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.

AN ALGORITHM TO DETERMINE THE NANODOSIMETRIC IMPACT OF GOLD NANOPARTICLES ON CELL MODELS.

High-Z nanomaterials, e.g. gold nanoparticles (GNPs), are being investigated worldwide for potential application in radiation imaging and therapy. Photon irradiation of cells containing GNP was shown to produce enhanced DNA damage which is believed to be related to the increased secondary electron (SE) yield and ionization density. In this work, an algorithm was developed for simulating the physical radiation damage inside the nucleus of a spherical cell model for the case of uniformly distributed GNPs within the cytoplasm. Previously calculated energy spectra of SE emerging from a single NP irradiated with different photon sources are used as input to obtain the SE energy spectrum at the surface of the cell nucleus. In a second step, the SE transport inside the cell nucleus is simulated with a track structure Monte Carlo code to obtain the spatial distribution of ionizations. The preliminary results presented here show that the developed algorithm allows for a fast calculation of the SE spectra at the cell nucleus surface, thus enabling a more realistic assessment of the ionization density inside the cell nucleus than that obtained by the simulation of a single GNP. Furthermore, the algorithm can be easily adapted to investigate both the effect of GNP clustering and the impact of GNP-GNP interactions on SE spectra.

Measurement of track structure parameters of low and medium energy helium and carbon ions in nanometric volumes.

Ionization cluster size distributions produced in the sensitive volume of an ion-counting wall-less nanodosimeter by monoenergetic carbon ions with energies between 45 MeV and 150 MeV were measured at the TANDEM-ALPI ion accelerator facility complex of the LNL-INFN in Legnaro. Those produced by monoenergetic helium ions with energies between 2 MeV and 20 MeV were measured at the accelerator facilities of PTB and with a 241Am alpha particle source. C3H8 was used as the target gas. The ionization cluster size distributions were measured in narrow beam geometry with the primary beam passing the target volume at specified distances from its centre, and in broad beam geometry with a fan-like primary beam. By applying a suitable drift time window, the effective size of the target volume was adjusted to match the size of a DNA segment. The measured data were compared with the results of simulations obtained with the PTB Monte Carlo code PTra. Before the comparison, the simulated cluster size distributions were corrected with respect to the background of additional ionizations produced in the transport system of the ionized target gas molecules. Measured and simulated characteristics of the particle track structure are in good agreement for both types of primary particles and for both types of the irradiation geometry. As the range in tissue of the ions investigated is within the typical extension of a spread-out Bragg peak, these data are useful for benchmarking not only 'general purpose' track structure simulation codes, but also treatment planning codes used in hadron therapy. Additionally, these data sets may serve as a data base for codes modelling the induction of radiation damages at the DNA-level as they almost completely characterize the ionization component of the nanometric track structure.

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.

Comparison of measured and Monte Carlo simulated track structure parameters in nanometric volumes.

The track structure of ionising particles in biological matter can only be assessed by simulations, since neither the type of interaction and its products nor the interaction positions in biological matter can be detected with nanometer resolution. Hence, there is a need to benchmark the deployed computer codes using suitable experimental data. For this purpose, the frequency distributions of ionisation clusters produced in the sensitive volume of the PTB ion counting nanodosemeter by monoenergetic protons and alpha particles (with energies between 0.1 and 20 MeV) were measured. C3H8 and N2 were alternately used as the working gas. The measured data were compared with the results of simulations obtained with the PTB Monte Carlo code PTra. Measured and simulated characteristics of the particle track structure are in good agreement for protons over the entire energy range investigated. For alpha particles with energies above the Bragg peak a good agreement can also be seen, whereas for energies below the Bragg peak differences of as much as 25 % occur.

Comparison of nanodosimetric parameters of track structure calculated by the Monte Carlo codes Geant4-DNA and PTra.

The concept of nanodosimetry is based on the assumption that initial damage to cells is related to the number of ionizations (the ionization cluster size) directly produced by single particles within, or in the close vicinity of, short segments of DNA. The ionization cluster-size distribution and other nanodosimetric quantities, however, are not directly measurable in biological targets and our current knowledge is mostly based on numerical simulations of particle tracks in water, calculating track structure parameters for nanometric target volumes. The assessment of nanodosimetric quantities derived from particle-track calculations using different Monte Carlo codes plays, therefore, an important role for a more accurate evaluation of the initial damage to cells and, as a consequence, of the biological effectiveness of ionizing radiation. The aim of this work is to assess the differences in the calculated nanodosimetric quantities obtained with Geant4-DNA as compared to those of the ad hoc particle-track Monte Carlo code 'PTra' developed at Physikalisch-Technische Bundesanstalt (PTB), Germany. The comparison of the two codes was made for incident electrons of energy in the range between 50 eV and 10 keV, for protons of energy between 300 keV and 10 MeV, and for alpha particles of energy between 1 and 10 MeV as these were the energy ranges available in both codes at the time this investigation was carried out. Good agreement was found for nanodosimetric characteristics of track structure calculated in the high-energy range of each particle type. For lower energies, significant differences were observed, most notably in the estimates of the biological effectiveness. The largest relative differences obtained were over 50%; however, generally the order of magnitude was between 10% and 20%.

Anthracyclines induce the accumulation of mutant p53 through E2F1-dependent and -independent mechanisms.

Mutant p53 frequently accumulates in cancer cells and promotes tumor cell invasion, as part of its gain of function. Its accumulation is partially due to enhanced stability, but little is known about how the mRNA levels of mutant p53 can be regulated. Likewise, the impact of cancer therapy on the levels of mutant p53 is poorly understood. We show here that the anthracyclines doxorubicin, daunorubicin and epirubicin further increase the amounts of mutant p53 mRNA and protein in cancer cells. Moreover, we show for the first time that the transcription factor E2F1 associates with the promoter DNA of TP53. Upon genotoxic treatment, E2F1 contributed to the expression of mutant p53, both directly and through induction of TAp73. In contrast, the anthracycline idarubicin and also another topoisomerase inhibitor, etoposide, failed to increase the levels of p53 mRNA, despite their ability to induce the synthesis of TAp73 mRNA. Instead, a natural antisense transcript of TP53, WRAP53, was strongly augmented by idarubicin and etoposide, but only less so by the other anthracyclines under study. RNA corresponding to the first exon of WRAP53 was mainly found in cell nuclei and it reduced the levels of mutant p53. Taken together, this suggests a reciprocal activation pattern of TP53 and WRAP53 by different chemotherapeutics. Reducing the levels of mutant p53 by small-interfering RNA increased chemosensitivity, and idarubicin prevented cell survival more efficiently than the mutant p53-inducing doxorubicin. We conclude that even closely related anthracyclines induce the synthesis of different, opposing transcripts from the TP53 locus. When using these drugs for cancer therapy, the increased levels of mutant p53 may augment its gain of function and thus favor unwanted chemoresistance and tumor progression.