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 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 1,500–1,700 cm^–1, which contain signals related to protein and lipid conformations and nucleic acid's CH stretching modes. The ratio of Raman intensities at 1,445 to 1,655 cm^–1 provided good differentiation between normal and malignant bronchial tissue (p < 0.0001). The results of this exploratory study indicate that NIR Raman spectroscopy provides significant potential for the noninvasive diagnosis of lung cancers in vivo based on the optic evaluation of biomolecules.

There are several available treatments for vitiligo but only limited data to actually guide the practical management of patients with vitiligo. Based on the currently available literature, it is difficult to compare the efficacy of different treatment modalities not only because measurement of repigmentation is not standardized, but also because most published studies have been uncontrolled. The rather slow response of vitiligo to treatment represents yet another impediment to conducting appropriate clinical trials for this condition.

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 = 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) = 0.879]; melanomas from nonmelanoma pigmented lesions (ROC = 0.823); and melanomas from seborrheic keratoses (ROC = 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 optical-based methods. Cancer Res; 72(10); 2491–500. ©2012 AACR.

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 $(400to460nm)$ 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.