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Register a new userInvestigation into the foundations of the track-event theory of cell survival and the radiation action model based on nanodosimetry
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This work aims at carving out more clearly the basic assumptions behind the track-event theory (TET) and its derivate radiation action model based on nanodosimetry (RAMN) by clearly distinguishing between effects of tracks at the cellular level and the induction of lesions in subcellular targets. It is demonstrated that the model assumptions of Poisson distribution and statistical independence of the frequency of single and clustered DNA lesions are dispensable for multi-event distributions, because they follow from the Poisson distribution of the number of tracks affecting the considered target volume. It is also shown that making these assumptions for the single-event distributions of the number of lethal and sublethal lesions within a cell would lead to an essentially exponential dose dependence of survival for practically relevant values of the absorbed dose. Furthermore, it is elucidated that the model equation used in the literature for consideration of repair within the TET is based on the assumption that DNA lesions induced by different tracks are repaired independently and that the model equation is presumably inconsistent with the model assumptions and requires an additional model parameter. Furthermore, the methodology for deriving model parameters from nanodosimetric properties of particle track structure is critically assessed. Based on data from proton track simulations it is shown that the assumption of statistically independent targets leads to a prediction of negligible frequency of clustered DNA damage. An approach is outlined how track structure could be considered in determining the model parameters, and the implications for TET and RAMN are discussed.
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The track event theory (TET) has been developed in recent years as an alternative to the phenomenological linear-quadratic model for cell survival under exposure to ionizing radiation, particularly for heavy charged particles. The TET is based on a few simple model assumptions including the possibility to derive some of the model parameters from nanodosimetry. This work intends to carve out more clearly the basic assumptions behind the TET and to critically review the resulting mathematical model equations. It is demonstrated that the model assumptions of Poisson distribution and statistical independence of the frequency distributions of so-called one-track and two-track events follow from the Poisson distribution of the number of tracks affecting the considered target volume. It is also shown that the modified TET model equation used in the literature for consideration of repair is inconsistent with the model assumptions and requires an additional model parameter. Furthermore, the derivation of the model parameters from nanodosimetric properties of particle track structure is revealed to lead to a pure exponential dose dependence when the potentially large number of relevant nanometric target volumes inside a cell nucleus is accounted for.
Biological effectiveness of a certain absorbed dose of ionizing radiation depends on the radiation quality, i. e. the spectrum of ionizing particles and their energy distribution. As has been shown in several studies, the biological effectiveness is related to the pattern of energy deposits on the microscopic scale, the so-called track structure. Clusters of lesions in the DNA molecule within site sizes of few nanometers play a particular role in this context. This work presents a brief overview of nanodosimetric approaches to relate biological effects with track structure derived quantities and experimental techniques to derive such quantities.
Starting from a general equation for organism (or cell system) growth and attributing additional cell death rate (besides the natural rate) to therapy, we derive an equation for cell response to {alpha} radiation. Different from previous models that are based on statistical theory, the present model connects the consequence of radiation with the growth process of a biosystem and each variable or parameter has meaning regarding the cell evolving process. We apply this equation to model the dose response for {alpha}-particle radiation. It interprets the results of both high and low linear energy transfer (LET) radiations. When LET is high, the additional death rate is a constant, which implies that the localized cells are damaged immediately and the additional death rate is proportional to the number of cells present. While at low LET, the additional death rate includes a constant term and a linear term of radiation dose, implying that the damage to some cell nuclei has a time accumulating effect. This model indicates that the oxygen-enhancement ratio (OER) decreases while LET increases consistently.
We present an effective method to model empirical action potentials of specific patients in the human atria based on the minimal model of Bueno-Orovio, Cherry and Fenton adapted to atrial electrophysiology. In this model, three ionic are currents introduced, where each of it is governed by a characteristic time scale. By applying a nonlinear optimization procedure, a best combination of the respective time scales is determined, which allows one to reproduce specific action potentials with a given amplitude, width and shape. Possible applications for supporting clinical diagnosis are pointed out.
An intercomparison of microdosimetric and nanodosimetric quantities simulated Monte Carlo codes is in progress with the goal of assessing the uncertainty contribution to simulated results due to the uncertainties of the electron interaction cross-sections used in the codes. In the first stage of the intercomparison, significant discrepancies were found for nanodosimetric quantities as well as for microdosimetric simulations of a radiation source placed at the surface of a spherical water scoring volume. This paper reports insight gained from further analysis, including additional results for the microdosimetry case where the observed discrepancies in the simulated distributions could be traced back to the difference between track-structure and condensed-history approaches. Furthermore, detailed investigations into the sensitivity of nanodosimetric distributions to alterations in inelastic electron scattering cross-sections are presented which were conducted in the lead up to the definition of an approach to be used in the second stage of the intercomparison to come. The suitability of simulation results for assessing the sought uncertainty contributions from cross-sections is discussed and a proposed framework is described.
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