The probabilities of one- and multi-track events for modeling radiation-induced cell kill.
Radiat Environ Biophys
; 56(3): 249-254, 2017 08.
Article
em En
| MEDLINE
| ID: mdl-28526979
In view of the clinical importance of hypofractionated radiotherapy, track models which are based on multi-hit events are currently reinvestigated. These models are often criticized, because it is believed that the probability of multi-track hits is negligible. In this work, the probabilities for one- and multi-track events are determined for different biological targets. The obtained probabilities can be used with nano-dosimetric cluster size distributions to obtain the parameters of track models. We quantitatively determined the probabilities for one- and multi-track events for 100, 500 and 1000 keV electrons, respectively. It is assumed that the single tracks are statistically independent and follow a Poisson distribution. Three different biological targets were investigated: (1) a DNA strand (2 nm scale); (2) two adjacent chromatin fibers (60 nm); and (3) fiber loops (300 nm). It was shown that the probabilities for one- and multi-track events are increasing with energy, size of the sensitive target structure, and dose. For a 2 × 2 × 2 nm3 target, one-track events are around 10,000 times more frequent than multi-track events. If the size of the sensitive structure is increased to 100-300 nm, the probabilities for one- and multi-track events are of the same order of magnitude. It was shown that target theories can play a role for describing radiation-induced cell death if the targets are of the size of two adjacent chromatin fibers or fiber loops. The obtained probabilities can be used together with the nano-dosimetric cluster size distributions to determine model parameters for target theories.
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1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Método de Monte Carlo
/
Modelos Biológicos
Tipo de estudo:
Health_economic_evaluation
Idioma:
En
Revista:
Radiat Environ Biophys
Ano de publicação:
2017
Tipo de documento:
Article
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