We introduce a method of azimuthally invariant 3D Mueller-matrix (MM) layer-by-layer mapping of the phase and amplitude parameters of anisotropy of the partially depolarizing layers of benign (adenoma) and malignant (carcinoma) prostate tumours. The technique is based on the analysis of spatial variations of Mueller matrix invariant (MMI) of histological sections of benign (adenoma) and malignant (carcinoma) tissue samples. The phase dependence of magnitudes of the first-to-fourth order statistical moments is applied to characterize 3D spatial distributions of MMI of linear and circular birefringence and dichroism of prostate tumours. The high order statistical moments and phase sections of the optimal differentiation of the polycrystalline structure of tissue samples are revealed. The obtained results are compared with the results obtained by conventional methods utilizing polarized light, including 2D and 3D Mueller matrix imaging.

Background: Using optical techniques for tissue diagnostics (so-called 'optical biopsy') has been a subject of extensive research for many years. Various groups have been exploring different spectral and/or imaging modalities (e.g. diffuse reflectance spectroscopy, autofluorescence, Raman spectroscopy, optical coherence tomography (OCT), polarized light microscopy, etc.) for biomedical applications. In this paper, we report on using multi-wavelength imaging Mueller polarimetry combined with an appropriated image post-processing for the detection of tissue malignancy. Methods: We investigate a possibility of complementary analysis of Mueller matrix images obtained for turbid tissue-like scattering phantoms and excised human normal and cancerous colorectal tissue samples embedded in paraffin. Combined application of correlation, fractal and statistical analysis was employed to assess quantitatively the polarization-inhomogeneous scattered fields observed at the surface of tissue samples. Results: The combined analysis of the polarimetric images of paraffin-embedded tissue blocks has proved to be an efficient tool for the unambiguous detection of tissue malignant transformation. A fractal structure was clearly observed at spatial distributions of depolarization of light scattered in healthy tissues in a visible range of spectrum, while corresponding distributions for cancerous tissues did not show such dependence. We demonstrate that paraffin does not destroy a fractal structure of spatial distribution of depolarization. Thus, the loss of fractality in spatial distributions of depolarization for cancerous tissue is related to the structural changes in the tissue sample induced by cancer itself and, therefore, may serve as a marker of the disease. Conclusion: The obtained results emphasize that a combined use of statistical, correlation and fractal analysis for the Mueller-matrix image post-processing is an effective approach for an assessment of variations of optical properties in turbid tissue-like scattering media and biological tissues, with a high potential to be transferred to clinical practice for screening cancerous tissue samples.

The purpose of the study is to demonstrate a new method of Stokes-correlometric evaluation of polarization-inhomogeneous images of optically thin (optical thickness smaller than 0.01) histological sections from optically anisotropic biological tissues of different morphological structure. This method is based on a correlation (‘two-point’) generalization of traditional optical methods for analyzing ‘one-point’ distributions of polarization states of microscopic images of biological tissues. Analytical algorithms are obtained for describing the ‘two-point’ complex parameters of the Stokes vector image of a birefringent biological tissue. An experimental technique has been developed for measuring polarization-correlation maps, i.e. the coordinate distributions of the magnitude and phase of the ‘two-point’ Stokes vector parameters. Within the framework of the statistical and correlation analysis of the obtained data, new quantitative criteria for the differentiation of the optical properties of biological tissues of various morphological structures are found. A comparative analysis of the distribution of the ‘single-point’ and ‘two-point’ parameters of the Stokes vector of polarizationally inhomogeneous images was performed. It revealed a higher sensitivity (2–5 times) of the Stokes-correlometry method to variations in orientation-phase structure of biological tissues compared to the single-point approach.

Increasing concerns about adulterated meat encouraged industry looking for new non-invasive methods for rapid accurate meat quality assessment. Main meat chromophores (myoglobin, oxy-myoglobin, fat, water, collagen) are characterized by close comparable absorption in visible to near-infrared (NIR) spectral region. Therefore, structural and compositional variations in meat may lead to relative differences in the absorption of light. Utilizing typical fiber-optic probes and integrating sphere, a degradation of pork samples freshness was observed at room temperature referring to the relative changes in absorbance of main meat chromophores. The application of principal component analysis (PCA) used for examination of measured absorbance spectra revealed more detailed sub-stages of freshness, which are not observed by the conventional analysis of the reflectance spectra. The results show a great potential of the combined application of optical-NIR spectroscopy with complementary use of PCA approach for assessing meat quality and monitoring relative absorbance alternation of oxymyoglobin and myoglobin in visible, and fat, water, collagen in NIR spectral ranges.

The possibilities of using Mueller matrix (MM) imaging polarimetry to assess meat quality have not yet been sufficiently explored. In the current study, the fresh porcine muscles are imaged at room emperature with a wide‐field MM imaging polarimeter over 26 hours to visualize dynamics of tissue optical properties through applying Lu‐Chipman decomposition. The MM images, frequency distribution histograms and statistical analysis of the MM elements show prominent changes over time. Further details can be found in the article by M. Peyvasteh, A. Popov, A. Bykov, A. Pierangelo, T. Novikova, I. Meglinski (https://onlinelibrary.wiley.com/doi/10.1002/jbio.202000376)