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NCT Number: NCT06550908

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

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.

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Key information

Conditions

Colonic Polyp Colon Adenoma Colonic Polyps Intestinal Polyps Pathological Conditions, Anatomical Pathological Conditions, Signs and Symptoms Polyps

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Physicians with or without experience in colonoscopy

Treatment and study plan

Lutetia Training Plattform - real images

Other

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

Lutetia Training Plattform - artifical images

Other

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

Primary outcomes

  1. Accuracy for Paris classification

    Time frame: 9 months

    Ability to correctly classify colonic polyps using the Paris classification

Secondary outcomes

  1. Range of misclassifications for Paris classification

    Time frame: 9 months

    Number of misclassification categorizes (eg 1-4)

  2. Influence of endoscopy experience on accuracy for correct Paris classification

    Time frame: 9 months

    Influence of endoscopy experience measured in number of perfomed colonoscopies on accuracy for correct Paris classification

  3. Influence of time to complete course on accuracy for correct Paris classification

    Time frame: 9 months

    Influence of time to complete course measured in days on accuracy for correct Paris classification

  4. Influence regular usage of Paris classification on accuracy for correct Paris classification

    Time frame: 9 months

    Influence regular usage of Paris classification (yes/no) on accuracy for correct Paris classification

Study contacts

Contact information is provided by the study sponsor or research team.

Alexander Hann, MD

CONTACT

[email protected]

0049931201 ext. 45918

Ronja Weber

CONTACT

[email protected]

0049931201 ext. 40242

Sponsors and collaborators

Lead sponsor

Wuerzburg University Hospital

Other

Registry information

Acronym: LUTETIA2

Important dates

Study start
2025
Primary completion
2025
Study completion
2025
First posted
Aug 13, 2024
Registry last updated
Aug 12, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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