| Abstract: | Early diagnosis of oral carcinomas is essential for successful treatment. The purpose of the present study is to apply near‐infrared Raman spectroscopy to detect oral squamous cell carcinoma (SCC) and leukoplakia (OLK), in order to establish the diagnostic model of the Raman spectra of oral diseases. We collected Raman spectra of normal, OLK and SCC by near‐infrared Fourier transform Raman spectroscopy. The biochemical variations between different lesions were analyzed by the characteristic bands in the subtracted mean spectra. Gaussian radial basis function support vector machines (SVM) were used to classify spectra and establish the diagnostic models. Major differences were observed in the range between 800 and 1800 cm−1. Compared with normal mucosa, high contents of protein, DNA and lipid in SCC and OLK were observed, but the difference between OLK and normal tissue was not as much as that between normal and SCC. SVM displayed a powerful ability in the classifying of normal and SCC, and the specificity, sensitivity and accuracy were 100, 97.56 and 98.75%, respectively. In discriminating between the OLK and normal groups, the three parameters were 85, 68 and 72.5%. The algorithm showed good ability in grouping and modeling of OLK and SCC, and the three parameters were 95, 97.43 and 96.25%. Combined with SVM, near‐infrared Raman spectroscopy can detect biochemical variations in oral normal mucosa, OLK and SCC, and establish diagnostic models accurately. Copyright © 2009 John Wiley & Sons, Ltd. |
