- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT03908645
Development and Validation of a Deep Learning Algorithm for Bowel Preparation Quality Scoring
April 8, 2019 updated by: Xiuli Zuo, Shandong University
The purpose of this study is to develop and validate the performance of an artificial intelligence(AI) assisted Boston Bowel preparation Scoring(BBPS) system for evaluation of bowel cleanness, then testify whether this new scoring system can help physicians to improve the quality control parameters of colonoscopy in clinic practice.
Study Overview
Status
Unknown
Conditions
Detailed Description
Colonoscopy is recommended as a routine examination for colorectal cancer screening.
Adequate bowel preparation is indispensable to ensure a clear vision of colonic mucosa,complete inspection of all colon segments, and furthermore improves the detection rates of small adenomas.
Thus, the adequacy of bowel preparation should be accurately evaluated and documented.
However, the accuracy of current bowel preparation quality scales greatly relies on intra-observer and inter-observer consistency for lack of objective measurements.
Recently, deep learning based on central neural networks (CNN) has shown multiple potential in computer-aided detection and computer-aided diagnose of gastrointestinal lesions.
While, no studies have been conducted to evaluate the performance of deep learning algorithm in bowel preparation quality scoring.
This study aims to train an algorithm to assess bowel preparation quality using the BBPS, and testify whether the engagement of AI can improve the quality control parameters of colonoscopy.
Study Type
Interventional
Enrollment (Anticipated)
100
Phase
- Not Applicable
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Locations
-
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Shandong
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Jinan, Shandong, China, 257000
- Qilu hosipital
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-
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
18 years to 70 years (Adult, Older Adult)
Accepts Healthy Volunteers
No
Genders Eligible for Study
All
Description
Inclusion Criteria:
• Patients aged 18-70 years undergoing afternoon colonoscopy
Exclusion Criteria:
- Known or suspected bowel obstruction, stricture or perforation
- Compromised swallowing reflex or mental status
- Severe chronic renal failure(creatinine clearance < 30 ml/min)
- Severe congestive heart failure (New York Heart Association class III or IV)
- Uncontrolled hypertension (systolic blood pressure > 170 mm Hg, diastolic blood pressure > 100 mm Hg)
- Dehydration
- Disturbance of electrolytes
- Pregnancy or lactation
- Hemodynamically unstable
- Unable to give informed consent
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
- Primary Purpose: Health Services Research
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: Single
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
---|---|
Experimental: Artificial Intelligence assisted Scoring Group
Patients in this group go through colonoscopy under the AI monitoring device.
|
After receiving standard bowel preparation regimen, patients go through colonoscopy under the AI monitoring device.
During the withdrawal process, bowel preparation quality is monitored by AI-associated scoring system.
Whenever a sub-score below 2 points is detected, endoscopist will be alarmed up to three times to wash and suck the colonic contents.
Videos will be recorded and re-evaluated by experts to determine the final BBPS score.
The withdrawal time is targeted at least 6min in accordance with colonoscopy quality practice.
All detected polyps will be removed and obtained for histological assessment, with the possible exception of diminutive(less than 5mm) rectal polyps.
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Active Comparator: Conventional Human Scoring Group
Patients in this group go through conventional colonoscopy without AI monitoring device.
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After receiving standard bowel preparation regimen, patients go through conventional colonoscopy without the AI monitoring device.
During the withdrawal process, after washing and sucking the colonic contents according to endoscopist's personal experience, bowel preparation quality is evaluated by human.
Videos will be recorded and re-evaluated by experts to determine the final BBPS score.
The withdrawal time is targeted at least 6min in accordance with colonoscopy quality practice.
All detected polyps will be removed and obtained for histological assessment, with the possible exception of diminutive(less than 5mm) rectal polyps.
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
The rate of patients achieving adequate bowel preparation in each group.
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.
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6 months
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Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Adenoma Detection Rate
Time Frame: 6 months
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The proportion of patients from whom at least one adenoma can be detected.
|
6 months
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Polyp Detection Rate
Time Frame: 6 months
|
The proportion of patients from whom at least one polyp can be detected.
|
6 months
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Actual)
December 15, 2018
Primary Completion (Anticipated)
December 15, 2019
Study Completion (Anticipated)
April 15, 2020
Study Registration Dates
First Submitted
April 8, 2019
First Submitted That Met QC Criteria
April 8, 2019
First Posted (Actual)
April 9, 2019
Study Record Updates
Last Update Posted (Actual)
April 9, 2019
Last Update Submitted That Met QC Criteria
April 8, 2019
Last Verified
April 1, 2019
More Information
Terms related to this study
Other Study ID Numbers
- 2019SDU-QILU-G001
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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