Light is an electromagnetic wave that can exist in a variety of polarization states, including linear, circular, and elliptical. These differ in the behavior of the oscillating electric field component of the electromagnetic wave.
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The polarization state of light is an incredibly important property when considering optical applications as the light-matter interactions are dependent on the incident polarization. For example, performing optical absorption experiments with linear or circularly polarized light on molecular systems results in different experimental observables.
For chiral molecules, where the two enantiomers often have identical absorption spectra when recorded with linearly polarized light, circularly polarized light can be used instead to distinguish between them. This is because one enantiomer will preferentially absorb one-handedness of the circularly polarized light and this can be used to examine the circular dichroism response of the sample.1
Polarization control is often used in biomedical imaging experiments to suppress unwanted signals from phenomena such as scattering from nearby issues. Scattering typically induces a degree of depolarization in the scattered light and so polarizers can be used as filters to reduce contributions from unwanted scatter, improving the image signal-to-noise ratio.2
The key to polarization control is the use of polarization optics. There are several optical components for optical control, including optically active crystals or dichroic materials to make polarizers. Where the polarization needs to be varied during an experiment, a common approach is to use a waveplate mounted in a rotational mount.
A waveplate will rotate the polarization of the incident light by introducing phase retardation between the polarization components. Waveplates are typically made from birefringent materials. The most common retardation specifications are λ/4 – which can be used to generate circular or elliptical polarization states depending on the incident polarization angle of the linear incident light or vice versa – or λ/2, for rotation of the polarization axis of linearly polarized light. Waveplates also offer another option for polarization control and to achieve a range of different phase changes.
While particularly in microscopy and image applications polarization control is typically performed for scattering suppression, the polarization information can also be used to extract additional information on the sample.3
Polarization Measurement Techniques
There are several different experimental schemes that can be used to extract polarimetric information in imaging experiments.3 Scattering suppression methods are usually used for bulk tissue samples but for thin tissue samples, polarimetric information can be used to distinguish between image features that can differentiate diseases such as Crohn’s disease and tuberculosis. Biomedical polarimetric imaging is useful for many types of cancer diagnosis as well as quantification of the fibrosis stage from a tissue sample.4
As the polarization of light can be treated as a vector property, and the system it interacts with can also be treated as vectorial information, these sets of information can be used to describe the interactions between the systems. This requires the use of a series of formalisms that can in turn help predict features in the polarimetric data or interpret them.
Depending on whether the biological system in question undergoes rapid exchange processes on short timescales or a time-averaged picture is an acceptable description, either single-shot or time-sequenced polarization measurements can be used. More straightforward experiments recover partial information though some approaches do make it possible to recover the full polarization information.
While rotating polarizers are cost-effective ways to perform many of these measurements, more advanced technologies such as ferroelectric liquid crystals or spatial light modulators that also offer routes for fast signal modulation are being used to reduce measurement times which is crucial for clinical applications.
There is a surge of interest in biomedical and clinical imaging applications for the application of machine learning techniques for automated image analysis and potentially even disease diagnosis. By combining automated image recognition with optical point-of-care measurement devices, it could become possible to provide vital information for clinical decision-making without the need for biopsies or samples to ever be analyzed in the lab.
Often there is a trade-off between spatial resolution and scanning time in imaging instruments but the use of machine learning with polarimetry may help gain higher effective imaging resolution as well as improve the quality of the polarimetry data with suppression of artifacts from the numerous sources of error in the experiments.3
As optics technologies continue to improve, such as the development of higher quality adaptive optics for full polarization control, this could also be integrated into feedback loops as part of the data acquisition process to refine measurement times.
References and Further Reading
- Miles, A. J., & Janes, R. W. (2021). Chem Soc Rev Tools and methods for circular dichroism spectroscopy of proteins: a tutorial review. Chemical Society Reviews. 8400–8413. https://doi.org/10.1039/d0cs00558d
- Ghosh, N., & Vitkin, I. A. (2011). Tissue polarimetry: concepts, challenges, applications, and outlook. Journal of Biomedical Optics, 16(11), 110801. https://doi.org/10.1117/1.3652896
- He, C., He, H., Chang, J., Chen, B., Ma, H., & Booth, M. J. (2021). Polarisation optics for biomedical and clinical applications: a review. Light: Science & Applications, 10, 194. https://doi.org/10.1038/s41377-021-00639-x
- Dong, Y. et al. (2017). Quantitatively characterizing the microstructural features of breast ductal carcinoma tissues in different progression stages by Mueller matrix microscope. Biomedical Optics Express, 8,3643–3655 https://doi.org/10.1364/BOE.8.003643