The purpose of this study was to explore the feasibility of using near-infrared (NIR) Raman spectroscopy and
multivariate techniques for distinguishing cancer from normal and benign tissue in the colon. A total of 105 colonic
specimens were used for Raman studies including 41 normal, 18 polyps, and 46 malignant tumors. The multivariate statistical techniques such as PCA-SVM were utilized to extract the significant Raman features and to develop
effective diagnostic algorithms for tissue classification. The results showed that high-quality Raman spectra in the
800-1800 cm<sup>-1</sup> range can be acquired from human colonic tissues in vitro, and Raman spectra differed significantly
between normal, benign and malignant tumor tissue. PCA-SVM yielded a diagnostic sensitivity of 100%, 100%, and
97.7%, and specificity of 99.8%, 100%, and 100%, respectively, for differentiation between normal, polyp, and
malignant tissue. Therefore, NIR Raman spectroscopy associated with multivariate techniques provides a significant
potential for the noninvasive diagnosis of colonic cancers <i>in vivo</i> based on optical evaluation of biomolecules.
A recent developed pattern recognition algorithm, Support Vector Machines (SVM), was employed to classify nearinfrared Raman spectroscopy data collected from normal and cancerous ENT tissues. Three types of classifiers, linear, 3<sup>rd</sup> order polynomial, and radial basis function, were used. Highest diagnostic accuracy was obtained by 3<sup>rd</sup> order polynomial with a sensitivity of 91.86% and a specificity of 100%. The possibility to simplify SVM implementation was also explored by using principal component analysis (PCA) to extract significant principal components. It was found that the first five principal components as the data inputs were already sufficient to produce sensitivities of 100% and specificities of 100% for all these three classifiers. Combination PCA and linear discriminant analysis (LDA) to classify these ENT data was also performed and analysis results show that both methods, combination PCA & SVM and PCA & LDA yielded comparable performance.
As part of an ongoing larger study of the molecular and supramolecular foundations of bone tissue biomechanics, we report thermal perturbations to bone mineral and related model compounds. The response of bone tissue to external mechanical and thermal loading under a variety of conditions is used to elucidate the response to physiologically relevant loads. Here NMR spectroscopy is used in conjunction with Raman spectroscopy to elucidate the mineral structure of the bone and track changes in the lattice due to temperature variation. Changes in the bone lattice are studied by examining the Raman spectral band widths and positions of the phosphate and carbonate bands. Expansion of the lattice leads to increased band widths as local ion motion is facilitated. Larger effects are found in undeproteinated bone powder than in deproteinated bone mineral powder. 1H MAS NMR is used to track the water content of deproteinated bone as a function of temperature. The differing effects observed in undeproteinated bone powder and deproteinated bone mineral powder suggest that mineral crystallite expansion may involve mechanical constraint by the bone matrix. 13C MAS NMR spectroscopy revealed a loss of carbonate in deproteinated bone mineral when heated to 225 C. This is a significantly lower temperature than previously reported for removal of carbonate from synthetic apatite material. The properties of bone mineral influenced by even small perturbations such as temperature elevation or reduction depend on the presence of matrix. It is reasonable to assume that bone tissue response to other external loads, including compression or bending under normal physiological conditions also depend on the interaction of mineral and matrix.