Computer-aided Detection of Colorectal Polyps

• Sponsor: University of Erlangen-Nürnberg Medical School (Other)
• Overall Status: Unknown status
• CT.gov ID: NCT04359355
• Collaborator: (none)
• Enrollment: 40
• Location: 1
• Anticipated Duration (Months): 5
• Patients Per Site Per Month: 8.1

Study Details

Study Description

Brief Summary

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

Condition or Disease	Intervention/Treatment	Phase
Adenoma Colon; Polyp of Colon	Device: Artificial Intelligence System for Detection of colorectal polyps

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 Design

• Study Type: Observational
• Anticipated Enrollment: 40 participants
• Observational Model: Cohort
• Time Perspective: Prospective
• Official Title: Development and Validation of a New Artificial Intelligence System for Automated Detection of Colorectal Polyps During Colonoscopy
• Actual Study Start Date: Jan 1, 2020
• Anticipated Primary Completion Date: Apr 30, 2020
• Anticipated Study Completion Date: May 31, 2020

Arms and Interventions

Arm	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

Outcome Measures

Primary Outcome Measures

1. Feasibility to use the AI System in vivo during colonoscopy [4 month]

   As a Primary outcome, whether the AI System is capable of detecting colorectal polyps in vivo during colonoscopy

Secondary Outcome Measures

1. Diagnostic Performance of the AI System for detecting colorectal polyps [4 month]

   As a secondary outcome, we assess the diagnostic Performance of the AI System for detecing colorectal Polyp in real time

Eligibility Criteria

Criteria

• Ages Eligible for Study: 18 Years to 85 Years
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: Yes

Inclusion Criteria:

• Screening or surveillance colonoscopy

Exclusion Criteria:

• known or suspected inflammatory bowel disease

• uncontrolled coagulopathy

• known polyps or referral for polypectomy

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	University Hospital Erlangen	Erlangen		Germany	91054

Sponsors and Collaborators

• University of Erlangen-Nürnberg Medical School

Investigators

None specified.

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

• Responsible Party: Timo Rath, Professor of Endoscopy, University of Erlangen-Nürnberg Medical School
• ClinicalTrials.gov Identifier: NCT04359355
• Other Study ID Numbers: CAID
• First Posted: Apr 24, 2020
• Last Update Posted: Apr 24, 2020
• Last Verified: Apr 1, 2020

• Individual Participant Data (IPD) Sharing Statement: No
• Plan to Share IPD: No
• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No
• Keywords provided by Timo Rath, Professor of Endoscopy, University of Erlangen-Nürnberg Medical School: colonoscopy; endoscopy; adenoma detection; polyp detection; artificial intelligence
• Additional relevant MeSH terms: Adenoma; Polyps; Colonic Polyps

Study Results

No Results Posted as of Apr 24, 2020