S K Teh1, W Zheng, K Y Ho, M Teh, K G Yeoh, Z Huang. 1. Optical Bioimaging Laboratory, Department of Bioengineering, Faculty of Engineering, National University of Singapore, Singapore.
Abstract
BACKGROUND: The aim of this study was to evaluate the feasibility of using near-infrared (NIR) Raman spectroscopy for early diagnosis and typing of intestinal and diffuse adenocarcinoma of the stomach. METHODS: A dispersive-type NIR Raman system was used for tissue measurements. One hundred gastric tissue samples from 62 patients who underwent endoscopy or gastrectomy were used (70 normal tissue specimens and 30 adenocarcinomas). Principal components analysis (PCA) and multinomial logistic regression (MNLR) were used to develop diagnostic algorithms for tissue classification. RESULTS: High-quality Raman spectra ranging from 800 to 1800 cm(-1) were acquired from gastric tissue within 5 s. There were significant differences in Raman spectra between normal stomach and the two gastric adenocarcinoma subtypes, particularly in the spectral ranges 850-1150, 1200-1500 and 1600-1750 cm(-1), which contain signals related to proteins, nucleic acids and lipids. PCA-MNLR achieved predictive accuracies of 88, 92 and 94 per cent for normal stomach, and intestinal- and diffuse-type gastric adenocarcinomas respectively. CONCLUSION: NIR Raman spectroscopy can detect gastric malignancy and identify the subtype of gastric adenocarcinoma. Copyright (c) 2010 British Journal of Surgery Society Ltd. Published by John Wiley & Sons, Ltd.
BACKGROUND: The aim of this study was to evaluate the feasibility of using near-infrared (NIR) Raman spectroscopy for early diagnosis and typing of intestinal and diffuse adenocarcinoma of the stomach. METHODS: A dispersive-type NIR Raman system was used for tissue measurements. One hundred gastric tissue samples from 62 patients who underwent endoscopy or gastrectomy were used (70 normal tissue specimens and 30 adenocarcinomas). Principal components analysis (PCA) and multinomial logistic regression (MNLR) were used to develop diagnostic algorithms for tissue classification. RESULTS: High-quality Raman spectra ranging from 800 to 1800 cm(-1) were acquired from gastric tissue within 5 s. There were significant differences in Raman spectra between normal stomach and the two gastric adenocarcinoma subtypes, particularly in the spectral ranges 850-1150, 1200-1500 and 1600-1750 cm(-1), which contain signals related to proteins, nucleic acids and lipids. PCA-MNLR achieved predictive accuracies of 88, 92 and 94 per cent for normal stomach, and intestinal- and diffuse-type gastric adenocarcinomas respectively. CONCLUSION: NIR Raman spectroscopy can detect gastric malignancy and identify the subtype of gastric adenocarcinoma. Copyright (c) 2010 British Journal of Surgery Society Ltd. Published by John Wiley & Sons, Ltd.
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