Chem. J. Chinese Universities ›› 2015, Vol. 36 ›› Issue (1): 74.doi: 10.7503/cjcu20140415

• Analytical Chemistry • Previous Articles     Next Articles

Study on Fresh Breast Tissues by Raman Spectroscopy Based on Robust Statistics

ZHENG Chao1, ZHANG Haipeng1, HAN Bing1, LIANG Lijia2, ZOU Yabin1, XU Shuping2, LIN Heping3, XU Weiqing2,*, FAN Zhimin1,*()   

  1. 1. First Hospital of Jilin University, Changchun 130021, China
    2. State Key Laboratory of Supramolecular Structure and Materials, Jilin University, Changchun 130012, China
    3. College of Computer Science and Technology, Northeast Normal University, Changchun 130117, China
  • Received:2014-04-30 Revised:2014-12-16 Online:2015-01-10 Published:2014-12-16
  • Contact: XU Weiqing,FAN Zhimin E-mail:fanzhimn@163. com
  • Supported by:
    Supported by the National Natural Science Foundation of China(Nos81202078, 21373096), the National Instrumentation Program of the Ministry of Science and Technology of China(No2011YQ03012408), the Science and Technology Development Plan of Jilin Province, China

Abstract:

A portable Raman spectrometer was used for distinguishing the characteristics of normal, malignant and benign fresh breast tissues. Robust statistics method was used to analyze the Raman spectrum data, and a standard Raman spectral atlas of fresh breast tissues was established. Based on the spectral profiles of the Raman spectral standard atlas, the presence of lipids(1078, 1297, 1437, 1653, 1746 cm-1) is indicated in normal tissue. And proteins(1259, 1530, 1650 cm-1) are found in benign and malignant tissues. Among normal, benign and malignant tissues, proteins(1340 cm-1) and β-carotene(1534 cm-1) are found to be good discrimination parameters, which are hardly achieved by other typical statistical methods. The established fresh breast tissue Raman spectral standard atlas based on robust statistics laid the foundation of benign and malignant breast lesions identify model.

Key words: Raman spectroscopy, Breast cancer, Robust statistics

CLC Number: 

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