Computer-aided Detection of Colorectal Polyps
Development and Validation of a New Artificial Intelligence System for Automated Detection of Colorectal Polyps During Colonoscopy
1 other identifier
observational
40
1 country
1
Brief Summary
In this observational pilot study, we assess the diagnostic performance of an artificial intelligence sytem for automated detection of colorectal polyps.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P25-P50 for all trials
Started Jan 2020
Shorter than P25 for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
Study Start
First participant enrolled
January 1, 2020
CompletedFirst Submitted
Initial submission to the registry
April 21, 2020
CompletedFirst Posted
Study publicly available on registry
April 24, 2020
CompletedPrimary Completion
Last participant's last visit for primary outcome
April 30, 2020
CompletedStudy Completion
Last participant's last visit for all outcomes
May 31, 2020
CompletedApril 24, 2020
April 1, 2020
4 months
April 21, 2020
April 21, 2020
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Feasibility to use the AI System in vivo during colonoscopy
As a Primary outcome, whether the AI System is capable of detecting colorectal polyps in vivo during colonoscopy
4 month
Secondary Outcomes (1)
Diagnostic Performance of the AI System for detecting colorectal polyps
4 month
Study Arms (1)
Artificial Intelligence
Interventions
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
Eligibility Criteria
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.
You may qualify if:
- Screening or surveillance colonoscopy
You may not qualify if:
- known or suspected inflammatory bowel disease
- uncontrolled coagulopathy
- known polyps or referral for polypectomy
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
University Hospital Erlangen
Erlangen, 91054, Germany
Related Publications (1)
Pfeifer L, Neufert C, Leppkes M, Waldner MJ, Hafner M, Beyer A, Hoffman A, Siersema PD, Neurath MF, Rath T. Computer-aided detection of colorectal polyps using a newly generated deep convolutional neural network: from development to first clinical experience. Eur J Gastroenterol Hepatol. 2021 Dec 1;33(1S Suppl 1):e662-e669. doi: 10.1097/MEG.0000000000002209.
PMID: 34034272DERIVED
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Professor of Endoscopy
Study Record Dates
First Submitted
April 21, 2020
First Posted
April 24, 2020
Study Start
January 1, 2020
Primary Completion
April 30, 2020
Study Completion
May 31, 2020
Last Updated
April 24, 2020
Record last verified: 2020-04
Data Sharing
- IPD Sharing
- Will not share
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.