Predicting Radiation-Induced Cell Mutations for Mars Missions: A Microdosimetric Kinetic Model Study
Kinnunen, Eeli (2024-11-15)
Predicting Radiation-Induced Cell Mutations for Mars Missions: A Microdosimetric Kinetic Model Study
(15.11.2024)
Julkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty.
avoin
Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2024111895033
https://urn.fi/URN:NBN:fi-fe2024111895033
Tiivistelmä
Ionising radiation from particles caused by solar particle events (SPEs) and galactic cosmic rays (GCRs) poses a cancer risk for astronauts in space. Cell survival and mutation after exposure to ionising radiation can be described with radiobiological models.
This study explores the use of the microdosimetric kinetic model (MKM) in the evaluation of carcinogenic mutations in cells induced by ionising radiation, and the application of the model to a mission on Mars. In addition to using the MKM to evaluate cell survival probabilities, for which it has almost solely been used before, it is used here to evaluate mutation probabilities. Linear quadratic model was used to fit survival and mutation as a function of dose in the experimental data. A subset of available experimental data was used in the identification of the parameters needed in the MKM. Predictions of cell survival and mutation were then carried out by simulations with `Survival' code utilising the Kiefer-Chatterjee particle track model and compared with the full set of experimental data. Additional analyses accounting for the effect of the dose rate were performed for the datasets that included dose rate information. The results of the simulations resembled experimental data with low linear energy transfer (LET) values more accurately than experimental data with high LET values.
Space radiation conditions on a habitat on Mars were obtained from OLTARIS (On-Line Tool for the Assessment of Radiation in Space). Simulations of cell survival and mutation were carried out for the SPE spectrum using the optimised parameters discovered from the linear quadratic fits and the comparisons to experimental data. Preliminary simulations accounting for the dose rate were currently carried out only for the low doses, in which cases the predictions of cell survival and observable mutation were similar to the predictions of the simulations not accounting for the dose rate.
Predicting the probability of observable cell mutation is the first step in modelling cancer risk. The methods presented in this study could assist in the evaluation of carcinogenic mutations caused by ionising radiation, including the effects of radiation on a space mission.
This study explores the use of the microdosimetric kinetic model (MKM) in the evaluation of carcinogenic mutations in cells induced by ionising radiation, and the application of the model to a mission on Mars. In addition to using the MKM to evaluate cell survival probabilities, for which it has almost solely been used before, it is used here to evaluate mutation probabilities. Linear quadratic model was used to fit survival and mutation as a function of dose in the experimental data. A subset of available experimental data was used in the identification of the parameters needed in the MKM. Predictions of cell survival and mutation were then carried out by simulations with `Survival' code utilising the Kiefer-Chatterjee particle track model and compared with the full set of experimental data. Additional analyses accounting for the effect of the dose rate were performed for the datasets that included dose rate information. The results of the simulations resembled experimental data with low linear energy transfer (LET) values more accurately than experimental data with high LET values.
Space radiation conditions on a habitat on Mars were obtained from OLTARIS (On-Line Tool for the Assessment of Radiation in Space). Simulations of cell survival and mutation were carried out for the SPE spectrum using the optimised parameters discovered from the linear quadratic fits and the comparisons to experimental data. Preliminary simulations accounting for the dose rate were currently carried out only for the low doses, in which cases the predictions of cell survival and observable mutation were similar to the predictions of the simulations not accounting for the dose rate.
Predicting the probability of observable cell mutation is the first step in modelling cancer risk. The methods presented in this study could assist in the evaluation of carcinogenic mutations caused by ionising radiation, including the effects of radiation on a space mission.