| Raman spectrum is a kind of molecule scattering spectroscopy. It can be used to analysis and detect the molecule structure.Raman spectrum has a lot of advantages, such as characteristic of non-osculatory, non-destructive, high sensitivity, short time, a spot of sample and non-preparative sample and so on. Due to these characteristic, Raman spectrum are widely used in material, environment, chemistry, biomedicine, archeology etc, and made extraordinary contribution.In this thesis, in order to search a new method which can diagnose postoperative breast cancer patients whether recurrent or metastatic, we research the Surface Enhanced Raman Spectrum (SERS) of serum form postoperative breast cancer patients., and adopting Principal Component Analysis (PCA) to distinguish the SERS of serum between postoperative the followed normal breast cancer patients and postoperative recurrent or metastatic breast cancer patients, the main content:Firstly, we introduce the basic theory of Raman spectroscopy, SERS and the application of Raman spectroscopy.Secondly, we introduce the basic idea and method of calculation of PCA.At last, we compare the characteristics of SERS of serum between two groups of patients. One is that10serum samples from postoperative recurrent or metastatic breast cancer patients. The other is that10serum samples from postoperative the followed normal breast cancer patients. Firstly, intensity and shift of characteristics peak is analyzed we found that the structure of molecule, the structure of lipid and the glucide saccharide environment are all changed. Through using the Matlab to complete the principal component analysis (PCA), we analyze the13elements of SERS of serum about the two groups patients. It reveals that the effectivity of distinguishing two groups patients is95%.It means that using PCA to research SERS of Serum from postoperative Breast Cancer Patients is an useful method to diagnose postoperative breast cancer patients whether recurrent or metastatic. |
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