DESCRIPTION (provided by applicant): In 2008, there were 47,560 new cases of head and neck cancers (HNC) in the United States. Early detection of new and locally recurrent cancers is clinically important to reduce not only cancer related mortality, but also treatment associated morbidity as it impacts multiple organ functions including respiration, olfaction, hearing, eating, swallowing, and speaking. Discrimination of cancer from non-malignant tissues is dependent on pathological examination of lesion biopsies. Although these lesions are identified during an initial clinical exam, obtaining a specimen for analysis can be technically challenging and uncomfortable for patients. Furthermore, there is an immense amount of labor, facility, and monetary resources that are expended on patients who ultimately have no malignancy. Once carcinoma is identified, treatment for advanced HNC commonly requires a combination of surgery, radiation, and chemotherapy to maximize the chance for cure. Multi-modality treatment causes undesirable side effects that affect a patient's physical well-being, e.g. eating and speaking, and quality of life. Using fewer modalities can minimize morbidity but with a potentially increased risk for treatment failure. Determination of the optimal strategy to both minimize morbidity and optimize the chance for cure is a major clinical challenge. There is a significant unmet clinical need associated with the screening and treatment of head and neck cancers. Our long-term goal is to develop a portable, optical technology that can provide accurate and precise analysis of tissue absorption and scattering of local tissue sites guided by white light and auto fluorescence imaging. The initial market will be applications related to the diagnosis and guided therapy of head and neck cancers. The clinical value of this tool would require it to be fast and non- invasive such that feedback could be obtained during the patient's visit, portable such that it can be used in an ambulatory setting and quantitative with minimal operator bias such that data obtained is consistent across operators and patients. |