The diagnosis of Crohn's Disease (CD) is based on a combination of clinical, biochemical (serological and fecal), endoscopic, radiological, and histological investigations. In the absence of obstructive symptoms or known stenosis, European guidelines recommend to investigate the small intestine using Video Capsule Endoscopy (VCE) if ileocolonoscopy is not decisive. To reduce the reading time of VCE and increase the number of identified lesions during the examination, various artificial intelligence software/tools have been developed in recent decades. This study aims to be the first prospective multicentric real-life trial to evaluate AI-assisted VCE using SmartScan in identifying typical mucosal abnormalities of the small intestine in patients with suspected CD and its ability to reduce reading time while maintaining the same diagnostic yield and diagnostic accuracy of standard reading. The objective of the study is to evaluate the role of AI-assisted VCE using the OMOM SmartScan in detecting typical small bowel inflammatory lesions (i.e. erosions and ulcers) in patients with suspected CD, and comparing AI with standard reading.
Age >= 18 and <= 75 years
Clinical suspicion of Crohn's Disease (CD) with/without occlusive symptoms
Ileocolonoscopy: negative examination, aspecific inflammatory findings
Signed informed consent form
Known diagnosis of CD
Endoscopic diagnosis of active diverticular disease, colorectal cancer, ulcerative colitis, or infectious colitis, microscopic colitis
Positive stool tests for pathogenic bacteria, Yersinia enterocolitica, parasites, C. difficile infection, fecal antigen for Giardia lamblia within 6 months before VCE
Known intestinal obstruction or unconfirmed small bowel patency
Eligible patients for the study are those with clinical symptoms and laboratory results suggestive of CD who have previously undergone an ileocolonoscopy which excluded other organic pathology and/or resulted inconclusive for CD (aspecific terminal ileitis).
Cohort
Prospective
Small bowel Video Capsule Endoscopy (VCE) using an Capsule System equipped with a Deep Neural Network based system called SmartScan (SC),
DeviceSmall bowel Video Capsule Endoscopy (VCE) will be performed using the an Capsule System equipped with a Deep Neural Network based system called SmartScan (SC), which is able to automatically select suspected lesions thus creating a very short video constituted only by selected images.
Diagnostic yield (DY)
Non-inferiority of AI-assisted reading (AIR) compared to standard reading (SR) in detecting (diagnostic yield - DY) typical lesions of suspected CD (erosions and/or ulcers and/or stenosis).
VCE reading time
Small bowel reading time of video capsule endoscopy in two setting: Artificial Intelligence Reading and in Standard Reading
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