Colorectal NeoplasmsNCT04915833
Computer-aided Detection During Screening Colonoscopy (Experts)
A study testing Standard high-definition colonoscopy and Colonoscopy with real-time AI assisted automated polyp detection in people with Colorectal Neoplasms and Colon Polyp, run by Instituto Ecuatoriano de Enfermedades Digestivas at 1 site in Ecuador.
Trial summary
Evaluation of the colonic mucosa with a high definition colonoscope (EPKi7010 video processor). The endoscopy images will be seen on a 27inch, flat-panel, high-definition LCD monitor (Radiance™ ultraSC-WU27-G1520 model) only by one expert endoscopist, randomly assigned. Read more about this study
- Who is it for?
- Ages 45 to 80 years
- Conditions the study is for
- Colorectal Neoplasms, Colon Polyp, Colon Adenoma
- What is being tested?
- Standard high-definition colonoscopy and Colonoscopy with real-time AI assisted automated polyp detection
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 209 participants
- Where
- 1 siteEcuador
- Study dates
- 26 Apr 2021to 28 Jun 2022
- 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 80 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Provided informed written consent
- Age greater than 45 years of age
- Adequate Bowel preparation
Who cannot join
- History of inflammatory bowel disease, familial polyposis syndrome
- History of colorectal carcinoma, colorectal surgery
- History of uncontrolled coagulopathy
- History of previously failed attempt colonoscopy
Trial locations and contacts
1 site in 1 country.
Ecuador1 site, 1 recruiting
- Recruiting
Ecuadorian Institute of Digestive Diseases
Guayaquil, Guayas, 090505
Carlos A Robles-Medranda, MD, +593989158865, carlosoakm@yahoo.es
Carlos A Robles-Medranda, MD
About this study
Official title: Real-time Computer-aided Polyp Detection During Screening Colonoscopy Performed by Expert Endoscopists
Evaluation of the colonic mucosa with a high definition colonoscope (EPKi7010 video processor).
The endoscopy images will be seen on a 27inch, flat-panel, high-definition LCD monitor (Radiance™ ultraSC-WU27-G1520 model) only by one expert endoscopist, randomly assigned.
Read more
The number, location, and polyps' features (Paris classification) will be recorded by the operator. If a polyp is detected, the endoscopist will remove the polyp endoscopically with a cold snare.
The same patient will be submitted to a second, the same session, computed aided real-time colonoscopy using the DISCOVERY, AI-assisted polyp detector. Colonoscopy will be performed by a same-level-of-expertise operator in comparison to the initial procedure. Any polyp or lesion detected with the AI system will be recorded and endoscopically removed and considered as a missed lesion from standard colonoscopy.
Read the detailed description
Screening colonoscopy has decreased the incidence of colorectal carcinoma in the previous decades. However, there are reports of missed polyps and interval CRC following screening colonoscopy. Several factors may affect the ADR, PDR, and missed lesions rates, such as bowel preparation, percentage of mucosal surface evaluation, and the training levels of operators.
Artificial intelligence using deep-learning algorithms has been implemented in gastrointestinal endoscopy, mainly for the detection and diagnosis of GI tract lesions such as colonic polyps and adenomas. The implementation of automated polyp detection software during screening colonoscopy may prevent the missing of polyp and adenoma during screening colonoscopy. Therefore, improving the ADR and PDR during colonoscopies. All of this, with the aim of decrease the incidence of interval colorectal carcinoma (CRC), and CRC-related morbidity and mortality.
The Discovery Artificial Intelligence assisted polyp detector (Pentax Medical, Hoya Group) was recently launched for clinical practice. This AI software was trained with 120,000 files from approximately 300 clinical cases. The visual aided detection (bounding box locating a polyp on the monitor) will alert the endoscopist if a polyp/adenoma was missed during the standard, screening procedure.
To the best of our knowledge, this may be the first study evaluating the Discovery AI-assisted polyp detector on clinical practice in the western hemisphere. The investigators aim to evaluate the real-world effectiveness of AI-assisted colonoscopy in clinical practice. The investigators will also evaluate the role of endoscopists' levels of training in the ADR, PDR, and missed lesion rate.
- Conditions
- Colorectal Neoplasms, Colon Polyp, Colon Adenoma
- Being tested
- Standard high-definition colonoscopy, Colonoscopy with real-time AI assisted automated polyp detection
- Keywords
- colonoscopy, colorectal cancer
- Medical subject headings
- Colorectal Neoplasms, Colonic Polyps
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Standard high-definition colonoscopyDiagnostic test
Evaluation of the colonic mucosa with a high definition colonoscope (EPKi7010 video processor).
The endoscopy images will be seen on a 27inch, flat panel, high-definition LCD monitor (Radiance™ ultraSC-WU27-G1520 model) only by one expert endoscopist, randomly assigned.
The number, location and polyps' features (Paris classification) will be recorded by the operator. If a polyp is detected, the endoscopist will remove the polyp endoscopically with a cold snare and forceps biopsy.
Colonoscopy with real-time AI assisted automated polyp detectionDiagnostic test
The same patient will be submitted to a second, same session, computed aided real-time colonoscopy using the DISCOVERY, AI assisted polyp detector. Colonoscopy will be performed by a same-level-of-expertise operator in comparison to the initial procedure. Any polyp or lesion detected with the AI system will be recorded and endoscopically removed and considered as a missed lesion from standard colonoscopy.
| Study group | Role | What they receive |
|---|---|---|
| Patients for CRC screening and diagnostic colonoscopy | Experimental | Consecutive patients >45 years of age submitted for diagnostic colonoscopy Receives: Diagnostic Test: Standard high-definition colonoscopy; Diagnostic Test: Colonoscopy with real-time AI assisted automated polyp detection |
What is being measured
The primary outcome is the main question the study is designed to answer.
Adenoma detection rate of computer-aided after standard colonoscopy.
Number of examinations with at least one adenoma detected during colonoscopy while using the AI-based model
Measured: 30 days
Polyp detection rate of computer-aided following standard colonoscopy.
Number of examination with at least one polyp detected while using the AI-based model
Measured: 30 days
Secondary outcomes (2)
Polyp miss rate of standard high-definition colonoscopy.
Total number of missed polyps/ (total number of missed polyps + total number of polyps on initial examination)
Measured: 30 days
Adenoma miss rate of standard high-definition colonoscopy.
Total number of missed adenomas/ (total number of missed adenomas + total number of adenomas on initial examination)
Measured: 30 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted7 Jun 2021
- Study start26 Apr 2021
- Primary completion30 Apr 2022 (estimated)
- Study completion28 Jun 2022 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for Colorectal NeoplasmsStudies 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
- Not applicable
- Intervention model
- Single group
- Model description
- A non-blinded, non-randomized prospective diagnostic trial. Two interventions: * Standard colonoscopy: 1 expert * AI-assisted colonoscopy: another expert
- Masking
- None (open label)
- Enrolment
- 209 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Instituto Ecuatoriano de Enfermedades Digestivas
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Carlos Robles-Medranda, MD FASGE, Principal investigator, Ecuadorian Institute of Digestive Diseases
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04915833
- Sponsor's protocol ID
- IECED-042621
- Status last verified
- Mar 2022
- First submitted
- 1 Jun 2021
- Last updated
- 31 Mar 2022
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Wang P, Berzin TM, Glissen Brown JR, Bharadwaj S, Becq A, Xiao X, Liu P, Li L, Song Y, Zhang D, Li Y, Xu G, Tu M, Liu X. Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study. Gut. 2019 Oct;68(10):1813-1819. doi: 10.1136/gutjnl-2018-317500. Epub 2019 Feb 27.
PubMed 30814121Vinsard DG, Mori Y, Misawa M, Kudo SE, Rastogi A, Bagci U, Rex DK, Wallace MB. Quality assurance of computer-aided detection and diagnosis in colonoscopy. Gastrointest Endosc. 2019 Jul;90(1):55-63. doi: 10.1016/j.gie.2019.03.019. Epub 2019 Mar 26.
PubMed 30926431
Study at a glance
From the registry record, last updated by the sponsor on 31 Mar 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Real-time Computer-aided Polyp Detection During Screening Colonoscopy Performed by Expert Endoscopists
- ClinicalTrials.gov ID
- NCT04915833
- Acronym / sponsor ID
- IECED-042621
- Conditions
- Colorectal Neoplasms, Colon Polyp, Colon Adenoma
- Keywords
- colonoscopy, colorectal cancer
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 209 participants (estimated)
- Lead sponsor
- Instituto Ecuatoriano de Enfermedades DigestivasUniversity, hospital or other
- Study start
- 26 Apr 2021 (actual)
- Primary completion
- 30 Apr 2022 (estimated)
- Study completion
- 28 Jun 2022 (estimated)
- First posted
- 7 Jun 2021 (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.
Evaluation of the colonic mucosa with a high definition colonoscope (EPKi7010 video processor).
The endoscopy images will be seen on a 27inch, flat-panel, high-definition LCD monitor (Radiance™ ultraSC-WU27-G1520 model) only by one expert endoscopist, randomly assigned.
The number, location, and polyps' features (Paris classification) will be recorded by the operator. If a polyp is detected, the endoscopist will remove the polyp endoscopically with a cold snare.
The same patient will be submitted to a second, the same session, computed aided real-time colonoscopy using the DISCOVERY, AI-assisted polyp detector. Colonoscopy will be performed by a same-level-of-expertise operator in comparison to the initial procedure. Any polyp or lesion detected with the AI system will be recorded and endoscopically removed and considered as a missed lesion from standard colonoscopy.
Detailed description
Screening colonoscopy has decreased the incidence of colorectal carcinoma in the previous decades. However, there are reports of missed polyps and interval CRC following screening colonoscopy. Several factors may affect the ADR, PDR, and missed lesions rates, such as bowel preparation, percentage of mucosal surface evaluation, and the training levels of operators.
Artificial intelligence using deep-learning algorithms has been implemented in gastrointestinal endoscopy, mainly for the detection and diagnosis of GI tract lesions such as colonic polyps and adenomas. The implementation of automated polyp detection software during screening colonoscopy may prevent the missing of polyp and adenoma during screening colonoscopy. Therefore, improving the ADR and PDR during colonoscopies. All of this, with the aim of decrease the incidence of interval colorectal carcinoma (CRC), and CRC-related morbidity and mortality.
The Discovery Artificial Intelligence assisted polyp detector (Pentax Medical, Hoya Group) was recently launched for clinical practice. This AI software was trained with 120,000 files from approximately 300 clinical cases. The visual aided detection (bounding box locating a polyp on the monitor) will alert the endoscopist if a polyp/adenoma was missed during the standard, screening procedure.
To the best of our knowledge, this may be the first study evaluating the Discovery AI-assisted polyp detector on clinical practice in the western hemisphere. The investigators aim to evaluate the real-world effectiveness of AI-assisted colonoscopy in clinical practice. The investigators will also evaluate the role of endoscopists' levels of training in the ADR, PDR, and missed lesion rate.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- A non-blinded, non-randomized prospective diagnostic trial. Two interventions: * Standard colonoscopy: 1 expert * AI-assisted colonoscopy: another expert
| Arm | Type | Receives |
|---|---|---|
| Patients for CRC screening and diagnostic colonoscopy | Experimental | Diagnostic Test: Standard high-definition colonoscopy, Diagnostic Test: Colonoscopy with real-time AI assisted automated polyp detectionConsecutive patients >45 years of age submitted for diagnostic colonoscopy |
Who may qualify
- Ages
- 45 to 80 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Provided informed written consent
- Age greater than 45 years of age
- Adequate Bowel preparation
Key exclusion criteria (4 listed)
- History of inflammatory bowel disease, familial polyposis syndrome
- History of colorectal carcinoma, colorectal surgery
- History of uncontrolled coagulopathy
- History of previously failed attempt colonoscopy
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 |
|---|---|---|
| Standard high-definition colonoscopyEvaluation of the colonic mucosa with a high definition colonoscope (EPKi7010 video processor). The endoscopy images will be seen on a 27inch, flat panel, high-definition LCD monitor (Radiance™ ultraSC-WU27-G1520 model) only by one expert endoscopist, randomly assigned. The number, location and polyps' features (Paris classification) will be recorded by the operator. If a polyp is detected, the endoscopist will remove the polyp endoscopically with a cold snare and forceps biopsy. | Diagnostic test | Patients for CRC screening and diagnostic colonoscopy |
| Colonoscopy with real-time AI assisted automated polyp detectionThe same patient will be submitted to a second, same session, computed aided real-time colonoscopy using the DISCOVERY, AI assisted polyp detector. Colonoscopy will be performed by a same-level-of-expertise operator in comparison to the initial procedure. Any polyp or lesion detected with the AI system will be recorded and endoscopically removed and considered as a missed lesion from standard colonoscopy. | Diagnostic test | Patients for CRC screening and diagnostic colonoscopy |
Primary outcome
Adenoma detection rate of computer-aided after standard colonoscopy.
Time frame: 30 days
Number of examinations with at least one adenoma detected during colonoscopy while using the AI-based model
Polyp detection rate of computer-aided following standard colonoscopy.
Time frame: 30 days
Number of examination with at least one polyp detected while using the AI-based model
2 secondary outcomes
Polyp miss rate of standard high-definition colonoscopy.
Time frame: 30 days
Adenoma miss rate of standard high-definition colonoscopy.
Time frame: 30 days
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 31 Mar 2022.
- Background: PubMed 30814121Wang P, Berzin TM, Glissen Brown JR, Bharadwaj S, Becq A, Xiao X, Liu P, Li L, Song Y, Zhang D, Li Y, Xu G, Tu M, Liu X. Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study. Gut. 2019 Oct;68(10):1813-1819. doi: 10.1136/gutjnl-2018-317500. Epub 2019 Feb 27.
- Background: PubMed 30926431Vinsard DG, Mori Y, Misawa M, Kudo SE, Rastogi A, Bagci U, Rex DK, Wallace MB. Quality assurance of computer-aided detection and diagnosis in colonoscopy. Gastrointest Endosc. 2019 Jul;90(1):55-63. doi: 10.1016/j.gie.2019.03.019. Epub 2019 Mar 26.
- 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.
Carlos Robles-Medranda, MD FASGE principal investigator
Ecuadorian Institute of Digestive Diseases
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Standard high-definition colonoscopy and Colonoscopy with real-time AI assisted automated polyp detection in people with Colorectal Neoplasms and Colon Polyp, run by Instituto Ecuatoriano de Enfermedades Digestivas at 1 site in Ecuador.
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 4 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 31 Mar 2022. 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 Ecuador. 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 Carlos Robles-Medranda, MD (+59342109180, carlosoakm@yahoo.es), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Adenoma detection rate of computer-aided after standard colonoscopy. (time frame: 30 days). 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 NCT04915833, which also lists 2 linked publications.
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 31 Mar 2022.