In an effort to increase the efficiency and cure rate of nonmelanoma skin cancer (NMSC) excisions, we have developed a point-of-care method of imaging and evaluation of skin cancer margins. We evaluate the skin surgical specimens using a smart, near-infrared probe (6qcNIR) that fluoresces in the presence of cathepsin proteases overexpressed in NMSC. Imaging is done with an inverted, flying-spot fluorescence scanner that reduces scatter, giving a 70% improved step response as compared to a conventional imaging system. We develop a scheme for careful comparison of fluorescent signals to histological annotation, which involves image segmentation, fiducial-based registration, and nonrigid free-form deformation on fluorescence images, corresponding color images, “bread-loafed” tissue images, hematoxylin and eosin (H&E)-stained slides, and pathological annotations. From epidermal landmarks, spatial accuracy in the bulk of the sample is ∼500 μm, which when extrapolated with a linear stretch model, suggests an error at the margin of ∼100 μm, within clinical reporting standards. Cancer annotations on H&E slides are transformed and superimposed on the fluorescence images to generate the final results. Using this methodology, fluorescence cancer signals are generally found to correspond spatially with histological annotations. This method will allow us to accurately analyze molecular probes for imaging skin cancer margins.
We have developed a point-of-care imaging method for non-melanoma skin cancer surgery whereby excised tissues are imaged with a smart near infrared quenched protease probe (6qcNIR) that fluoresces in the presence of overexpressed cathepsin proteases in basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), and determine if margins are clear of cancer. Here we report our imaging system and our method to validate the detection of skin cancer. We imaged skin samples with an inverted, flying spot fluorescence scanner (LI-COR Odyssey CLx). Scatter in Odyssey system was greatly reduced giving an 80% improvement in the step response as compared to a previously used macroscopic imaging system with imaging of a fluorescence phantom. We developed a validation scheme for careful comparison of fluorescent cancer signal to histology annotation, involving image segmentation, fiducial based registration and non-rigid free-form deformation, using our LI-COR fluorescence images, corresponding color images, bread-loafed tissue images, H&E slides and pathologist annotation. Spatial accuracy in the bulk of the sample was ∼500 μm. Extrapolated with a linear stretch model suggests an error at the margin of <100 μm. Cancer annotations on H&E slides were transformed and superimposed on the probe fluorescence to generate the final result. In general, the fluorescence cancer signal corresponded with histological annotation.
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