Development and Validation of an Artificial Intelligence System for Bowel Preparation Quality Scoring

Not Applicable

Completed

• Conditions: Colonic Disease
• Interventions: Device: AI

• Registration Number: NCT04487626
• Lead Sponsor: National Cancer Center, Korea

Brief Summary

The purpose of this study is to develop and validate the accuracy and reliability of an artificial intelligence(AI) system for bowel preparation quality scoring based of Boston Bowel preparation Scoring(BBPS). Then evaluate whether this AI system can help endoscopists to improve the quality of colonoscopy in clinical practice.

Detailed Description

Bowel preparation is one of the most important factors which decide the quality of colonoscopy. Adequate bowel preparation is essential to guarantee a clear vision of colonic mucosa, complete inspection of entire colon and improves the adenoma detection rates(ADRs). Therefore, the quality of bowel preparation should be evaluated accurately and objectively. However, current bowel preparation quality scales depend on memories and subjective decision of endoscopists. Recently, articifial intelligence system based on deep learning algorithm has been used widely in medical fields. But, few studies have been reported to evaluate the performance of AI system based on deep learning in bowel preparation quality scoring. This study aims to develop and train an AI system to assess bowel preparation quality using the BBPS, and validate the AI system to improve the quality of colonoscopy.

Study Timeline

• Study Start: 2020-07-01
• Study First Submitted: 2020-07-22
• Study First Submitted QC: 2020-07-22
• Study First Posted: 2020-07-27
• Primary Completion: 2020-10-01
• Study Completion: 2020-12-30
• Status Verified: 2021-03
• Last Update Submitted: 2021-03-01
• Last Update Posted: 2021-03-03

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 100

Inclusion Criteria

• Patients aged 20-80 years undergoing elective colonoscopy

Exclusion Criteria

• Patients received colon or rectal surgery

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: SINGLE_GROUP

Arm && Interventions

Group	Intervention	Description
Artificial Intelligence assisted Scoring Group	AI	Patients in this group go through colonoscopy under the AI monitoring device.

Primary Outcome Measures

Name	Time	Method
accuracy of bowel preparation score	6 months	Bowel preparation quality was measured by BBPS. After fully washing or suctioning of colonic contents, three segments including right colon (containing cecum and ascending colon), transvers colon (containing hepatic and splenic flexures) and left colon (containing descending and sigmoid colon) were individually scored from 0 to 3. Point 0 refers to unprepared colon segment with obscured solid stool making mucosa cannot be seen; Point 1 refers to part of mucosa can be seen, but some areas are covered by staining, residual stool, and/or opaque liquid; Point 2 refers to entire mucosa is well-seen; Point 3 refers to clean colon segment without staining, fecal materials or liquids. A sub-score of each colon segment was used, ranging from minimum 0 to maximum 3. The highest score means the excellent bowel preparation. Adequate bowel preparation was defined as a total BBPS≥6 and sub-BBPS≥2 per segment.

Trial Locations

Locations (1)

National Cancer Center; 🇰🇷 Goyang-si, Gyeonggi-do, Korea, Republic of