Colon PolypLUTETIA1NCT07108569
Ability of Physicians to Distinguish Real From Artificial Colon Polyp Images
A study testing Lutetia in people with Colon Polyp and Colonic Adenoma, run by Wuerzburg University Hospital at 1 site in Germany.
Trial summary
Training in endoscopy is essential for the early detection of precursors of colorectal cancer. Up to now, this training has been carried out with image collections of findings and in practice when working on patients. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Colon Polyp, Colonic Adenoma
- What is being tested?
- Lutetia
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 53 participants
- Where
- 1 siteGermany
- Study dates
- 6 Nov 2024to 1 Feb 2025
- 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 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Physicians with or without experience in colonoscopy
Who cannot join
None listed.
Trial locations and contacts
1 site in 1 country.
About this study
Training in endoscopy is essential for the early detection of precursors of colorectal cancer. Up to now, this training has been carried out with image collections of findings and in practice when working on patients.
The investigators want to use artificial intelligence (AI) to better train doctors to recognise these precursors. By using generative AI, the investigators were able to create realistic images that comply with data protection regulations and whose content can be predefined. Parts of the image can also be regenerated so that it is possible to create different precancerous stages in the same place in the image.
In this study the investigators want to identify the ability of physicians to distinguish artificial from real polyp images.
- Conditions
- Colon Polyp, Colonic Adenoma
- Being tested
- Lutetia
- Keywords
- Colonoscopy
- Medical subject headings
- Colonic Polyps
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
LutetiaOther
Lutetia is an AI-based training plattform
| Study group | Role | What they receive |
|---|---|---|
| Image assessment | Experimental | Physicians judge whether the random image presented to them is real or artificial Receives: Other: Lutetia |
What is being measured
The primary outcome is the main question the study is designed to answer.
Ability to detect artificial images as artificial
The ability to recognise artificial images as being artificial, using an online questionnaire - binary question
Measured: 6 months
Secondary outcomes (2)
Ability to detect real images as real
The ability to recognise real images as being real using an online questionnaire - binary question
Measured: 6 months
Accuracy to correctly classify images
Accuracy to correctly classify images using an online questionnaire
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 posted7 Aug 2025
- Study start6 Nov 2024
- Primary completion1 Feb 2025
- Study completion1 Feb 2025
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 Colon PolypStudies 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
- Basic science
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 53 participants (actual)
Sponsor and investigators
- Lead sponsor
- Wuerzburg University Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Alexander Hann, MD, Principal investigator, Wuerzburg University Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07108569
- Sponsor's protocol ID
- 2022120701
- Acronym
- LUTETIA1
- Status last verified
- Aug 2025
- First submitted
- 8 Aug 2024
- Last updated
- 7 Aug 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Sodmann P, Weber R, Wettstein V, Kafetzis I, Chiang Y, Parayitam V, Pauletti M, Kouladouros K, Meining A, Hann A. Assessing realism of artificial intelligence-generated colorectal polyp images: International multicenter blinded reader study. Endosc Int Open. 2026 May 15;14:a28653480. doi: 10.1055/a-2865-3480. eCollection 2026.
PubMed 42344396
Study at a glance
From the registry record, last updated by the sponsor on 7 Aug 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Ability of Physicians to Distinguish Real From Artificial Colon Polyp Images
- ClinicalTrials.gov ID
- NCT07108569
- Acronym / sponsor ID
- LUTETIA1 / 2022120701
- Conditions
- Colon Polyp, Colonic Adenoma
- Keywords
- Colonoscopy
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 53 participants (actual)
- Lead sponsor
- Wuerzburg University HospitalUniversity, hospital or other
- Study start
- 6 Nov 2024 (actual)
- Primary completion
- 1 Feb 2025 (actual)
- Study completion
- 1 Feb 2025 (actual)
- First posted
- 7 Aug 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.
Training in endoscopy is essential for the early detection of precursors of colorectal cancer. Up to now, this training has been carried out with image collections of findings and in practice when working on patients.
The investigators want to use artificial intelligence (AI) to better train doctors to recognise these precursors. By using generative AI, the investigators were able to create realistic images that comply with data protection regulations and whose content can be predefined. Parts of the image can also be regenerated so that it is possible to create different precancerous stages in the same place in the image.
In this study the investigators want to identify the ability of physicians to distinguish artificial from real polyp images.
Study design
- Primary purpose
- Basic science
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Image assessment | Experimental | Other: LutetiaPhysicians judge whether the random image presented to them is real or artificial |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (1 listed)
- Physicians with or without experience in colonoscopy
Key exclusion criteria (0 listed)
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 |
|---|---|---|
| LutetiaLutetia is an AI-based training plattform | Other | Image assessment |
Primary outcome
Ability to detect artificial images as artificial
Time frame: 6 months
The ability to recognise artificial images as being artificial, using an online questionnaire - binary question
2 secondary outcomes
Ability to detect real images as real
Time frame: 6 months
Accuracy to correctly classify images
Time frame: 6 months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 7 Aug 2025.
- Derived from this study: PubMed 42344396Sodmann P, Weber R, Wettstein V, Kafetzis I, Chiang Y, Parayitam V, Pauletti M, Kouladouros K, Meining A, Hann A. Assessing realism of artificial intelligence-generated colorectal polyp images: International multicenter blinded reader study. Endosc Int Open. 2026 May 15;14:a28653480. doi: 10.1055/a-2865-3480. eCollection 2026.
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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.
Alexander Hann, MD principal investigator
Wuerzburg University Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Lutetia in people with Colon Polyp and Colonic Adenoma, run by Wuerzburg University Hospital 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 0 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: finished, as of the sponsor's last update on 7 Aug 2025. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Ability to detect artificial images as artificial (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 NCT07108569, 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 7 Aug 2025.