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W.Ralph Nelson

Bio: W.Ralph Nelson is an academic researcher. The author has contributed to research in topics: Calorimeter (particle physics). The author has an hindex of 1, co-authored 1 publications receiving 1409 citations.

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01 Jan 2009
TL;DR: The PENELOPE as mentioned in this paper computer code system performs Monte Carlo simulation of coupled electron-photon transport in arbitrary materials for a wide energy range, from a few hundred eV to about 1 GeV.
Abstract: The computer code system PENELOPE (version 2008) performs Monte Carlo simulation of coupled electron-photon transport in arbitrary materials for a wide energy range, from a few hundred eV to about 1 GeV. Photon transport is simulated by means of the standard, detailed simulation scheme. Electron and positron histories are generated on the basis of a mixed procedure, which combines detailed simulation of hard events with condensed simulation of soft interactions. A geometry package called PENGEOM permits the generation of random electron-photon showers in material systems consisting of homogeneous bodies limited by quadric surfaces, i.e., planes, spheres, cylinders, etc. This report is intended not only to serve as a manual of the PENELOPE code system, but also to provide the user with the necessary information to understand the details of the Monte Carlo algorithm.

1,675 citations

DOI
01 Jan 1994
TL;DR: GEANT as discussed by the authors is a system of detector description and simulation tools that help physicists in high energy particle physics experiments, and it can be used to design and optimise the detectors, develop and test the reconstruction and analysis programs, and interpret the experimental data.
Abstract: As the scale and complexity of High Energy Physics experiments increase, simulation studies require more and more care and become essential to design and optimise the detectors, develop and test the reconstruction and analysis programs, and interpret the experimental data. GEANT is a system of detector description and simulation tools that help physicists in such studies.

973 citations

Journal ArticleDOI
TL;DR: A new method to convert CT numbers into mass density and elemental weights of tissues required as input for dose calculations with Monte Carlo codes such as EGS4 is described, and no loss of accuracy is accepted when using the interpolation functions.
Abstract: We describe a new method to convert CT numbers into mass density and elemental weights of tissues required as input for dose calculations with Monte Carlo codes such as EGS4. As a first step, we calculate the CT numbers for 71 human tissues. To reduce the effort for the necessary fits of the CT numbers to mass density and elemental weights, we establish four sections on the CT number scale, each confined by selected tissues. Within each section, the mass density and elemental weights of the selected tissues are interpolated. For this purpose, functional relationships between the CT number and each of the tissue parameters, valid for media which are composed of only two components in varying proportions, are derived. Compared with conventional data fits, no loss of accuracy is accepted when using the interpolation functions. Assuming plausible values for the deviations of calculated and measured CT numbers, the mass density can be determined with an accuracy better than 0.04 g cm(-3). The weights of phosphorus and calcium can be determined with maximum uncertainties of 1 or 2.3 percentage points (pp) respectively. Similar values can be achieved for hydrogen (0.8 pp) and nitrogen (3 pp). For carbon and oxygen weights, errors up to 14 pp can occur. The influence of the elemental weights on the results of Monte Carlo dose calculations is investigated and discussed.

641 citations

Journal ArticleDOI
TL;DR: The purpose of this report is to set out the salient issues associated with clinical implementation and experimental verification of MC dose algorithms, and to provide the framework upon which to build a comprehensive program for commissioning and routine quality assurance of MC-based treatment planning systems.
Abstract: The Monte Carlo (MC) method has been shown through many research studies to calculate accurate dose distributions for clinical radiotherapy, particularly in heterogeneous patient tissues where the effects of electron transport cannot be accurately handled with conventional, deterministic dose algorithms. Despite its proven accuracy and the potential for improved dose distributions to influence treatment outcomes, the long calculation times previously associated with MC simulation rendered this method impractical for routine clinical treatment planning. However, the development of faster codes optimized for radiotherapy calculations and improvements in computer processor technology have substantially reduced calculation times to, in some instances, within minutes on a single processor. These advances have motivated several major treatment planning system vendors to embark upon the path of MC techniques. Several commercial vendors have already released or are currently in the process of releasing MC algorithms for photon and/or electron beam treatment planning. Consequently, the accessibility and use of MC treatment planning algorithms may well become widespread in the radiotherapy community. With MC simulation, dose is computed stochastically using first principles; this method is therefore quite different from conventional dose algorithms. Issues such as statistical uncertainties, the use of variance reduction techniques, theability to account for geometric details in the accelerator treatment head simulation, and other features, are all unique components of a MC treatment planning algorithm. Successful implementation by the clinical physicist of such a system will require an understanding of the basic principles of MC techniques. The purpose of this report, while providing education and review on the use of MC simulation in radiotherapy planning, is to set out, for both users and developers, the salient issues associated with clinical implementation and experimental verification of MC dose algorithms. As the MC method is an emerging technology, this report is not meant to be prescriptive. Rather, it is intended as a preliminary report to review the tenets of the MC method and to provide the framework upon which to build a comprehensive program for commissioning and routine quality assurance of MC-based treatment planning systems.

591 citations