The macro Monte Carlo (MMC) method has been developed to improve the speed of traditional Monte Carlo (MC) high-energy electron transport calculations without loss in accuracy. The MMC algorithm uses results derived from conventional MC simulations of electron transport through macroscopic spheres of various radii and consisting of a variety of media. Based on these results, electrons are transported in macroscopic steps through the absorber. The absorber geometry is represented by a three-dimensional (3D) density matrix, typically derived from computer tomographic (CT) data. Energy lost by the electrons along their paths through the absorber is scored in a 3D dose matrix. Transport of secondary electrons and bremsstrahlung photons is taken into account. Major modifications of the original implementation of the MMC algorithm have resulted in an improved version of the code, resolving earlier problems with electron transport across interfaces of different materials, and running at a substantially higher speed. Furthermore, the code has been integrated into a clinical 3D treatment planning system. MMC results are in good agreement with results from conventional MC codes and are obtained with a speed gain of about one order of magnitude for clinically relevant irradiation situations. Calculation times to obtain a relative statistical accuracy of 2% per dose grid voxel for small electron field sizes are short enough to be routinely useful in radiotherapy clinics on present day affordable workstation computers. Considering speed, accuracy and memory requirements, MMC is a promising alternative to currently available electron dose planning algorithms.
The macro Monte Carlo (MMC) method is a fast Monte Carlo (MC) algorithm for high energy electron transport in an absorbing medium. Incident electrons are transported in large-scale macroscopic steps through the absorber. Electron parameters after each step are calculated from probability distributions. Transport of secondary electrons and bremsstrahlung photons is taken into account. For electron beam dose calculations, the energy, angular and spatial distributions of primary electrons have to be provided. The absorber geometry is represented by a 3D density matrix and the energy lost by the electrons along their paths is scored in a 3D dose matrix of user-definable resolution. Measurements in the beam of a Philips SL75-20 linear accelerator incident on homogeneous and simple inhomogeneous phantoms are in good agreement with MMC simulations.
The purpose of this work was to study and quantify the differences in dose distributions computed with some of the newest dose calculation algorithms available in commercial planning systems. The study was done for clinical cases originally calculated with pencil beam convolution (PBC) where large density inhomogeneities were present. Three other dose algorithms were used: a pencil beam like algorithm, the anisotropic analytic algorithm (AAA), a convolution superposition algorithm, collapsed cone convolution (CCC), and a Monte Carlo program, voxel Monte Carlo (VMC++). The dose calculation algorithms were compared under static field irradiations at 6 MV and 15 MV using multileaf collimators and hard wedges where necessary. Five clinical cases were studied: three lung and two breast cases. We found that, in terms of accuracy, the CCC algorithm performed better overall than AAA compared to VMC++, but AAA remains an attractive option for routine use in the clinic due to its short computation times. Dose differences between the different algorithms and VMC++ for the median value of the planning target volume (PTV) were typically 0.4% (range: 0.0 to 1.4%) in the lung and -1.3% (range: -2.1 to -0.6%) in the breast for the few cases we analysed. As expected, PTV coverage and dose homogeneity turned out to be more critical in the lung than in the breast cases with respect to the accuracy of the dose calculation. This was observed in the dose volume histograms obtained from the Monte Carlo simulations.
Since the Swiss Association for Palliative Care (SAPC) considers itself an important partner in the national debate on euthanasia, the Board decided to conduct a survey among its members. An anonymous questionnaire was sent to the 726 members of the SAPC, consisting of multiple choice questions on positions that might be adopted in different hypothetical scenarios and one open question about the rationale for the answers. The response rate achieved with one mailing was 55.6%. The proportions of the respondents who were opposed to different forms of euthanasia were, in ascending order: 56% opposed to physician-assisted suicide (PAS); 69% to direct active euthanasia (DAE); 75% to DAE for psychiatric patients; 84% to delegation of DAE in the case of incompetent patients; and 90% to life-terminating acts without explicit requests (LAWER). Almost 10% of the members reported personal experiences with PAS and different forms of DAE. The main decisional bases drawn on for the answers were ethical values and the clinical or personal experience of the respondents; however, the same categories of arguments were used both by those opposing and by those favouring DAE. There are important variations among the members of the SAPC in the debate on euthanasia. Individual autonomy seems to be an important underlying concept for the different positions; the categories of arguments cited by opponents and supporters of DAE did not differ.
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