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Development and Validation of a Deep Learning Algorithm for Bowel Preparation Quality Scoring

NCT03908645 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 100

Last updated 2019-04-09

No results posted yet for this study

Summary

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.

Conditions

  • Bowel Preparation

Interventions

DEVICE

Artificial intelligence assisted bowel preparation quality scoring system

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.

DEVICE

Conventional human scoring

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.

Sponsors & Collaborators

  • Shandong University

    lead OTHER

Principal Investigators

  • Xiuli Zuo, MD,PhD · Qilu Hospital of Shandong University

Study Design

Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
SINGLE
Model
PARALLEL

Eligibility

Min Age
18 Years
Max Age
70 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2018-12-15
Primary Completion
2019-12-15
Completion
2020-04-15

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT03908645 on ClinicalTrials.gov