Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/146309
Title: Feasibility evaluation of micro-optical coherence tomography (μOCT) for rapid brain tumor type and grade discriminations : μOCT images versus pathology
Authors: Yu, Xiaojun
Hu, Chi
Zhang, Wenfei
Zhou, Jie
Ding, Qianshan
Sadiq, M. T.
Fan, Zeming
Yuan, Zhaohui
Liu, Linbo
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2019
Source: Yu, X., Hu, C., Zhang, W., Zhou, J., Ding, Q., Sadiq, M. T., . . . Liu, L. (2019). Feasibility evaluation of micro-optical coherence tomography (μOCT) for rapid brain tumor type and grade discriminations : μOCT images versus pathology. BMC Medical Imaging, 19(1), 102-. doi:10.1186/s12880-019-0405-6
Journal: BMC Medical Imaging
Abstract: Background: Precise identification, discrimination and assessment of central nervous system (CNS) tumors is of critical importance to brain neoplasm treatment. Due to the complexity and limited resolutions of the existing diagnostic tools, however, it is difficult to identify the tumors and their boundaries precisely in clinical practice, and thus, the conventional way of brain neoplasm treatment relies mainly on the experiences of neurosurgeons to make resection decisions in the surgery process. The purpose of this study is to explore the potential of Micro-optical coherence tomography (μOCT) as an intraoperative diagnostic imaging tool for identifying and discriminating glioma and meningioma with their microstructure imaging ex vivo, which thus may help neurosurgeons to perform precise surgery with low costs and reduced burdens. Methods: Fresh glioma and meningioma samples were resected from patients, and then slices of such samples were excised and imaged instantly ex vivo with a lab-built μOCT, which achieves a spatial resolution of ~ 2.0 μm (μm). The acquired optical coherence tomography (OCT) images were pathologically evaluated and compared to their corresponding histology for both tumor type and tumor grade discriminations in different cases. Results: By using the lab-built μOCT, both the cross-sectional and en face images of glioma and meningioma were acquired ex vivo. Based upon the morphology results, both the glioma and meningioma types as well as the glioma grades were assessed and discriminated. Comparisons between OCT imaging results and histology showed that typical tissue microstructures of glioma and meningioma could be clearly identified and confirmed the type and grade discriminations with satisfactory accuracy. Conclusions: μOCT could provide high-resolution three-dimensional (3D) imaging of the glioma and meningioma tissue microstructures rapidly ex vivo. μOCT imaging results could help discriminate both tumor types and grades, which illustrates the potential of μOCT as an intraoperative diagnostic imaging tool to help neurosurgeons perform their surgery precisely in tumor treatment process.
URI: https://hdl.handle.net/10356/146309
ISSN: 1471-2342
DOI: 10.1186/s12880-019-0405-6
Schools: School of Electrical and Electronic Engineering 
Rights: © 2019 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Fulltext Permission: open
Fulltext Availability: With Fulltext
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