Computer Aided Polyp Detection (C3PO) Trial

Purpose

Computer aided detection (CADe) algorithms have been developed to overcome human errors and assist endoscopists in detecting more polyps during colonoscopy. The aim of this study was to investigate the accuracy of the novel Pentax Discovery CADe system (Discovery-AI) against pre-recorded videos of colon polyps of various size, shape and pathology while using videos of normal colon segments as controls from two different institutes.

Condition

  • Colonic Polyp

Eligibility

Eligible Ages
Over 18 Years
Eligible Genders
All
Accepts Healthy Volunteers
No

Inclusion Criteria

  • Patients scheduled for a regular or screening colonoscopy at the institution as standard of care. - Over 18 years of age

Exclusion Criteria

  • None if they qualify based on inclusion criteria - Pregnant patients - Inmate or prisoners - Unable to provide informed consent

Study Design

Phase
Study Type
Observational
Observational Model
Cohort
Time Perspective
Prospective

Recruiting Locations

Memorial Hermann Hospital
Houston, Texas 77030
Contact:
Prithvi B Patil
713-480-1179
prithvi.b.patil@uth.tmc.edu

More Details

Status
Recruiting
Sponsor
The University of Texas Health Science Center, Houston

Study Contact

Prithvi B Patil, MS
7134801179
prithvi.b.patil@uth.tmc.edu

Detailed Description

Details regarding polyp size and location, morphology including Paris classification, optical assessment, and bowel preparation were prospectively collected and recorded in the online Redcap software. Final results of polyp histology were also collected. The video library was then independently reviewed for quality assessment by 3 experienced gastroenterologists. Videos that passed the initial quality assessment were then independently evaluated using the Discovery-AI system. Aim of the study was to evaluate overall performance of Discovery-AI system for polyps of various size, morphology and pathology utilizing a prospectively developed video library.