6 March 2018 Molecular imaging and validation of non-melanoma skin cancer margins
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Abstract
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.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yiqiao Liu, Yiqiao Liu, Ethan Walker, Ethan Walker, InYoung Kim, InYoung Kim, Mark Biro, Mark Biro, Sukanya Raj Iyer, Sukanya Raj Iyer, Bo Zhou, Bo Zhou, Matthew Bogyo, Matthew Bogyo, James P. Basilion, James P. Basilion, Daniel Popkin, Daniel Popkin, David Wilson, David Wilson, } "Molecular imaging and validation of non-melanoma skin cancer margins", Proc. SPIE 10579, Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications, 105790Y (6 March 2018); doi: 10.1117/12.2293847; https://doi.org/10.1117/12.2293847
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