In the present paper we numerically investigate, using Monte Carlo simulation, the theoretical results predicted by the Generalized Stochastic Microdosimetric Model (GSM2), as shown in the published companion paper. Taking advantage of the particle irradiation data ensemble (PIDE) dataset, we calculated GSM2 biological parameters of human salivary gland (HSG) and V79 cell lines. Further, exploiting the TOPASmicrodosimetric extension, we simulated the microdosimetric spectra of different radiation fields of therapeutic interest generated by four different ions (protons, helium-4, carbon-12 and oxygen-16) each at three different residual ranges. We investigated the properties of the initial damage distributions as well as the cell survival curve predicted by GSM2, focusing especially on the non-Poissonian effects naturally included in the model. GSM2 successfully computed cell survival curves, accurately describing experimental behavior even under challenging LET and dose conditions.
Cell Survival Computation via the Generalized Stochastic Microdosimetric Model (GSM2); Part II: Numerical Results / Missiaggia, M.; Cordoni, F. G.; Scifoni, E.; La Tessa, C.. - In: RADIATION RESEARCH. - ISSN 0033-7587. - 201:2(2024), pp. 104-114. [10.1667/RADE-22-00025.1.S1]
Cell Survival Computation via the Generalized Stochastic Microdosimetric Model (GSM2); Part II: Numerical Results
Missiaggia M.;Cordoni F. G.;Scifoni E.;La Tessa C.
2024-01-01
Abstract
In the present paper we numerically investigate, using Monte Carlo simulation, the theoretical results predicted by the Generalized Stochastic Microdosimetric Model (GSM2), as shown in the published companion paper. Taking advantage of the particle irradiation data ensemble (PIDE) dataset, we calculated GSM2 biological parameters of human salivary gland (HSG) and V79 cell lines. Further, exploiting the TOPASmicrodosimetric extension, we simulated the microdosimetric spectra of different radiation fields of therapeutic interest generated by four different ions (protons, helium-4, carbon-12 and oxygen-16) each at three different residual ranges. We investigated the properties of the initial damage distributions as well as the cell survival curve predicted by GSM2, focusing especially on the non-Poissonian effects naturally included in the model. GSM2 successfully computed cell survival curves, accurately describing experimental behavior even under challenging LET and dose conditions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione