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Multi-center Validation of a Deep Learning Based Bowel Preparation Evaluation System

Validation of a Deep Learning Based Bowel Preparation Evaluation System: A Prospective, Multi-center, Cross-sectional Study

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT04591145
Enrollment
1400
Registered
2020-10-19
Start date
2020-10-09
Completion date
2020-12-31
Last updated
2020-10-19

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Adenoma, Bowel Preparation

Brief summary

A deep learning based system to calculate the proportion of Boston Bowel Prep Scale (BBPS) score of 0-1 during withdrawal phase has been constructed previously. This multi-center study is going to perform a prospective observational study to validate the threshold of the adequate proportion.

Detailed description

Inadequate bowel preparation is insufficient for identification of polyps greater than 5 mm. However, bowel preparation assessment involved subjectivity and uncertainty. We constructed a deep learning based system to calculate the proportion of Boston Bowel Prep Scale (BBPS) score of 0-1 during withdrawal phase and performed a prospective observational study to validate the threshold of the adequate proportion.The multi-center study is aimed to verify the extrapolation and robustness of the scoring threshold based on artificial intelligence intestinal cleanliness evaluation system explored in the early stage, and propose a more accurate and quantifiable threshold for evaluating the eligibility of intestinal preparation.

Interventions

Patient receive the standard bowel preparation strategy and routine colonoscopy

Sponsors

Hubei Hospital of Traditional Chinese Medicine
CollaboratorOTHER
Wuhan Central Hospital
CollaboratorOTHER
Wuhan Third Hospital
CollaboratorOTHER
The General Hospital of Central Theater Command
CollaboratorOTHER
The Third People's Hospital of Hubei Province
CollaboratorOTHER
Wuhan Puren Hospital
CollaboratorOTHER
Wuhan Puai Hospital
CollaboratorUNKNOWN
Tian You Hospital Affiliated to Wuhan University of Science and Technology
CollaboratorUNKNOWN
Wuhan Red Cross Hospital
CollaboratorUNKNOWN
Renmin Hospital of Wuhan University
Lead SponsorOTHER

Study design

Observational model
CASE_CROSSOVER
Time perspective
CROSS_SECTIONAL

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes

Inclusion criteria

* Male or female aged 18 years or above; * Ability to read, understand and sign informed consent forms; * The researchers believe that the subjects can understand the process of the clinical study and are willing and able to complete all the study procedures and follow-up visits to cooperate with the study procedures.

Exclusion criteria

* Patients with contraindications to colonoscopy (obstruction or perforation, severe acute inflammatory bowel disease, toxic megacolon, severe heart failure, severe heart failure, etc.); * Patients with galactosemia; * Pregnant or lactating women; * Patients used lactulose, a stimulant, or laxative within 7 days; * Patients refused to sign informed consent forms.

Design outcomes

Primary

MeasureTime frameDescription
Cleanliness assessment of different intestinal segment in the artificial intelligence system3 MonthsThe Artificial intelligence evaluates the Boston Bowel Preparation score of the ascending colon, transverse colon and descending colon in real-time, and calculates the proportion of 0-1 Score
Adenoma detection rate3 MonthsThe numerator is the number of cases of adenomas detected by colonoscopy, and the denominator is the total number of cases of patients undergoing colonoscopy.

Secondary

MeasureTime frameDescription
The mean number of adenomas per procedure3 MonthsThe numerator is the total number of polyps detected by colonoscopy, and the denominator is the total number of patients undergoing colonoscopy
Detection rate of large, small and diminutive polyps3 MonthsThe numerator was the number of patients with large (≥10 mm), small (\>5 to \<10 mm), and diminutive(≤5 mm) polyps detected by colonoscopy, and the denominator was the total number of patients receiving colonoscopy.
The mean number of large, small and diminutive polyps per procedure3 MonthsThe numerator was the number of large (≥10 mm), small (\>5 to \<10 mm), and diminutive(≤5 mm) polyps detected by colonoscopy, and the denominator was the total number of patients receiving colonoscopy.
Detection rate of large, small and diminutive adenomas3 MonthsThe numerator was the number of patients with large (≥10 mm), small (\>5 to \<10 mm), and diminutive(≤5 mm) adenomas detected by colonoscopy, and the denominator was the total number of patients receiving colonoscopy.
Advanced adenoma detection rate3 MonthsThe numerator is the number of cases of advanced adenomas detected by colonoscopy, and the denominator is the total number of cases of patients undergoing colonoscopy.
Detection rate of adenoma in different sites3 MonthsThe numerator is the number of cases of adenoma detected in the rectum, sigmoid colon, descending colon, transverse colon, ascending colon and ileocecal region during colonoscopy, and the denominator is the total number of patients undergoing colonoscopy.
The mean number of adenomas in different sites per procedure3 MonthsThe numerator is the total number of adenomas detected in the rectum, sigmoid colon, descending colon, transverse colon, ascending colon and ileocecal region during colonoscopy, and the denominator is the total number of patients undergoing colonoscopy.
Time of colonoscopic insertion/withdrawal3 MonthsThe duration of colonoscopic insertion from rectum to ileocecal valve or appendiceal opening and the duration of colonoscopic withdrawal from ileocecal valve or appendiceal opening to colonoscopy finished.
The mean number of large, small and diminutive adenomas per procedure3 MonthsThe numerator was the number of large (≥10 mm), small (\>5 to \<10 mm), and diminutive(≤5 mm) adenomas detected by colonoscopy, and the denominator was the total number of patients receiving colonoscopy.
Polyps detection rate3 MonthsThe numerator is the number of cases of polyps detected by colonoscopy, and the denominator is the total number of cases of patients undergoing colonoscopy.

Countries

China

Contacts

Primary ContactHonggang Yu, MD
yuhonggang1968@163.com+8613871281899

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026