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Endoscopy 2022; 54(08): 757-768
DOI: 10.1055/a-1706-6174
Original article

Effect of an artificial intelligence-based quality improvement system on efficacy of a computer-aided detection system in colonoscopy: a four-group parallel study

Liwen Yao‡   *
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
3   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
,
Lihui Zhang‡   *
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
3   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
,
Jun Liu
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
4   Department of Nursing, Renmin Hospital of Wuhan University, Wuhan, China
,
Wei Zhou
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
3   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
,
Chunping He
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
3   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
,
Jun Zhang
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
3   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
,
Lianlian Wu
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
3   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
,
Hongguang Wang
5   Department of Gastroenterology, Jilin Renmin Hospital, Jilin, China
,
Youming Xu
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
3   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
,
Dexin Gong
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
3   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
,
Ming Xu
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
3   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
,
Xun Li
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
3   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
,
Yutong Bai
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
3   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
,
Rongrong Gong
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
3   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
,
Prateek Sharma
6   University of Kansas School of Medicine and Veterans Affairs Medical Center, Kansas City, Missouri, United States
,
Honggang Yu
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
3   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
› Author AffiliationsSupported by: the Project of Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incisio 2018BCC337
Supported by: Hubei Province Major Science and Technology Innovation Project 2018–916–000–008

Trial Registration: ClinicalTrials.gov Registration number (trial ID): NCT04453956 Type of study: Prospective, Randomized, Single-Center Study
› Further Information
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Referred to by:

Computer-aided detection is here: will computer-aided quality algorithms soon follow?Endoscopy 2022; 54(08): 769-770
DOI: 10.1055/a-1798-0154

Abstract

Background Tandem colonoscopy studies have found that about one in five adenomas are missed at colonoscopy. It remains debatable whether the combination of a computer-aided polyp detection (CADe) system with a computer-aided quality improvement (CAQ) system for real-time monitoring of withdrawal speed results in additional benefits in adenoma detection or if the synergetic effect may be harmed due to excessive visual burden resulting from information overload. This study aimed to evaluate the interaction effect on improving the adenoma detection rate (ADR).

Methods This single-center, randomized, four-group, parallel, controlled study was performed at Renmin Hospital of Wuhan University. Between 1 July and 15 October 2020, 1076 patients were randomly allocated into four treatment groups: control 271, CADe 268, CAQ 269, and CADe plus CAQ (COMBO) 268. The primary outcome was ADR.

Results The ADR in the control, CADe, CAQ, and COMBO groups was 14.76 % (95 % confidence interval [CI] 10.54 to 18.98), 21.27 % (95 %CI 16.37 to 26.17), 24.54 % (95 %CI 19.39 to 29.68), and 30.60 % (95 %CI 25.08 to 36.11), respectively. The ADR was higher in the COMBO group compared with the CADe group (21.27 % vs. 30.6 %, P = 0.024, odds ratio [OR] 1.284, 95 %CI 1.033 to 1.596) but not compared with the CAQ group (24.54 % vs. 30.6 %, P = 0.213, OR 1.309, 95 %CI 0.857 to 2.000, respectively).

Conclusions CAQ significantly improved the efficacy of CADe in a four-group, parallel, controlled study. No significant difference in the ADR or polyp detection rate was found between CAQ and COMBO.

* These authors contributed equally to this work.


Supplementary material



Publication History

Received: 28 June 2021

Accepted after revision: 25 November 2021

Accepted Manuscript online:
25 November 2021

Article published online:
04 February 2022

© 2021. Thieme. All rights reserved.

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Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • References

  • 1 Siegel RL, Miller KD, Goding Sauer A. et al. Colorectal cancer statistics, 2020. CA Cancer J Clin 2020; 70: 145-164
    CrossrefPubMedGoogle Scholar
  • 2 Doubeni CA, Corley DA, Quinn VP. et al. Effectiveness of screening colonoscopy in reducing the risk of death from right and left colon cancer: a large community-based study. Gut 2018; 67: 291-298
    CrossrefPubMedGoogle Scholar
  • 3 Zhao S, Wang S, Pan P. et al. Magnitude, risk factors, and factors associated with adenoma miss rate of tandem colonoscopy: a systematic review and meta-analysis. Gastroenterology 2019; 156: 1661-1674
    Google Scholar
  • 4 Wang P, Xiao X, Glissen Brown JR. et al. Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy. Nat Biomed Eng 2018; 2: 741-748
    CrossrefPubMedGoogle Scholar
  • 5 Repici A, Badalamenti M, Maselli R. et al. Efficacy of real-time computer-aided detection of colorectal neoplasia in a randomized trial. Gastroenterology 2020; 159: 512-520
    Google Scholar
  • 6 Wang P, Berzin TM, Brown JRG. et al. Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study. Gut 2019; 68: 1813-1819
    CrossrefPubMedGoogle Scholar
  • 7 Wang P, Liu P, Brown JRG. et al. Lower adenoma miss rate of computer-aided detection-assisted colonoscopy vs routine white-light colonoscopy in a prospective tandem study. Gastroenterology 2020; 159: 1252-1261
    CrossrefPubMedGoogle Scholar
  • 8 Wang P, Liu X, Berzin TM. et al. Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study. Lancet Gastroenterol Hepatol 2020; 5: 343-351
    CrossrefPubMedGoogle Scholar
  • 9 Gong D, Wu L, Zhang J. et al. Detection of colorectal adenomas with a real-time computer-aided system (ENDOANGEL): a randomised controlled study. Lancet Gastroenterol Hepatol 2020; 5: 352-361
    CrossrefPubMedGoogle Scholar
  • 10 Lami M, Singh H, Dilley JH. et al. Gaze patterns hold key to unlocking successful search strategies and increasing polyp detection rate in colonoscopy. Endoscopy 2018; 50: 701-707
    Article in Thieme ConnectPubMedGoogle Scholar
  • 11 Kudo T, Saito Y, Ikematsu H. et al. New-generation full-spectrum endoscopy versus standard forward-viewing colonoscopy: a multicenter, randomized, tandem colonoscopy trial (J-FUSE Study). Gastrointest Endosc 2018; 88: 854-864
    CrossrefPubMedGoogle Scholar
  • 12 Aslanian HR, Shieh FK, Chan FW. et al. Nurse observation during colonoscopy increases polyp detection: a randomized prospective study. Am J Gastroenterol 2013; 108: 166-172
    CrossrefPubMedGoogle Scholar
  • 13 Luo Y, Zhang Y, Liu M. et al. Artificial intelligence-assisted colonoscopy for detection of colon polyps: a prospective, randomized cohort study. J Gastrointest Surg 2021; 25: 2011-2018
    CrossrefPubMedGoogle Scholar
  • 14 Shaukat A, Rector TS, Church TR. et al. Longer withdrawal time is associated with a reduced incidence of interval cancer after screening colonoscopy. Gastroenterology 2015; 149: 952-957
    CrossrefPubMedGoogle Scholar
  • 15 Suzuki S, Gotoda T, Kusano C. et al. Seven-day vonoprazan and low-dose amoxicillin dual therapy as first-line treatment: a multicentre randomised trial in Japan. Gut 2020; 69: 1019-1026
    CrossrefPubMedGoogle Scholar
  • 16 Hung IFN, Lung KC, Tso EYK. et al. Triple combination of interferon beta-1b, lopinavir-ritonavir, and ribavirin in the treatment of patients admitted to hospital with COVID-19: an open-label, randomised, phase 2 trial. Lancet 2020; 395: 1695-1704
    CrossrefPubMedGoogle Scholar
  • 17 Crockett SD, Nagtegaal ID. Terminology, molecular features, epidemiology, and management of serrated colorectal neoplasia. Gastroenterology 2019; 157: 949-966
    CrossrefPubMedGoogle Scholar
  • 18 Bailey CE, Hu CY, You YN. et al. Increasing disparities in the age-related incidences of colon and rectal cancers in the United States, 1975–2010. JAMA Surg 2015; 150: 17-22
    CrossrefPubMedGoogle Scholar
  • 19 Corley DA, Jensen CD, Marks AR. et al. Adenoma detection rate and risk of colorectal cancer and death. New Engl J Med 2014; 370: 1298-1306
    CrossrefPubMedGoogle Scholar
  • 20 Urban G, Tripathi P, Alkayali T. et al. Deep learning localizes and identifies polyps in real time with 96% accuracy in screening colonoscopy. Gastroenterology 2018; 155: 1069-1078
    CrossrefPubMedGoogle Scholar
  • 21 Click B, Pinsky PF, Hickey T. et al. Association of colonoscopy adenoma findings with long-term colorectal cancer incidence. JAMA 2018; 319: 2021-2031
    Google Scholar
  • 22 Rex DK, Schoenfeld PS, Cohen J. et al. Quality indicators for colonoscopy. Gastrointest Endosc 2015; 81: 31-53
    CrossrefPubMedGoogle Scholar
  • 23 Barclay RL, Vicari JJ, Doughty AS. et al. Colonoscopic withdrawal times and adenoma detection during screening colonoscopy. New Engl J Med 2006; 355: 2533-2541
    CrossrefPubMedGoogle Scholar
  • 24 Adler A, Wegscheider K, Lieberman D. et al. Factors determining the quality of screening colonoscopy: a prospective study on adenoma detection rates, from 12 134 examinations (Berlin colonoscopy project 3, BECOP-3). Gut 2013; 62: 236-241
    CrossrefPubMedGoogle Scholar
  • 25 Sawhney MS, Cury MS, Neeman N. et al. Effect of institution-wide policy of colonoscopy withdrawal time ≥7 minutes on polyp detection. Gastroenterology 2008; 135: 1892-1898
    CrossrefPubMedGoogle Scholar
  • 26 Jung Y, Joo YE, Kim HG. et al. Relationship between the endoscopic withdrawal time and adenoma/polyp detection rate in individual colonic segments: a KASID multicenter study. Gastrointest Endosc 2019; 89: 523-530
    CrossrefPubMedGoogle Scholar