Adenoma ColonNCT04359355
Computer-aided Detection of Colorectal Polyps
An observational study of Adenoma Colon and Polyp of Colon, run by University of Erlangen-Nürnberg Medical School at 1 site in Germany.
Trial summary
In this observational pilot study, we assess the diagnostic performance of an artificial intelligence sytem for automated detection of colorectal polyps. Read more about this study
- Who is it for?
- Ages 18 to 85 yearsHealthy volunteers can take part
- Conditions the study is for
- Adenoma Colon, Polyp of Colon
- What is being tested?
- Artificial Intelligence System for Detection of colorectal polyps
- Type of treatment
- Medical device
- How many people
- 40 participants
- Where
- 1 siteGermany
- Study dates
- 1 Jan 2020to 31 May 2020
- Phase
- Observational
- 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 85 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: All patients presenting between January and May 2020 for surveillance or Screening colonoscopy in the Ludwig Demling Endoscopy Center of Excellence will be prospectively included under the above mentioned inclusion and exclusion criteria. Prior to enrollment, written informed consent will be obtained.
Who may be able to join
- Screening or surveillance colonoscopy
Who cannot join
- known or suspected inflammatory bowel disease
- uncontrolled coagulopathy
- known polyps or referral for polypectomy
Trial locations and contacts
1 site in 1 country.
Germany1 site, 1 recruiting
- Recruiting
University Hospital Erlangen
Erlangen, 91054
Timo Rath, Professor of Endoscopy, 49 9131 ext. 85 45041, timo.rath@uk-erlangen.de
About this study
Official title: Development and Validation of a New Artificial Intelligence System for Automated Detection of Colorectal Polyps During Colonoscopy
In this observational pilot study, we assess the diagnostic performance of an artificial intelligence sytem for automated detection of colorectal polyps.
Read the detailed description
During standard colonoscopy, a substantial number of colorectal polyps can be missend. As shown in a recent meta-analysis, miss rates for adenomas can reach up to 26%. In this study, it is tested whether an artificial intelligence system that highlights colorectal polyps during screening or surveillance colonoscopy in real time can lead to an increased detection of colorectal polyps during the examination.
- Conditions
- Adenoma Colon, Polyp of Colon
- Being tested
- Artificial Intelligence System for Detection of colorectal polyps
- Keywords
- colonoscopy, endoscopy, adenoma detection, polyp detection, artificial intelligence
- Medical subject headings
- Colonic Polyps
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial Intelligence System for Detection of colorectal polypsDevice
In this group, an artificial Intelligence System will be used for computer-aided diagnosis of colorectal polyps. Diagnostic Performance of the artificial intelligence System for detection of polyps will be compared against Operator-based detection in the same group
| Study group | Role | What they receive |
|---|---|---|
| Artificial Intelligence | Not described Receives: Device: Artificial Intelligence System for Detection of colorectal polyps |
What is being measured
The primary outcome is the main question the study is designed to answer.
Feasibility to use the AI System in vivo during colonoscopy
As a Primary outcome, whether the AI System is capable of detecting colorectal polyps in vivo during colonoscopy
Measured: 4 month
Secondary outcomes (1)
Diagnostic Performance of the AI System for detecting colorectal polyps
As a secondary outcome, we assess the diagnostic Performance of the AI System for detecing colorectal Polyp in real time
Measured: 4 month
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Apr 2020
- Study start1 Jan 2020
- Primary completion30 Apr 2020 (estimated)
- Study completion31 May 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 Adenoma ColonStudies 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
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 40 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Erlangen-Nürnberg Medical School
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Timo Rath, University of Erlangen-Nürnberg Medical School
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04359355
- Sponsor's protocol ID
- CAID
- Status last verified
- Apr 2020
- First submitted
- 21 Apr 2020
- Last updated
- 24 Apr 2020
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: The study will be published in scientific magazines after competion and thus will be made available to other Researchers. Individual Patient data will not be displayed or shared.
Publications
Pfeifer L, Neufert C, Leppkes M, Waldner MJ, Hafner M, Beyer A, Hoffman A, Siersema PD, Neurath MF, Rath T. Computer-aided detection of colorectal polyps using a newly generated deep convolutional neural network: from development to first clinical experience. Eur J Gastroenterol Hepatol. 2021 Dec 1;33(1S Suppl 1):e662-e669. doi: 10.1097/MEG.0000000000002209.
PubMed 34034272
Study at a glance
From the registry record, last updated by the sponsor on 24 Apr 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development and Validation of a New Artificial Intelligence System for Automated Detection of Colorectal Polyps During Colonoscopy
- ClinicalTrials.gov ID
- NCT04359355
- Acronym / sponsor ID
- CAID
- Conditions
- Adenoma Colon, Polyp of Colon
- Keywords
- colonoscopy, endoscopy, adenoma detection, polyp detection, artificial intelligence
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 40 participants (estimated)
- Lead sponsor
- University of Erlangen-Nürnberg Medical SchoolUniversity, hospital or other
- Study start
- 1 Jan 2020 (actual)
- Primary completion
- 30 Apr 2020 (estimated)
- Study completion
- 31 May 2020 (estimated)
- First posted
- 24 Apr 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.
In this observational pilot study, we assess the diagnostic performance of an artificial intelligence sytem for automated detection of colorectal polyps.
Detailed description
During standard colonoscopy, a substantial number of colorectal polyps can be missend. As shown in a recent meta-analysis, miss rates for adenomas can reach up to 26%. In this study, it is tested whether an artificial intelligence system that highlights colorectal polyps during screening or surveillance colonoscopy in real time can lead to an increased detection of colorectal polyps during the examination.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Artificial Intelligence | – | Device: Artificial Intelligence System for Detection of colorectal polyps |
Who may qualify
- Ages
- 18 to 85 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- All patients presenting between January and May 2020 for surveillance or Screening colonoscopy in the Ludwig Demling Endoscopy Center of Excellence will be prospectively included under the above mentioned inclusion and exclusion criteria. Prior to enrollment, written informed consent will be obtained.
Key inclusion criteria (1 listed)
- Screening or surveillance colonoscopy
Key exclusion criteria (3 listed)
- known or suspected inflammatory bowel disease
- uncontrolled coagulopathy
- known polyps or referral for polypectomy
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 System for Detection of colorectal polypsIn this group, an artificial Intelligence System will be used for computer-aided diagnosis of colorectal polyps. Diagnostic Performance of the artificial intelligence System for detection of polyps will be compared against Operator-based detection in the same group | Device | Artificial Intelligence |
Primary outcome
Feasibility to use the AI System in vivo during colonoscopy
Time frame: 4 month
As a Primary outcome, whether the AI System is capable of detecting colorectal polyps in vivo during colonoscopy
1 secondary outcome
Diagnostic Performance of the AI System for detecting colorectal polyps
Time frame: 4 month
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Apr 2020.
- Derived from this study: PubMed 34034272Pfeifer L, Neufert C, Leppkes M, Waldner MJ, Hafner M, Beyer A, Hoffman A, Siersema PD, Neurath MF, Rath T. Computer-aided detection of colorectal polyps using a newly generated deep convolutional neural network: from development to first clinical experience. Eur J Gastroenterol Hepatol. 2021 Dec 1;33(1S Suppl 1):e662-e669. doi: 10.1097/MEG.0000000000002209.
- Individual participant dataSharing planned: No. The study will be published in scientific magazines after competion and thus will be made available to other Researchers. Individual Patient data will not be displayed or shared.
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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.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Adenoma Colon and Polyp of Colon, run by University of Erlangen-Nürnberg Medical School at 1 site in Germany.
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 3 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 24 Apr 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 Germany. 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 Timo Rath, MD (49 9131 85 ext. 45041, timo.rath@uk-erlangen.de), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Feasibility to use the AI System in vivo during colonoscopy (time frame: 4 month). 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 NCT04359355, 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 24 Apr 2020; AzTrials last refreshed its copy on 27 Oct 2026.