AI for Colorectal Polyp Detection in Endoscopy

Focus of the Study is to Evaluate a New Developed Deep-learning Computer-aided Detection System in Combination With LCI for Colorectal Polyp Detection Clinical Trial

Official title:

Artificial Intelligence Combined With LCI for Colorectal Polyp Detection

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT04339855
• Other study ID #: HN_01KR7Zt
• Status: Active, not recruiting
• Start date: February 1, 2019
• Est. completion date: September 30, 2020

Study information

• Verified date: September 2020
• Source: Johannes Gutenberg University Mainz
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Linked color imaging (LCI) has shown its effectiveness in multiple randomized controlled trials for enhanced colorectal polyp detection. Most recently, artificial intelligence (AI) with deep learning through convolutional neural networks has dramatically improved and is increasingly recognized as a promising new technique enhancing colorectal polyp detection. Study aim was to evaluate a new developed deep-learning computer-aided detection (CAD) system in combination with LCI for colorectal polyp detection.

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 600
• Est. completion date: September 30, 2020
• Est. primary completion date: August 31, 2020
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Full endoscopy withdrawal videos with LCI of patients ondergoing screening or surveillance endoscopy

Exclusion Criteria:

• non adequate bowel preparation

• no full length withdrawal in LCI mode

Related Conditions & MeSH terms

• Focus of the Study is to Evaluate a New Developed Deep-learning Computer-aided Detection System in Combination With LCI for Colorectal Polyp Detection
• Polyps

Intervention

Other:
• CAD with LCI for colorectal polyp detection
Polyps within fully recorded endoscopy videos with LCI mode, covering the whole spectrum of adenomatous histology, are used to evaluate the efficacy of CAD with LCI for polyp detection.

Locations

Country	Name	City	State
Germany	University Hospital Mainz	Mainz

Sponsors (1)

Lead Sponsor	Collaborator
Johannes Gutenberg University Mainz

Country where clinical trial is conducted

Germany, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Colorectal polyp detection rate in comparison to traditional detection rate		2019-2020