EligibleTrials

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

Recruiting · NCT07111715 · Observational (researchers observe without assigning treatment) · Lead sponsor: Fondazione Poliambulanza Istituto Ospedaliero

View the official record on ClinicalTrials.gov →
Crohn's disease

Interventions studied

Small bowel Video Capsule Endoscopy (VCE) using an Capsule System equipped with a Deep Neural Network based system called SmartScan (SC),

What this trial is about

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.

Who can take part

Age range
18 Years to 75 Years
Sex
All (male and female)
Healthy volunteers
No - a diagnosis or condition is required
Phase
Not specified
Study type
Observational (researchers observe without assigning treatment)

Inclusion criteria

Exclusion criteria

Where it is running

1 location listed.

Read the full protocol, contacts and eligibility on ClinicalTrials.gov →

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