University of Oulu

Hogan BT, Ushenko VA, Syvokorovskaya A-V, Dubolazov AV, Vanchulyak OY, Ushenko AG, Ushenko YA, Gorsky MP, Tomka Y, Kuznetsov SL, Bykov A and Meglinski I (2021) 3D Mueller Matrix Reconstruction of the Optical Anisotropy Parameters of Myocardial Histopathology Tissue Samples. Front. Phys. 9:737866. doi: 10.3389/fphy.2021.737866

3D Mueller matrix reconstruction of the optical anisotropy parameters of myocardial histopathology tissue samples

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Author: Hogan, Benjamin T.1; Ushenko, Volodimyr A.2; Syvokorovskaya, Anastasia-Vira3;
Organizations: 1Optoelectronics and Measurement Techniques, University of Oulu, Oulu, Finland
2Optics and Publishing Department, Chernivtsi National University, Chernivtsi, Ukraine
3Department of Forensic Medicine, Bukovinian State Medical University, Chernivtsi, Ukraine
4Taizhou Research Institute, Zhejiang University, Taizhou, China
5I.M. Sechenov First Moscow State Medical University, Moscow, Russia
6Interdisciplinary Laboratory of Biophotonics, Tomsk State University, Tomsk, Russia
7Immanuel Kant Baltic Federal University, Kaliningrad, Russia
8V.A. Negovsky Scientific Research Institute of General Reanimatology, Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russia
9College of Engineering and Physical Science, Aston University, Birmingham, United Kingdom
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 3.8 MB)
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Language: English
Published: Frontiers Media, 2021
Publish Date: 2022-01-28


Diseases affecting myocardial tissues are currently a leading cause of death in developed nations. Fast and reliable techniques for analysing and understanding how tissues are affected by disease and respond to treatment are fundamental to combating the effects of heart disease. A 3D Mueller matrix method that reconstructs the linear and circular birefringence and dichroism parameters has been developed to image the biological structures in myocardial tissues. The required optical data is gathered using a Stokes polarimeter and then processed mathematically to recover the individual optical anisotropy parameters, expanding on existing 2D Mueller matrix implementations by combining with a digital holography approach. Changes in the different optical anisotropy parameters are rationalised with reference to the general tissue structure, such that the structures can be identified from the anisotropy distributions. The first to fourth order statistical moments characterising the distribution of the parameters of the optical anisotropy of the polycrystalline structure of the partially depolarising layer of tissues in different phase sections of their volumes are investigated and analysed. The third and fourth order statistical moments are found to be the most sensitive to changes in the phase and amplitude anisotropy. The possibility of forensic medical differentiation of death in cases of acute coronary insufficiency (ACI) and coronary heart disease (CHD) is considered as a diagnostic application. The optimal phase plane (θ = 0.7rad) has been found, in which excellent differentiation accuracy is achieved ACI and CHD -Ac(ΔZ₄(θLL))=93.05%÷95.8%. A comparative analysis of the accuracy of the Mueller-matrix reconstruction of the parameters of the optical anisotropy of the myocardium in different phase planes (θ = 0.9rad and θ = 1.2rad), as well as the 2D Mueller-matrix reconstruction method was carried out. This work demonstrates that a 3D Mueller matrix method can be used to effectively analyse the optical anisotropy parameters of myocardial tissues with potential for definitive diagnostics in forensic medicine.

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Series: Frontiers in physics
ISSN: 2296-424X
ISSN-E: 2296-424X
ISSN-L: 2296-424X
Volume: 9
Article number: 737866
DOI: 10.3389/fphy.2021.737866
Type of Publication: A1 Journal article – refereed
Field of Science: 217 Medical engineering
213 Electronic, automation and communications engineering, electronics
Funding: Current research supported by the ATTRACT project funded by the EC under Grant Agreement 777222, Academy of Finland (grants 314639 and 325097), National Research Foundation of Ukraine (Project 2020.02/0061) and INFOTECH strategic funding, and with the support of a grant under the Decree of the Government of the Russian Federation No. 220 of 09 April 2010 (Agreement No. 075-15-2021-615 of 04 June 2021). This work was also financed by the Ministry of Science and Higher Education of the Russian Federation (Agreement no. 075-02-2021-1748).
Academy of Finland Grant Number: 325097
Detailed Information: 325097 (Academy of Finland Funding decision)
Copyright information: © 2021 Hogan, Ushenko, Syvokorovskaya, Dubolazov, Vanchulyak, Ushenko, Ushenko, Gorsky, Tomka, Kuznetsov, Bykov and Meglinski. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.