Observational Study
Copyright ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jan 21, 2021; 27(3): 281-293
Published online Jan 21, 2021. doi: 10.3748/wjg.v27.i3.281
Comparative study on artificial intelligence systems for detecting early esophageal squamous cell carcinoma between narrow-band and white-light imaging
Bing Li, Shi-Lun Cai, Wei-Min Tan, Ji-Chun Li, Ayimukedisi Yalikong, Xiao-Shuang Feng, Hon-Ho Yu, Pin-Xiang Lu, Zhen Feng, Li-Qing Yao, Ping-Hong Zhou, Bo Yan, Yun-Shi Zhong
Bing Li, Shi-Lun Cai, Ayimukedisi Yalikong, Li-Qing Yao, Ping-Hong Zhou, Yun-Shi Zhong, Department of Endoscopy Center, Zhongshan Hospital of Fudan University, Shanghai 200032, China
Wei-Min Tan, Ji-Chun Li, Bo Yan, School of Computer Science, Fudan University, Shanghai 200433, China
Xiao-Shuang Feng, Clinical Statistical Center, Shanghai Cancer Center of Fudan University, Shanghai 200032, China
Hon-Ho Yu, Department of Gastroenterology, Kiang Wu Hospital, Macau SAR 999078, China
Pin-Xiang Lu, Zhen Feng, Department of Endoscopy Center, Xuhui Hospital, Zhongshan Hospital of Fudan University, Shanghai 200031, China
Author contributions: Zhong YS and Yan B conceived the study design; Li B, Cai SL, Tan WM, Li JC, Yalikong A, Yu HH, Lu PX, and Feng Z acquired the data; Li B, Cai SL, Yalikong A, Tan WM, Feng XS, Yao LQ, Zhou PH, and Zhong YS analyzed and interpreted the data; Li B, Tan WM, and Cai SL drafted the manuscript; Zhong YS critically revised the manuscript for important intellectual content; Li B, Cai SL, Tan WM, Li JC, Yalikong A, Feng XS, Yu HH, Lu PX, Feng Z, Yao LQ, Zhou PH, Yan B, and Zhong YS approved the final version of the manuscript; Li B, Cai SL and Tan WM contributed equally to this article.
Supported by National Key R&D Program of China, No. 2018YFC1315000, No. 2018YFC1315005, No. 2019YFC1315800, and No. 2019YFC1315802; National Natural Science Foundation of China, No. 81861168036 and No. 81702305; Science and Technology Commission Foundation of Shanghai Municipality, No. 19411951600, and No. 19411951601; Macao SAR Science and Technology Development Foundation, No. 0023/2018/AFJ; and Dawn Program of Shanghai Education Commission, No. 18SG08.
Institutional review board statement: This study was reviewed and approved by the Ethics Committee of Zhongshan Hospital, Fudan University.
Informed consent statement: Patients were not required to give informed consent to the study because the analysis used anonymous clinical data that were obtained after each patient agreed to undergo treatment by written consent.
Conflict-of-interest statement: The authors declare that they have no competing interests.
Data sharing statement: The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
STROBE statement: The authors have read the STROBE Statement checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Yun-Shi Zhong, MD, PhD, Professor, Department of Endoscopy Center, Zhongshan Hospital of Fudan University, No. 180 Fenglin Road, Shanghai 200032, China. zhongyunshi@yahoo.com
Received: October 9, 2020
Peer-review started: October 9, 2020
First decision: November 23, 2020
Revised: December 5, 2020
Accepted: December 22, 2020
Article in press: December 22, 2020
Published online: January 21, 2021
Processing time: 97 Days and 2.1 Hours
Core Tip

Core Tip: The computer-assisted diagnosis (CAD) system under conventional endoscopic white-light imaging (WLI) for screening of early esophagus squamous cell carcinoma (ESCC) has high accuracy. However, few studies have examined different characteristics of CAD application in WLI and narrow-band imaging (NBI) models. In this study, the CAD system we constructed under the NBI model for screening of early ESCC had higher accuracy and specificity than the CAD-WLI system. Endoscopists could achieve the best diagnostic efficacy by using both CAD-WLI and CAD-NBI. The two CAD systems have different advantages in avoiding missed diagnosis and excessive biopsy, which could help endoscopists, especially those with less experience, in more efficient screening of early ESCC.