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24 May 2018 Pre-clinical parametric imaging for tumor delineation with optical coherence tomography (Conference Presentation)
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Volumetric texture analysis method was developed for tumor segmentation of 3D optical coherence tomography (OCT) images. Images were divided into small volumes of interest (VOI) around each voxel. OCT speckle intensities from those VOIs were plotted as histograms and fitted with gamma distribution function to obtain curve shape (alpha) and scale (beta) parameters. Alpha/beta ratio 3D parametric images clearly delineated tumor and normal tissues otherwise not separable in structural OCT images. Method was validated with confocal fluorescence microscopy, tumor cells fluorescence and histological staining. Volumetric variation of OCT speckle intensities from same datasets was used to obtain microvascular information. Method was tested on three different tumor types (melanoma, cervical carcinoma and pancreas adenocarcinoma) in two mouse models: a) Nude mice with B16F10 pigmented murine melanoma tumors grown under the skin; b) NRG mice with human ME-180 and Bx-PC3 tumors grown in dorsal skin window chambers. Combined alpha/beta and microvascular images for all three tumor types demonstrate robustness of the method for detection of tissue variability and separation of tumor and normal tissues.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Valentin Demidov, Dina Guryanova, Costel Flueraru, and I. Alex Vitkin "Pre-clinical parametric imaging for tumor delineation with optical coherence tomography (Conference Presentation)", Proc. SPIE 10685, Biophotonics: Photonic Solutions for Better Health Care VI, 106851U (24 May 2018);

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