AI-driven Narrow-band Imaging Score for Disease Assessment and Outcome Prediction in Ulcerative Colitis

Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18-75
SponsorUniversity College Cork

About this trial

This international multicentre prospective study aims to develop a new simple score using enhanced endoscopic techniques which focus on the vascular features of the colon and reliably distinguish between a quiescent and a mild inflammation in ulcerative colitis (UC). The diagnostic performance of the new score in defining disease activity/remission compared to existing endoscopic and histological scores and predict long-term clinical outcomes will be evaluated. The study also aims to adapt current artificial intelligence (AI) algorithms for enhanced endoscopic techniques to improve standardization in UC disease assessment and outcome prediction.

Eligibility criteria

Qualifiers

Adult patients aged 18 to 75 years old

Established diagnosis of UC (for at least six months in duration), independently from their active treatment

Undergoing endoscopy for disease activity assessment or cancer surveillance.

Disqualifiers

Contraindications to endoscopy (including toxic megacolon) and biopsies (including severe coagulopathy/thrombocytopenia)

Poor bowel preparation (defined as total BBPS <6 or BBPS <2 in observed segment for sigmoidoscopy)

Significant co-morbidities limiting life expectancy and conferring high risk of endoscopy

Pregnant and breast-feeding subjects

Trial design

Treatments tested in this trial

  • Colonoscopy after bowel cleansing
  • Intestinal biopsies
  • blood sampling
  • Stool
  • Clinical follow-up

Treatment groups

300 Participants
are divided into 1 treatment group

Sponsors and collaborators