Near-infrared raman spectroscopy for detection of gastric cancer peritoneal dissemination in vivo

Abstract

The nude mice injected with human gastric cancer cells (SGC-7901) in their peritoneums were chosen as the animal models of gastric cancer peritoneal dissemination in this research. The Raman spectra at 785nm excitation of both these nude mice which were in different tumor planting periods and the normal counterpart were taken in vivo in the imitate laparotomy. 205 spectra were collected. The spectra of different tissue types were compared and classified by Support Vector Machine (SVM) algorithm. Significant differences were showed between normal and malignant tissues. The gastric cancer nodules had lower Raman intensities at 870, 1330, 1450, and 1660cm−1, but higher at 1007, 1050, 1093 and 1209cm−1, compared with normal tissues. Additionally, the spectra of malignant tissues had two peaks around 1330 cm−1 (1297cm−1 and 1331cm-1), while the spectra of normal tissues had only one peak (1297cm−1). The differences were attributed to the intensities of the stretching bands of the nucleic acid, protein and water. These features could be used to diagnose gastric cancer. The Support Vector Machine (SVM) algorithm was used to classify these spectra. For normal and malignant tissues, the sensitivity, specificity and accuracy were 95.73%, 70.73% and 90.73%, respectively, while for different tumor planting periods, they were 98.82%, 98.73% and 98.78%. The experimental results show that Raman spectra differ significantly between cancerous and normal gastric tissues, which provides the experimental basis for the diagnosis of gastric cancer by Raman spectroscopy technology. And SVM algorithm can give the well generalized classification performance for the samples, which expands the application of mathematical algorithms in the classification.