Abstract:

Objective To evaluate the value of the near infrared Raman spectroscope in diagnosing oral squamous cell carcinoma（OSCC）. Methods Near infrared Raman spectra of ten normal mucosa, twenty OSCC and thirty oral leukoplakia（OLK） cases were collected in the research. Based on the previous researches, the information of the subtracted spectra of compared group was gained by the characteristic band in them. A Gaussian radial basis function support vector machine was used to classify spectra and establish the diagnostic models. The efficacy and validity of the algorithm were evaluated. Results By analyzing the subtracted mean spectra, the increasing peak intensity in wavenumber range of 500-2 200 cm-1 hinted us of the high contents of DNA, protein and lipid in OSCC, which elucidate the high proliferative activity. The increasing peak intensity in the wavenumber range of 500-2 200 cm-1 hinted us of the high contents of DNA, protein and lipid in OSCC, which elucidate the high proliferative activity, but the difference between OLK and OSCC was not as much as that between normal and OSCC. The Gaussian radial basis function support vector machine showed powerful ability in grouping and modeling of normal and OSCC, and the specificity, sensitivity and accuracy were 100％, 97.44％ and 98.81％ correspondingly. The algorithm showed good ability in grouping and modeling of OLK and OSCC, the specificity, sensitivity and accuracy were 95.00％, 86.36％and 96.30％. Conclusion Combined with support vector machines, near infrared Raman spectroscopy could detect the biochemical variations in oral normal, OLK and OSCC, and establish diagnostic model accurately.

Key words: oral squamous cell carcinoma, oral leukoplakia, near infrared Raman spectra, support vector machine, diagnosis