Unique Properties of Polarization for Use in Biomedical and Clinical Applications

As an electromagnetic wave, light has a number of fundamental properties, including wavelength, intensity, phase and polarization (the oscillation direction of the light waves).

Unique Properties of Polarization for Use in Biomedical and Clinical Applications.
Image Credit: by Chao He, Honghui He, Jintao Chang, Binguo Chen, Hui Ma & Martin J. Booth.

The first three are scalar quantities, but polarization possesses vectorial properties (because of its representation by the mathematical concept of vectors); its use has thus necessitated more advanced computational and optical methods.

Therefore, studies dealing with the vector properties of light, or the complete vectorial transformation properties of an object, have a shorter history in biomedical analysis compared with their scalar equivalents, and the degree of their application is still being investigated.

Thus far, several intriguing areas of research have been improved by utilizing vectorial information obtained via polarization optics; these include material characterization, quantum physics, biomedical/clinical applications, etc.

For biomedical/clinical applications, the polarization method features exceptional advantages compared to other equivalents: sensitive to sub-cellular structures, ideal for in vivo label-free imaging/sensing, simple to miniaturize and well-matched with other current optical systems.

In a new paper published in Light: Science & Applications, a research team, led by Professor Martin Booth, Dr. Chao He and Professor Honghui He from the University of Oxford and Tsinghua University and his co-workers, has written a review article titled “Polarisation optics for biomedical and clinical applications.”

This review starts with an overview of the standard polarization optical representation tools, with a focus on the adoption of the Stokes-Mueller formalism, for which the Stokes vector is used to illustrate the polarization state of the light beam, while the Mueller matrix illustrates the transformation characteristics of the object that influence the Stokes vector.

Ellipsometry for thin films measurement is compared with polarimetry for biomedical samples and their development trend are all given in the article. The polarization measurement methods, including time-sequenced, partially Stokes/Mueller, simultaneous snap-shot measurement and full Stokes/Mueller techniques, are briefly described.

Furthermore, the vectorial information measurement theory is established with a structure that comprises “denoising,” “optimization” and “calibration.”

After the measurement theory, the polarization information extraction and analysis methods for Stokes/Mueller formalism are described. Particularly, Mueller matrix polar decomposition, Mueller matrix transformation and the development trend toward data-based information extraction methods for biomedical and clinical applications are illustrated.

Next, examples for polarization information analysis of thin/bulk tissues characterization are provided, with a focus on ex vivo pathological tissue analysis (for example, cancer detection and differentiation) and in vivo clinical diagnosis.

Finally, the review also pinpoints the potential for future multi-modal synergy with other pioneering technologies, which include but are not restricted to machine learning methods and big data, non-linear optics, orbital angular momentum, metasurface-based methods and vector vortex beam manipulations.

The main goal of the review is to provide readers with a broad overview of the use of vectorial information that can be acquired by polarization optics for applications in clinical and biomedical research. Moreover, such a summary could encourage new discussions, investigations and further potential advances in related prospective fields.

Journal Reference:

He, C., et al. (2021) Polarisation optics for biomedical and clinical applications: a review. Light: Science & Applications. doi.org/10.1038/s41377-021-00639-x.

Source: http://english.ciomp.cas.cn/

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