Spatial analysis of polarimetric images to enhance near-surface sampling sensitivity: feasibility in demineralized teeth and other tissue-like media.

Significance: Early tooth demineralization may be detectable through spatial analysis of polarized light images as demonstrated in this study. This may also prove useful in the early detection of epithelial tumors that comprise the majority of the cancer burden worldwide. Aim: The spatial properties of polarized light images have not been greatly exploited in biomedicine to improve sensitivity to superficial tissue regions; therefore, we investigate the optical sampling depth effects as a function of location in the backscattered polarimetric images. Approach: Backscattered linear polarization intensity distributions exhibit four-lobed patterns arising through single-scattering, multiple-scattering, and geometrical effects. These photon pathway dynamics are investigated through experimental imaging of microsphere suspensions along with corroborative computational polarization-sensitive Monte Carlo modeling. The studied sampling depth effects of linear and circular polarization images (explored in a previous study) are then evaluated on normal and demineralized human teeth, which are known to differ in their surface and sub-surface structures. Results: Backscattered linear polarization images exhibit enhanced sensitivity to near-surface properties of media (for example, surface roughness and turbidity) at specific locations within the four-lobed patterns. This yields improved differentiation of two tooth types when spatially selecting image regions in the direction perpendicular to the incident linear polarization vector. Circular polarimetric imaging also yields improved differentiation through spatial selection of regions close to the site of illumination. Improved sensitivity to superficial tissues is achieved through a combination of these linear and circular polarimetric imaging approaches. Conclusions: Heightened sampling sensitivity to tissue microstructure in the surface/near-surface region of turbid tissue-like media and dental tissue is achieved through a judicious spatial selection of specific regions in the resultant co-linear and cross-circular backscattered polarimetric images.

Spatial helicity response metric to quantify particle size and turbidity of heterogeneous media through circular polarization imaging.

Backscattered circularly polarized light from turbid media consists of helicity-flipped and helicity-preserved photon sub-populations (i.e., photons of perpendicular and parallel circular handedness). Their intensities and spatial distributions are found to be acutely sensitive to average scatterer size and modestly sensitive to the scattering coefficient (medium turbidity) through an interplay of single and multiple scattering effects. Using a highly sensitive intensified-CCD camera, helicity-based images of backscattered light are captured, which, with the aid of corroborating Monte Carlo simulation images and statistics, enable (1) investigation of subsurface photonic pathways and (2) development of the novel 'spatial helicity response' metric to quantify average scatterer size and turbidity of tissue-like samples. An exciting potential application of this work is noninvasive early cancer detection since malignant tissues exhibit alterations in scatterer size (larger nuclei) and turbidity (increased cell density).

Discriminating turbid media by scatterer size and scattering coefficient using backscattered linearly and circularly polarized light.

The effects of scatterer size and scattering coefficient on backscattered linearly and circularly polarized light are investigated through Stokes polarimetry. High-SNR polarization modulation/synchronous detection measurements are corroborated by polarization-sensitive Monte Carlo simulations. Circular degree of polarization (DOP) is found to be sensitive to scatterer size, but is equivocal at times due to helicity flipping effects; linear DOP appears to be mostly dependent on the medium scattering coefficient. We exploit these trends to generate a DOPC - DOPL response surface which clusters turbid samples based on these medium properties. This work may prove useful in biomedicine, for example in noninvasive assessment of epithelial precancer progression.