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A novel artificial intelligence system for the assessment of bowel preparation (with video)

  • Author Footnotes
    ∗ Drs Zhou, Wu, and Wan contributed equally to this article.
    Jie Zhou
    Footnotes
    ∗ Drs Zhou, Wu, and Wan contributed equally to this article.
    Affiliations
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China

    Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China

    Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
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  • Author Footnotes
    ∗ Drs Zhou, Wu, and Wan contributed equally to this article.
    Lianlian Wu
    Footnotes
    ∗ Drs Zhou, Wu, and Wan contributed equally to this article.
    Affiliations
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China

    Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China

    Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
    Search for articles by this author
  • Author Footnotes
    ∗ Drs Zhou, Wu, and Wan contributed equally to this article.
    Xinyue Wan
    Footnotes
    ∗ Drs Zhou, Wu, and Wan contributed equally to this article.
    Affiliations
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China

    Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China

    Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
    Search for articles by this author
  • Lei Shen
    Affiliations
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China

    Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China

    Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
    Search for articles by this author
  • Jun Liu
    Affiliations
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China

    Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
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  • Jun Zhang
    Affiliations
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China

    Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China

    Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
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  • Xiaoda Jiang
    Affiliations
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China

    Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China

    Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
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  • Zhengqiang Wang
    Affiliations
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China

    Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China

    Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
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  • Shijie Yu
    Affiliations
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China

    Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China

    Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
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  • Jian Kang
    Affiliations
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China

    Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China

    Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
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  • Ming Li
    Affiliations
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China

    Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China

    Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
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  • Shan Hu
    Affiliations
    School of Resources and Environmental Sciences, Wuhan University, Wuhan, China
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  • Xiao Hu
    Affiliations
    School of Resources and Environmental Sciences, Wuhan University, Wuhan, China
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  • Dexin Gong
    Affiliations
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China

    Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China

    Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
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  • Di Chen
    Affiliations
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China

    Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China

    Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
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  • Liwen Yao
    Affiliations
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China

    Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China

    Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
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  • Yijie Zhu
    Affiliations
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China

    Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China

    Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
    Search for articles by this author
  • Honggang Yu
    Correspondence
    Reprint requests: Honggang Yu, MD, Department of Gastroenterology, Renmin Hospital of Wuhan University, 99 Zhangzhidong Rd, Wuhan 430060, Hubei Province, China.
    Affiliations
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China

    Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China

    Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
    Search for articles by this author
  • Author Footnotes
    ∗ Drs Zhou, Wu, and Wan contributed equally to this article.
Published:November 26, 2019DOI:https://doi.org/10.1016/j.gie.2019.11.026

      Background and Aims

      The quality of bowel preparation is an important factor that can affect the effectiveness of a colonoscopy. Several tools, such as the Boston Bowel Preparation Scale (BBPS) and Ottawa Bowel Preparation Scale, have been developed to evaluate bowel preparation. However, understanding the differences between evaluation methods and consistently applying them can be challenging for endoscopists. There are also subjective biases and differences among endoscopists. Therefore, this study aimed to develop a novel, objective, and stable method for the assessment of bowel preparation through artificial intelligence.

      Methods

      We used a deep convolutional neural network to develop this novel system. First, we retrospectively collected colonoscopy images to train the system and then compared its performance with endoscopists via a human-machine contest. Then, we applied this model to colonoscopy videos and developed a system named ENDOANGEL to provide bowel preparation scores every 30 seconds and to show the cumulative ratio of frames for each score during the withdrawal phase of the colonoscopy.

      Results

      ENDOANGEL achieved 93.33% accuracy in the human–machine contest with 120 images, which was better than that of all endoscopists. Moreover, ENDOANGEL achieved 80.00% accuracy among 100 images with bubbles. In 20 colonoscopy videos, accuracy was 89.04%, and ENDOANGEL continuously showed the accumulated percentage of the images for different BBPS scores during the withdrawal phase and prompted us for bowel preparation scores every 30 seconds.

      Conclusions

      We provided a novel and more accurate evaluation method for bowel preparation and developed an objective and stable system—ENDOANGEL—that could be applied reliably and steadily in clinical settings.

      Graphical abstract

      Abbreviations:

      AI (artificial intelligence), BBPS (Boston Bowel Preparation Scale), DCNN (deep convolutional neural networks)
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