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22 April 2014 Modeling Cell Survival after Irradiation with Ultrasoft X Rays using the Giant Loop Binary Lesion Model
Thomas Friedrich, Marco Durante, Michael Scholz
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Abstract

We present an application of the Giant LOop Binary LEsion (GLOBLE) model to the case of cell killing after irradiation with ultrasoft X rays. The model is based on the analysis of DSB clustering on the level of chromatin organization on a megabase pair length scale; it distinguishes between two classes of damage, characterized by either an isolated, single DSB (iDSB) or multiple, clustered DSB (cDSB) within a single giant loop. These corresponding fractions of iDSB and cDSB depend on the total number of DSB and thus on the dose as well as the yield of DSB per Gy per cell. Based on the increased yield of DSB with decreasing photon energy as reported in the literature, we demonstrate that according to the model this increased yield of DSB is sufficient to explain the increased RBE of ultrasoft X rays. Further assumptions as e.g., a higher lethality of individual DSB induced by ultrasoft X rays compared to high-energy photons, which might be a consequence of the more localized energy deposition, seem not to be a prerequisite. Since the model is also suitable to take into account local dose variations within the cell nucleus, we further analyze the impact of attenuation of low-energy photon radiation when penetrating a cell layer. We show that the inhomogenous dose distribution resulting from attenuation further increases the effectiveness and particularly affects the beta-term of the corresponding dose response curve. Finally, we compare and discuss the mechanisms of increased RBE as observed after ultrasoft X-ray irradiation with those observed after high-LET ion beam irradiation.

Thomas Friedrich, Marco Durante, and Michael Scholz "Modeling Cell Survival after Irradiation with Ultrasoft X Rays using the Giant Loop Binary Lesion Model," Radiation Research 181(5), 485-494, (22 April 2014). https://doi.org/10.1667/RR13518.1
Received: 16 August 2013; Accepted: 1 January 2014; Published: 22 April 2014
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