AI for Colorectal Polyp Detection in Endoscopy

Johannes Gutenberg University (JGU)

Status: Unknown

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

Treatments: Other: CAD with LCI for colorectal polyp detection

Study type: Observational

Funder types: Other

Identifiers

NCT04339855

HN_01KR7Zt

Details and patient eligibility

About

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.

Enrollment: 600 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

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