The Study On Diagnosis Of Lung Cancer Using Serum Auto-fluorescence And Raman Spectroscopy

Laser-induced fluorescence spectroscopy could reflect the various features from the composition, structure and microenvironment of fluorescent substance. In this paper the method of laser-induced auto-fluorescence Raman spectrum was used to analyze the spectrum of serum of lung cancer patients and healthy people to find some differences and to confirm whether the laser-induced auto-fluorescence Raman spectrum might be used to diagnose the lung cancer.Ar-ion laser (488.0nm) was used to radiate serum of lung cancer patients and healthy people, and the data of auto-fluorescence Raman spectrum was collected from 492nm to 640nm. The principal component analysis (PCA) and discriminant analysis were used for analysis and data processing of auto-fluorescence spectrum creatively.From the statistic results of auto-fluorescence Raman spectrum we could obtain several conclusions: the auto-fluorescence spectroscopy of serum of lung cancer patients is smoother than that of healthy people; the main peak of lung cancer patients(533nm) appears red shift compared with healthy people(555nm); with the number of radiates increasing, the Raman peak of the same sample was diminished. Then we analyzed the PCA-LDA of the intensity ratio by SPSS, and find that the error probability of diagnosis of lung cancer is 13.3%, and the healthy people is 5%. The sensitivity of the diagnosis is 86.7%, the specificity of the diagnosis is 95%, and the accuracy of the diagnosis is 90%. This analysis method has a high rate of accuracy. It may be useful for cancer diagnosis, treatment and early prevention.We analyzed the mechanism and obtained that the differences of auto- fluorescence Raman spectroscopy were mainly affected byβ-Carotene; Vitamin C, Hematoporphyrin derivative, Zinc porphyrin and the change of serum tissue microenvironment may cause the red shift.