Development of a combined model of tissue kinetics and radiation response of human bronchiolar epithelium with single cell resolution
Ostrovskaya, Natela Grigoryevna
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Lack of accurate data for epidemiological studies of low dose radiation effects necessitates development of dosimetric models allowing prediction of cancer risks for different organs. The objective of this work is to develop a model of the radiation response of human bronchiolar tissue with single cell resolution. The computer model describes epithelial tissue as an ensemble of individual cells, with the geometry of a human bronchiole and the properties of different cell types are taken into account. The model simulates the tissue kinetics and radiation exposure in four dimensions: three spatial dimensions and a temporal dimension. The bronchiole is modeled as a regular hollow cylinder with the epithelial cells of three different types (basal, secretory, and ciliated) lining its interior. For the purposes of assessment of radiation damage to the cells only the nuclei of the cells have been modeled. Subroutines describing cellular kinetics have been developed to simulate cell turnover in a normal epithelial tissue. Monte Carlo subroutines have been developed to simulate exposure to alpha particles; the GEANT4 toolkit has been used to simulate exposure to low LET radiation. Each hit cell is provided with a record of energy deposition, and this record is passed to the progeny if the cell survives. The model output provides data on the number of basal progenitor cells in different phases of a cell life-cycle and secretory to ciliated cell ratio after several generations of cell proliferation. The model calculates labeling and mitotic indices and estimates the average cell turnover time for the bronchiolar tissue. Microdosimetric calculations are performed for cells traversed by ionizing particles. The model will be used to assess the accumulation of damage in cells due to protracted low level radiation exposure. The model output may provide directions for the future experimental design.