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

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.

Completed

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Key information

Conditions

Colonic Disease Colonic Diseases Digestive System Diseases Gastrointestinal Diseases Intestinal Diseases

Age range

20 year–80 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

National Cancer Center

Goyang-si, Gyeonggi-do, 410-769, South Korea

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

Patients aged 20-80 years undergoing elective colonoscopy

Exclusion criteria

Patients received colon or rectal surgery

Treatment and study plan

AI

Device

After taking standard bowel preparation regimen, patients receive colonoscopy under the AI system device. During the withdrawal phase, bowel preparation quality is assessed by AI-associated scoring system. The withdrawal time is targeted at least 6min. Every detected polyp will be removed and obtained for pathological assessment.

Primary outcomes

accuracy of bowel preparation score

Time frame: 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.

Sponsors and collaborators

Lead sponsor

National Cancer Center, Korea

Other Gov

Registry information

Important dates

Study start: 2020
Primary completion: 2020
Study completion: 2020
First posted: Jul 27, 2020
Registry last updated: Mar 3, 2021

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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Completed