Abstract
We use an extensive set of quantitative histopathology data to construct realistic three-dimensional models of normal and dysplastic cervical cell nuclei at different epithelial depths. We then employ the finite-difference time-domain method to numerically simulate the light scattering response of these representative models as a function of the polar and azimuthal scattering angles. The results indicate that intensity and shape metrics computed from two-dimensional scattering patterns can be used to distinguish between different diagnostic categories. Our numerical study also suggests that different epithelial layers and angular ranges need to be considered separately to fully exploit the diagnostic potential of two-dimensional light scattering measurements.
Highlights
Analysis of light scattering properties of tissues has always been a major focus of biomedical optics research
It is obvious that each layer exhibits different characteristics; basal, parabasal, and intermediate nuclei are generally larger and rounder, whereas superficial nuclei are smaller with a denser internal composition
The images shown illustrate typical morphological and structural changes associated with dysplastic progression
Summary
Analysis of light scattering properties of tissues has always been a major focus of biomedical optics research. Numerous studies have been carried out to quantify the optical scattering. The main goal of these studies was to establish a link between disease-related modifications in tissue components and the resulting alterations in their respective scattering profiles. Dysplastic progression in epithelial tissues is known to be associated with changes in internal structure of cells and cell-to-cell spatial organization. It is well established that dysplastic nuclei are larger and more irregularly shaped with increased DNA content and coarse chromatin distribution. As evidenced by prior computational studies, these properties result in elevated scattering that can be used as an optical signature for precancer detection [3,4]
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