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

Not Applicable

Not yet recruiting

• Conditions: Colon Adenoma; Colonic Polyp
• Interventions: Other: Lutetia Training Plattform

• Registration Number: NCT06550908
• Lead Sponsor: Wuerzburg University Hospital

Brief 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. We want to use artificial intelligence (AI) to better train doctors to recognise these precursors. By using generative AI, we 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 we want to train physicians using real images or artificial images in order to compare which version helps classify polyps better.

Detailed Description

Not available

Study Timeline

• Status Verified: 2024-08
• Study First Submitted: 2024-08-08
• Study First Submitted QC: 2024-08-08
• Last Update Submitted: 2024-08-08
• Study First Posted: 2024-08-13
• Last Update Posted: 2024-08-13
• Study Start: 2024-09
• Primary Completion: 2025-07
• Study Completion: 2025-07

Recruitment & Eligibility

• Status: NOT_YET_RECRUITING
• Sex: All
• Target Recruitment: 70

Inclusion Criteria

• Physicians with or without experience in colonoscopy

Exclusion Criteria

Not provided

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Arm && Interventions

Group	Intervention	Description
Training with real images	Lutetia Training Plattform	Physicians train using the Paris classification with real colon polyp images
Training with artificial images	Lutetia Training Plattform	Physicians train using the Paris classification with artificial colon polyp images

Primary Outcome Measures

Name	Time	Method
Accuracy for Paris classification	9 months	Ability to correctly classify colonic polyps using the Paris classification

Secondary Outcome Measures

Name	Time	Method
Influence regular usage of Paris classification on accuracy for correct Paris classification	9 months	Influence regular usage of Paris classification (yes/no) on accuracy for correct Paris classification
Range of misclassifications for Paris classification	9 months	Number of misclassification categorizes (eg 1-4)
Influence of endoscopy experience on accuracy for correct Paris classification	9 months	Influence of endoscopy experience measured in number of perfomed colonoscopies on accuracy for correct Paris classification
Influence of time to complete course on accuracy for correct Paris classification	9 months	Influence of time to complete course measured in days on accuracy for correct Paris classification