Crohn Disease Clinical Trial
Official title:
Development of New Diagnostic Tools in Capsule Endoscopy
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.
Capsule endoscopy is a minimally-invasive diagnostic procedure based on the ingestion (or endoscopic delivery) of a miniaturized biocompatible, camera. Capsules capture tenths of thousands images of the digestive tract. Reading the captured images and reporting is long, tedious, and at risk of errors when the reader's attention is disturbed. Artificial intelligence is expected to alleviate these limitations, by both improving diagnostic performances of capsule endoscopy while reducing reading time. Any patient in whom a capsule endoscopy examination is performed as part of routine care will be invited to participate to the study. Their de-identified images and videos will be extracted, thus allowing the creation of several databases for training, tuning and testing technological bricks of artificial intelligence. Basic clinical data will be collected (age, gender, indication for capsule endoscopy, type of device, ingestion or delivery of capsule). Images and videos will be characterized centrally and consensually by a panel of 3 expert readers, according to their level of relevance in relation to the type and indication of capsule endoscopy. The various, developed technological bricks will aim to automatically detect and characterize anatomical landmarks and abnormal findings, and to quote the intestine cleanliness. Assessment of diagnostic performance and reading time will be performed within a few months or up to five years, for each technological brick, individually and then combined, according to their stepwise development. ;
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