Li Yi, Wen Zhi-Ning, Li Long-Jiang, Li Meng-Long, Zhang Zhuang, Gao Ning
State Key Laboratory of Oral Diseases, Sichuan University, Chengdu 610041, China.
Hua Xi Kou Qiang Yi Xue Za Zhi. 2010 Feb;28(1):61-4.
To evaluate the value of the near infrared Raman spectroscope in diagnosing oral squamous cell carcinoma (OSCC).
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.
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%.
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.
评估近红外拉曼光谱仪在诊断口腔鳞状细胞癌(OSCC)中的价值。
本研究收集了10例正常黏膜、20例OSCC和30例口腔白斑(OLK)病例的近红外拉曼光谱。基于先前的研究,通过比较组的特征谱带获得相减光谱的信息。使用高斯径向基函数支持向量机对光谱进行分类并建立诊断模型。评估该算法的有效性和准确性。
通过分析相减后的平均光谱,波数范围在500 - 2200 cm⁻¹内峰强度增加提示OSCC中DNA、蛋白质和脂质含量较高,这表明其具有较高的增殖活性。波数范围在500 - 2200 cm⁻¹内峰强度增加提示OSCC中DNA、蛋白质和脂质含量较高,这表明其具有较高的增殖活性,但OLK与OSCC之间的差异不如正常组织与OSCC之间的差异大。高斯径向基函数支持向量机在正常组织和OSCC的分组及建模方面表现出强大能力,特异性、敏感性和准确性分别为100%、97.44%和98.81%。该算法在OLK和OSCC的分组及建模方面也表现出良好能力,特异性、敏感性和准确性分别为95.00%、86.36%和96.30%。
结合支持向量机,近红外拉曼光谱能够检测口腔正常组织、OLK和OSCC中的生化变化,并准确建立诊断模型。