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Test of label-free Nasopharyngeal carinoma tissue at different stages by Raman spectroscopy

机译:用拉曼光谱法检测不同阶段的无标记鼻咽癌组织

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Raman spectroscopy (RS) of Nasopharyngeal carcinoma (NPC) tissue contained various biomedicine features. These features indicated molecular-level information of tissue at different carcinoma development-level. This study suggested an automatic and quick method for the NPC Raman spectra classification at different stages by multivariate statistical analysis. In the RS measurement, high quality Raman spectra was acquired from each NPC tissue sample in two groups: one group consisted of 30 NPC patients at the early stages (I-II), another group was 46 NPC patients at the advanced stages (III-IV). Moreover, tentative diagnostic algorithms based on principle components analysis (PCA) and support vector machine (SVM) were employed to classify the multivariate data of Raman spectra effectively. The classification performance (sensitivities and specificities were 70% (21/30) and 91% (42/46)) was achieved by the PCA-SVM in conjunction with leave-one-out cross validation method. In this beneficial study, the RS technique in conjunction with PCA-SVM provided a great clinical potential for rapid NPC stage diagnosis.
机译:鼻咽癌(NPC)组织的拉曼光谱(RS)包含各种生物医学特征。这些特征表明了不同癌症发展水平的组织的分子水平信息。这项研究提出了通过多元统计分析在不同阶段对NPC拉曼光谱进行分类的一种自动,快速的方法。在RS测量中,从每组NPC组织样本中获得了高质量的拉曼光谱,分为两组:一组由30例处于早期(I-II)的NPC患者组成,另一组是46例处于晚期(N-II)的NPC患者IV)。此外,采用基于主成分分析(PCA)和支持向量机(SVM)的初步诊断算法对拉曼光谱的多变量数据进行有效分类。通过PCA-SVM结合留一法交叉验证方法,实现了分类性能(敏感性和特异性分别为70%(21/30)和91%(42/46))。在这项有益的研究中,RS技术与PCA-SVM的结合为NPC的快速诊断提供了巨大的临床潜力。

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