Stochastic modelling for biodosimetry : predicting the chromosomal response to radiation at different time points after exposure

2014
journal article
article
2
dc.abstract.enCytogenetic data accumulated from the experiments with peripheral blood lymphocytes exposed to densely ionizing radiation clearly demonstrate that for particles with linear energy transfer (LET) >100 keV/\mu m the derived relative biological effectiveness (RBE) will strongly depend on the time point chosen for the analysis. A reasonable prediction of radiation-induced chromosome damage and its distribution among cells can be achieved by exploiting Monte Carlo methodology along with the information about the radius of the penetrating ion-track and the LET of the ion beam. In order to examine the relationship between the track structure and the distribution of aberrations induced in human lymphocytes and to clarify the correlation between delays in the cell cycle progression and the aberration burden visible at the first post-irradiation mitosis, we have analyzed chromosome aberrations in lymphocytes exposed to Fe-ions with LET values of 335 keV/\mu m and formulated a Monte Carlo model which reflects time-delay in mitosis of aberrant cells. Within the model the frequency distributions of aberrations among cells follow the pattern of local energy distribution and are well approximated by a time-dependent compound Poisson statistics. The cell-division cycle of undamaged and aberrant cells and chromosome aberrations are modelled as a renewal process represented by a random sum of (independent and identically distributed) random elements $S_{N} = \sum _{i=0}^{N} X_{i}$. Here N stands for the number of particle traversals of cell nucleus, each leading to a statistically independent formation of $X_{i}$ aberrations. The parameter N is itself a random variable and reflects the cell cycle delay of heavily damaged cells. The probability distribution of S N follows a general law for which the moment generating function satisfies the relation $\Phi _{S_{N}}=\Phi _{N}\left ( \Phi _{X_{i}} \right )$. Formulation of the Monte Carlo model which allows to predict expected fluxes of aberrant and non-aberrant cells has been based on several input information: (i) experimentally measured mitotic index in the population of irradiated cells; (ii) scored fraction of cells in first cell cycle; (iii) estimated average number of particle traversals per cell nucleus. By reconstructing the local dose distribution in the biological target, the relevant amount of lesions induced by ions is estimated from the biological effect induced by photons at the same dose level. Moreover, the total amount of aberrations induced within the entire population has been determined. For each subgroup of intact (non-hit) and aberrant cells the cell-division cycle has been analyzed reproducing correctly an expected correlation between mitotic delay and the number of aberrations carried by a cell. This observation is of particular importance for the proper estimation of the biological efficiency of ions and for the estimation of health risks associated with radiation exposure.pl
dc.affiliationWydział Fizyki, Astronomii i Informatyki Stosowanej : Instytut Fizyki im. Mariana Smoluchowskiegopl
dc.contributor.authorDeperas-Standyło, Joanna - 177997 pl
dc.contributor.authorGudowska-Nowak, Ewa - 128235 pl
dc.contributor.authorRitter, Sylviapl
dc.date.accessioned2015-06-25T14:49:33Z
dc.date.available2015-06-25T14:49:33Z
dc.date.issued2014pl
dc.date.openaccess0
dc.description.accesstimew momencie opublikowania
dc.description.admin[AB] Deperas-Standylo, Joannapl
dc.description.number7pl
dc.description.publication0,5pl
dc.description.versionostateczna wersja wydawcy
dc.description.volume68pl
dc.identifier.articleid204pl
dc.identifier.doi10.1140/epjd/e2014-50014-xpl
dc.identifier.eissn1434-6079pl
dc.identifier.issn1434-6060pl
dc.identifier.urihttp://ruj.uj.edu.pl/xmlui/handle/item/10399
dc.languageengpl
dc.language.containerengpl
dc.rightsDodaję tylko opis bibliograficzny*
dc.rights.licenceCC-BY-SA
dc.rights.uri*
dc.share.typeinne
dc.subtypeArticlepl
dc.titleStochastic modelling for biodosimetry : predicting the chromosomal response to radiation at different time points after exposurepl
dc.title.journalEuropean Physical Journal. D, Atomic, Molecular, and Optical Physicspl
dc.typeJournalArticlepl
dspace.entity.typePublication
dc.abstract.enpl
Cytogenetic data accumulated from the experiments with peripheral blood lymphocytes exposed to densely ionizing radiation clearly demonstrate that for particles with linear energy transfer (LET) >100 keV/\mu m the derived relative biological effectiveness (RBE) will strongly depend on the time point chosen for the analysis. A reasonable prediction of radiation-induced chromosome damage and its distribution among cells can be achieved by exploiting Monte Carlo methodology along with the information about the radius of the penetrating ion-track and the LET of the ion beam. In order to examine the relationship between the track structure and the distribution of aberrations induced in human lymphocytes and to clarify the correlation between delays in the cell cycle progression and the aberration burden visible at the first post-irradiation mitosis, we have analyzed chromosome aberrations in lymphocytes exposed to Fe-ions with LET values of 335 keV/\mu m and formulated a Monte Carlo model which reflects time-delay in mitosis of aberrant cells. Within the model the frequency distributions of aberrations among cells follow the pattern of local energy distribution and are well approximated by a time-dependent compound Poisson statistics. The cell-division cycle of undamaged and aberrant cells and chromosome aberrations are modelled as a renewal process represented by a random sum of (independent and identically distributed) random elements $S_{N} = \sum _{i=0}^{N} X_{i}$. Here N stands for the number of particle traversals of cell nucleus, each leading to a statistically independent formation of $X_{i}$ aberrations. The parameter N is itself a random variable and reflects the cell cycle delay of heavily damaged cells. The probability distribution of S N follows a general law for which the moment generating function satisfies the relation $\Phi _{S_{N}}=\Phi _{N}\left ( \Phi _{X_{i}} \right )$. Formulation of the Monte Carlo model which allows to predict expected fluxes of aberrant and non-aberrant cells has been based on several input information: (i) experimentally measured mitotic index in the population of irradiated cells; (ii) scored fraction of cells in first cell cycle; (iii) estimated average number of particle traversals per cell nucleus. By reconstructing the local dose distribution in the biological target, the relevant amount of lesions induced by ions is estimated from the biological effect induced by photons at the same dose level. Moreover, the total amount of aberrations induced within the entire population has been determined. For each subgroup of intact (non-hit) and aberrant cells the cell-division cycle has been analyzed reproducing correctly an expected correlation between mitotic delay and the number of aberrations carried by a cell. This observation is of particular importance for the proper estimation of the biological efficiency of ions and for the estimation of health risks associated with radiation exposure.
dc.affiliationpl
Wydział Fizyki, Astronomii i Informatyki Stosowanej : Instytut Fizyki im. Mariana Smoluchowskiego
dc.contributor.authorpl
Deperas-Standyło, Joanna - 177997
dc.contributor.authorpl
Gudowska-Nowak, Ewa - 128235
dc.contributor.authorpl
Ritter, Sylvia
dc.date.accessioned
2015-06-25T14:49:33Z
dc.date.available
2015-06-25T14:49:33Z
dc.date.issuedpl
2014
dc.date.openaccess
0
dc.description.accesstime
w momencie opublikowania
dc.description.adminpl
[AB] Deperas-Standylo, Joanna
dc.description.numberpl
7
dc.description.publicationpl
0,5
dc.description.version
ostateczna wersja wydawcy
dc.description.volumepl
68
dc.identifier.articleidpl
204
dc.identifier.doipl
10.1140/epjd/e2014-50014-x
dc.identifier.eissnpl
1434-6079
dc.identifier.issnpl
1434-6060
dc.identifier.uri
http://ruj.uj.edu.pl/xmlui/handle/item/10399
dc.languagepl
eng
dc.language.containerpl
eng
dc.rights*
Dodaję tylko opis bibliograficzny
dc.rights.licence
CC-BY-SA
dc.rights.uri*
dc.share.type
inne
dc.subtypepl
Article
dc.titlepl
Stochastic modelling for biodosimetry : predicting the chromosomal response to radiation at different time points after exposure
dc.title.journalpl
European Physical Journal. D, Atomic, Molecular, and Optical Physics
dc.typepl
JournalArticle
dspace.entity.type
Publication

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