Optical percutaneous needle biopsy of the liver : a pilot animal and clinical study |
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Author: | Dremin, Viktor1,2; Potapova, Elena1; Zherebtsov, Evgeny1,3; |
Organizations: |
1Research & Development Center of Biomedical Photonics, Orel State University, Orel 302026, Russia 2Aston Institute of Photonic Technologies, School of Engineering & Applied Science, Aston University, Birmingham B4 7ET, UK 3Faculty of Information Technology and Electrical Engineering, Optoelectronics and Measurement Techniques Unit, University of Oulu, Oulu 90570, Finland
4Department of Anatomy, Operative Surgery and Emergency Medicine, Medical Institute, Orel State University, Orel 302026, Russia
5Orel Regional Clinical Hospital, Orel 302028, Russia |
Format: | article |
Version: | published version |
Access: | open |
Online Access: | PDF Full Text (PDF, 3.3 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2020111790914 |
Language: | English |
Published: |
Springer Nature,
2020
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Publish Date: | 2020-11-17 |
Description: |
AbstractThis paper presents the results of the experiments which were performed using the optical biopsy system specially developed for in vivo tissue classification during the percutaneous needle biopsy (PNB) of the liver. The proposed system includes an optical probe of small diameter acceptable for use in the PNB of the liver. The results of the feasibility studies and actual tests on laboratory mice with inoculated hepatocellular carcinoma and in clinical conditions on patients with liver tumors are presented and discussed. Monte Carlo simulations were carried out to assess the diagnostic volume and to trace the sensing depth. Fluorescence and diffuse reflectance spectroscopy measurements were used to monitor metabolic and morphological changes in tissues. The tissue oxygen saturation was evaluated using a recently developed approach to neural network fitting of diffuse reflectance spectra. The Support Vector Machine Classification was applied to identify intact liver and tumor tissues. Analysis of the obtained results shows the high sensitivity and specificity of the proposed multimodal method. This approach allows to obtain information before the tissue sample is taken, which makes it possible to significantly reduce the number of false-negative biopsies. see all
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Series: |
Scientific reports |
ISSN: | 2045-2322 |
ISSN-E: | 2045-2322 |
ISSN-L: | 2045-2322 |
Volume: | 10 |
Article number: | 14200 |
DOI: | 10.1038/s41598-020-71089-5 |
OADOI: | https://oadoi.org/10.1038/s41598-020-71089-5 |
Type of Publication: |
A1 Journal article – refereed |
Field of Science: |
217 Medical engineering |
Subjects: | |
Funding: |
This study was supported by the Russian Science Foundation under project No. 18-15-00201. The authors are very grateful to Dr. Olga V. Morozova (N.N. Blokhin Russian Cancer Research Center, Moscow, Russia) for tumor cell inoculation. |
Copyright information: |
© The Author(s) 2020. 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/. |
https://creativecommons.org/licenses/by/4.0/ |