Optical anisotropy composition of benign and malignant prostate tissues revealed by Mueller-matrix imaging

Oleksii Sieryi, Yuriy Ushenko, Volodimir Ushenko, Olexander Dubolazov, Anastasia V. Syvokorovskaya, Oleh Vanchulyak, Alexander G. Ushenko, Mykhailo Gorsky, Yuriy Tomka, Alexander Bykov, Wenjun Yan, Igor Meglinski

Research output: Contribution to journalArticlepeer-review


A Mueller matrix imaging approach is employed to disclose the three-dimensional composition framework of optical anisotropy within cancerous biotissues. Visualized by the Mueller matrix technique spatial architecture of optical anisotropy of tissues is characterised by high-order statistical moments. Thus, quantitative analysis of the spatial distribution of optical anisotropy, such as linear and circular birefringence and dichroism, is revealed by using high-order statistical moments, enabling definitively discriminate prostate adenoma and carcinoma. The developed approach provides greater (>90%) accuracy of diagnostic achieved by using either the 3-rd or 4-th order statistical moments of the linear anisotropy parameters. Noticeable difference is observed between prostate adenoma and carcinoma tissue samples in terms of the extinction coefficient and the degree of depolarisation. Juxtaposition to other optical diagnostic modalities demonstrates the greater accuracy of the approach described herein, paving the way for its wider application in cancer diagnosis and tissue characterization.
Original languageEnglish
Article number6019
Pages (from-to)6019-6034
Number of pages16
JournalBiomedical Optics Express
Issue number11
Early online date25 Oct 2022
Publication statusPublished - 1 Nov 2022

Bibliographical note

Published by Optica Publishing Group under the terms of the Creative Commons Attribution 4.0 License [https://creativecommons.org/licenses/by/4.0/]. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

Funding: Royal Society (APX111232); National Research Foundation of Ukraine (2020.02/0061); ATTRACT Horizon 2020 Framework Programme for Research and Innovation (1010004462); Academy of Finland (314639, 325097, 351068).


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