Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/87751
Title: Diagnosis of gastric cancer using near-infrared Raman spectroscopy and classification and regression tree techniques
Authors: Teh, S.K. 
Zheng, W. 
Ho, K.Y.
Teh, M.
Yeoh, K.G.
Huang, Z. 
Keywords: cancer diagnosis
classification and regression tree
near-infrared Raman spectroscopy
stomach
Issue Date: 2008
Citation: Teh, S.K., Zheng, W., Ho, K.Y., Teh, M., Yeoh, K.G., Huang, Z. (2008). Diagnosis of gastric cancer using near-infrared Raman spectroscopy and classification and regression tree techniques. Journal of Biomedical Optics 13 (3) : -. ScholarBank@NUS Repository.
Abstract: The purpose of this study is to apply near-infrared (NIR) Raman spectroscopy and classification and regression tree (CART) techniques for identifying molecular changes of tissue associated with cancer transformation. A rapid-acquisition NIR Raman system is utilized for tissue Raman spectroscopic measurements at 785-nm excitation. 73 gastric tissue samples (55 normal, 18 cancer) from 53 patients are measured. The CART technique is introduced to develop effective diagnostic algorithms for classification of Raman spectra of different gastric tissues. 80% of the Raman dataset are randomly selected for spectral learning, while 20% of the dataset are reserved for validation. High-quality Raman spectra in the range of 800to1800cm -1 are acquired from gastric tissue within 5s. The diagnostic sensitivity and specificity of the learning dataset are 90.2 and 95.7%; and the predictive sensitivity and specificity of the independent validation dataset are 88.9 and 92.9%, respectively, for separating cancer from normal. The tissue Raman peaks at 875 and 1745cm -1 are found to be two of the most significant features to discriminate gastric cancer from normal tissue. NIR Raman spectroscopy in conjunction with the CART technique has the potential to provide an effective and accurate diagnostic means for cancer detection in the gastric system. © 2008 Society of Photo-Optical Instrumentation Engineers.
Source Title: Journal of Biomedical Optics
URI: http://scholarbank.nus.edu.sg/handle/10635/87751
ISSN: 10833668
Appears in Collections:Staff Publications

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