Computer-aided Detection of Colorectal Polyps

April 21, 2020 updated by: Timo Rath, University of Erlangen-Nürnberg Medical School

Development and Validation of a New Artificial Intelligence System for Automated Detection of Colorectal Polyps During Colonoscopy

In this observational pilot study, we assess the diagnostic performance of an artificial intelligence sytem for automated detection of colorectal polyps.

Study Overview

Status

Unknown

Conditions

Intervention / Treatment

Detailed Description

During standard colonoscopy, a substantial number of colorectal polyps can be missend. As shown in a recent meta-analysis, miss rates for adenomas can reach up to 26%. In this study, it is tested whether an artificial intelligence system that highlights colorectal polyps during screening or surveillance colonoscopy in real time can lead to an increased detection of colorectal polyps during the examination.

Study Type

Observational

Enrollment (Anticipated)

40

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • Germany
      • Erlangen, Germany, 91054
        • Recruiting
        • University Hospital Erlangen
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 85 years (Adult, Older Adult)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

All patients presenting between January and May 2020 for surveillance or Screening colonoscopy in the Ludwig Demling Endoscopy Center of Excellence will be prospectively included under the above mentioned inclusion and exclusion criteria. Prior to enrollment, written informed consent will be obtained.

Description

Inclusion Criteria:

  • Screening or surveillance colonoscopy

Exclusion Criteria:

  • known or suspected inflammatory bowel disease
  • uncontrolled coagulopathy
  • known polyps or referral for polypectomy

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Artificial Intelligence
Device: Artificial Intelligence System for Detection of colorectal polyps
In this group, an artificial Intelligence System will be used for computer-aided diagnosis of colorectal polyps. Diagnostic Performance of the artificial intelligence System for detection of polyps will be compared against Operator-based detection in the same group

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Feasibility to use the AI System in vivo during colonoscopy
Time Frame: 4 month
As a Primary outcome, whether the AI System is capable of detecting colorectal polyps in vivo during colonoscopy
4 month

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Diagnostic Performance of the AI System for detecting colorectal polyps
Time Frame: 4 month
As a secondary outcome, we assess the diagnostic Performance of the AI System for detecing colorectal Polyp in real time
4 month

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

University of Erlangen-Nürnberg Medical School

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 1, 2020

Primary Completion (Anticipated)

April 30, 2020

Study Completion (Anticipated)

May 31, 2020

Study Registration Dates

First Submitted

April 21, 2020

First Submitted That Met QC Criteria

April 21, 2020

First Posted (Actual)

April 24, 2020

Study Record Updates

Last Update Posted (Actual)

April 24, 2020

Last Update Submitted That Met QC Criteria

April 21, 2020

Last Verified

April 1, 2020

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • CAID

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

The study will be published in scientific magazines after competion and thus will be made available to other Researchers. Individual Patient data will not be displayed or shared.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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