Raman spectroscopy is a vibrational spectroscopic technique that can be used to optically probe the molecular changes associated with diseased tissues. The objective of our study was to explore near-infrared (NIR) Raman spectroscopy for distinguishing tumor from normal bronchial tissue. Bronchial tissue specimens (12 normal, 10 squamous cell carcinoma (SCC) and 6 adenocarcinoma) were obtained from 10 patients with known or suspected malignancies of the lung. A rapid-acquisition dispersive-type NIR Raman spectroscopy system was used for tissue Raman studies at 785 nm excitation. High-quality Raman spectra in the 700 -1,800 cm -1 range from human bronchial tissues in vitro could be obtained within 5 sec. Raman spectra differed significantly between normal and malignant tumor tissue, with tumors showing higher percentage signals for nucleic acid, tryptophan and phenylalanine and lower percentage signals for phospholipids, proline and valine, compared to normal tissue. Raman spectral shape differences between normal and tumor tissue were also observed particularly in the spectral ranges of 1,000 -1,100, 1,200 -1,400 and 1,500 -1

A significant advantage of Raman spectroscopy as a noninvasive optical technique is its ability to detect subtle molecular or biochemical signatures within tissue. One of the major challenges for biomedical Raman spectroscopy is the removal of intrinsic autofluorescence background signals, which are usually a few orders of magnitude stronger than those arising from Raman scattering. A number of methods have been proposed for fluorescence background removal including excitation wavelength shifting, Fourier transformation, time gating, and simple or modified polynomial fitting. The single polynomial and the modified multi-polynomial fitting methods are relatively simple and effective, and thus are widely used in biological applications. However, their performance in real-time in vivo applications and low signal-to-noise ratio environments is sub-optimal. An improved automated algorithm for fluorescence removal has been developed based on modified multi-polynomial fitting, but with the addition of (1) a peak-removal procedure during the first iteration, and (2) a statistical method to account for signal noise effects. Experimental results demonstrate that this approach improves the automated rejection of the fluorescence background during real-time Raman spectroscopy and for in vivo measurements characterized by low signal-to-noise ratios.

Raman spectroscopy is a noninvasive optical technique capable of measuring vibrational modes of biomolecules within viable tissues. In this study, we evaluated the application of an integrated real-time system of Raman spectroscopy for in vivo skin cancer diagnosis. Benign and malignant skin lesions (n ¼ 518) from 453 patients were measured within 1 second each, including melanomas, basal cell carcinomas, squamous cell carcinomas, actinic keratoses, atypical nevi, melanocytic nevi, blue nevi, and seborrheic keratoses. Lesion classification was made using a principal component with general discriminant analysis and partial least-squares in three distinct discrimination tasks: skin cancers and precancers from benign skin lesions [receiver operating characteristic (ROC) ¼ 0.879]; melanomas from nonmelanoma pigmented lesions (ROC ¼ 0.823); and melanomas from seborrheic keratoses (ROC ¼ 0.898). For sensitivities between 95% and 99%, the specificities ranged between 15% and 54%. Our findings establish that real-time Raman spectroscopy can be used to distinguish malignant from benign skin lesions with good diagnostic accuracy comparable with clinical examination and other opticalbased methods. Cancer Res; 72(10); 2491-500. Ó2012 AACR.

Background:There is currently no quantitative tool for evaluating vitiligo treatment response using parametric methods.Objective: To develop and apply a simple clinical tool, the Vitiligo Area Scoring Index (VASI), to model the response of vitiligo to narrowband UV-B (NB-UV-B) phototherapy using parametric tests.

Early identification of high-risk disease could greatly reduce both mortality and morbidity due to oral cancer. We describe a simple handheld device that facilitates the direct visualization of oral-cavity fluorescence for the detection of high-risk precancerous and early cancerous lesions. Blue excitation light (400 to 460 nm) is employed to excite green-red fluorescence from fluorophores in the oral tissues. Tissue fluorescence is viewed directly along an optical axis collinear with the axis of excitation to reduce inter- and intraoperator variability. This robust, field-of-view device enables the direct visualization of fluorescence in the context of surrounding normal tissue. Results from a pilot study of 44 patients are presented. Using histology as the gold standard, the device achieves a sensitivity of 98% and specificity of 100% when discriminating normal mucosa from severe dysplasia/carcinoma in situ (CIS) or invasive carcinoma. We envisage this device as a suitable adjunct for oral cancer screening, biopsy guidance, and margin delineation.

A rapid dispersive-type near-infrared (NIR) Raman spectroscopy system and a Raman probe were developed to facilitate real-time, noninvasive, in vivo human skin measurements. Spectrograph image aberration was corrected by a parabolic-line fiber array, permitting complete CCD vertical binning, thereby yielding a 3.3-16-fold improvement in signal-to-noise ratio. Good quality in vivo cutaneous NIR Raman spectra free of interference from fiber fluorescence and silica Raman scattering can be acquired in less than 1 s, which greatly facilitates practical noninvasive tissue characterization and clinical diagnosis.

The capabilities of using gold nanoparticle based surface-enhanced Raman spectroscopy (SERS) to obtain blood serum biochemical information for non-invasive colorectal cancer detection were presented in this paper. SERS measurements were performed on two groups of blood serum samples: one group from patients (n = 38) with pathologically confirmed colorectal cancer and the other group from healthy volunteers (control subjects, n = 45). Tentative assignments of the Raman bands in the measured SERS spectra suggested interesting cancer specific biomolecular changes, including an increase in the relative amounts of nucleic acid, a decrease in the percentage of saccharide and proteins contents in the blood serum of colorectal cancer patients as compared to that of healthy subjects. Both empirical approach and multivariate statistical techniques, including principal components analysis (PCA) and linear discriminant analysis (LDA) were employed to develop effective diagnostic algorithms for classification of SERS spectra between normal and colorectal cancer serum. The empirical diagnostic algorithm based on the ratio of the SERS peak intensity at 725 cm(-1) for adenine to the peak intensity at 638 cm(-1) for tyrosine achieved a diagnostic sensitivity of 68.4% and specificity of 95.6%, whereas the diagnostic algorithms based on PCA-LDA yielded a diagnostic sensitivity of 97.4% and specificity of 100% for separating cancerous samples from normal samples. Receiver operating characteristic (ROC) curves further confirmed the effectiveness of the diagnostic algorithm based on PCA-LDA technique. The results from this exploratory study demonstrated that gold nanoparticle based SERS serum analysis combined with PCA-LDA has tremendous potential for the non-invasive detection of colorectal cancers.

We successfully acquire the in vivo Raman spectrum of melanin from human skin using a rapid near-infrared (NIR) Raman spectrometer. The Raman signals of in vivo cutaneous melanin are similar to those observed from natural and synthetic eumelanins. The melanin Raman spectrum is dominated by two intense and broad peaks at about 1580 and 1380 cm(-1), which can be interpreted as originating from the in-plane stretching of the aromatic rings and the linear stretching of the C-C bonds within the rings, along with some contributions from the C-H vibrations in the methyl and methylene groups. Variations in the peak frequencies and bandwidths of these two Raman signals due to differing biological environments have been observed in melanin from different sources. The ability to acquire these unique in vivo melanin signals suggests that Raman spectroscopy may be a useful clinical method for noninvasive in situ analysis and diagnosis of the skin.