Application of artificial intelligence in endoscopic image analysis for the diagnosis of a gastric cancer pathogen-Helicobacter pylori infection

doi:10.1038/s41598-023-40179-5

. 2023 Aug 17;13(1):13380.

doi: 10.1038/s41598-023-40179-5.

Application of artificial intelligence in endoscopic image analysis for the diagnosis of a gastric cancer pathogen-Helicobacter pylori infection

Chih-Hsueh Lin^#^{1

2}, Ping-I Hsu^#³, Chin-Dar Tseng^{4

5}, Pei-Ju Chao^{1

2}, I-Ting Wu³, Supratip Ghose⁶, Chih-An Shih^{7

8}, Shen-Hao Lee^{1

2

9}, Jia-Hong Ren^{1

2}, Chang-Bih Shie³, Tsair-Fwu Lee^{10

11

12

13

14}

Affiliations

¹ Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan.
² Medical Physics and Informatics Laboratory of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan.
³ Division of Gastroenterology, Department of Medicine, An Nan Hospital, China Medical University, Tainan, Taiwan.
⁴ Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan. a1102405111@gmail.com.
⁵ Medical Physics and Informatics Laboratory of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan. a1102405111@gmail.com.
⁶ Department of Education and Research, An Nan Hospital, China Medical University, Tainan, Taiwan.
⁷ Division of Gastroenterology and Hepatology, Department of Internal Medicine, Antai Medical Care Corporation, Antai Tian-Sheng Memorial Hospital, Donggan, Pingtung County, Taiwan.
⁸ Department of Nursing, Meiho University, Neipu, Pingtung County, Taiwan.
⁹ Department of Radiation Oncology, Linkou Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Linkou, Taiwan.
¹⁰ Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan. tsairfwulee@gmail.com.
¹¹ Medical Physics and Informatics Laboratory of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan. tsairfwulee@gmail.com.
¹² Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan. tsairfwulee@gmail.com.
¹³ PhD Program in Biomedical Engineering, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan. tsairfwulee@gmail.com.
¹⁴ School of Dentistry, College of Dental Medicine, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan. tsairfwulee@gmail.com.

^# Contributed equally.

PMID: 37592004
PMCID: PMC10435453
DOI: 10.1038/s41598-023-40179-5

Application of artificial intelligence in endoscopic image analysis for the diagnosis of a gastric cancer pathogen-Helicobacter pylori infection

Chih-Hsueh Lin et al. Sci Rep. 2023.

. 2023 Aug 17;13(1):13380.

doi: 10.1038/s41598-023-40179-5.

Authors

Affiliations

¹ Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan.
² Medical Physics and Informatics Laboratory of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan.
³ Division of Gastroenterology, Department of Medicine, An Nan Hospital, China Medical University, Tainan, Taiwan.
⁴ Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan. a1102405111@gmail.com.
⁵ Medical Physics and Informatics Laboratory of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan. a1102405111@gmail.com.
⁶ Department of Education and Research, An Nan Hospital, China Medical University, Tainan, Taiwan.
⁷ Division of Gastroenterology and Hepatology, Department of Internal Medicine, Antai Medical Care Corporation, Antai Tian-Sheng Memorial Hospital, Donggan, Pingtung County, Taiwan.
⁸ Department of Nursing, Meiho University, Neipu, Pingtung County, Taiwan.
⁹ Department of Radiation Oncology, Linkou Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Linkou, Taiwan.
¹⁰ Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan. tsairfwulee@gmail.com.
¹¹ Medical Physics and Informatics Laboratory of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan. tsairfwulee@gmail.com.
¹² Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan. tsairfwulee@gmail.com.
¹³ PhD Program in Biomedical Engineering, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan. tsairfwulee@gmail.com.
¹⁴ School of Dentistry, College of Dental Medicine, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan. tsairfwulee@gmail.com.

^# Contributed equally.

PMID: 37592004
PMCID: PMC10435453
DOI: 10.1038/s41598-023-40179-5

Abstract

Helicobacter pylori (H. pylori) infection is the principal cause of chronic gastritis, gastric ulcers, duodenal ulcers, and gastric cancer. In clinical practice, diagnosis of H. pylori infection by a gastroenterologists' impression of endoscopic images is inaccurate and cannot be used for the management of gastrointestinal diseases. The aim of this study was to develop an artificial intelligence classification system for the diagnosis of H. pylori infection by pre-processing endoscopic images and machine learning methods. Endoscopic images of the gastric body and antrum from 302 patients receiving endoscopy with confirmation of H. pylori status by a rapid urease test at An Nan Hospital were obtained for the derivation and validation of an artificial intelligence classification system. The H. pylori status was interpreted as positive or negative by Convolutional Neural Network (CNN) and Concurrent Spatial and Channel Squeeze and Excitation (scSE) network, combined with different classification models for deep learning of gastric images. The comprehensive assessment for H. pylori status by scSE-CatBoost classification models for both body and antrum images from same patients achieved an accuracy of 0.90, sensitivity of 1.00, specificity of 0.81, positive predictive value of 0.82, negative predicted value of 1.00, and area under the curve of 0.88. The data suggest that an artificial intelligence classification model using scSE-CatBoost deep learning for gastric endoscopic images can distinguish H. pylori status with good performance and is useful for the survey or diagnosis of H. pylori infection in clinical practice.

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Conflict of interest statement

The authors declare no competing interests.

Figures

**Figure 1**
Overall research flow chart.

**Figure 2**
(a) Endoscopic images of the body and (b) Endoscopic images of the antrum.

**Figure 3**
(a) Body and (b) Antrum image capture.

**Figure 4**
Channel attention mechanism of cSE architecture model.

**Figure 5**
Spatial attention mechanism of sSE architecture model.

**Figure 6**
A scSE architecture model composed of cSE and sSE.

**Figure 7**
Convolutional network combined with classification model.

See this image and copyright information in PMC

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References

1. Abadi ATB, Kusters JG. Management of Helicobacter pylori infections. BMC Gastroenterol. 2016;16:1–4. doi: 10.1186/s12876-016-0496-2. - DOI - PMC - PubMed
1. Liou J-M, Malfertheiner P, Lee Y-C, Sheu B-S, Sugano K, Cheng H-C, Yeoh K-G, Hsu P-I, Goh K-L, Mahachai V. Screening and eradication of Helicobacter pylori for gastric cancer prevention: the Taipei global consensus. Gut. 2020;69:2093–2112. doi: 10.1136/gutjnl-2020-322368. - DOI - PubMed
1. Sabbagh P, Mohammadnia-Afrouzi M, Javanian M, Babazadeh A, Koppolu V, Vasigala VR, Nouri HR, Ebrahimpour SJ. Diagnostic methods for Helicobacter pylori infection: ideals, options, and limitations. Eur. J. Clin. Microbiol. Infect. Dis. 2019;38:55–66. doi: 10.1007/s10096-018-3414-4. - DOI - PubMed
1. Braden BJB. Diagnosis of Helicobacter pylori infection. BMJ. 2012;344:e282. doi: 10.1136/bmj.e828. - DOI - PubMed
1. Lewis JD, Kroser J, Bevan J, Furth EE, Metz DCJ. Urease-based tests for Helicobacter pylori gastritis: Accurate for diagnosis but poor correlation with disease severity. J. Clin. Gastroenterol. 1997;25:415–420. doi: 10.1097/00004836-199709000-00003. - DOI - PubMed

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[1] Abadi ATB, Kusters JG. Management of Helicobacter pylori infections. BMC Gastroenterol. 2016;16:1–4. doi: 10.1186/s12876-016-0496-2. - DOI - PMC - PubMed

[2] Abadi ATB, Kusters JG. Management of Helicobacter pylori infections. BMC Gastroenterol. 2016;16:1–4. doi: 10.1186/s12876-016-0496-2. - DOI - PMC - PubMed

[3] Liou J-M, Malfertheiner P, Lee Y-C, Sheu B-S, Sugano K, Cheng H-C, Yeoh K-G, Hsu P-I, Goh K-L, Mahachai V. Screening and eradication of Helicobacter pylori for gastric cancer prevention: the Taipei global consensus. Gut. 2020;69:2093–2112. doi: 10.1136/gutjnl-2020-322368. - DOI - PubMed

[4] Liou J-M, Malfertheiner P, Lee Y-C, Sheu B-S, Sugano K, Cheng H-C, Yeoh K-G, Hsu P-I, Goh K-L, Mahachai V. Screening and eradication of Helicobacter pylori for gastric cancer prevention: the Taipei global consensus. Gut. 2020;69:2093–2112. doi: 10.1136/gutjnl-2020-322368. - DOI - PubMed

[5] Sabbagh P, Mohammadnia-Afrouzi M, Javanian M, Babazadeh A, Koppolu V, Vasigala VR, Nouri HR, Ebrahimpour SJ. Diagnostic methods for Helicobacter pylori infection: ideals, options, and limitations. Eur. J. Clin. Microbiol. Infect. Dis. 2019;38:55–66. doi: 10.1007/s10096-018-3414-4. - DOI - PubMed

[6] Sabbagh P, Mohammadnia-Afrouzi M, Javanian M, Babazadeh A, Koppolu V, Vasigala VR, Nouri HR, Ebrahimpour SJ. Diagnostic methods for Helicobacter pylori infection: ideals, options, and limitations. Eur. J. Clin. Microbiol. Infect. Dis. 2019;38:55–66. doi: 10.1007/s10096-018-3414-4. - DOI - PubMed

[7] Braden BJB. Diagnosis of Helicobacter pylori infection. BMJ. 2012;344:e282. doi: 10.1136/bmj.e828. - DOI - PubMed

[8] Braden BJB. Diagnosis of Helicobacter pylori infection. BMJ. 2012;344:e282. doi: 10.1136/bmj.e828. - DOI - PubMed

[9] Lewis JD, Kroser J, Bevan J, Furth EE, Metz DCJ. Urease-based tests for Helicobacter pylori gastritis: Accurate for diagnosis but poor correlation with disease severity. J. Clin. Gastroenterol. 1997;25:415–420. doi: 10.1097/00004836-199709000-00003. - DOI - PubMed

[10] Lewis JD, Kroser J, Bevan J, Furth EE, Metz DCJ. Urease-based tests for Helicobacter pylori gastritis: Accurate for diagnosis but poor correlation with disease severity. J. Clin. Gastroenterol. 1997;25:415–420. doi: 10.1097/00004836-199709000-00003. - DOI - PubMed

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Application of artificial intelligence in endoscopic image analysis for the diagnosis of a gastric cancer pathogen-Helicobacter pylori infection

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Application of artificial intelligence in endoscopic image analysis for the diagnosis of a gastric cancer pathogen-Helicobacter pylori infection

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