Training Physicians to Differentiate the Paris Classification Using Artificial Colon Polyp Images

NCT ID: NCT06550908

Last Updated: 2025-08-12

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Clinical Phase

NA

Total Enrollment

70 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-04-15

Study Completion Date

2025-08-31

Brief Summary

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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 train physicians using real images or artificial images in order to compare which version helps classify polyps better.

Detailed Description

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Conditions

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Colonic Polyp Colon Adenoma

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

BASIC_SCIENCE

Blinding Strategy

NONE

Study Groups

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Training with real images

Physicians train using the Paris classification with real colon polyp images

Group Type ACTIVE_COMPARATOR

Lutetia Training Plattform - real images

Intervention Type OTHER

Training platform Lutetia offers training the Paris classification using real images of colon polyps.

Training with artificial images

Physicians train using the Paris classification with artificial colon polyp images

Group Type EXPERIMENTAL

Lutetia Training Plattform - artifical images

Intervention Type OTHER

Training platform Lutetia offers training the Paris classification using artificial images of colon polyps.

Interventions

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Lutetia Training Plattform - real images

Training platform Lutetia offers training the Paris classification using real images of colon polyps.

Intervention Type OTHER

Lutetia Training Plattform - artifical images

Training platform Lutetia offers training the Paris classification using artificial images of colon polyps.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Physicians with or without experience in colonoscopy
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Wuerzburg University Hospital

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Alexander Hann

Role: PRINCIPAL_INVESTIGATOR

Wuerzburg University Hospital

Locations

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University hospital Würzburg

Würzburg, , Germany

Site Status RECRUITING

Countries

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Germany

Central Contacts

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Alexander Hann, MD

Role: CONTACT

0049931201 ext. 45918

Ronja Weber

Role: CONTACT

0049931201 ext. 40242

Facility Contacts

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Prof. Dr. med. Hann

Role: primary

+49 931 201 45918

Other Identifiers

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2022120701-2

Identifier Type: -

Identifier Source: org_study_id

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