MedTrace Logo

Detection of Colonic Polyps Via a Large Scale Artificial Intelligence (AI) System

NCT04693078 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 100

Last updated 2021-03-03

Study results available
· View outcomes & findings →

Summary

Colonoscopy is the gold standard for detection and removal of precancerous lesions, and has been amply shown to reduce mortality. However, the miss rate for polyps during colonoscopies is 22-28%, while 20-24% of the missed lesions are histologically confirmed precancerous adenomas. To address this shortcoming, the investigators propose a new polyp detection system based on deep learning, which can alert the operator in real-time to the presence and location of polyps during a colonoscopy. The investigators dub the system DEEP: (DEEP) DEtection of Elusive Polyps. The DEEP system was trained on 3,611 hours of colonoscopy videos derived from two sources, and was validated on a set comprising 1,393 hours of video, coming from a third, unrelated source. For the validation set, the ground truth labelling was provided by offline gastroenterologist annotators, who were able to watch the video in slow-motion and pause/rewind as required; two or three specialist annotators examined each video.

This is a prospective, non-blinded, non-randomized pilot study of patients undergoing elective screening and surveillance colonoscopies using DEEP.

The aim of the study is to:

Assess the:

1. Number of additional polyps detected by the DEEP system in real time colonoscopy.
2. Safety by prospective assessment of the rate of adverse events during the study period attributed or not to the use of the DEEP system.
3. Stability of the DEEP system by measuring the rate of false positives (False Alarms) per colonoscopies 4 And to examine its feasibility and usefulness of in clinical practice by assessing the colonoscopist user experience while using the DEEP system in a 5 point scale.

Conditions

  • Colonic Polyp

Interventions

DEVICE

AI polyp detection system based on deep learning

A Polyp detection system based on deep learning and artificial intelligence, which can alert the operator in real-time to the presence and location of polyps during a colonoscopy.

Sponsors & Collaborators

  • Google LLC.

    collaborator INDUSTRY

  • Shaare Zedek Medical Center

    lead OTHER

Study Design

Allocation
NA
Purpose
SCREENING
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
40 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2020-05-18
Primary Completion
2020-11-30
Completion
2020-12-30

Countries

  • Israel

Study Locations

More Related Trials

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04693078 on ClinicalTrials.gov