Back to resultsDevelopment and Validation of an Artificial Intelligence System for Bowel Preparation Quality Scoring
Primary Purpose
Colonic Disease
Status
Completed
Phase
Not Applicable
Locations
Korea, Republic of
Study Type
Interventional
Intervention
AI
Sponsored by
About this trial
This is an interventional health services research trial for Colonic Disease focused on measuring artificial intelligence, deep learning, bowel preparation
Eligibility Criteria
Inclusion Criteria:
- Patients aged 20-80 years undergoing elective colonoscopy
Exclusion Criteria:
- Patients received colon or rectal surgery
Sites / Locations
- National Cancer Center
Arms of the Study
Arm 1
Arm Type
Experimental
Arm Label
Artificial Intelligence assisted Scoring Group
Arm Description
Patients in this group go through colonoscopy under the AI monitoring device.
Outcomes
Primary Outcome Measures
accuracy of bowel preparation score
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.
Secondary Outcome Measures
Full Information
NCT ID
NCT04487626
First Posted
July 22, 2020
Last Updated
March 1, 2021
Sponsor
National Cancer Center, Korea
1. Study Identification
Unique Protocol Identification Number
NCT04487626
Brief Title
Development and Validation of an Artificial Intelligence System for Bowel Preparation Quality Scoring
Official Title
Development and Validation of an Artificial Intelligence System for Bowel Preparation Quality Scoring
Study Type
Interventional
2. Study Status
Record Verification Date
March 2021
Overall Recruitment Status
Completed
Study Start Date
July 1, 2020 (Actual)
Primary Completion Date
October 1, 2020 (Actual)
Study Completion Date
December 30, 2020 (Actual)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Principal Investigator
Name of the Sponsor
National Cancer Center, Korea
4. Oversight
Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
No
5. Study Description
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.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Colonic Disease
Keywords
artificial intelligence, deep learning, bowel preparation
7. Study Design
Primary Purpose
Health Services Research
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Masking
None (Open Label)
Allocation
N/A
Enrollment
100 (Actual)
8. Arms, Groups, and Interventions
Arm Title
Artificial Intelligence assisted Scoring Group
Arm Type
Experimental
Arm Description
Patients in this group go through colonoscopy under the AI monitoring device.
Intervention Type
Device
Intervention Name(s)
AI
Intervention Description
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 Outcome Measure Information:
Title
accuracy of bowel preparation score
Description
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.
Time Frame
6 months
10. Eligibility
Sex
All
Minimum Age & Unit of Time
20 Years
Maximum Age & Unit of Time
80 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria:
Patients aged 20-80 years undergoing elective colonoscopy
Exclusion Criteria:
Patients received colon or rectal surgery
Facility Information:
Facility Name
National Cancer Center
City
Goyang-si
State/Province
Gyeonggi-do
ZIP/Postal Code
410-769
Country
Korea, Republic of
12. IPD Sharing Statement
Plan to Share IPD
No
Learn more about this trial
Development and Validation of an Artificial Intelligence System for Bowel Preparation Quality Scoring
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