A stochastic model of radiation carcinogenesis: Latent time distributions and their properties
A stochastic model of radiation carcinogenesis is studied. The model of the effect of prolonged irradiation during the time interval \([0,T]\) is based on three basic assumptions: (1) The number of lesions accumulated by time \(T\) is a Poisson random variable with expectation \(\gamma T\), where \(\gamma\) is the parameter related to the dose rate. (2) There is a repair system for radiation injury. The number of unrepaired lesions is assumed to follow the Poisson process with intensity \(p\gamma\), where \(p\) is the stationary probability not to be repaired. (3) Each promoted lesion gives rise to an overt tumor after a certain period of time. These time periods are independent, identically distributed, nonnegative random variables. The distribution for the latent period is computed under the assumptions 1-3. The case of short-term irradiation, \(T\to 0\), is also considered. The final parts of the paper are devoted to the estimation problems and to the numerical examples.
parametric family of substochastic-type distributions for time of tumor latency
stochastic model of radiation carcinogenesis
scientific article; zbMATH DE number 219756
scientific article