Comparison of monte carlo collimator transport methods for photon treatment planning in radiotherapy

The aim of this work was a Monte Carlo (MC) based investigation of the impact of different radiation transport methods in collimators of a linear accelerator on photon beam characteristics, dose distributions, and efficiency. Thereby it is investigated if it is possible to use different simplifications in the radiation transport for some clinical situations in order to save calculation time.

More than just Good Luck. How to Explain the Success of Monte Carlo Simulations

Monte Carlo simulation is a powerful method in many natural and social sciences. But what sort of method is it? And where does its power come from? Are Monte Carlo simulations experiments, theories or something else? The aim of this talk is to answer these questions and to explain the power of Monte Carlo simulations. I provide a classification of Monte Carlo techniques and defend the claim that Monte Carlo simulation is a sort of inference.

Monte Carlo source model for photon beam radiotherapy: photon source characteristics

A major barrier to widespread clinical implementation of Monte Carlo dose calculation is the difficulty in characterizing the radiation source within a generalized source model. This work aims to develop a generalized three-component source model (target, primary collimator, flattening filter) for 6- and 18-MV photon beams that match full phase-space data (PSD). Subsource by subsource comparison of dose distributions, using either source PSD or the source model as input, allows accurate source characterization and has the potential to ease the commissioning procedure, since it is possible to obtain information about which subsource needs to be tuned. This source model is unique in that, compared to previous source models, it retains additional correlations among PS variables, which improves accuracy at nonstandard source-to-surface distances (SSDs). In our study, three-dimensional (3D) dose calculations were performed for SSDs ranging from 50 to 200 cm and for field sizes from 1 x 1 to 30 x 30 cm2 as well as a 10 x 10 cm2 field 5 cm off axis in each direction. The 3D dose distributions, using either full PSD or the source model as input, were compared in terms of dose-difference and distance-to-agreement. With this model, over 99% of the voxels agreed within +/-1% or 1 mm for the target, within 2% or 2 mm for the primary collimator, and within +/-2.5% or 2 mm for the flattening filter in all cases studied. For the dose distributions, 99% of the dose voxels agreed within 1% or 1 mm when the combined source model-including a charged particle source and the full PSD as input-was used. The accurate and general characterization of each photon source and knowledge of the subsource dose distributions should facilitate source model commissioning procedures by allowing scaling the histogram distributions representing the subsources to be tuned.

Why Monte Carlo Simulations are Inferences and not Experiments

Monte Carlo simulations arrive at their results by introducing randomness, sometimes derived from a physical randomizing device. Nonetheless, we argue, they open no new epistemic channels beyond that already employed by traditional simulations: the inference by ordinary argumentation of conclusions from assumptions built into the simulations. We show that Monte Carlo simulations cannot produce knowledge other than by inference, and that they resemble other computer simulations in the manner in which they derive their conclusions. Simple examples of Monte Carlo simulations are analysed to identify the underlying inferences.

Measurement of the Z/ѵ* boson transverse momentum distribution in pp collisions at √s = 7 TeV with the ATLAS detector

This paper describes a measurement of the Z/ѵ* boson transverse momentum spectrum using ATLAS proton-proton collision data at a centre-of-mass energy of √s = 7 TeV at the LHC. The measurement is performed in the Z/ѵ* → e+e− and Z/ѵ* → μ+μ− channels, using data corresponding to an integrated luminosity of 4.7 fb−1. Normalized differential cross sections as a function of the Z/ѵ* boson transverse momentum are measured for transverse momenta up to 800 GeV. The measurement is performed inclusively for Z/ѵ* rapidities up to 2.4, as well as in three rapidity bins. The channel results are combined, compared to perturbative and resummed QCD calculations and used to constrain the parton shower parameters of Monte Carlo generators.

Conceptual design and simulation of a water Cherenkov muon veto for the XENON1T experiment

XENON is a dark matter direct detection project, consisting of a time projection chamber (TPC) filled with liquid xenon as detection medium. The construction of the next generation detector, XENON1T, is presently taking place at the Laboratori Nazionali del Gran Sasso (LNGS) in Italy. It aims at a sensitivity to spin-independent cross sections of 2 10-47 c 2 for WIMP masses around 50 GeV2, which requires a background reduction by two orders of magnitude compared to XENON100, the current generation detector. An active system that is able to tag muons and muon-induced backgrounds is critical for this goal. A water Cherenkov detector of ~ 10 m height and diameter has been therefore developed, equipped with 8 inch photomultipliers and cladded by a reflective foil. We present the design and optimization study for this detector, which has been carried out with a series of Monte Carlo simulations. The muon veto will reach very high detection efficiencies for muons (>99.5%) and showers of secondary particles from muon interactions in the rock (>70%). Similar efficiencies will be obtained for XENONnT, the upgrade of XENON1T, which will later improve the WIMP sensitivity by another order of magnitude. With the Cherenkov water shield studied here, the background from muon-induced neutrons in XENON1T is negligible.

Denoising Your Monte Carlo Renders: Recent Advances in Image Space-Adaptive Sampling and Reconstruction

With the ongoing shift in the computer graphics industry toward Monte Carlo rendering, there is a need for effective, practical noise-reduction techniques that are applicable to a wide range of rendering effects and easily integrated into existing production pipelines. This course surveys recent advances in image-space adaptive sampling and reconstruction algorithms for noise reduction, which have proven very effective at reducing the computational cost of Monte Carlo techniques in practice. These approaches leverage advanced image-filtering techniques with statistical methods for error estimation. They are attractive because they can be integrated easily into conventional Monte Carlo rendering frameworks, they are applicable to most rendering effects, and their computational overhead is modest.

Plant species decline due to abandonment of meadows cannot easily be reversed by mowing. A case study from the southern Alps

Abstract. We resumed mowing in two plots of ca. 100 m2 in an abandoned meadow dominated by Brachypodium pinnatum on the slope of Monte Generoso (Switzerland). We monitored species composition and hay yield using point quadrats and biomass samples. Species frequencies changed little during 10 yr (1988–1997) while hay yields showed large fluctuations according to mean relative humidity in April-June. We performed a seed-addition experiment to test whether the establishment of meadow species is limited by lack of diaspores or favourable microsites for germination and recruitment from the seed bank. We sowed ca. 12 000 seeds of 12 species originating from a nearby meadow individually in plots of a 4 × 6 unbalanced Latin square with four treatments, burning, mowing, mowing and removal of a layer of decayed organic matter, and a control. We monitored the fate of seedling individuals for 24 months. Seedlings of all species were established and survived for 12 months, 10 species survived during at least 24 months, some reached a reproductive stage. Species responded to different qualities of microsites provided by the different treatments thus required different regeneration niches. Spontaneous long-distance immigration was insignificant. We conclude that the former species composition of abandoned meadows cannot easily be restored by mowing alone because many plant species of meadows do not have persistent seed banks and immigration over distances of more than 25 m and successful establishment is very unlikely.

Photon-beam subsource sensitivity to the initial electron-beam parameters

One limitation to the widespread implementation of Monte Carlo (MC) patient dose-calculation algorithms for radiotherapy is the lack of a general and accurate source model of the accelerator radiation source. Our aim in this work is to investigate the sensitivity of the photon-beam subsource distributions in a MC source model (with target, primary collimator, and flattening filter photon subsources and an electron subsource) for 6- and 18-MV photon beams when the energy and radial distributions of initial electrons striking a linac target change. For this purpose, phase-space data (PSD) was calculated for various mean electron energies striking the target, various normally distributed electron energy spread, and various normally distributed electron radial intensity distributions. All PSD was analyzed in terms of energy, fluence, and energy fluence distributions, which were compared between the different parameter sets. The energy spread was found to have a negligible influence on the subsource distributions. The mean energy and radial intensity significantly changed the target subsource distribution shapes and intensities. For the primary collimator and flattening filter subsources, the distribution shapes of the fluence and energy fluence changed little for different mean electron energies striking the target, however, their relative intensity compared with the target subsource change, which can be accounted for by a scaling factor. This study indicates that adjustments to MC source models can likely be limited to adjusting the target subsource in conjunction with scaling the relative intensity and energy spectrum of the primary collimator, flattening filter, and electron subsources when the energy and radial distributions of the initial electron-beam change.

New technology enables high precision multislit collimators for microbeam radiation therapy

During the past decade microbeam radiation therapy has evolved from preclinical studies to a stage in which clinical trials can be planned, using spatially fractionated, highly collimated and high intensity beams like those generated at the x-ray ID17 beamline of the European Synchrotron Radiation Facility. The production of such microbeams typically between 25 and 100 microm full width at half maximum (FWHM) values and 100-400 microm center-to-center (c-t-c) spacings requires a multislit collimator either with fixed or adjustable microbeam width. The mechanical regularity of such devices is the most important property required to produce an array of identical microbeams. That ensures treatment reproducibility and reliable use of Monte Carlo-based treatment planning systems. New high precision wire cutting techniques allow the fabrication of these collimators made of tungsten carbide. We present a variable slit width collimator as well as a single slit device with a fixed setting of 50 microm FWHM and 400 microm c-t-c, both able to cover irradiation fields of 50 mm width, deemed to meet clinical requirements. Important improvements have reduced the standard deviation of 5.5 microm to less than 1 microm for a nominal FWHM value of 25 microm. The specifications of both devices, the methods used to measure these characteristics, and the results are presented.