Multi-step validation of a deep learning-based system with visual explanations for optical diagnosis of polyps with advanced features

Qing-Wei Zhang; Zhengjie Zhang; Jianwei Xu; Zi-Hao Dai; Ran Zhao; Jian Huang; Hong Qiu; Zhao-Rong Tang; Bo Niu; Xun-Bing Zhang; Peng-Fei Wang; Mei Yang; Wan-Yin Deng; Yan-Sheng Lin; Suncheng Xiang; Zhi-Zheng Ge; Dahong Qian; Xiao-Bo Li

doi:10.1016/j.isci.2024.109461

Multi-step validation of a deep learning-based system with visual explanations for optical diagnosis of polyps with advanced features

iScience. 2024 Mar 8;27(4):109461. doi: 10.1016/j.isci.2024.109461. eCollection 2024 Apr 19.

Authors

Qing-Wei Zhang¹, Zhengjie Zhang², Jianwei Xu², Zi-Hao Dai¹, Ran Zhao³, Jian Huang⁴, Hong Qiu⁵, Zhao-Rong Tang⁵, Bo Niu⁶, Xun-Bing Zhang⁷, Peng-Fei Wang⁸, Mei Yang⁹, Wan-Yin Deng¹⁰, Yan-Sheng Lin¹¹, Suncheng Xiang², Zhi-Zheng Ge¹, Dahong Qian², Xiao-Bo Li¹

Affiliations

¹ Division of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China.
² School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
³ Department of Gastroenterology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China.
⁴ Department of Gastroenterology, Yuyao People's Hospital, Medical School of Ningbo University, Ningbo, Zhejiang Province, China.
⁵ Department of Gastroenterology and Hepatology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China.
⁶ Department of Digestive Endoscopy Center, Yuncheng First Hospital, Yuncheng, Shanxi Province, China.
⁷ Department of Digestive Endoscopy Center, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
⁸ First Division of Gastroenterology Department, Lanzhou University Second Hospital, Lanzhou, Gansu Province, China.
⁹ Department of Gastroenterology and Hepatology, The Third People's Hospital of Chengdu, Chengdu, Sichuan Province, China.
¹⁰ Department of Digestive Endoscopy Center, Fujian Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian, China.
¹¹ Department of Medicine, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China.

Abstract

Artificial intelligence (AI) has been found to assist in optical differentiation of hyperplastic and adenomatous colorectal polyps. We investigated whether AI can improve the accuracy of endoscopists' optical diagnosis of polyps with advanced features. We introduced our AI system distinguishing polyps with advanced features with more than 0.870 of accuracy in the internal and external validation datasets. All 19 endoscopists with different levels showed significantly lower diagnostic accuracy (0.410-0.580) than the AI. Prospective randomized controlled study involving 120 endoscopists into optical diagnosis of polyps with advanced features with or without AI demonstration identified that AI improved endoscopists' proportion of polyps with advanced features correctly sent for histological examination (0.960 versus 0.840, p < 0.001), and the proportion of polyps without advanced features resected and discarded (0.490 versus 0.380, p = 0.007). We thus developed an AI technique that significantly increases the accuracy of colorectal polyps with advanced features.

Keywords: Artificial intelligence; Health sciences; Machine learning.