Bowel Cancer
Conditions
Keywords
bowel, cancer, AI
Brief summary
The CESCAIL study tests the use of Artificial Intelligence (AI) on a video taken from a minimally-invasive imaging device, to improve efficiency and accuracy of the detection of polyps, which are little outgrowths within the lining of the bowel.
Detailed description
Participants will be continuing to follow their standard care pathway, and there are no additional requirements of the participants other than providing consent for their pseudonymised capsule video and data to be used to test the AI system. The participant's final diagnosis will only be determined by the clinician's standard analysis pathway and not influenced by the AI enabled analysis pathway. All data is de-identified before a video is created and re-identified only once the standard final report is signed-off by the referring clinician. Therefore, the risk of patient harm due to exposed data is minimised.
Interventions
None listed
Sponsors
University Hospitals Coventry and Warwickshire NHS Trust
University of Barcelona
Study design
Observational model
OTHER
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Aged 18 or over * Patients who have been selected by overseeing clinician meeting NHS England criteria to undergo colon capsule endoscopy as part of their standard of care
Exclusion criteria
* Patients unable to provide consent to take part in the study
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Sensitivity and specificity of polyp detection in AI enabled CCE reporting | 11 months | Sensitivity and specificity of polyp detection in AI enabled CCE reporting |
| Time taken to read video by clinicians and AI tool | 11 months | Time taken to read video by clinicians and AI tool |
Countries
United Kingdom
Outcome results
None listed