OBJECTIVE: Fourier-transform (FT)-Raman spectroscopy has been used to explore the changes in the vibrational bands of normal, dysplastic (DE) and squamous cell carcinoma (SCC) tissues. BACKGROUND DATA: Raman spectroscopy has been applied as a diagnostic tool for the detection of cancers, due to its sensitivity to the changes in molecular composition and conformation that occurs in malignant tissues. The detection of weak Raman signals from biotissues becomes easier by FT-Raman due to fluorescence suppression. METHODS: A carcinogen (7,12-dimethybenz[a]anthracene [DMBA]) was applied daily in the oral pouch of 21 hamster to induce oral carcinoma. After 14 weeks, the fragments of squamous cell carcinomas and oral normal tissue were collected and analyzed by FT-Raman spectroscopy, using a 1064-nm Nd:YAG laser line as an excitation source. A total of 123 spectra were obtained and divided in normal and malignant tissue groups, and analyzed statistically through principal components analysis (PCA) and classified using Mahalanobis distance. RESULTS: Major differences between normal and malignant spectra seem to arise from the composition, conformational, and structural changes of proteins, and possible increase of its content in malignant epithelia. An algorithm based on PCA was able to separate the samples into two groups--normal and carcinoma. For the algorithm training group, 91% sensitivity and 69% specificity were observed, while the prospective group had 100% sensitivity and 55% specificity. CONCLUSION: The algorithm based on PCA has the potential for classifying Raman spectra and can be useful for detection of dysplastic and malign oral lesion.
OBJECTIVE: Fourier-transform (FT)-Raman spectroscopy has been used to explore the changes in the vibrational bands of normal, dysplastic (DE) and squamous cell carcinoma (SCC) tissues. BACKGROUND DATA: Raman spectroscopy has been applied as a diagnostic tool for the detection of cancers, due to its sensitivity to the changes in molecular composition and conformation that occurs in malignant tissues. The detection of weak Raman signals from biotissues becomes easier by FT-Raman due to fluorescence suppression. METHODS: A carcinogen (7,12-dimethybenz[a]anthracene [DMBA]) was applied daily in the oral pouch of 21 hamster to induce oral carcinoma. After 14 weeks, the fragments of squamous cell carcinomas and oral normal tissue were collected and analyzed by FT-Raman spectroscopy, using a 1064-nm Nd:YAG laser line as an excitation source. A total of 123 spectra were obtained and divided in normal and malignant tissue groups, and analyzed statistically through principal components analysis (PCA) and classified using Mahalanobis distance. RESULTS: Major differences between normal and malignant spectra seem to arise from the composition, conformational, and structural changes of proteins, and possible increase of its content in malignant epithelia. An algorithm based on PCA was able to separate the samples into two groups--normal and carcinoma. For the algorithm training group, 91% sensitivity and 69% specificity were observed, while the prospective group had 100% sensitivity and 55% specificity. CONCLUSION: The algorithm based on PCA has the potential for classifying Raman spectra and can be useful for detection of dysplastic and malign oral lesion.
Authors: Froukje L J Cals; Tom C Bakker Schut; José A Hardillo; Robert J Baatenburg de Jong; Senada Koljenović; Gerwin J Puppels Journal: Lab Invest Date: 2015-08-03 Impact factor: 5.662
Authors: Elizabeth M Kanter; Shovan Majumder; Elizabeth Vargis; Amy Robichaux-Viehoever; Gary J Kanter; Heidi Shappell; Howard W Jones; Anita Mahadevan-Jansen Journal: J Raman Spectrosc Date: 2009-02 Impact factor: 3.133
Authors: Jouber Mateus dos Santos Aciole; Isabele Cardoso Vieira de Castro; Luiz Guilherme Pinheiro Soares; Artur Felipe Santos Barbosa; Gilberth Tadeu dos Santos Aciole; Landulfo Silveira; Antonio L B Pinheiro Journal: Lasers Med Sci Date: 2014-01-29 Impact factor: 3.161