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Yin F, Zhang X, Fan A, Liu X, Xu J, Ma X, Yang L, Su H, Xie H, Wang X, Gao H, Wang Y, Zhang H, Zhang X, Jin P, Sheng J. A novel detection technology for early gastric cancer based on Raman spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 292:122422. [PMID: 36753864 DOI: 10.1016/j.saa.2023.122422] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 12/28/2022] [Accepted: 01/27/2023] [Indexed: 06/18/2023]
Abstract
Despite universal endoscopic screening, early detection of gastric cancer is challenging, led researchers to seek for a novel approach in detecting. Raman spectroscopy measurements as a fingerprint of biochemical structure, enable accurate prediction of gastric lesions non-destructively. This study aimed to evaluate the diagnostic power of Raman spectroscopy in early gastric cancer (EGC), and reveal dynamic biomolecular changes in vitro from normal to EGC. To clarify the biochemical alterations in Correa's cascade, Raman spectra of human normal gastric mucosa, intestinal metaplasia, dysplasia, and adenocarcinoma were compared at tissue and cellular levels based on a self-developed data processing program. For effectively identify EGC, Raman spectroscopy was used combined with multiple machine learning methods, including partial least-squares discriminant analysis (PLS-DA), support vector machine (SVM), and convolutional neural network (CNN) with leave-one-out (LOO) cross validation. A total of 450 Raman spectra were investigated in this study. The upregulation of νsym(O-P-O) backbone (p < 0.001) was identified as a favorable factor for the diagnosis of EGC, the area under the ROC curve (AUC) was up to 0.918. In addition, higher levels of lactic acid (p < 0.001), lipids (p < 0.001), phenylalanine (p = 0.002), and carotenoids (p < 0.001) were detected in EGC. Multivariate machine learning methods for diagnosis of EGC based on Raman spectroscopy, the sensitivity, specificity, accuracy, and AUC were 91.0%, 100%, 94.8%, and 95.8% for SVM, and 84.8%, 92.0%, 88.8%, and 95.5% for CNN, respectively. Raman spectroscopy can be used as a powerful tool for detecting EGC while elucidating biomolecular dynamics in tumorigenesis. (Chictr.org.cn, ChiCTR2200060720.).
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Affiliation(s)
- Fumei Yin
- Medical School of Chinese PLA, Beijing, China; Department of Gastroenterology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xiaoyu Zhang
- Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Engineering Mechanics, Tsinghua University, Beijing, China
| | - Aoran Fan
- Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Engineering Mechanics, Tsinghua University, Beijing, China
| | - Xiangqian Liu
- Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Engineering Mechanics, Tsinghua University, Beijing, China
| | - Junfeng Xu
- Senior Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xianzong Ma
- Medical School of Chinese PLA, Beijing, China; Department of Gastroenterology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Lang Yang
- Department of Gastroenterology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China; Senior Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Hui Su
- Department of Gastroenterology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Hui Xie
- Department of Gastroenterology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xin Wang
- Department of Gastroenterology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Hanbing Gao
- Department of Gastroenterology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yilin Wang
- Medical School of Chinese PLA, Beijing, China; Department of Gastroenterology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Heng Zhang
- Medical School of Chinese PLA, Beijing, China; Department of Gastroenterology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xing Zhang
- Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Engineering Mechanics, Tsinghua University, Beijing, China.
| | - Peng Jin
- Department of Gastroenterology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China; Senior Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, China.
| | - Jianqiu Sheng
- Department of Gastroenterology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China; Senior Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, China.
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Murakami D, Yamato M, Amano Y, Tada T. Challenging detection of hard-to-find gastric cancers with artificial intelligence-assisted endoscopy. Gut 2021; 70:1196-1198. [PMID: 32816967 PMCID: PMC8108284 DOI: 10.1136/gutjnl-2020-322453] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2020] [Revised: 07/20/2020] [Accepted: 07/21/2020] [Indexed: 12/29/2022]
Affiliation(s)
- Daisuke Murakami
- Department of Gastroenterology, New Tokyo Hospital, Chiba, Japan .,Institute of Advanced Biomedical Engineering and Science, Tokyo Women's Medical University, Tokyo, Japan
| | - Masayuki Yamato
- Institute of Advanced Biomedical Engineering and Science, Tokyo Women's Medical University, Tokyo, Japan
| | - Yuji Amano
- Department of Endoscopy, New Tokyo Hospital, Chiba, Japan
| | - Tomohiro Tada
- Tada Tomohiro Institute of Gastroenterology and Proctology, Saitama, Japan,Department of Surgical Oncology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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