Development of New Diagnostic Tools in Capsule Endoscopy
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
AgeNot listed
SponsorAssistance Publique - Hôpitaux de Paris
About this trial
Patients participating to this study will provide images and videos of capsule endoscopy to train, tune and evaluate technological bricks of artificial intelligence solutions, in order to improve diagnostic performances of the procedure, while reducing reading time by physicians.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
None
Disqualifiers
None
Trial population
Any patient in whom a capsule endoscopy examination is performed as part of routine care
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Not listed
Trial groups
No trial groups listed
Trial outcomes
Primary outcomes
1
Develop an artificial intelligence solution to help with diagnosis in VCE
Sensitivity in detection of lesions of intermediate to high relevance as identified centrally and consensually by a panel of 3 expert readers (AI vs standard reading)
Time frame
Through study completion, 5 yearsSecondary outcomes
1
Evaluation of the diagnostic performance of the A.I. solution in terms of detection
Other diagnostic performance (specificity, positive and negative predictive values, accuracy) in detection of lesions of intermediate to high relevance as identified centrally and consensually by a panel of 3 expert readers (AI vs standard reading)
Time frame
Through study completion, 5 years2
Evaluation of the diagnostic performance of the A.I. solution in terms of characterisation
Time needed for detection of lesions of intermediate to high relevance as identified centrally and consensually by a panel of 3 expert readers (AI vs standard reading)
Time frame
Through study completion, 5 years3
Evaluation of the diagnostic performance of the A.I. solution in terms of recognition of anatomical landmarks
Diagnostic performances in positioning anatomical landmarks (1st gastric, small bowl and colonic images) as identified centrally and consensually by a panel of 3 expert readers (AI vs standard reading)
Time frame
Through study completion, 5 years4
Evaluation of the diagnostic performance of the A.I. solution in terms of quality of preparation of the various segments of the digestive tract
Diagnostic performances in quoting small bowel and colonic quality of preparation, as compared toed centrally and consensually quoted by a panel of 3 expert readers
Time frame
Through study completion, 5 yearsSponsors and contacts
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Source ClinicalTrials.gov