Assessing distribution features of fibrous structures using Mueller matrix derived parameters: a quantitative method for breast carcinoma tissues detection and staging

Yuanxing Shen; Wei Sheng; Honghui He; Weipeng Li; Hui Ma

doi:10.1117/12.2545512

21 February 2020 Assessing distribution features of fibrous structures using Mueller matrix derived parameters: a quantitative method for breast carcinoma tissues detection and staging

Yuanxing Shen, Wei Sheng, Honghui He, Weipeng Li, Hui Ma

Author Affiliations +

Proceedings Volume 11239, Dynamics and Fluctuations in Biomedical Photonics XVII; 112390F (2020) https://doi.org/10.1117/12.2545512
Event: SPIE BiOS, 2020, San Francisco, California, United States

Abstract

Breast cancer is a serious threat to women worldwide due to its high incidence and mortality. The early detection is very crucial for the treatment of breast cancer. Currently, for breast cancer patients, mammography and stereotactic needle biopsy followed by time-consuming pathological observations are the primary diagnostic approaches. In our previous study, it was found that the characteristic features of breast carcinoma tissues often include fibrous structures induced by inflammatory reactions, which can be quantitatively evaluated by polarimetric techniques. In this study, we further measure the transmission Mueller matrix microscopic images of 30 breast ductal tissue samples at different progression stages. We calculate the Mueller matrix derived parameters, which can provide the quantitative information on the location, density and distribution behavior of the fibrous structures in the tissues. To evaluate the distribution behavior of fibrous structures more quantitatively and precisely, we also analyze the parameters δ and θ using the gray level cooccurrence matrix (GLCM) analyzing method. The results demonstrate that, the GLCM features Contrast, Energy, Correlation and Homogeneity of δ and θ can be used to describe different textures of fibers distributions among the healthy, ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) tissue samples, whereas the parameters of unpolarized light intensity images show no prominent differences. The Mueller matrix derived parameters combined with image analyzing methods can be used for label-free detecting and quantitative staging of breast carcinoma tissues, which can be helpful for clinical diagnosis.

Conference Presentation

Citation Download Citation

Yuanxing Shen, Wei Sheng, Honghui He, Weipeng Li, and Hui Ma "Assessing distribution features of fibrous structures using Mueller matrix derived parameters: a quantitative method for breast carcinoma tissues detection and staging", Proc. SPIE 11239, Dynamics and Fluctuations in Biomedical Photonics XVII, 112390F (21 February 2020); https://doi.org/10.1117/12.2545512

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