Endoscopic Severity Image Recognition to Advance Research and Training in Inflammatory Bowel Disease (EVEREST - IBD)

NHS Trust

Status

Enrolling

Conditions

Inflammatory Bowel Disease 1

Study type

Observational

Funder types

Other

Identifiers

NCT04867408

299614

Details and patient eligibility

About

To develop and train a convolutional neural network to detect and characterize disease severity of inflammatory bowel disease during endoscopy

Full description

To develop and train a Convolutional Neural Network to detect and characterize disease severity in inflammatory bowel disease during endoscopy. This initiative will inevitably establish a high-quality large image database. Our secondary study aims are therefore to use the images we collect to advance the field of deep learning and computer aided diagnosis in inflammatory bowel disease by establishing an image database. This will involve developing a framework combining deep learning and computer vision algorithms. The ultimate aim is to use the image database to produce high impact research outcomes and training resources leading to an improvement in the quality of endoscopy performed, reduce inter-observer variability in disease assessment and a reduction in missed bowel cancer rates and associated mortality.

Enrollment

4,000 estimated patients

Sex

All

Ages

16 to 99 years old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

• Any adult patient aged 16 years or older who has consented to undergo endoscopic investigation where images are captured as part of routine clinical care.

Exclusion criteria

• Any patient under the age of 16
- Patients who are unable to give informed consent to undergo endoscopic investigation or those who do not wish their pseudo-anonymised images to be used