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Terahertz Mie scattering in tissue: diffuse polarimetric imaging and Monte Carlo validation in highly attenuating
Erica Heller1, Kuangyi Xu1, Zachery B Harris1
1Stony Brook University, Department of Biomedical Engineering, Stony Brook, New York, United States.
Significance:
Changes in the structure of tissue occur in many disease processes, such as the boundaries of cancerous tumors and burn injuries. Spectroscopic and polarimetric alterations of terahertz light caused by Mie scattering patterns have the potential to be a diagnostic marker.
Aim:
We present an analysis of Monte Carlo simulation of Mie scattering of polarized terahertz light from cancerous tumor budding, compare the simulation with experimental results obtained in phantom models, and present an analysis of a polarization-sensitive terahertz scan of an ex vivo porcine burn injury.
Approach:
Using a Monte Carlo simulation, we modeled the changes in diffuse intensity and degree of polarization of broadband off-specular terahertz light due to scattering particles in highly attenuating tissue. We extracted the Mueller matrix of the tissue using this model and analyzed the Lu-Chipman product decomposition matrices. We compared this model with experimental data from four phantoms consisting of polypropylene particles of varying sizes embedded in gelatin. Finally, we induced a full-thickness burn injury in ex vivo porcine skin samples and compared experimental data captured over burned and healthy regions of the tissue.
Results:
Simulation revealed contrast in the Stokes vectors and Mueller Matrix elements for varying scattering particle sizes. Experimental phantom results showed contrast between different sizes of scattering particles in degree of polarization and diffuse intensity in agreement with Monte Carlo simulation results. Finally, we demonstrated a similar diffused imaging signal contrast between burned and healthy regions of ex vivo porcine skin.
Conclusion:
Polarimetric terahertz imaging has the potential to detect structural changes due to biological disease processes.
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