Discrimination of parotid neoplasms from the normal parotid gland by use of Raman spectroscopy and support vector machine.

Preoperative diagnosis of neoplasms in the parotid gland is essential for successful surgical treatment. The purpose of this study is to apply Raman spectroscopy in order to distinguish the spectral differences between pleomorphic adenoma and Warthin tumor from that of normal parotid gland tissues. Furthermore we establish the diagnostic model of the Raman spectra of neoplasms in parotid gland by employing support vector machine (SVM) with Gaussian radial basis function. Firstly, Raman spectra from different histopathological tissues were obtained by near-infrared Raman microscope, SVM was then employed to analyze the different spectra and establish a discriminating model. As a result, the differences of peaks in the region 800-1800 cm(-1) demonstrated the biochemical molecular alterations between different histopathological tissues. Compared with normal parotid gland tissues, the content of proteins, lipids and DNA increased in pleomorphic adenoma. The content of DNA increased but proteins and lipids decreased in Warthin tumor. SVM displayed a powerful role in the classification of three different groups. The sensitivities and specificities of discrimination between different groups reached above 95% and 99%, respectively. Raman spectroscopy combined SVM algorithm could have great potential for providing a noninvasive, effective and accurate diagnostic technology for neoplasm diagnosis in the parotid gland.