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Comparison Between Artificial Intelligence and Standard Reading to Investigate Suspected Crohn Disease: the SCAI STUDY
Sponsor: Fondazione Poliambulanza Istituto Ospedaliero
Summary
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.
Official title: Comparison Between Artificial Intelligence Assisted Capsule Endoscopy and Standard Reading to Investigate Suspected Crohn Disease: the SCAI STUDY
Key Details
Gender
All
Age Range
18 Years - 75 Years
Study Type
OBSERVATIONAL
Enrollment
180
Start Date
2025-07-21
Completion Date
2028-12-31
Last Updated
2025-08-08
Healthy Volunteers
No
Conditions
Interventions
Small bowel Video Capsule Endoscopy (VCE) using an Capsule System equipped with a Deep Neural Network based system called SmartScan (SC),
Small 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.
Locations (1)
Fondazione Poliambulanza Istituto Ospedaliero
Brescia, Italy