Gastric cancer differentiation using Fourier transform near-infrared spectroscopy with unsupervised pattern recognition
[Display omitted] ► Major spectral differences were observed in three regions. ► Unsupervised pattern recognition techniques (PCA and CA) were used. ► The sensitivity, specificity and accuracy were 100%, 68.2% and 81.1%, respectively. The manuscript has investigated the application of near-infrared...
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Published in | Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Vol. 101; pp. 127 - 131 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
England
Elsevier B.V
15.01.2013
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Subjects | |
Online Access | Get full text |
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Summary: | [Display omitted]
► Major spectral differences were observed in three regions. ► Unsupervised pattern recognition techniques (PCA and CA) were used. ► The sensitivity, specificity and accuracy were 100%, 68.2% and 81.1%, respectively.
The manuscript has investigated the application of near-infrared (NIR) spectroscopy for differentiation gastric cancer. The 90 spectra from cancerous and normal tissues were collected from a total of 30 surgical specimens using Fourier transform near-infrared spectroscopy (FT-NIR) equipped with a fiber-optic probe. Major spectral differences were observed in the CH-stretching second overtone (9000–7000cm−1), CH-stretching first overtone (6000–5200cm−1), and CH-stretching combination (4500–4000cm−1) regions. By use of unsupervised pattern recognition, such as principal component analysis (PCA) and cluster analysis (CA), all spectra were classified into cancerous and normal tissue groups with accuracy up to 81.1%. The sensitivity and specificity was 100% and 68.2%, respectively. These present results indicate that CH-stretching first, combination band and second overtone regions can serve as diagnostic markers for gastric cancer. |
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ISSN: | 1386-1425 1873-3557 |
DOI: | 10.1016/j.saa.2012.09.037 |