Comparison Between Artificial Intelligence and Standard Reading to Investigate Suspected Crohn Disease: the SCAI STUDY

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Conditions studied: Crohn Disease (CD)

In brief

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.

Key facts

Study ID
NCT07111715
Run by
Fondazione Poliambulanza Istituto Ospedaliero
People needed
180
Starts
2025-07-21
Expected to finish
2028-12-31
Last updated by the study team
2025-08-08

Who can join

Age: 18 and older, up to 75. Sex: any. Healthy volunteers: not accepted.

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Where it is running

Full record on ClinicalTrials.gov

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