Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Jun 15;12(6):e00366.
doi: 10.14309/ctg.0000000000000366.

A Gastrointestinal Endoscopy Quality Control System Incorporated With Deep Learning Improved Endoscopist Performance in a Pretest and Post-Test Trial

Liwen Yao  1   2   3 , Jun Liu  1   2   3 , Lianlian Wu  1   2   3 , Lihui Zhang  1   2   3 , Xiao Hu  4 , Jinzhu Liu  4 , Zihua Lu  1   2   3 , Dexin Gong  1   2   3 , Ping An  1   2   3 , Jun Zhang  1   2   3 , Guiying Hu  1   2   3 , Di Chen  1   2   3 , Renquan Luo  1   2   3 , Shan Hu  4 , Yanning Yang  5 , Honggang Yu  1   2   3
Affiliations
Free PMC article

A Gastrointestinal Endoscopy Quality Control System Incorporated With Deep Learning Improved Endoscopist Performance in a Pretest and Post-Test Trial

Liwen Yao et al. Clin Transl Gastroenterol. .
Free PMC article

Abstract

Introduction: Gastrointestinal endoscopic quality is operator-dependent. To ensure the endoscopy quality, we constructed an endoscopic audit and feedback system named Endo.Adm and evaluated its effect in a form of pretest and posttest trial.

Methods: Endo.Adm system was developed using Python and Deep Convolutional Neural Ne2rk models. Sixteen endoscopists were recruited from Renmin Hospital of Wuhan University and were randomly assigned to undergo feedback of Endo.Adm or not (8 for the feedback group and 8 for the control group). The feedback group received weekly quality report cards which were automatically generated by Endo.Adm. We then compared the adenoma detection rate (ADR) and gastric precancerous conditions detection rate between baseline and postintervention phase for endoscopists in each group to evaluate the impact of Endo.Adm feedback. In total, 1,191 colonoscopies and 3,515 gastroscopies were included for analysis.

Results: ADR was increased after Endo.Adm feedback (10.8%-20.3%, P < 0.01, <odds ratio (OR) 2.13, 95% confidence interval (CI) 1.317-3.447), and endoscopists' ADR without feedback remained nearly unchanged (10.8%-10.9%, P = 0.57, OR 1.086, 95% CI 0.814-1.447). Gastric precancerous conditions detection rate increased in the feedback group (3%-7%, P < 0.01, OR 1.866, 95% CI 1.399-2.489) while no improvement was observed in the control group (3.9%-3.5%, P = 0.489, OR 0.856, 95% CI 0.550-1.332).

Discussion: Endo.Adm feedback contributed to multifaceted gastrointestinal endoscopic quality improvement. This system is practical to implement and may serve as a standard model for quality improvement in routine work (http://www.chictr.org.cn/, ChiCTR1900024153).

PubMed Disclaimer

Conflict of interest statement

Guarantor of the article: Honggang Yu, MD.

Specific author contributions: Liwen Yao and Jun Liu, and Yanning Yang and Honggang Yu contributed equally to this work. H.G.Y. and Y.Y.N.: conceived and designed the study; J.Z.L., S.H., and X.H.: trained and tested the models; G.Y.H., J.L., L.W.Y., L.L.W., and R.Q.L.: collected and reviewed images; Z.H.L., D.X.G., L.H.Z., D.H., and L.W.Y.: collected, collated, and analyzed the data; L.W.Y.: wrote the manuscript; J.Z. and P.A.: performed extensive editing of the manuscript; all authors reviewed and approved the final manuscript for submission. All authors were involved in data acquisition, general design of the trial, interpretation of the data, and critical revision of the manuscript.

Financial support: This work was partly supported by the grant from Project of Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision (grant no. 2018BCC337); Hubei Province Major Science and Technology Innovation Project (grant no. 2018-916-000-008); and the National Natural Science Foundation of China (grant no. 81770899). The funder had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Potential competing interests: The authors declared no conflict of interest. The coauthor lists do not include endoscopists who participated in the clinical trial.

Figures

Figure 1.
Figure 1.
Technical flowchart of Endo.Adm system. Three DCNN models (DCNN1, DCNN2, and DCNN3) and 2 data interfaces were used for constructing the Endo.Adm system. DCNN, Deep Convolutional Neural Ne2rks.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Tan G, Rao SS. Part I: How to ergonomically design a modern endoscopic suite. Tech Gastrointest Endosc 2019;21(3):133–9.
    1. Wang LW, Lin H, Xin L, et al. . Establishing a model to measure and predict the quality of gastrointestinal endoscopy. World J Gastroenterol 2019;25(8):1024–30. - PMC - PubMed
    1. Rutter MD, Rees CJ. Quality in gastrointestinal endoscopy. Endoscopy 2014;46(6):526–8. - PubMed
    1. Rutter MD, Senore C, Bisschops R, et al. . The European Society of Gastrointestinal Endoscopy quality improvement initiative: Developing performance measures. Endoscopy 2016;48(1):81–9. - PubMed
    1. Burr NE, Derbyshire E, Taylor J, et al. . Variation in post-colonoscopy colorectal cancer across colonoscopy providers in English National Health Service: Population based cohort study. BMJ 2019;367:l6090. - PMC - PubMed

Publication types