Usefulness of a novel computer-aided detection system for colorectal neoplasia: a randomized controlled trial

被引:24
作者
Gimeno-Garcia, Antonio Z. [1 ,2 ]
Negrin, Domingo Hernandez [1 ,2 ]
Hernandez, Anjara [1 ,2 ]
Nicolas-Perez, David [1 ,2 ]
Rodriguez, Eduardo [1 ,2 ]
Montesdeoca, Carlota [1 ,2 ]
Alarcon, Onofre [1 ,2 ]
Romero, Rafael [1 ,2 ]
Dorta, Jose Luis Baute [1 ,2 ]
Cedres, Yaiza [1 ,2 ]
del Castillo, Rocio [1 ,2 ]
Jimenez, Alejandro [3 ]
Felipe, Vanessa [1 ,2 ]
Morales, Dalia [1 ,2 ]
Ortega, Juan [1 ,2 ]
Reygosa, Cristina [1 ,2 ]
Quintero, Enrique [1 ,2 ]
Hernandez-Guerra, Manuel [1 ,2 ]
机构
[1] Univ La Laguna, Hosp Univ Canarias, Inst Univ Tecnol Biomed ITB, Serv Gastroenterol, Tenerife, Spain
[2] Univ La Laguna, Ctr Invest Biomed Canarias CIBICAN, Dept Med Interna, Tenerife, Spain
[3] Hosp Univ Canarias, Unidad Invest, Tenerife, Spain
关键词
DETECTION-ASSISTED COLONOSCOPY; ADENOMA DETECTION; ARTIFICIAL-INTELLIGENCE; ENDOSCOPY; CLASSIFICATION; STATEMENT; SOCIETY;
D O I
10.1016/j.gie.2022.09.029
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
Background and Aims: Artificial intelligence-based computer-aid detection (CADe) devices have been recently tested in colonoscopies, increasing the adenoma detection rate (ADR), mainly in Asian populations. However, ev-idence for the benefit of these devices in the occidental population is still low. We tested a new CADe device, namely, ENDO-AID (OIP-1) (Olympus, Tokyo, Japan), in clinical practice. Methods: This randomized controlled trial included 370 consecutive patients who were randomized 1:1 to CADe (n = 185) versus standard exploration (n = 185) from November 2021 to January 2022. The primary endpoint was the ADR. Advanced adenoma was defined as >10 mm, harboring high-grade dysplasia, or with a villous pattern. Otherwise, the adenoma was nonadvanced. ADR was assessed in both groups stratified by endoscopist ADR and colon cleansing. Results: In the intention-to-treat analysis, the ADR was 55.1% (102/185) in the CADe group and 43.8% (81/185) in the control group (P = .029). Nonadvanced ADRs (54.8% vs 40.8%, P = .01) and flat ADRs (39.4 vs 24.8, P = .006), polyp detection rate (67.1% vs 51%; P = .004), and number of adenomas per colonoscopy were signifi- cantly higher in the CADe group than in the control group (median [25th-75th percentile], 1 [0-2] vs 0 [0-1.5], respectively; P Z .014). No significant differences were found in serrated ADR. After stratification by endoscopist and bowel cleansing, no statistically significant differences in ADR were found. Conclusions: Colonoscopy assisted by ENDO-AID (OIP-1) increases ADR and number of adenomas per colonoscopy, suggesting it may aid in the detection of colorectal neoplastic lesions, especially because of its detection of diminutive and flat adenomas. (Clinical trial registration number: NCT04945044.) (Gastrointest Endosc 2023;97:528-36.)
引用
收藏
页码:528 / +
页数:10
相关论文
共 33 条
  • [1] Causes of Post-Colonoscopy Colorectal Cancers Based on World Endoscopy Organization System of Analysis
    Anderson, Rebecca
    Burr, Nicholas E.
    Valori, Roland
    [J]. GASTROENTEROLOGY, 2020, 158 (05) : 1287 - +
  • [2] [Anonymous], 2003, GASTROINTEST ENDOSC, V58, pS3
  • [3] Impact of real-time use of artificial intelligence in improving adenoma detection during colonoscopy: A systematic review and meta-analysis
    Ashat, Munish
    Klair, Jagpal Singh
    Singh, Dhruv
    Murali, Arvind Rangarajan
    Krishnamoorthi, Rajesh
    [J]. ENDOSCOPY INTERNATIONAL OPEN, 2021, 09 (04) : E513 - E521
  • [4] Artificial intelligence for polyp detection during colonoscopy: a systematic review and meta-analysis
    Barua, Ishita
    Vinsard, Daniela Guerrero
    Jodal, Henriette C.
    Loberg, Magnus
    Kalager, Mette
    Holme, Oyvind
    Misawa, Masashi
    Bretthauer, Michael
    Mori, Yuichi
    [J]. ENDOSCOPY, 2021, 53 (03) : 277 - 284
  • [5] Position statement on priorities for artificial intelligence in GI endoscopy: a report by the ASGE Task Force
    Berzin, Tyler M.
    Parasa, Sravanthi
    Wallace, Michael B.
    Gross, Seth A.
    Repici, Alessandro
    Sharma, Prateek
    [J]. GASTROINTESTINAL ENDOSCOPY, 2020, 92 (04) : 951 - 959
  • [6] Trends in Adenoma Detection Rates During the First 10 Years of the German Screening Colonoscopy Program
    Brenner, Hermann
    Altenhofen, Lutz
    Kretschmann, Jens
    Roesch, Thomas
    Pox, Christian
    Stock, Christian
    Hoffmeister, Michael
    [J]. GASTROENTEROLOGY, 2015, 149 (02) : 356 - +
  • [7] Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial)
    Brown, Jeremy R. Glissen
    Mansour, Nabil M.
    Wang, Pu
    Chuchuca, Maria Aguilera
    Minchenberg, Scott B.
    Chandnani, Madhuri
    Liu, Lin
    Gross, Seth A.
    Sengupta, Neil
    Berzin, Tyler M.
    [J]. CLINICAL GASTROENTEROLOGY AND HEPATOLOGY, 2022, 20 (07) : 1499 - +
  • [8] Corley DA, 2014, NEW ENGL J MED, V370, P2541, DOI [10.1056/NEJMc1405329, 10.1056/NEJMoa1309086]
  • [9] Artificial intelligence (AI) real-time detection vs. routine colonoscopy for colorectal neoplasia: a meta-analysis and trial sequential analysis
    Deliwala, Smit S.
    Hamid, Kewan
    Barbarawi, Mahmoud
    Lakshman, Harini
    Zayed, Yazan
    Kandel, Pujan
    Malladi, Srikanth
    Singh, Adiraj
    Bachuwa, Ghassan
    Gurvits, Grigoriy E.
    Chawla, Saurabh
    [J]. INTERNATIONAL JOURNAL OF COLORECTAL DISEASE, 2021, 36 (11) : 2291 - 2303
  • [10] Detection of colorectal adenomas with a real-time computer-aided system (ENDOANGEL): a randomised controlled study
    Gong, Dexin
    Wu, Lianlian
    Zhang, Jun
    Mu, Ganggang
    Shen, Lei
    Liu, Jun
    Wang, Zhengqiang
    Zhou, Wei
    An, Ping
    Huang, Xu
    Jiang, Xiaoda
    Li, Yanxia
    Wan, Xinyue
    Hu, Shan
    Chen, Yiyun
    Hu, Xiao
    Xu, Youming
    Zhu, Xiaoyun
    Li, Suqin
    Yao, Liwen
    He, Xinqi
    Chen, Di
    Huang, Li
    Wei, Xiao
    Wang, Xuemei
    Yu, Honggang
    [J]. LANCET GASTROENTEROLOGY & HEPATOLOGY, 2020, 5 (04): : 352 - 361