Abstract
Light scattering from biological cells has been used for many years as a diagnostic tool. Several simulation methods of the scattering process were developed in the last decades in order to understand and predict the scattering patterns. We developed an analytical model of a multilayer spherical scattering cell. Here, we describe the model and show that the results obtained within this simple method are similar to those obtained with far more complicated methods such as finite-difference time-domain (FDTD). The multilayer model is then used to study the effects of changes in the distribution of internal cell structures like mitochondria distribution or nucleus internal structures that exist in biological cells. Such changes are related with cancerous processes within the cell as well as other cell pathologies. Results show the ability to discriminate between different cell stages related to the mitochondria distributions and to internal structure of the nucleolus.
Highlights
Light scattering from biological cells has been used for many years as a tool for the measurement and characterization of cell size and cell internal structure [1]
Any method that improves our understanding of how different structural compositions inside of single cells affect the scatter pattern can potentially have an enormous impact in applications where flow cytometry is used
We have developed and implemented a MATLAB multilayer Mie-like model for the scattering of light from biological cells that have internal structures with spherical symmetry
Summary
Light scattering from biological cells has been used for many years as a tool for the measurement and characterization of cell size and cell internal structure [1]. One application in which a better model of light scattering from a single cell can be used to improve cell characterization in flow cytometry is presented in [2]. In light scattering-based flow cytometry applications, two critical factors measured are the fractions of forwardscattered and side-scattered light (typically near 90 degrees), which are used to assess cell size and shape, respectively [2]. By plotting the forward scattered light against the side scattered light for a large number of of individual cells, one can apply statistical methods to identify various cell populations present inside of a cell suspension. Any method that improves our understanding of how different structural compositions inside of single cells affect the scatter pattern can potentially have an enormous impact in applications where flow cytometry is used
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