Artificial IntelligenceNCT04126265
Artificial Intelligence-assisted Colonoscopy for Detection of Colon Polyps
A study testing Artificial intelligence assisted colonoscopy in people with Artificial Intelligence and Colonoscopy, run by Side Liu at 1 site in China.
Trial summary
All subjects shall sign informed consent before screening, and subjects shall be included according to inclusion and exclusion criteria. A total of four endoscopists were included in the study, two in each group of senior endoscopists and two in each group of junior endoscopists. Read more about this study
- Who is it for?
- Ages 18 to 80 yearsHealthy volunteers can take part
- Conditions the study is for
- Artificial Intelligence, Colonoscopy
- What is being tested?
- Artificial intelligence assisted colonoscopy
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 560 participants
- Where
- 1 siteChina
- Study dates
- 1 Sep 2019to 31 Aug 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 18 to 80 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Chinese population aged 18-80 years old; Patients voluntarily signed informed consent form; In accordance with the indications of colonoscopy.
Who cannot join
- (IBD) history of inflammatory bowel disease; History of colorectal surgery; Previous failed colonoscopy; Polyposis syndrome; Highly suspected colorectal cancer (CRC)
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Nanfang Hospital
Guangzhou, Guangdong
YI ZHANG, master degree, +86 13533787871
About this study
Official title: Artificial Intelligence-assisted Colonoscopy for Detection of Colon Polyps: a Prospective Randomized Cohort Study
All subjects shall sign informed consent before screening, and subjects shall be included according to inclusion and exclusion criteria.
A total of four endoscopists were included in the study, two in each group of senior endoscopists and two in each group of junior endoscopists.
Read more
Patients were randomly enrolled into the senior endoscopy group and the junior endoscopy group, and received artificial intelligence assisted colonoscopy and conventional colonoscopy successively. The two colonoscopy methods were performed back to back by different endoscopy physicians with the same seniority.
All patients were examined and treated according to routine medical procedures. The routine colonoscopy group and the artificial-intelligence-assisted colonoscopy group made detailed records of the patients' withdrawal time, entry time, number of polyps detected, polyp Paris classification, polyp size, polyp shape, polyp location and intestinal preparation during the colonoscopy process
Read the detailed description
This is a prospective randomized clinical study.This study was conducted in the Endoscopy Center of the Nanfang Hospital, China. Routine bowel preparation consisted of 4 L of polyethylene glycol, given in split doses. Colonoscopies were performed with high definition colonoscopes and high-definition monitors.
All subjects shall sign informed consent before screening, and subjects shall be included according to inclusion and exclusion criteria.
A total of four endoscopists were included in the study, two in each group of senior endoscopists (>1000 colonoscopies) and two in each group of junior endoscopists ( <1000 colonoscopies).
Patients were randomly enrolled into the senior endoscopy group and the junior endoscopy group, and received artificial intelligence assisted colonoscopy and conventional colonoscopy successively. The two colonoscopy methods were performed by different endoscopy physicians back to back with the same seniority.
All patients were examined and treated according to routine medical procedures (outpatient patients and inpatients who did not sign the consent form for polypectomy were not resected for the lesions detected during the examination, while inpatients who signed the consent form for polypectomy were left in the original position after the first colonoscopy and removed at the end of the second examination).
The routine colonoscopy group and the artificial-intelligence-assisted colonoscopy group made detailed records of the patients' withdrawal time, entry time, number of polyps detected, polyp Paris classification, polyp size, polyp shape, polyp location and intestinal preparation during the colonoscopy process.
- Conditions
- Artificial Intelligence, Colonoscopy
- Being tested
- Artificial intelligence assisted colonoscopy
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial intelligence assisted colonoscopyDevice
The colonoscopy is connected to the real-time polyp detection system. If the polyp is detected by enteroscopy, the alarm will be given.
| Study group | Role | What they receive |
|---|---|---|
| Routine colonoscopy group | No intervention | The patient underwent routine colonoscopy. |
| Artificial intelligence assisted colonoscopy group | Experimental | The real-time automatic polyp detection system was used to assist the endoscopist. Receives: Device: Artificial intelligence assisted colonoscopy |
What is being measured
The primary outcome is the main question the study is designed to answer.
Detection rate of small polyps (diameter < 6mm)
In each group, the number of patients with small polyps was detected as a percentage of the total number of patients.
Measured: 6 months
Secondary outcomes (3)
Number of polyps detected
Number of polyps found in each group.
Measured: 6 months
Polyp size
Average size of all polyps detected in each group.
Measured: 6 months
Polyp morphology
Morphological classification of all polyps detected in each group.
Measured: 6 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted15 Oct 2019
- Study start1 Sep 2019
- Primary completion30 Apr 2020 (estimated)
- Study completion31 Aug 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 Artificial IntelligenceStudies of the same condition, open and under way.
- 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
- None (open label)
- Enrolment
- 560 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Side Liu
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Side Liu, Nanfang Hospital, Southern Medical University
- Investigators
- side liu, doctor degree, Principal investigator, Chief physician
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04126265
- Sponsor's protocol ID
- NCT201908-K5-01
- Status last verified
- Dec 2019
- First submitted
- 11 Oct 2019
- Last updated
- 2 Jan 2020
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Luo Y, Zhang Y, Liu M, Lai Y, Liu P, Wang Z, Xing T, Huang Y, Li Y, Li A, Wang Y, Luo X, Liu S, Han Z. Artificial Intelligence-Assisted Colonoscopy for Detection of Colon Polyps: a Prospective, Randomized Cohort Study. J Gastrointest Surg. 2021 Aug;25(8):2011-2018. doi: 10.1007/s11605-020-04802-4. Epub 2020 Sep 23.
PubMed 32968933
Study at a glance
From the registry record, last updated by the sponsor on 2 Jan 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence-assisted Colonoscopy for Detection of Colon Polyps: a Prospective Randomized Cohort Study
- ClinicalTrials.gov ID
- NCT04126265
- Acronym / sponsor ID
- NCT201908-K5-01
- Conditions
- Artificial Intelligence, Colonoscopy
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 560 participants (estimated)
- Lead sponsor
- Side LiuUniversity, hospital or other
- Study start
- 1 Sep 2019 (actual)
- Primary completion
- 30 Apr 2020 (estimated)
- Study completion
- 31 Aug 2020 (estimated)
- First posted
- 15 Oct 2019 (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.
All subjects shall sign informed consent before screening, and subjects shall be included according to inclusion and exclusion criteria.
A total of four endoscopists were included in the study, two in each group of senior endoscopists and two in each group of junior endoscopists.
Patients were randomly enrolled into the senior endoscopy group and the junior endoscopy group, and received artificial intelligence assisted colonoscopy and conventional colonoscopy successively. The two colonoscopy methods were performed back to back by different endoscopy physicians with the same seniority.
All patients were examined and treated according to routine medical procedures. The routine colonoscopy group and the artificial-intelligence-assisted colonoscopy group made detailed records of the patients' withdrawal time, entry time, number of polyps detected, polyp Paris classification, polyp size, polyp shape, polyp location and intestinal preparation during the colonoscopy process
Detailed description
This is a prospective randomized clinical study.This study was conducted in the Endoscopy Center of the Nanfang Hospital, China. Routine bowel preparation consisted of 4 L of polyethylene glycol, given in split doses. Colonoscopies were performed with high definition colonoscopes and high-definition monitors.
All subjects shall sign informed consent before screening, and subjects shall be included according to inclusion and exclusion criteria.
A total of four endoscopists were included in the study, two in each group of senior endoscopists (>1000 colonoscopies) and two in each group of junior endoscopists ( <1000 colonoscopies).
Patients were randomly enrolled into the senior endoscopy group and the junior endoscopy group, and received artificial intelligence assisted colonoscopy and conventional colonoscopy successively. The two colonoscopy methods were performed by different endoscopy physicians back to back with the same seniority.
All patients were examined and treated according to routine medical procedures (outpatient patients and inpatients who did not sign the consent form for polypectomy were not resected for the lesions detected during the examination, while inpatients who signed the consent form for polypectomy were left in the original position after the first colonoscopy and removed at the end of the second examination).
The routine colonoscopy group and the artificial-intelligence-assisted colonoscopy group made detailed records of the patients' withdrawal time, entry time, number of polyps detected, polyp Paris classification, polyp size, polyp shape, polyp location and intestinal preparation during the colonoscopy process.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Routine colonoscopy group | No intervention | –The patient underwent routine colonoscopy. |
| Artificial intelligence assisted colonoscopy group | Experimental | Device: Artificial intelligence assisted colonoscopyThe real-time automatic polyp detection system was used to assist the endoscopist. |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (1 listed)
- Chinese population aged 18-80 years old; Patients voluntarily signed informed consent form; In accordance with the indications of colonoscopy.
Key exclusion criteria (1 listed)
- (IBD) history of inflammatory bowel disease; History of colorectal surgery; Previous failed colonoscopy; Polyposis syndrome; Highly suspected colorectal cancer (CRC)
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 |
|---|---|---|
| Artificial intelligence assisted colonoscopyThe colonoscopy is connected to the real-time polyp detection system. If the polyp is detected by enteroscopy, the alarm will be given. | Device | Artificial intelligence assisted colonoscopy group |
Primary outcome
Detection rate of small polyps (diameter < 6mm)
Time frame: 6 months
In each group, the number of patients with small polyps was detected as a percentage of the total number of patients.
3 secondary outcomes
Number of polyps detected
Time frame: 6 months
Polyp size
Time frame: 6 months
Polyp morphology
Time frame: 6 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 2 Jan 2020.
- Derived from this study: PubMed 32968933Luo Y, Zhang Y, Liu M, Lai Y, Liu P, Wang Z, Xing T, Huang Y, Li Y, Li A, Wang Y, Luo X, Liu S, Han Z. Artificial Intelligence-Assisted Colonoscopy for Detection of Colon Polyps: a Prospective, Randomized Cohort Study. J Gastrointest Surg. 2021 Aug;25(8):2011-2018. doi: 10.1007/s11605-020-04802-4. Epub 2020 Sep 23.
- 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. This study is not recruiting at the moment.
side liu, doctor degree principal investigator
Chief physician
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Artificial intelligence assisted colonoscopy in people with Artificial Intelligence and Colonoscopy, run by Side Liu 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 1 inclusion and 1 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 2 Jan 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 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact YI zhang, master degree (+86 13533787871, 13533787871@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Detection rate of small polyps (diameter < 6mm) (time frame: 6 months). 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 NCT04126265, 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 2 Jan 2020.