Dremin, V., Potapova, E., Zherebtsov, E. et al. Optical percutaneous needle biopsy of the liver: a pilot animal and clinical study. Sci Rep 10, 14200 (2020). https://doi.org/10.1038/s41598-020-71089-5
Optical percutaneous needle biopsy of the liver : a pilot animal and clinical study
|Author:||Dremin, Viktor1,2; Potapova, Elena1; Zherebtsov, Evgeny1,3;|
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
|Online Access:||PDF Full Text (PDF, 3.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2020111790914
|Publish Date:|| 2020-11-17
This 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.
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
217 Medical engineering
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.
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