New descriptors of radiation quality based on nanodosimetry, a first approach

Großwendt, B.; Pszona, S.; Bantsar, A.

doi:10.1093/rpd/ncm088

Cited by 37 publications

(36 citation statements)

References 36 publications

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“…Furthermore, these quantities can be related to the probability of producing a DSB via models, such as those proposed by Grosswendt et al or Garty et al [2,11]. In the following sections, the track structure simulation by means of PTra and the analytical approach to determine the aforementioned physical parameters are described.…”

Section: Physical Parameters Of Track Structurementioning

confidence: 99%

“…The ionization cluster size is defined as the number of direct ionizations produced by a single incident particle of specific type and energy (and its secondaries) within a specified volume, which is typically chosen to be equal in size to one DNA convolution [2]. This quantity is used in nanodosimetry where it is related to the number of DNA strand breaks [2,3]. The electron fluence, on the other hand, was used within the framework of a multiscale approach to the physics of ion-beam cancer therapy [4].…”

Section: Introductionmentioning

confidence: 99%

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Nanoscale characterization of ion tracks: MC simulations versus analytical approach

et al. 2012

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The goal of this work was to investigate the agreement of physical parameters related to the particle track structure on the nanometer scale, obtained by means of a detailed track structure simulation (PTra) as well as by a rapid analytical approach. Parameters describing the tracks of secondary electrons produced by 0.3 MeV/ u C6+-ions were of particular interest as those particles are densely ionizing. For this purpose, the target volume in form of a nanometric water cylinder was positioned at different radial distances from the ion trajectory and track structure parameters were determined as function of the radial distance. While the fluence of electrons through the target surface and the mean ionization cluster size obtained by both approaches were in good agreement, the probabilities of specific cluster sizes (one, two and three) turned out to be rather different in the two approaches. Abstract. The scope of this work was to investigate the agreement of physical parameters related to the particle track structure on the nanometer scale, obtained by means of a detailed track structure simulation (PTra) as well as by a rapid analytical approach. Parameters describing the tracks of secondary electrons produced by 0.3 MeV/u C 6+ -ions were of particular interest as those particles are densely ionizing. For this purpose, the target volume in form of a nanometric water cylinder was positioned at different radial distances from the ion trajectory and track structure parameters were determined as function of the radial distance. While the fluence of electrons through the target surface and the mean ionization cluster size obtained by both approaches were in good agreement, the probabilities of specific cluster sizes (one, two and three) turn out to be rather different in the two approaches.

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Section: Physical Parameters Of Track Structurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Nanoscale characterization of ion tracks: MC simulations versus analytical approach

et al. 2012

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“…The ionisations occurring were scored for the two target volumes to obtain the ionisation cluster size distribution, i.e. the probability distribution of the number of ionisations produced in a sensitive volume (Grosswendt et al 2007).…”

Section: Methodsmentioning

confidence: 99%

“…This was done by simulating electron, proton and alpha particle tracks and calculating nanodosimetric parameters related to the particle track structure (Grosswendt et al 2007). Furthermore, the model proposed by Garty et al (Garty et al 2010) was used to estimate the probability of producing a double strand break.…”

Section: Introductionmentioning

confidence: 99%

Effect of a static magnetic field on nanodosimetric quantities in a DNA volume

Lazarakis

Bug

Gargioni

et al. 2011

International Journal of Radiation Biology

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Short title: Effect of a magnetic field on track structure Index Terms: Radiotherapy, nanodosimetry, magnetic field, secondary electrons, Geant4, Monte Carlo, cluster size Abstract Purpose: With the advent of MRI (magnetic resonance imaging) guided radiation therapy it is becoming increasingly important to consider the potential influence of a magnetic field on ionising radiation. This paper aims to study the effect of a magnetic field on the track structure of radiation to determine if the biological effectiveness may be altered.Methods: Using the Geant4-DNA (GEometry ANd Tracking 4) Monte Carlo simulation toolkit, nanodosimetric track structure parameters were calculated for electrons, protons and alpha particles moving in transverse magnetic fields up to 10 Tesla. Applying the model proposed by Garty et al. the track structure parameters were used to derive the probability of producing a double strand break (DSB).Results: For simulated primary particles of electrons (200 eV -10 keV), protons (300 keV -30 MeV) and alpha particles (1 MeV -9 MeV) the application of a magnetic field was shown to have no significant effect (within statistical uncertainty limits) on the parameters characterising radiation track structure or the probability of producing a DSB.Conclusions: The null result found here implies that if the presence of a magnetic field were to induce a change in the biological effectiveness of radiation, the effect would likely not be due to a change in the track structure of the radiation.

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“…The following radiation properties have been characterized and mathematically modeled with relatively high precision: radiation track structure (reviewed in Friedland 25 ); micro-and nanodosimetry (reviewed in Grosswendt et al 26 and Hei et al 27 ); inter-and intratissue dose distributions, such as human dose-volume histograms 28 ; radiation action at submillisecond times (reviewed in Wardman 29 ); subsequent DNA damage-repairmisrepair mechanisms 30 ; DNA damage-processing outcomes (eg, chromosomal aberrations, 31 which are especially important here because of their relevance to BCR-ABL translocations, 32 gene mutations, 33 and transcriptome changes 34 ); and many additional relevant end points. 35 Overall, radiation perturbations in humans are frequently more informative than chemical perturbations, because of: (1) better known dose localization, both spatially and temporally; (2) thorough knowledge of particle-track physics; and (3) the ability to change not only the dose but also the ionizing particle type and/or energy, 36 with resulting changes in response giving extra information.…”

Section: Radiobiologymentioning

confidence: 99%

Quantitative modeling of chronic myeloid leukemia: insights from radiobiology

Radivoyevitch

Hlatky

Landaw

et al. 2012

Blood

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Mathematical models of chronic myeloid leukemia (CML) cell population dynamics are being developed to improve CML understanding and treatment. We review such models in light of relevant findings from radiobiology, emphasizing 3 points. First, the CML models almost all assert that the latency time, from CML initiation to diagnosis, is at most ϳ 10 years. Meanwhile, current radiobiologic estimates, based on Japanese atomic bomb survivor data, indicate a substantially higher maximum, suggesting longer-term relapses and extra resistance mutations. Second, different CML models assume different numbers, between 400 and 10 6 , of normal HSCs. Radiobiologic estimates favor values > 10 6 for the number of normal cells (often assumed to be the HSCs) that are at risk for a CML-initiating BCR-ABL translocation. Moreover, there is some evidence for an HSC dead-band hypothesis, consistent with HSC numbers being very different across different healthy adults. Third, radiobiologists have found that sporadic (background, agedriven) chromosome translocation incidence increases with age during adulthood. BCR-ABL translocation incidence increasing with age would provide a hitherto underanalyzed contribution to observed background adult-onset CML incidence acceleration with age, and would cast some doubt on stage-number inferences from multistage carcinogenesis models in general. (Blood. 2012; 119(19):4363-4371) IntroductionChronic myeloid leukemia (CML) is characterized by Ph ϩ cells, that is, cells having a Philadelphia (BCR-ABL) chromosome translocation. 1,2 Treatment with the tyrosine kinase inhibitor (TKI) imatinib mesylate ("imatinib"), which suppresses bcr-abl oncoprotein action, 3 improves patient prognosis dramatically. 4 However, in some cases this treatment fails, a problem mitigated but not fully solved by the use of more recently developed TKI. 5,6 Moreover, many patients may need to continue TKI treatment indefinitely to avoid relapse. 7 CML is one of the best understood cancers; it has a simpler etiology than most cancers 8 and its time course is comparatively easy to monitor in the clinic. 9,10 Consequently, despite being much less prevalent than major solid tumors, CML has often been regarded as a kind of "model organism" for quantitative modeling of human carcinogenesis. 11,12 CML cell population dynamicsIn this review, we emphasize how radiobiologic studies impact CML models grounded in understanding underlying cell population dynamics. These models track CML time evolution by differential equations and/or stochastic formalisms. Such biologically based quantitative models are more ambitious, more comprehensive, and as yet less definitive than models often used in statistical analyses, which emphasize correlations analyzed by adjusting parameters in functions chosen mainly for mathematical convenience.After work by Rubinow and Lebowitz 13 on hematopoiesis, biologically based, mathematical CML models were pioneered by Clarkson and coworkers. 14 Many additional models have been suggested in the last decade. Recent a...

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New descriptors of radiation quality based on nanodosimetry, a first approach

Cited by 37 publications

References 36 publications

Nanoscale characterization of ion tracks: MC simulations versus analytical approach

Nanoscale characterization of ion tracks: MC simulations versus analytical approach

Effect of a static magnetic field on nanodosimetric quantities in a DNA volume

Quantitative modeling of chronic myeloid leukemia: insights from radiobiology

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