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      DPM as a radiation transport engine for PRIMO

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          Abstract

          Background

          PRIMO is a dose verification system based on the general-purpose Monte Carlo radiation transport code penelope, which implements an accurate physics model of the interaction cross sections and the radiation transport process but with low computational efficiency as compared with fast Monte Carlo codes. One of these fast Monte Carlo codes is the Dose Planning Method (DPM). The purpose of this work is to describe the adaptation of DPM as an alternative PRIMO computation engine, to validate its performance against penelope and to validate it for some specific cases.

          Methods

          DPM was parallelized and modified to perform radiation transport in quadric geometries, which are used to describe linacs, thus allowing the simulation of dynamic treatments. To benchmark the new code versus penelope, both in terms of accuracy of results and simulation time, several tests were performed, namely, irradiation of a multi-layer phantom, irradiation of a water phantom using a collimating pattern defined by the multileaf collimator (MLC), and four clinical cases. The gamma index, with passing criteria of 1 mm/1%, was used to compare the absorbed dose distributions. Clinical cases were compared using a 3-D gamma analysis.

          Results

          The percentage of voxels passing the gamma criteria always exceeded 99% for the phantom cases, with the exception of the transport through air, for which dose differences between DPM and penelope were as large as 24%. The corresponding percentage for the clinical cases was larger than 99%. The speedup factor between DPM and penelope ranged from 2.5 ×, for the simulation of the radiation transport through a MLC and the subsequent dose estimation in a water phantom, up to 11.8 × for a lung treatment. A further increase of the computational speed, up to 25 ×, can be obtained in the clinical cases when a voxel size of (2.5 mm) 3 is used.

          Conclusions

          DPM has been incorporated as an efficient and accurate Monte Carlo engine for dose estimation in PRIMO. It allows the concatenated simulation of the patient-dependent part of the linac and the patient geometry in static and dynamic treatments. The discrepancy observed between DPM and penelope, which is due to an artifact of the cross section interpolation algorithm for low energy electrons in air, does not affect the results in other materials.

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          Most cited references17

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          Zur Theorie des Durchgangs schneller Elektronen durch Materie

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            Multiple Scattering in an Infinite Medium

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              DPM, a fast, accurate Monte Carlo code optimized for photon and electron radiotherapy treatment planning dose calculations.

              A new Monte Carlo (MC) algorithm, the 'dose planning method' (DPM), and its associated computer program for simulating the transport of electrons and photons in radiotherapy class problems employing primary electron beams, is presented. DPM is intended to be a high accuracy MC alternative to the current generation of treatment planning codes which rely on analytical algorithms based on an approximate solution of the photon/electron Boltzmann transport equation. For primary electron beams, DPM is capable of computing 3D dose distributions (in 1 mm3 voxels) which agree to within 1% in dose maximum with widely used and exhaustively benchmarked general-purpose public-domain MC codes in only a fraction of the CPU time. A representative problem, the simulation of 1 million 10 MeV electrons impinging upon a water phantom of 128(3) voxels of 1 mm on a side, can be performed by DPM in roughly 3 min on a modern desktop workstation. DPM achieves this performance by employing transport mechanics and electron multiple scattering distribution functions which have been derived to permit long transport steps (of the order of 5 mm) which can cross heterogeneity boundaries. The underlying algorithm is a 'mixed' class simulation scheme, with differential cross sections for hard inelastic collisions and bremsstrahlung events described in an approximate manner to simplify their sampling. The continuous energy loss approximation is employed for energy losses below some predefined thresholds, and photon transport (including Compton, photoelectric absorption and pair production) is simulated in an analogue manner. The delta-scattering method (Woodcock tracking) is adopted to minimize the computational costs of transporting photons across voxels.
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                Author and article information

                Contributors
                miguel.rodriguez@cmpaitilla.com
                josep.sempau@upc.es
                christian.baeumer@uk-essen.de
                beate.timmermann@uk-essen.de
                lorenzo.brualla@uni-duisburg-essen.de
                Journal
                Radiat Oncol
                Radiat Oncol
                Radiation Oncology (London, England)
                BioMed Central (London )
                1748-717X
                27 December 2018
                27 December 2018
                2018
                : 13
                : 256
                Affiliations
                [1 ]Centro Médico Paitilla, Calle 53 y ave. Balboa, Panama City, Panama
                [2 ]ISNI 0000 0004 1800 2151, GRID grid.452535.0, Instituto de Investigaciones Científicas y de Alta Tecnología, INDICASAT-AIP, ; City of Knowledge, Building 219, Panama City, Panama
                [3 ]GRID grid.6835.8, Universitat Politècnica de Catalunya, ; Diagonal 647, Barcelona, E-08028 Spain
                [4 ]West German Proton Therapy Centre Essen (WPE), Hufelandstraße 55, Essen, D-45147 Germany
                [5 ]West German Cancer Center (WTZ), Hufelandstraße 55, Essen, D-45147 Germany
                [6 ]ISNI 0000 0001 0262 7331, GRID grid.410718.b, University Hospital Essen, ; Hufelandstraße 55, Essen, D-45147 Germany
                [7 ]ISNI 0000 0004 0492 0584, GRID grid.7497.d, German Cancer Consortium (DKTK), ; Hufelandstraße 55, Essen, D-45147 Germany
                [8 ]ISNI 0000 0001 0262 7331, GRID grid.410718.b, Department of Particle Therapy, University Hospital Essen, ; Hufelandstraße 55, Essen, D-45147 Germany
                Author information
                http://orcid.org/0000-0003-3385-9623
                Article
                1188
                10.1186/s13014-018-1188-6
                6307123
                30591056
                39338f3f-6b74-4a96-b81a-6c68e18f3ee8
                © The Author(s) 2018

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 22 August 2018
                : 19 November 2018
                Funding
                Funded by: Open Access Publication Fund of the University of Duisburg-Essen
                Award ID: N/A
                Funded by: Deutsche Forschungsgemeinschaft
                Award ID: BR 4043/3-1
                Funded by: H2020 EJP Concert
                Award ID: 003-2017-PODIUM
                Funded by: Spanish Networking Research Center CIBER-BBN
                Award ID: N/A
                Categories
                Research
                Custom metadata
                © The Author(s) 2018

                Oncology & Radiotherapy
                monte carlo,radiation transport,linear accelerator
                Oncology & Radiotherapy
                monte carlo, radiation transport, linear accelerator

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