Results illustrate the potential of EGF-targeted fluorescent agents for in vivo molecular imaging, a technique that may aid in the diagnosis and characterization of oral neoplasia and allow real-time detection of tumor margins.

Abstract. In this longitudinal study, a mouse model of 4-nitroquinoline 1-oxide chemically induced tongue carcinogenesis was used to assess the ability of optical imaging with exogenous and endogenous contrast to detect neoplastic lesions in a heterogeneous mucosal surface. Widefield autofluorescence and fluorescence images of intact 2-NBDG-stained and proflavine-stained tissues were acquired at multiple time points in the carcinogenesis process. Confocal fluorescence images of transverse fresh tissue slices from the same specimens were acquired to investigate how changes in tissue microarchitecture affect widefield fluorescence images of intact tissue. Widefield images were analyzed to develop and evaluate an algorithm to delineate areas of dysplasia and cancer. A classification algorithm for the presence of neoplasia based on the mean fluorescence intensity of 2-NBDG staining and the standard deviation of the fluorescence intensity of proflavine staining was found to separate moderate dysplasia, severe dysplasia, and cancer from non-neoplastic regions of interest with 91% sensitivity and specificity. Results suggest this combination of noninvasive optical imaging modalities can be used in vivo to discriminate non-neoplastic from neoplastic tissue in this model with the potential to translate this technology to the clinic. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Biomarkers of cancer can indicate the presence of disease and serve as therapeutic targets. Our goal is to develop an optical imaging approach using molecularly targeted contrast agents to assess several centimeters of mucosal surface for mapping expression of multiple biomarkers simultaneously with high spatial resolution. The ability to image biomarker expression level and heterogeneity in vivo would be extremely useful for clinical cancer research, patient selection of personalized medicine, and monitoring therapy. In this proof-of-concept ex vivo study, we examined correlation of neoplasia with two clinically relevant biomarkers: epidermal growth factor receptor (EGFR) and metabolic activity. Two hundred eighty-six unique locations in nine samples of freshly resected oral mucosa were imaged after topically applying optical imaging agents EGF-Alexa 647 (to target EGFR) and 2-(N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino)-2-deoxyglucose (to target metabolic activity). Quantitative features were calculated from resulting fluorescence images and compared with tissue histopathology maps. The EGF-Alexa 647 signal correlated well with EGFR expression as indicated by immunohistochemistry. A classification algorithm for presence of neoplasia based on the signal from both contrast agents resulted in an area under the curve of 0.83. Regions with a posterior probability from 0.80 to 1.00 contained more than 50% neoplasia 99% (84/85) of the time. This study demonstrates a proof-of-concept of how noninvasive optical imaging can be used as a tool to study expression levels of multiple biomarkers and their heterogeneity across a large mucosal surface and how biomarker characteristics correlate with presence of neoplasia. Applications of this approach include predicting regions with the highest likelihood of disease, elucidating the role of biomarker heterogeneity in cancer biology, and identifying patients who will respond to targeted therapy.

This prospective pilot study evaluates the potential of high-resolution fiber optic microscopy (HRFM) to identify lymph node metastases in breast cancer patients. 43 lymph nodes were collected from 14 consenting breast cancer patients. Proflavine dye was topically applied to lymph nodes ex vivo to allow visualization of nuclei. 242 images were collected at 105 sites with confirmed histopathologic diagnosis. Quantitative statistical features were calculated from images, assessed with one-way ANOVA, and were used to develop a classification algorithm with the goal of objectively discriminating between normal and metastatic tissue. A classification algorithm using mean image intensity and skewness achieved sensitivity of 79% (27/34) and specificity of 77% (55/71). This study demonstrates the technical feasibility and diagnostic potential of HRFM with fluorescent contrast in the ex vivo evaluation of lymph nodes from breast cancer patients.

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