A mathematical model of dynamics of cell populations in squamous epithelium after irradiation



Parga-Pazos, Martin, Lopez Pouso, Oscar, Fenwick, John D and Pardo-Montero, Juan
(2020) A mathematical model of dynamics of cell populations in squamous epithelium after irradiation. International Journal of Radiation Biology, 96 (9). pp. 1165-1172.

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Abstract

Purpose To develop multi-compartment mechanistic models of dynamics of stem and functional cell populations in epithelium after irradiation. Methods and materials: We present two models, with three (3C) and four (4C) compartments respectively. We use delay differential equations, and include accelerated proliferation, loss of division asymmetry, progressive death of abortive stem cells, and turnover of functional cells. The models are used to fit experimental data on the variations of the number of cells in mice mucosa after irradiation with 13 Gy and 20 Gy. Akaike information criteria (AIC) was used to evaluate the performance of each model. Results Both 3C and 4C models provide good fits to experimental data for 13 Gy. Fits for 20 Gy are slightly poorer and may be affected by larger uncertainties and fluctuations of experimental data. Best fits are obtained by imposing constraints on the fitting parameters, so to have values that are within experimental ranges. There is some degeneration in the fits, as different sets of parameters provide similarly good fits. Conclusions The models provide good fits to experimental data. Mechanistic approaches like this can facilitate the development of mucositis response models to nonstandard schedules/treatment combinations not covered by datasets to which phenomenological models have been fitted. Studying the dynamics of cell populations in multifraction treatments, and finding links with induced toxicity, is the next step of this work.

Item Type: Article
Uncontrolled Keywords: Biomathematical model, radiotherapy, mucositis, radiobiology
Depositing User: Symplectic Admin
Date Deposited: 01 Sep 2020 09:38
Last Modified: 18 Jan 2023 23:35
DOI: 10.1080/09553002.2020.1787540
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3099138