Multiresolution FLIM and Reflectance Confocal Microscopy to Detect Dysplasia

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DESCRIPTION (provided by applicant): Approximately 35,000 patients in the United States are diagnosed annually with cancer of the oral cavity, and 7,500 Americans die of this disease each year. The long-term goal of this research is to design, construct, and test a novel multiresolution fiber optic endoscope combining wide-field fluorescence lifetime imaging (FLIM) and reflectance confocal microscopy (RCM) to achieve unprecedented sensitivity and specificity of epithelial precancers in vivo. Subcellular resolution and the associated computational framework will enable interpretation of the resulting images to yield diagnostic information based on physiological, biochemical, and morphologic changes. The specific goal of this proposal is to apply the resulting multiresolution FLIM-RCM system to detect oral precancer. The specific aims of this proposal are to: 1) construct a bench-top multiresolution FLIM-RCM system to demonstrate the capability of FLIM-RCM to characterize normal, dysplastic, and cancerous tissue; 2) design and construct a fiber-based handheld FLIM-RCM probe for in vivo imaging of oral precancer and cancer; 3) optimize the sensitivity and specificity of FLIM-RCM for early detection of oral cancer; and 4) demonstrate the capability of FLIM-RCM to detect epithelial precancer in vivo. The successful completion of this work will enable the development of the first fiber-based multiresolution FLIM-RCM system for tissue characterization and will demonstrate its potential for non-invasive optical detection of oral premalignant and malignant lesions. This novel technology has significant potential to become a clinical diagnostic and screening tool, a navigation system for guiding standard biopsy and surgical intervention, and a tool for quantitative evaluation of responses to current and novel chemopreventive and therapeutic interventions. Although this proposal is focused on the detection of oral precancer, the imaging system and algorithms developed will be generally applicable to many of the cancers of the epithelium (e.g., cervix, colon, rectum, and bladder).