Preliminary study on early detection technology of lung cancer based on surface-enhanced Raman spectroscopy

This paper analyzes the data of surface-enhanced Raman spectroscopy of the saliva which come from the issues of 19 lung cancers and 45 normal people. The original data are normalized, and then selected the 14 screened characteristic peaks for further Logistic Regression Analysis using SPSS16.0 software. There is significant difference between lung cancer and normal human´s Raman spectra of saliva and the accuracy is up to 96.9% by Logistic Regression Analysis. It is also found that two spectrum peaks are different between the normal and the lung cancer´s SERS: Raman peak 758 cm-1 is existed in the normal, compared with lower 7cm-1 in patients of lung cancer, and Raman peak 1244cm-1 is existed in the normal compared with lower 11cm-1 in patients of lung cancer. It provides characteristic peaks for clinical diagnosis of lung cancer, especially in the early period.