Mathematical modeling plays a pivotal role in understanding the mechanism of radiation-induced cellular effects, and also in quantifying the radiation risk to the cell. However, there are still compelling challenges facing the conventional modeling in radiobiology, such as lacking a generalized theory structure of quantifying target effect and non-target effect in the simulation of radiation effects. Most of the models still are based on heavy assumptions treating the unknown mechanisms as a black box, and a detailed correlation between the radiation dose and its microscopic outcomes, both at the cell and tissue level, is still missing. Considering these challenges, there are still significant gaps in the body of knowledge that need to be addressed.
In this study, an integrated spatial and temporal stochastic model was developed, and was implemented using a modularized methodology. The model implementation resulted in a simulation package, radcell, which could be used to study a variety of problems in modeling the radiation-induced cellular effects. Its flexibility and easy extensibility enable it to undertake multi-platform coupled simulations concerning the radiation transport and cell biology. The main results for model design and implementation in this study are: a thorough literature review concerning radiation-induced cellular effects and mechanistic modeling in radiation biology, a rigorous mathematical model formalization concerning a variety of process inducing of cellular effects after irradiation, and a complete model implementation based on object-oriented programming. Additionally, the results for model application were divided into three separate simulation studies concerning radiation-induced bystander effect, modeling vascular tumor response in microbeam radiation therapy, and quantifying the radiation risk of fast growing early stage biota. Each investigates particularly important questions using the developed simulation package.
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