Health TrialsbyHealthPanel

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

ConditionsColonic PolypColon Adenoma
Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorWuerzburg University Hospital

About this trial

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.

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

Physicians with or without experience in colonoscopy

Disqualifiers

None

Trial design

Design model

Parallel

Treatments tested in this trial

  • Lutetia Training Plattform - real images

    Other intervention

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

  • Lutetia Training Plattform - artifical images

    Other intervention

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

Treatment groups

70 Participants
are divided into 2 treatment groups
Group A: Training with real imagesActive comparator 1 intervention
Group B: Training with artificial imagesExperimental treatment 1 intervention

Trial outcomes

Primary outcomes

1

Accuracy for Paris classification

Ability to correctly classify colonic polyps using the Paris classification

Time frame
9 months

Secondary outcomes

1

Range of misclassifications for Paris classification

Number of misclassification categorizes (eg 1-4)

Time frame
9 months
2

Influence of endoscopy experience on accuracy for correct Paris classification

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

Time frame
9 months
3

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

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

Time frame
9 months
4

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

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

Time frame
9 months

Other outcomes

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

Wuerzburg University Hospital

Lead sponsor

Source ClinicalTrials.gov
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