Training Physicians to Differentiate the Paris Classification Using Artificial Colon Polyp Images (LUTETIA2)

Wuerzburg University Hospital

Status: Enrolling

Conditions: Colonic Polyp; Colon Adenoma

Treatments: Other: Lutetia Training Plattform - artifical images; Other: Lutetia Training Plattform - real images

Study type: Interventional

Funder types: Other

Identifiers

NCT06550908

2022120701-2

Details and patient eligibility

About

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.

Enrollment: 70 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: Accepts Healthy Volunteers

Inclusion and exclusion criteria

Inclusion Criteria:

• Physicians with or without experience in colonoscopy

Trial design

Primary purpose: Basic Science

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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70 participants in 2 patient groups

Training with real images

Active Comparator group

Description:

Physicians train using the Paris classification with real colon polyp images

Treatment:

Other: Lutetia Training Plattform - real images

Training with artificial images

Experimental group

Description:

Physicians train using the Paris classification with artificial colon polyp images

Treatment:

Other: Lutetia Training Plattform - artifical images