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|Title:||Evaluating micro-optical coherence tomography as a feasible imaging tool for pancreatic disease diagnosis||Authors:||Yu, Xiaojun
|Keywords:||Engineering::Electrical and electronic engineering||Issue Date:||2018||Source:||Yu, X., Ding, Q., Hu, C., Mu, G., Deng, Y., Luo, Y., . . . Liu, L. (2019). Evaluating micro-optical coherence tomography as a feasible imaging tool for pancreatic disease diagnosis. IEEE Journal of Selected Topics in Quantum Electronics, 25(1), 6800108-. doi:10.1109/JSTQE.2018.2827662||Journal:||IEEE Journal of Selected Topics in Quantum Electronics||Abstract:||Pancreatic cancer is one of the leading causes of cancer mortality worldwide due to the lack of reliable tools for early diagnosis of this cancer. In this study, we evaluated the feasibility of micro-optical coherence tomography (μOCT) as an imaging tool for the diagnosis of pancreatic cancers. Specifically, we constructed a μOCT device that achieves a resolution of 1.67 ± 0.01 μm and 1.79 ± 0.01 μm in axial and lateral directions, respectively, and acquired three-dimensional μOCT images of mouse, rat, and human pancreatic specimens ex vivo. We compared the results of μOCT with those of the corresponding histology. In μOCT images of normal pancreatic specimens, the detailed cellular and subcellular-level pancreatic microstructures, e.g., the islet of Langerhans (IL), IL cell nuclei, blood vessels, and serous acini, could be clearly resolved in different cases. To the best of our knowledge, this study is the first to demonstrate that the cellular and subcellular structures of pancreatic tissues were identified using OCT. More importantly, we showed that these normal cellular-level structures were lost in μOCT images of cancerous specimens, demonstrating the feasibility of differentiating malignant lesions from normal tissues using μOCT. Moving forward, the development of an intraoperative imaging device may realize optical biopsies in vivo or real-time cellular-resolution examination of specimens from needle aspiration biopsies.||URI:||https://hdl.handle.net/10356/143867||ISSN:||1077-260X||DOI:||10.1109/JSTQE.2018.2827662||Rights:||© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/JSTQE.2018.2827662.||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Journal Articles|
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