Research Papers:

Evaluating oral epithelial dysplasia classification system by near-infrared Raman spectroscopy

Bo Li, Zhi-Yu Gu, Kai-Xiao Yan, Zhi-Ning Wen, Zhi-He Zhao, Long-Jiang Li _ and Yi Li

PDF  |  HTML  |  How to cite

Oncotarget. 2017; 8:76257-76265. https://doi.org/10.18632/oncotarget.19343

Metrics: PDF 1415 views  |   HTML 2836 views  |   ?  


Bo Li1, Zhi-Yu Gu1, Kai-Xiao Yan1,2, Zhi-Ning Wen3, Zhi-He Zhao1, Long-Jiang Li1,2 and Yi Li1,2

1State Key Laboratory of Oral Disease, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China

2Department of Head and Neck Oncology, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China

3College of Chemistry, Sichuan University, Chengdu 610064, China

Correspondence to:

Long-Jiang Li, email: [email protected]

Yi Li, email: [email protected]

Keywords: oral epithelial dysplasia, near-infrared Raman spectroscopy, support vector machine, classification system

Received: November 10, 2016    Accepted: June 27, 2017    Published: July 18, 2017


Until now, the classification system of oral epithelial dysplasia is still based on the architectural and cytological changes, which relies on the observation of pathologists and is relatively subjective. The purpose of present research was to discriminate the oral dysplasia by the near-infrared Raman spectroscope, in order to evaluate the classification system. We collected Raman spectra of normal mucosa, oral squamous cell carcinoma (OSCC) and dysplasia by near-infrared Raman spectroscope. The biochemical variations between different stages were analyzed by the characteristic peaks in the subtracted mean spectra. Gaussian radial basis function support vector machines (SVM) were used to establish the diagnostic models. At the same time, principal component analysis (PCA) and linear discriminant analysis (LDA) were used to verify the results of SVM. Raman spectral differences were observed in the range between 730~1913 cm-1. Compared with normal mucosa, high contents of protein and DNA in oral dysplasia and OSCC were observed. There were no significant or gradual variation of Raman peaks among different dysplastic grades. The accuracies of comparison between mild, moderate, severe dysplasia with OSCC were 100%, 44.44%, 71.15%, which elucidated the low modeling ability of support vector machines, especially for the moderate dysplasia. The analysis by PCA-LDA could not discriminate the stages, either. Combined with support vector machines, near-infrared Raman spectroscopy could detect the biochemical variations in oral normal, OSCC and dysplastic tissues, but could not establish diagnostic model accurately. The classification system needs further improvements.

Creative Commons License All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 4.0 License.
PII: 19343