Multispectral Optical Tissue Imager for Skin

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DESCRIPTION (provided by applicant): Skin cancer the most common type of cancer in the United States, accounting for nearly half of all reported incidences of cancer. Both melanoma and nonmelanoma skin cancer are associated with damage caused by sun exposure and the use of sunscreens has been advocated as the best prevention of these diseases. Studies to demonstrate the photoprotective effect of UV absorbers are often conducted using animal models which require sacrificing the animals to perform a number of measurements along the longitudinal studies. Besides this, such measurements, including in vivo ones are subjective and therefore, prone to inter- and intra- subject variability. A Multispectral Optical Tissue Imager (MOTI) for skin is proposed that will apply statistical models of spectra as a means to detect and track the changes in tissue structure due to UV exposure damage in an animal model. The proposed device acquires spectral signatures from the UV exposed skin of the animal under study. Then a set of analytical tools will be used to detect and track the progression of the damage. Such tools include Principal Component Analysis (PCA) and Blind Source Separation (BSS). PCA is a technique used in hyperspectral applications to detect the features that describe the variability of data whereas BSS is used to solve problems that require the identification of the signals that are combined in order to generate a measurable signal. The use of PCA and BSS for analyzing the change of spectral characteristics in skin has not been described in the literature. Because of the magnitude of the skin cancer problem and the pervasiveness of the animal model to find the means to solve it, our proposed instrument will make a significant impact in the clinical community for many more years. Commercialization Potential: The MOTI system can provide quantitative information of the changes in cellular structure due to UV exposure in an animal model and thus has the potential to advance the diagnostic techniques and time to diagnosis for skin cancer.