colonoscopy.
- Byrne et al demonstrated that their AI model for real-time assessment of endoscopic video images of colorectal polyp can differentiate between hyperplastic diminutive polyps vs adenomatous polyps with sensitivity of 98% and specificity of 83% (Byrne et al. GUT 2019)
- Urban et al designed and trained deep CNNs to detect polyps in archived video with a ROC curve of 0.991 and accuracy of 96.4%. The total number of polyps identified is significantly higher but mainly in the small (1-3mm and 4-6mm polyps) (Urban et al. Gastroenterol 2018)
- Wang et al conducted an open, non-blinded trial consecutive patients (n=1058) prospectively randomized to undergo diagnostic colonoscopy with or without AI assistance. They found that AI system increased ADR from 20.3% to 29.1% and the mean number of adenomas per patients from 0.31 to 0.53. This was due to a higher number of diminutive polyps found while there was no statistic difference in larger adenoma. (Wang et al. GUT 2019). In this study, they excluded patients with IBD, CRC and colorectal surgery. The patients presented with symptoms to hospital for investigation.
To date, there is a lack of large-scale randomized controlled study using AI assistance in the detection of polyps/adenoma in a screening population. The correlation of fecal occult blood test (FIT or FOBT) and the advantage of AI-assisted colonoscopy has not been investigated. There is also a lack of information of the benefit of AI-assisted colonoscopy in experienced colonoscopist versus trainee/resident.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (participant)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI-assisted Group | Active comparator | Procedure: AI-assisted Colonoscopy |
| Standard | Active comparator | Procedure: Standard Colonoscopy |
Who may qualify
- Ages
- 45 to 75 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Patients receiving colonoscopy screening
- Patients aged 45-75 years
- Both patients who have or have not done a FIT test and both FIT +ve and FIT -ve subjects
Key exclusion criteria (7 listed)
- Patients who have symptom(s) suggestive of colorectal diseases
- Patients who have a history of inflammatory bowel disease, colorectal cancer or polyposis syndrome (anaemia, bloody stool, tenesmus and obstructive symptoms)
- Patients who had colonoscopy or other investigation of colon and rectum in the past 10 years
- Patients who had surgery for colorectal diseases
- Patients who cannot tolerate bowel preparation or have suboptimal bowel preparations (Boston Bowel Preparation Scale)
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 ColonoscopyThis is a multi-center prospective randomized controlled study comparing real-time AI-assisted colonoscopy versus standard colonoscopy in a real-life setting. | Procedure or surgery | AI-assisted Group |
| Standard ColonoscopyStandard Colonoscopy | Procedure or surgery | Standard |
Primary outcome
Per-patient ADR in each group
Time frame: 12 months
For the AI-Assisted group, it is defined as the number of patients with at least 1 adenoma identified in the colon divided by the total number of patients in the AI-Assisted group.
Per-patient ADR in each group
Time frame: 12 months
For the Standard group, it is defined as the number of patients with at least 1 adenoma identified in the colon divided by the total number of patients in the Standard group.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 16 Jul 2020.
- Derived from this study: PubMed 35863686Xu H, Tang RSY, Lam TYT, Zhao G, Lau JYW, Liu Y, Wu Q, Rong L, Xu W, Li X, Wong SH, Cai S, Wang J, Liu G, Ma T, Liang X, Mak JWY, Xu H, Yuan P, Cao T, Li F, Ye Z, Shutian Z, Sung JJY. Artificial Intelligence-Assisted Colonoscopy for Colorectal Cancer Screening: A Multicenter Randomized Controlled Trial. Clin Gastroenterol Hepatol. 2023 Feb;21(2):337-346.e3. doi: 10.1016/j.cgh.2022.07.006. Epub 2022 Jul 19.
- Individual participant dataSharing planned: No
Related trials for Screening Colonoscopy
Recruiting
Artificial Intelligence to Implement Cost-saving Strategies for Colonoscopy Screening Based on in Vivo Prediction of Polyp Histology
Colonic Neoplasms
Active, not recruiting
The PRIME-CRC Trial to Promote CRC Screening in Rural Communities
Colorectal Cancer
Recruiting
Performance and Safety of MiWEndo-assisted Colonoscopy (MiWEndo II)
Colorectal Cancer, Colorectal Polyp
Not yet recruiting
Mailed FIT-Based Outreach Interventions
Colorectal Cancer
Not yet recruiting
A Novel Multi-functional Artificial Intelligence System on Treatment Efficacy and Implementation in Colonoscopy
Colorectal Cancer (CRC) Screening
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. This study is not recruiting at the moment.
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 and Standard Colonoscopy in people with Screening Colonoscopy, run by Chinese University of Hong Kong at 1 site in Hong Kong.
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 7 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: status not confirmed, as of the sponsor's last update on 16 Jul 2020. 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 Hong Kong. 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Andrew Ming Yeung HO (26371398, andrewho@cuhk.edu.hk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Per-patient ADR in each group (time frame: 12 months). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04422548, which also lists 1 linked publication.
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 Jul 2020.