Real-Time Evaluation of Helicobacter pylori Infection by Convolution Neural Network During White-Light Endoscopy: A Prospective, Multicenter Study (With Video)

被引:4
|
作者
Shen, Yuqin [1 ,2 ]
Chen, Angli [3 ]
Zhang, Xinsen [4 ]
Zhong, Xingwei [5 ]
Ma, Ahuo [6 ]
Wang, Jianping [5 ]
Wang, Xinjie [1 ]
Zheng, Wenfang [7 ]
Sun, Yingchao [1 ]
Yue, Lei [1 ]
Zhang, Zhe [8 ]
Zhang, Xiaoyan [4 ]
Lin, Ne [1 ]
Kim, John J. [9 ]
Du, Qin [10 ]
Liu, Jiquan [4 ]
Hu, Weiling [1 ]
机构
[1] Zhejiang Univ, Sir Run Run Shaw Hosp, Med Sch, Dept Gastroenterol, Hangzhou, Peoples R China
[2] Sichuan Univ, West China Xiamen Hosp, Xiamen, Peoples R China
[3] Shaoxing Univ, Sch Med, Shaoxing, Zhejiang, Peoples R China
[4] Zhejiang Univ, Coll Biomed Engn & Instrument Sci, Key Lab Biomed Engn, Minist Educ, Hangzhou, Peoples R China
[5] Deqing Cty Peoples Hosp, Dept Gastroenterol, Huzhou, Peoples R China
[6] Shaoxing Peoples Hosp, Dept Gastroenterol, Shaoxing, Peoples R China
[7] Hangzhou First Peoples Hosp, Dept Gastroenterol, Hangzhou, Peoples R China
[8] Longyou Cty Peoples Hosp, Dept Gastroenterol, Quzhou, Peoples R China
[9] Loma Linda Univ Hlth, Div Gastroenterol & Hepatol, Loma Linda, CA USA
[10] Zhejiang Univ, Affiliated Hosp 2, Med Sch, Dept Gastroenterol, Hangzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
Helicobacter; H; pylori; convolutional neural network; real-time; artificial intelligence; DIAGNOSIS; GASTRITIS; ACCURACY; FEATURES;
D O I
10.14309/ctg.0000000000000643
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
INTRODUCTION: Convolutional neural network during endoscopy may facilitate evaluation of Helicobacter pylori infection without obtaining gastric biopsies. The aim of the study was to evaluate the diagnosis accuracy of a computer-aided decision support system for H. pylori infection (CADSS-HP) based on convolutional neural network under white-light endoscopy. METHODS: Archived video recordings of upper endoscopy with white-light examinations performed at Sir Run Run Shaw Hospital (January 2019-September 2020) were used to develop CADSS-HP. Patients receiving endoscopy were prospectively enrolled (August 2021-August 2022) from 3 centers to calculate the diagnostic property. Accuracy of CADSS-HP for H. pylori infection was also compared with endoscopic impression, urea breath test (URT), and histopathology. H. pylori infection was defined by positive test on histopathology and/or URT. RESULTS: Video recordings of 599 patients who received endoscopy were used to develop CADSS-HP. Subsequently, 456 patients participated in the prospective evaluation including 189 (41.4%) with H. pylori infection. With a threshold of 0.5, CADSS-HP achieved an area under the curve of 0.95 (95% confidence interval [CI], 0.93-0.97) with sensitivity and specificity of 91.5% (95% CI 86.4%-94.9%) and 88.8% (95% CI 84.2%-92.2%), respectively. CADSS-HP demonstrated higher sensitivity (91.5% vs 78.3%; mean difference 5 13.2%, 95% CI 5.7%-20.7%) and accuracy (89.9% vs 83.8%, mean difference 5 6.1%, 95% CI 1.6%-10.7%) compared with endoscopic diagnosis by endoscopists. Sensitivity of CADSS-HP in diagnosing H. pylori was comparable with URT (91.5% vs 95.2%; mean difference 5 3.7%, 95% CI 21.8% to 9.4%), better than histopathology (91.5% vs 82.0%; mean difference 5 9.5%, 95% CI 2.3%-16.8%). DISCUSSION: CADSS-HP achieved high sensitivity in the diagnosis of H. pylori infection in the real-time test, outperforming endoscopic diagnosis by endoscopists and comparable with URT. Clinicaltrials.gov; ChiCTR2000030724.
引用
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页数:8
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