Analysis of polarization features of human breast cancer tissue by Mueller matrix visualization

• Published in: Journal of biomedical optics Vol. 29; no. 5; p. 052917
• Main Authors: Pham, Thi-Thu-Hien, Ngoc Quach, Thao-Ngan, Vo, Quoc-Hoang-Quyen
• Format: Journal Article
• Language: English
• Published: United States 01-05-2024
• Subjects: Breast Neoplasms - diagnostic imaging; Diagnostic Imaging - methods; Female; Humans; Microscopy, Polarization - methods; Refraction, Ocular; Spectrum Analysis - methods; Mueller matrix transformation; backscattering polarization imaging; depolarization power; human breast cancer
• ISSN: 1083-3668; 1560-2281; 1560-2281
• DOI: 10.1117/1.JBO.29.5.052917

Breast cancer ranks second in the world in terms of the number of women diagnosed. Effective methods for its early-stage detection are critical for facilitating timely intervention and lowering the mortality rate.
Polarimetry provides much useful information on the structural properties of breast cancer tissue samples and is a valuable diagnostic tool. The present study classifies human breast tissue samples as healthy or cancerous utilizing a surface-illuminated backscatter polarization imaging technique.
The viability of the proposed approach is demonstrated using 95 breast tissue samples, including 35 healthy samples, 20 benign cancer samples, 20 grade-2 malignant samples, and 20 grade-3 malignant samples.
The observation results reveal that element
in the Mueller matrix of the healthy samples has a deeper color and greater intensity than that in the breast cancer samples. Conversely, element
shows a lighter color and reduced intensity. Finally, element
has a darker color in the healthy samples than in the cancer samples. The analysis of variance test results and frequency distribution histograms confirm that elements
,
, and
provide an effective means of detecting and classifying human breast tissue samples.
Overall, the results indicate that surface-illuminated backscatter polarization imaging has significant potential as an assistive tool for breast cancer diagnosis and classification.