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Raman spectroscopic detection of high-grade cervical cytology: Using morphologically normal appearing cells

机译:高级宫颈细胞学的拉曼光谱检测:使用形态学正常出现的细胞

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This study aims to detect high grade squamous intraepithelial cells (HSIL) by investigating HSIL associated biochemical changes in morphologically normal appearing intermediate and superficial cells using Raman spectroscopy. Raman spectra (n?=?755) were measured from intermediate and superficial cells from negative cytology ThinPrep specimens (n?=?18) and from morphologically normal appearing intermediate and superficial cells from HSIL cytology ThinPrep specimens (n?=?17). The Raman data was subjected to multivariate algorithms including the standard principal component analysis (PCA)-linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA) together with random subsets cross-validation for discriminating negative cytology from HSIL. The PCA-LDA method yielded sensitivities of 74.9%, 72.8%, and 75.6% and specificities of 89.9%, 81.9%, and 84.5%, for HSIL diagnosis based on the dataset obtained from intermediate, superficial and mixed intermediate/superficial cells, respectively. The PLS-DA method provided improved sensitivities of 95.5%, 95.2% and 96.1% and specificities of 92.7%, 94.7% and 93.5% compared to the PCA-LDA method. The results demonstrate that the biochemical signatures of morphologically normal appearing cells can be used to discriminate between negative and HSIL cytology. In addition, it was found that mixed intermediate and superficial cells could be used for HSIL diagnosis as the biochemical differences between negative and HSIL cytology were greater than the biochemical differences between intermediate and superficial cell types.
机译:该研究旨在通过使用拉曼光谱研究形态学正常出现的中间体和浅表细胞的HSIL相关的生物化学变化来检测高级鳞状上皮细胞(HSIL)。从阴性细胞学薄雾样品(N?= 18)的中间体和浅表细胞中测量拉曼光谱(N?=α755),并从形态学上正常出现来自HSIL细胞学薄雾样品的中间体和浅表细胞(n?= 17)。将拉曼数据进行多元组分分析(PCA)-linear判别分析(LDA)和部分最小二乘判别分析(PLS-DA)以及随机亚族交叉验证,用于区分HSIL的阴性细胞学。 PCA-LDA方法产生的敏感性为74.9%,75.6%,75.6%,特异性为89.9%,81.9%和84.5%,其基于从中间,表面和混合中间/浅表细胞所获得的数据集。与PCA-LDA方法相比,PLS-DA方法提供了95.5%,95.2%和96.1%,94.7%和93.5%的特异性。结果表明,形态学正常出现的细胞的生化签名可用于区分阴性和HSIL细胞学。此外,发现混合中间体和浅表细胞可用于HSIL诊断,因为阴性和智能细胞学之间的生物化学差异大于中间体和浅表细胞类型之间的生化差异。

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