Intercomparison of Monte Carlo calculated dose enhancement ratios for gold nanoparticles irradiated by X-rays: Assessing the uncertainty and correct methodology for extended beams.

Results of a Monte Carlo code intercomparison exercise for simulations of the dose enhancement from a gold nanoparticle (GNP) irradiated by X-rays have been recently reported. To highlight potential differences between codes, the dose enhancement ratios (DERs) were shown for the narrow-beam geometry used in the simulations, which leads to values significantly higher than unity over distances in the order of several tens of micrometers from the GNP surface. As it has come to our attention that the figures in our paper have given rise to misinterpretation as showing 'the' DERs of GNPs under diagnostic X-ray irradiation, this article presents estimates of the DERs that would have been obtained with realistic radiation field extensions and presence of secondary particle equilibrium (SPE). These DER values are much smaller than those for a narrow-beam irradiation shown in our paper, and significant dose enhancement is only found within a few hundred nanometers around the GNP. The approach used to obtain these estimates required the development of a methodology to identify and, where possible, correct results from simulations whose implementation deviated from the initial exercise definition. Based on this methodology, literature on Monte Carlo simulated DERs has been critically assessed.

Consistency checks of results from a Monte Carlo code intercomparison for emitted electron spectra and energy deposition around a single gold nanoparticle irradiated by X-rays.

Organized by the European Radiation Dosimetry Group (EURADOS), a Monte Carlo code intercomparison exercise was conducted where participants simulated the emitted electron spectra and energy deposition around a single gold nanoparticle (GNP) irradiated by X-rays. In the exercise, the participants scored energy imparted in concentric spherical shells around a spherical volume filled with gold or water as well as the spectral distribution of electrons leaving the GNP. Initially, only the ratio of energy deposition with and without GNP was to be reported. During the evaluation of the exercise, however, the data for energy deposition in the presence and absence of the GNP were also requested. A GNP size of 50 nm and 100 nm diameter was considered as well as two different X-ray spectra (50 kVp and 100kVp). This introduced a redundancy that can be used to cross-validate the internal consistency of the simulation results. In this work, evaluation of the reported results is presented in terms of integral quantities that can be benchmarked against values obtained from physical properties of the radiation spectra and materials involved. The impact of different interaction cross-section datasets and their implementation in the different Monte Carlo codes is also discussed.

PROPOSAL FOR A EUROPEAN METROLOGY NETWORK ON BIOLOGICAL IONISING RADIATION EFFECTS.

Progress in the field of ionising radiation (IR) metrology achieved in the BioQuaRT project raised the question to what extent radiobiological investigations would benefit from metrological support of the applied methodologies. A panel of experts from the medical field, fundamental research and radiation protection attended a workshop at Physikalisch-Technische Bundesanstalt to consult on metrology needs related to biological radiation effects. The panel identified a number of metrological needs including the further development of experimental and computational techniques for micro- and nanodosimetry, together with the determination of related fundamental material properties and the establishment of rigorous uncertainty budgets. In addition to this, a call to develop a metrology support for assisting quality assurance of radiobiology experiments was expressed. Conclusions from the workshop were presented at several international conferences for further discussion with the scientific community and stakeholder groups that led to an initiative within the metrology community to establish a European Metrology Network on biological effects of IR.

A New Standard DNA Damage (SDD) Data Format.

Our understanding of radiation-induced cellular damage has greatly improved over the past few decades. Despite this progress, there are still many obstacles to fully understand how radiation interacts with biologically relevant cellular components, such as DNA, to cause observable end points such as cell killing. Damage in DNA is identified as a major route of cell killing. One hurdle when modeling biological effects is the difficulty in directly comparing results generated by members of different research groups. Multiple Monte Carlo codes have been developed to simulate damage induction at the DNA scale, while at the same time various groups have developed models that describe DNA repair processes with varying levels of detail. These repair models are intrinsically linked to the damage model employed in their development, making it difficult to disentangle systematic effects in either part of the modeling chain. These modeling chains typically consist of track-structure Monte Carlo simulations of the physical interactions creating direct damages to DNA, followed by simulations of the production and initial reactions of chemical species causing so-called "indirect" damages. After the induction of DNA damage, DNA repair models combine the simulated damage patterns with biological models to determine the biological consequences of the damage. To date, the effect of the environment, such as molecular oxygen (normoxic vs. hypoxic), has been poorly considered. We propose a new standard DNA damage (SDD) data format to unify the interface between the simulation of damage induction in DNA and the biological modeling of DNA repair processes, and introduce the effect of the environment (molecular oxygen or other compounds) as a flexible parameter. Such a standard greatly facilitates inter-model comparisons, providing an ideal environment to tease out model assumptions and identify persistent, underlying mechanisms. Through inter-model comparisons, this unified standard has the potential to greatly advance our understanding of the underlying mechanisms of radiation-induced DNA damage and the resulting observable biological effects when radiation parameters and/or environmental conditions change.

ASSESSING THE CONTRIBUTION OF CROSS-SECTIONS TO THE UNCERTAINTY OF MONTE CARLO CALCULATIONS IN MICRO- AND NANODOSIMETRY.

Within EURADOS Working Group 6 'Computational Dosimetry', the micro and nanodosimetry task group 6.2 has recently conducted a Monte Carlo (MC) exercise open to participants around the world. The aim of this exercise is to quantify the contribution to the uncertainty of micro and nanodosimetric simulation results arising from the use of different electron-impact cross-sections, and hence physical models, employed by different MC codes (GEANT4-DNA, PENELOPE, MCNP6, FLUKA, NASIC and PHITS). Comparison of the participants' simulation results for both micro and nanodosimetric quantities using different MC codes was the first step of the exercise. The deviation between results is due to different cross-sections but also different tracking methods and particle transport cut-off energies. The second step of the exercise will involve using identical cross-section datasets to account only for the other variations in the first step, thus enabling the determination of the uncertainty contribution due to different cross-sections. This paper presents a comparison of the MC simulation results obtained in the first part of the exercise. For the microdosimetric simulations, particularly in the configuration where the electron source is contained within the micrometric target, the choice of MC code has a small influence on the results. For the nanodosimetric results, on the other hand, the mean ionisation cluster size distribution (ICSD) was sensitive to the physical models used in the MC codes. The ICSD was therefore chosen to study the influence of different cross-section data on the uncertainty of simulation results.

Future development of biologically relevant dosimetry.

Proton and ion beams are radiotherapy modalities of increasing importance and interest. Because of the different biological dose response of these radiations as compared with high-energy photon beams, the current approach of treatment prescription is based on the product of the absorbed dose to water and a biological weighting factor, but this is found to be insufficient for providing a generic method to quantify the biological outcome of radiation. It is therefore suggested to define new dosimetric quantities that allow a transparent separation of the physical processes from the biological ones. Given the complexity of the initiation and occurrence of biological processes on various time and length scales, and given that neither microdosimetry nor nanodosimetry on their own can fully describe the biological effects as a function of the distribution of energy deposition or ionization, a multiscale approach is needed to lay the foundation for the aforementioned new physical quantities relating track structure to relative biological effectiveness in proton and ion beam therapy. This article reviews the state-of-the-art microdosimetry, nanodosimetry, track structure simulations, quantification of reactive species, reference radiobiological data, cross-section data and multiscale models of biological response in the context of realizing the new quantities. It also introduces the European metrology project, Biologically Weighted Quantities in Radiotherapy, which aims to investigate the feasibility of establishing a multiscale model as the basis of the new quantities. A tentative generic expression of how the weighting of physical quantities at different length scales could be carried out is presented.

Proton-impact ionisation cross sections for nanodosimetric track structure simulations.

Monte Carlo simulations of the particle track structure require accurate ion- and electron-impact cross-section data of the medium. These data are scarce and often inconsistent when measured by different groups. In this work, literature data on ionisation cross sections (CSs) of nitrogen and propane for protons with energies 0.1-10 MeV are reviewed and implemented in the code PTra. Methane data were used to obtain proton-impact CSs of propane due to their absence in the literature. PTra is benchmarked by comparing simulated particle-track parameters to experimental results, measured with an ion-counting nanodosemeter.

MOSFET dosimetry with high spatial resolution in intense synchrotron-generated x-ray microbeams.

Various dosimeters have been tested for assessing absorbed doses with microscopic spatial resolution in targets irradiated by high-flux, synchrotron-generated, low-energy (approximately 30-300 keV) x-ray microbeams. A MOSFET detector has been used for this study since its radio sensitive element, which is extraordinarily narrow (approximately 1 microm), suits the main applications of interest, microbeam radiation biology and microbeam radiation therapy (MRT). In MRT, micrometer-wide, centimeter-high, and vertically oriented swaths of tissue are irradiated by arrays of rectangular x-ray microbeams produced by a multislit collimator (MSC). We used MOSFETs to measure the dose distribution, produced by arrays of x-ray microbeams shaped by two different MSCs, in a tissue-equivalent phantom. Doses were measured near the center of the arrays and maximum/minimum (peak/valley) dose ratios (PVDRs) were calculated to determine how variations in heights and in widths of the microbeams influenced this for the therapy, potentially important parameter. Monte Carlo (MC) simulations of the absorbed dose distribution in the phantom were also performed. The results show that when the heights of the irradiated swaths were below those applicable to clinical therapy (< 1 mm) the MC simulations produce estimates of PVDRs that are up to a factor of 3 higher than the measured values. For arrays of higher microbeams (i.e., 25 microm x 1 cm instead of 25 x 500 microm2), this difference between measured and simulated PVDRs becomes less than 50%. Closer agreement was observed between the measured and simulated PVDRs for the Tecomet MSC (current collimator design) than for the Archer MSC. Sources of discrepancies between measured and simulated doses are discussed, of which the energy dependent response of the MOSFET was shown to be among the most important.

Microbeam radiation therapy: a Monte Carlo study of the influence of the source, multislit collimator, and beam divergence on microbeams.

Microbeam radiation therapy (MRT) is a new oncology method currently under development for the treatment of inoperable pediatric brain tumors. Monte Carlo simulation, or the computational study of radiation transport in matter, is often used in radiotherapy to theoretically estimate the dose required for treatment. However, its potential use in MRT dose planning systems is currently hindered by the significant discrepancies that have been observed between measured and theoretical dose and the PVDR (peak to valley dose ratio). The need to resolve these discrepancies is driven by the desirability of making MRT available to humans in the next few years. This article aims to resolve some of the discrepancies by examining the simplifications adopted in previous MRT Monte Carlo studies, such as the common practice of commencing microbeam transport on the surface of the target which neglects the influence of the distributed synchrotron source, multislit collimator, and the beam divergence between them. This article uses PENELOPE Monte Carlo simulation to investigate the influence of these beamline components upstream of the target on the lateral dose profiles and PVDRs of an array of 25 microbeams. It also compares the dose profiles and PVDRs of a microbeam array produced from a single simulation (full array) to those produced from the superposition of a single microbeam profile (sup array). The effect of modeling the distributed source and the beam divergence was an increase in the absorbed dose in the penumbral and valley regions of the microbeam profiles. Inclusion of the multislit collimator resulted in differences of up to 5 microm in the FWHM of microbeam profiles across the array, which led to minor variations in the corresponding PVDR yields.

Effect of transverse magnetic fields on dose distribution and RBE of photon beams: comparing PENELOPE and EGS4 Monte Carlo codes.

The application of a strong transverse magnetic field to a volume undergoing irradiation by a photon beam can produce localized regions of dose enhancement and dose reduction. This study uses the PENELOPE Monte Carlo code to investigate the effect of a slice of uniform transverse magnetic field on a photon beam using different magnetic field strengths and photon beam energies. The maximum and minimum dose yields obtained in the regions of dose enhancement and dose reduction are compared to those obtained with the EGS4 Monte Carlo code in a study by Li et al (2001), who investigated the effect of a slice of uniform transverse magnetic field (1 to 20 Tesla) applied to high-energy photon beams. PENELOPE simulations yielded maximum dose enhancements and dose reductions as much as 111% and 77%, respectively, where most results were within 6% of the EGS4 result. Further PENELOPE simulations were performed with the Sheikh-Bagheri and Rogers (2002) input spectra for 6, 10 and 15 MV photon beams, yielding results within 4% of those obtained with the Mohan et al (1985) spectra. Small discrepancies between a few of the EGS4 and PENELOPE results prompted an investigation into the influence of the PENELOPE elastic scattering parameters C(1) and C(2) and low-energy electron and photon transport cut-offs. Repeating the simulations with smaller scoring bins improved the resolution of the regions of dose enhancement and dose reduction, especially near the magnetic field boundaries where the dose deposition can abruptly increase or decrease. This study also investigates the effect of a magnetic field on the low-energy electron spectrum that may correspond to a change in the radiobiological effectiveness (RBE). Simulations show that the increase in dose is achieved predominantly through the lower energy electron population.