Diagnostic Performance of a Convolutional Neural Network for Diminutive Colorectal Polyp Recognition (POLAR)

Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)

Status: Completed

Conditions: Colorectal Polyp; Artificial Intelligence

Treatments: Device: CAD-CNN system

Study type: Observational

Funder types: Other

Identifiers

NCT03822390

W18_422

Details and patient eligibility

About

Rationale: Diminutive colorectal polyps (1-5mm in size) have a high prevalence and very low risk of harbouring cancer. Current practice is to send all these polyps for histopathological assessment by the pathologist. If an endoscopist would be able to correctly predict the histology of these diminutive polyps during colonoscopy, histopathological examination could be omitted and practise could become more time- and cost-effective. Studies have shown that prediction of histology by the endoscopist remains dependent on training and experience and varies greatly between endoscopists, even after systematic training. Computer aided diagnosis (CAD) based on convolutional neural networks (CNN) may facilitate endoscopists in diminutive polyp differentiation. Up to date, studies comparing the diagnostic performance of CAD-CNN to a group of endoscopists performing optical diagnosis during real-time colonoscopy are lacking.

Objective: To develop a CAD-CNN system that is able to differentiate diminutive polyps during colonoscopy with high accuracy and to compare the performance of this system to a group of endoscopist performing optical diagnosis, with the histopathology as the gold standard.

Study design: Multicentre, prospective, observational trial. Study population: Consecutive patients who undergo screening colonoscopy (phase 2)

Main study parameters/endpoints: The accuracy of optical diagnosis of diminutive colorectal polyps (1-5mm) by CAD-CNN system compared with the accuracy of the endoscopists. Histopathology is used as the gold standard.

Enrollment: 292 patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion and exclusion criteria

Phase 1A -

• Patients with one polyp subtype (based on histology)

Phase 1B Patients older than 18 years that underwent colonoscopy in one of the participating centres.

Phase 2:- Validation CAD-CNN system

Inclusion Criteria:

All patients older than 18 years old undergoing screenings colonoscopy in one of the participating centres.

Exclusion Criteria:

• Diagnosis of inflammatory bowel disease, Lynch syndrome or (serrated) polyposis syndrome.
• Boston Bowel Preparation Scale (BBPS) <2 in one of the colon segments
• Patients who are unwilling or unable to give informed consent

Trial design

292 participants in 1 patient group

Patients

Description:

Patients older than 18 years undergoing colonoscopy in one the participating centres.

Treatment:

Device: CAD-CNN system