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Resonance Raman Spectroscopy of human brain metastasis of lung cancer analyzed by blind source separation

机译:盲源分离法分析肺癌人脑转移的共振拉曼光谱

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摘要

Resonance Raman (RR) spectroscopy offers a novel Optical Biopsy method in cancer discrimination by a means of enhancement in Raman scattering. It is widely acknowledged that the RR spectrum of tissue is a superposition of spectra of various key building block molecules. In this study, the Resonance Raman (RR) spectra of human metastasis of lung cancerous and normal brain tissues excited by a visible selected wavelength at 532 ran are used to explore spectral changes caused by the tumor evolution. The potential application of RR spectra human brain metastasis of lung cancer was investigated by Blind Source Separation such as Principal Component Analysis (PCA). PCA is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components (PCs). The results show significant RR spectra difference between human metastasis of lung cancerous and normal brain tissues analyzed by PCA. To evaluate the efficacy of for cancer detection, a linear discriminant analysis (LDA) classifier is utilized to calculate the sensitivity, and specificity and the receiver operating characteristic (ROC) curves are used to evaluate the performance of this criterion. Excellent sensitivity of 0.97, specificity (close to 1.00) and the Area Under ROC Curve (AUC) of 0.99 values are achieved under best optimal circumstance. This research demonstrates that RR spectroscopy is effective for detecting changes of tissues due to the development of brain metastasis of lung cancer. RR spectroscopy analyzed by blind source separation may have potential to be a new armamentarium.
机译:共振拉曼光谱(RR)通过增强拉曼散射技术提供了一种新颖的光学活检方法,用于癌症鉴别。众所周知,组织的RR光谱是各种关键构件分子的光谱的叠加。在这项研究中,人类的肺癌和正常脑组织的转移的共振拉曼光谱(RR)由532 nm的可见选定波长激发,用于探索由肿瘤进化引起的光谱变化。通过盲源分离(例如主成分分析(PCA))研究了RR光谱在人脑肺癌转移中的潜在应用。 PCA是一种统计过程,它使用正交变换将一组可能相关的变量的观测值转换为一组线性不相关的变量值,称为主成分(PC)。结果显示,通过PCA分析,肺癌和正常脑组织的人转移之间的RR光谱差异显着。为了评估癌症检测的功效,使用线性判别分析(LDA)分类器来计算灵敏度,并使用特异性和受体工作特征(ROC)曲线来评估该标准的性能。在最佳的最佳情况下,可获得极佳的灵敏度0.97,特异性(接近1.00)和ROC曲线下面积(AUC)值为0.99。这项研究表明,RR光谱法可有效检测由于肺癌脑转移发生而引起的组织变化。通过盲源分离分析的RR光谱可能具有成为新武器库的潜力。

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  • 来源
    《Neural Imaging and Sensing》|2017年|100511i.1-100511i.7|共7页
  • 会议地点 San Francisco(US)
  • 作者单位

    Air Force General Hospital, PLA, No.30 Fuchenglu, Haidian District, Beijing, 100142, R. R. China;

    Institute for Ultrafast Spectroscopy and Lasers, Department of Physics, The City College of the City University of New York, 160 Convent Avenue, New York, NY 10031, U. S. A;

    Institute for Ultrafast Spectroscopy and Lasers, Department of Physics, The City College of the City University of New York, 160 Convent Avenue, New York, NY 10031, U. S. A;

    Air Force General Hospital, PLA, No.30 Fuchenglu, Haidian District, Beijing, 100142, R. R. China;

    Department of Neurosurgery, PLA General Hospital, 28th Fuxing Road, Beijing, 100039, R. R. China;

    Beijing Cancer Hospital, No.52 Fuchenglu, Haidian District, Beijing, 100142, R. R. China;

    Beijing Cancer Hospital, No.52 Fuchenglu, Haidian District, Beijing, 100142, R. R. China;

    Institute of Physics, Chinese Academy of Sciences (CAS), Beijing, 100190, R. R. China;

    Institute for Ultrafast Spectroscopy and Lasers, Department of Physics, The City College of the City University of New York, 160 Convent Avenue, New York, NY 10031, U. S. A;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Resonance Raman Spectroscopy; Human brain metastasis of lung cancerous tissues; Blind Source Separation (BSS); Principal component analysis (PCA); Linear Discriminant Analysis (LDA) classifier;

    机译:共振拉曼光谱;肺癌组织的人脑转移;盲源分离(BSS);主成分分析(PCA);线性判别分析(LDA)分类器;

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