Dynamic optical contrast imaging (DOCI) is a novel optical imaging technology that rapidly generates image contrast from measurements of aggregate endogenous fluorescence lifetime in a clinically meaningful field of view. Recently, our use of this system in both human ex-vivo and in-vivo specimens generated statistically significant contrast between tumor and adjacent normal tissue in biopsies taken from patients undergoing surgery for head and neck squamous cell carcinoma and primary hyperthyroidism. In this work we evaluated the components and resolution of our next-generation DOCI system. We also standardized the quantitative output of our system against the fluorescence lifetime values of three dye standards with monoexponential decay using a commercial Leica two-photon fluorescence lifetime imaging microscope. Significantly, our system continued to demonstrate clinically meaningful contrast between tissue samples with multiexponential decay in near real-time.
KEYWORDS: Luminescence, Tissues, Imaging systems, Data modeling, Convolution, Optical imaging, Mathematical modeling, Signal to noise ratio, Systems modeling, Statistical modeling
Dynamic Optical Contrast Imaging (DOCi) is an imaging technique that generates image contrast through ratiometric measurements of the autouflorescence decay rates of aggregate uorophores in tissue. This method enables better tissue characterization by utilizing wide-field signal integration, eliminating constraints of uniform illumination, and reducing time-intensive computations that are bottlenecks in the clinical translation of traditional fluorescence lifetime imaging. Previous works have demonstrated remarkable tissue contrast between tissue types in clinical human pilot studies [Otolaryngology-Head and Neck Surgery 157, 480 (2017)]. However, there are still challenges in the development of several subsystems, which results in existing works to use relative models. A comprehensive mathematical framework is presented to describe the contrast mechanism of the DOCi system to allow intraoperative quantitative imaging, which merits consideration for evaluation in measuring tissue characteristics in several important clinical settings.
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