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International Workshop on Monte Carlo Techniques in Medical Physics June 17-20, 2014, Québec, Canada Program and Abstracts International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 2 Program and Abstracts International Workshop on Monte Carlo Techniques in Medical Physics Organized by Université Laval and McGill University June 17-20, 2014 Organizers: Luc Beaulieu Philippe Després Issam El Naqa Jan Seuntjens Local committee: Daniel Maneval Jean-François Montégiani Isabelle Poulin International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 3 Preface This document contains the program and abstracts of invited and proferred papers to the International Workshop on Monte Carlo Techniques in Medical Physics held in Quebec City on June 17-20th , 2014, organized in cooperation by Université Laval and McGill University. Due to the provisional nature of the content of the contributed materials, and since changes of substance or detail may have to be made before publication of the papers, the abstracts are made available on the understanding that they will not be cited in the literature or in any way be reproduced in its present form. The view expressed and the statements made remain the responsibility of the authors. Acknowledgements This workshop is endorsed by the American Association of Physicists in Medicine. Following organizations and bodies have contributed financially to the Workshop and are hereby gratefully acknowledged: • Centre de recherche sur le cancer (Université Laval) • Medical Physics Research Training Network (NSERC CREATE Funding) • Natural Sciences and Engineering Research Council of Canada (NSERC) • Association québécoise des physicien(ne)s médicaux cliniques (AQPMC) • Canadian Organization of Medical Physicists (COMP) • Elekta Inc. (official sponsor of the day for June 18th , 2014 ) • Varian Medical Systems (official sponsor of the day for June 19th , 2014) International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 Program – Wednesday June 18th Day sponsored by Elekta Amphithéâtre Hydro-Québec (room 2530), Pavillon Desjardins, Université Laval Opening/keynote 8:30 Philippe Després Canada Workshop opening 8:45 Frank Verhaegen, Patrick Granton, Stefan Van Hoof, Daniela Trani and Ludwig Dubois NL Monte Carlo simulations for small animal precision radiotherapy research Update on MC code/physics I Chair : Philippe Després, Université Laval, Canada 09:15 J. Bert, Y. Lemaréchal and D. Visvikis France Particle navigator for hybrid voxelized/analytical phantoms in Monte Carlo simulations for medical applications 09:30 E. S. M. Ali, M. R. McEwen and D. W. O. Rogers Canada The role of accurate Monte Carlo modelling of an experiment in deducing photon cross section uncertainty 09:45 V. N. Malkov and D. W. O. Rogers Canada Incorporating Electric and Magnetic Fields into EGSnrc 10:00 J.P. Archambault and E. Mainegra-Hing Canada Comparison between EGSnrc, Geant4, MCNP5 and Penelope for electron beams 10:15 A. Croc de Suray and Juan-Carlos GarciaHernandez France A New Monte-Carlo Simulation Tool: Penelope Rewritten From Scratch 10:30 Coffee Update on MC codes/physics II Chair : Shirin Enger, McGill University, Canada 11:00 Blake Walters and Iwan Kawrakow Canada Increasing efficiency of BEAMnrc-simulated Co-60 beams using directional source biasing (DSB) 11:15 F. Smekens, J. M. Létang, C. Noblet, S. Chiavassa, G. Delpon, N. Freud, S. Rit and D. Sarrut France Fast exponential track length estimator for Monte-Carlo simulations of small-animal radiation therapy 11:30 Hugo Bouchard and Alex Bielajew UK A theoretical framework to improve Monte Carlo algorithms coupled to magnetic fields 11:45 Ernesto Mainegra-Hing Canada Ausgab objects in EGSnrc: Track, dose, and fluence scoring 12:00 Lunch 4 International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 5 Day sponsored by Elekta Amphithéâtre Hydro-Québec (room 2530), Pavillon Desjardins, Université Laval MC in brachytherapy Chair : Frank Verhaegen, MAASTRO Clinic, The Netherlands 13:30 D. W. O. Rogers and M. Rodrigue Canada Improving LDR brachytherapy TLD measurements using Monte Carlo techniques 14:00 Martin Martinov, David W. O. Rogers, and Rowan M. Thomson Canada Recent advances in BrachyDose 14:15 N. Miksys, L. Beaulieu, J. E. Cygler, C. Xu, J. M. Caudrelier, R. M. Thomson Canada Monte Carlo dose calculations for permanent implant brachytherapy: Interdependence of metallic artifact reduction and tissue assignment 14:30 Éric Bonenfant, Vincent Magnoux, Sami Hissoiny, Benoît Ozell, Luc Beaulieu and Philippe Després Canada Fast GPU-based Monte Carlo dose calculations for permanent prostate implant 14:45 Coffee Parallel MC implementations Chair : Harald Paganetti, Harvard Medical School, USA 15:15 Xun Jia USA Developments of GPU-based Monte Carlo simulations and their applications in radiotherapy 15:45 X George Xu, Tianyu Liu, Lin Su, Xining Du and Peter Caracappa USA Hardware-Accelerated Sub-minute Monte Carlo Methods: Hope or Hype? 16;00 Reid W. Townson and Sergei Zavgorodni Canada Hybridizing primary histogram-based photon source models with phase-space-lets for GPU-based Monte Carlo dose calculation 16:15 Vincent Magnoux, Philippe Després and Benoît Ozell Canada A multi-GPU approach to GPU-based Monte Carlo dose calculations 16:30 J. Bert, Y. Lemaréchal, E. Garrido and D. Visvikis France GGEMS platform: Simulation 16:45 Marc-André Renaud, David Roberge and Jan Seuntjens Canada Pre-calculated Monte Carlo on GPU: Performance and Uncertainties 17:00 Sami Hissoiny Canada Improvements and developments of the GPUMCD platform (Elekta sponsored talk) 17:30 Closing Day 1 GPU GEant4-based Monte Carlo International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 Program – Thursday June 19th Day sponsored by Varian Amphithéâtre Hydro-Québec (room 2530), Pavillon Desjardins, Université Laval MC applications in imaging/nuclear imaging Chair : George Ding, Vanderbilt University, USA 08:30 Anna Celler Canada The Use of Monte Carlo Simulations in Nuclear Medicine 09:00 Sonoko Nakano, Amir Pourmoghaddas, Rachel Timmins, Manfred Trummer, Troy Farncombe, Glenn R Wells and Anna Celler Canada The role of GATE Monte Carlo simulations in dynamic studies using a dedicated cardiac SPECT camera 09:15 Jean-François Montégiani, Émilie Gaudin, Price A. Jackson, Jean-Mathieu Beauregard and Philippe Després Canada Personalized calculation of gamma-photon absorbed dose in 177 Lu-octreotate radionuclide therapy of neuroendocrine tumors with a GPU-based Monte Carlo code 09:30 Susannah Hickling, Pierre Leger, Issam El Naqa Canada Development and validation of a simulation platform to model acoustic waves induced by linear accelerator irradiation 09:45 Sarahi Rosas-González, Mercedes RodriguezVillafuerte, Arnulfo Martinez-Davalos Mexico Monte Carlo simulation of an X-ray Luminescence Optical Tomography scanner prototype 10:00 Coffee Dosimetry I (low energy) Chair : Hugo Bouchard, Physical National Laboratory, UK 10:30 George Ding USA The application of Monte Carlo techniques in patient imaging dose calculations and imaging dose reductions 11:00 Jeffrey F. Williamson and Andrew J. Sampson USA Transport-theoretic variance reduction tools for Monte Carlo simulation of kilovoltage photon fields 11:30 Peter Watson and Jan Seuntjens Canada Modelling spectra and HVL of a miniature low-energy xray source using EGSnrc 11:45 Bryan R. Muir and David W. O. Rogers Canada Monte Carlo simulations to assess the accuracy of lowenergy electron beam reference dosimetry 11:30 Mathieu Agelou, Rachel Delorme, Hélène Elleaume and Florence Taupin France Modelling interactions in radiotherapy by photon activation of high-Z nanoparticles 12:15 Lunch 6 International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 7 Day sponsored by Varian Amphithéâtre Hydro-Québec (room 2530), Pavillon Desjardins, Université Laval MC in radiobiology/microdosimetry/health physics Chair : Issam El Naqa, McGill University, Canada 13:30 Sébastien Incerti France The Geant4-DNA project: developments overview and recent 14:00 Gloria Bäckström, Nina Tilly, José M. Fernández-Varea and Anders Ahnesjö Sweden Clusters of energy deposit sites after simulating irradiation by light ions with the track structure MC code LIonTrack 14:15 Fernanda Villegas, Nina Tilly and Anders Ahnesjö Sweden Monte Carlo calculated cluster patterns for energy deposition sites for low and high energy brachytherapy sources 14:30 Juan-Carlos Garcia-Hernandez, Bessières I., Bordy J-M. and Poumarède. B. Sweden Peripheral dose estimation with pseudo-deterministic transport in C++ version of PENELOPE 14:45 R. Maglieri, A. Licea, J. Seuntjens and J. Kildea Canada A Monte Carlo Model of an 18 MV Varian Linac to Simulate Neutron Spectra 14:45 Coffee MC for QA/clinical applications Chair : Luc Beaulieu, Université Laval, Canada 15:30 Tony Popescu Canada Monte Carlo in clinical practice: patient-specific QA, 4D phase-space predictions, and in-vivo EPID dosimetry 16:00 E. Heath, T. Karan and T. Popescu Canada 4D Monte Carlo simulations of gated and free-breathing dose delivery with a Varian TrueBeam linac 16:15 I. Chabert, D. Lazaro, E. Barat, T. Dautremer, T. Montagu, M. Agelou, A. Croc de Suray, J.C. Garcia-Hernandez, M.Benkreira, M. Nigoul, S. Gempp and L. De Carlan France Development of a new virtual source model for portal image prediction using the Monte Carlo code PENELOPE 16:30 Yana Zlateva and Issam El Naqa Canada Monte Carlo Simulation of Cherenkov Emission by High-Energy Radiotherapy Beams: Investigating a Novel Optical Approach to Dosimetry and Online Imaging in Radiotherapy 16:45 Saadia Benhalouche, Julien Bert, Nicolas Boussion, Awen Autret, Olivier Pradier and Dimitris Visvikis France Imaging and Radiation Therapy: GATE Monte Carlo Simulation of a 6 MV photon beam LINAC and its MVCBCT Flat Panel for IMRT applications 17:00 Bruce A. Faddegon and Peng Dong USA Least Restrictive Assignment of Dose-Distance Differences (LRAD) in comparing radiotherapy dose distributions 17:15 Tanner Connell and Jan Seuntjens Canada The use of Monte Carlo beam models in the design of optimized scattering foils for Modulated Electron Radiation Therapy 17:30 Closing Day 2 Workshop dinner at Le Parlementaire : Hôtel du Parlement, Québec 18:30 International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 8 Program – Friday June 20th Amphithéâtre Hydro-Québec (room 2530), Pavillon Desjardins, Université Laval MC in hadrontherapy I Chair : Jan Seuntjens, McGill University, Canada 08:30 Harald Paganetti USA Application of Monte Carlo dose and effect calculations in proton therapy 09:00 Shirin Enger, Valerio Giusti and Pedro Arce Canada Accuracy of proton interactions below 20 MeV in Geant4 09:30 J. Perl, J. Schümann, J. Shin, J. Ramos,-Méndez Bruce A. Faddegon and H. Paganetti USA Status of the TOPAS Monte Carlo System for Proton Therapy 09:45 J. Schümann, Bruce A. Faddegon, D. Giantsoudi, A. McNamura, J. Perl, L. Polster, J. RamosMéndez, I. Rinaldi, J. Shin and H. Paganetti USA Biological modeling in TOPAS 10:00 Coffee MC in hadrontherapy II Chair : Anna Celler, University of British Columbia, Canada 10:30 Marta F. Dias, Charles-Antoine Collins Fekete, David C. Hansen, Marco Riboldi and Joao Seco Italia Improving carbon relative stopping power estimates for patients, using daily carbon imaging with pre-treatment single or dual energy CT. 10:45 J. Ramos-Méndez, J. Perl, J. Schümann, J. Shin, H. Paganetti and Bruce A. Faddegon USA Improved Efficiency in Monte Carlo Simulation for Passive-Scattering Proton Therapy 11:00 Bruce A. Faddegon, J. Shin, Castenada and Inder K. Daftari USA A sub-millimeter experimental benchmark of a 67.5 MeV proton depth dose curve in water Carlos M. Tissue assignment in MC Chair : Tony Popescu, University of British Columbia, Canada 11:15 Mathieu Gaudreault, Guillaume Landry, Luc Beaulieu, and Frank Verhaegen NL, Canada Tissue Identification by Dual Tomography for Brachytherapy 11:30 A. Di Salvio, S. Bedwani, H. Bouchard and J-F. Carrier Canada Evaluation of the performance of a dual energy CT segmentation method using a Monte Carlo imaging simulation environment 11:45 Bas W. Raaymakers, G. H. Bol, C. Kontaxis, J. J. E. Kleijnen, J. Wolthaus, B. Van Asselen, S. P. M. Crijns, A. N. T. J. Kotte and J. J. W. Lagendijk NL Application of Monte Carlo dose calculations for online replanning for the hybrid MRI radiotehrapy accelerator 12:15 Lunch Energy Computed International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 Amphithéâtre Hydro-Québec (room 2530), Pavillon Desjardins, Université Laval Dosimetry II Chair : David W O Rogers, Carleton University, Canada 13:30 Yuji Kamio and Hugo Bouchard Canada A study of the limitation of radiation detectors in nonstandard conditions using EGSnrc 13:45 Yuji Kamio and Hugo Bouchard Canada Characterization of the response of nine radiation detectors in small fields and IMRT beams using EGSnrc 14:00 P. Papaconstadopoulos, Seuntjens Canada On-axis and off-axis correction factors for modern detectors in small field dosimetry 14:15 Kyle O’Grady, Stephen D Davis, Papaconstadopoulos and Jan Seuntjens Canada Depth and off-axis dose perturbation effects in water in an 18 MV photon beam for a liquid ionization chamber and an air-filled ionization chamber 14:30 Johnny E. Morales, Scott B. Crowe, R. Hill and J. V. Trapp Australia A comparison of field factors for small field x-ray dosimetry with Gachromic EBT3 film and Monte Carlo simulations for a Novalis linear accelerator 14:45 Jan Seuntjens Canada Workshop closing and future directions 15:00 End of workshop F. Tessier and J. Pavlos Grand Salon, Pavillon Desjardins, Université Laval Posters Charles-Antoine Collins Fekete, Marta F. Dias, David C. Hansen, Luc Beaulieu and Joao Seco USA, Canada On-line relative stopping power optimisation using multiple angle proton radiography and SECT/DECT prior-knowledge information V. Letellier, E. Constant, L. De Marzi, J. Argaud, N. Fournier-Bidoz and A. Mazal France AVOQA: Application for Voxelization Optimized by Quadtree Algorithm, New CT-scan voxelization tool for MCNPX Nicolas Garnier, Dyaa Amer, Rémy Villeneuve, Eric Franchisseur, Mourad Benabdesselam, Cécile Ortholan and Benjamin Serrano Monaco Impact of correlation between CT numbers and tissue parameters on Monte Carlo simulations : dosimetric aspects Benjamin Auer, Virgile Bekaert, Jean-Michel Gallone, David Brasse and Ziad El Bitar France Scatter correction with Monte Carlo pre-calculated kernels M. Šefl, V. Štěpán, K. Pachnerová Brabcová, I. Ambrožová, O. Ploc, S. Incerti and M. Davídková Czech Republic Calculation of solid-state track-etched detectors response in 290 MeV/u and 400 MeV/u carbon-12 ion beams using Geant4 Daniel Maneval, Benoît Ozell and Philippe Després Canada Challenges in implementing a GPU-based Monte Carlo transport code for proton dose calculations Guilherme Franco Inocente, Ana Flávia Vidotti Roder and Joel Mesa Brazil Effects of the position variation of an inhomogeneous material in water using Monte Carlo simulation Dmitri Matenine, Yves Goussard and Philippe Després Canada Fast Monte-Carlo simulation of Cone-Beam X-ray image formation using GPUMCD 9 International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 10 Abstracts Monte Carlo simulations for small animal precision radiotherapy research Frank Verhaegen1,2 , Patrick Granton1,2 , Stefan Van Hoof1,2 , Daniela Trani1,2 and Ludwig Dubois1,2 1 2 Department of Radiation Oncology, MAASTRO (GROW), Maastricht, the Netherlands School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, the Netherlands The novel field of small animal radiotherapy (SmART) image-guided precision research aims to downscale radiotherapy to the size of small animals, enabling the study of models for radiation response of normal tissue and tumors. Novel image-guided precision irradiators are now available that greatly facilitate this. They also enable studies of synergies of e.g. drugs and radiation. In this work we will give an overview of the role of Monte Carlo modelling in this novel field. A small animal precision irradiator (XRAD 225Cx, PXi, North Branford, CT), equipped with a high resolution cone beam CT imager, and a bioluminescent imaging system has been used for various small animal research projects. The irradiation unit and the CBCT share a common reference coordinate frame. A procedure was implemented to extract dual-energy CT data from the CBCT imager, enabling the derivation of 3D geometric distributions of mass density maps or atomic number maps. These are useful to improve treatment planning dose calculations and tissue segmentation To enable the usage of the animal imaging information at the treatment planning stage, a dedicated treatment planning system (TPS), SmART-Plan, based on Monte Carlo simulations, was developed and validated. It can plan the irradiation of small specimens such as mice or rats with either multiple coplanar beams or arcs for 225 kV x-rays. Special care was given to dose calculation accuracy for these low energy x-rays. For the dose calculations a full phase space source of the x-ray target was used as well as a simplified faster analytical technique to construct phase space sources at the collimator exit. To verify the dose delivery to the animals, the onboard imager was used. The acquired images were compared to images calculated from Monte Carlo simulations. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 11 Particle navigator for hybrid voxelized/analytical phantoms in Monte Carlo simulations for medical applications Julien Bert1 , Y. Lemaréchal1 and D. Visvikis1 1 LaTIM INSERM UMR 1101, CHU Morvan, Brest, France Monte Carlo simulations (MCS) applied in particle physics play a key role in medical imaging and particle therapy. In such simulations particles are transported through voxelized phantoms derived from patient CT images. However, a voxelised phantom representation has limitations in certain medical applications. Voxel sizes do not allow incorporating fine elements within the patient CT phantoms like artificial implants from CAD modeling (screws, hip replacements, brachytherapy seeds, etc) or anatomical details extracted from other imaging modalities, such as for example MRI (arteries, spinal cord, atheroma, etc). A potential solution based on the use of smaller voxels for modeling complex objects will dramatically increase simulation computational run times. Another approach is the use of the parallel world concept [1-3] to resolve the voxelized/analytical simulation issue. However, each parallel world requires its own navigator, and the particle stepping is driven by the smaller step returned by these navigators. In addition, running several navigators within the same simulation and considering every step is not efficient. In this work we propose the combination of both voxelized and analytical phantoms within the same MCS by defining a new hybrid particle navigator. This navigator allows MCS using voxelized phantoms including overlapping complex analytical objects. It improves particle stepping by taking advantage of the uniform grid naturally defined by the voxelized geometry. Both voxelized and analytical geometries are described within a common representation using a hierarchical tree. This new hybrid navigator was assessed considering different applications, including brachytherapy, intra-operative radiotherapy, and angiography imaging simulations. Brachytherapy performance was assessed by comparing MCS using a pure analytical and the proposed hybrid (voxelized/analytical) geometries. A perfect agreement was found between both simulations for the different applications considered without any impact in the overall execution times. We demonstrated through different medical applications, Fig. 1 (a) angiography imaging and (b) intraoperative radiotherapy using IntraBeam, the capability of the proposed projector to accurately and efficiently handle phantoms defined by a mixture of voxelized and analytical objects. [1] G. Yegin 2003 Nucl. Inst. and Meth. in Phys. Research 211-331; [2] J. Apostolakis et al. 2008 IEEE MIC 883; [3] Enger S A et al. 2012 PMB 57 6269 International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 12 The role of accurate Monte Carlo modelling of an experiment in deducing photon cross section uncertainty E. S. M. Ali1,2 , M. R. McEwen3 and David W. O. Rogers1 1 Carleton Laboratory for Radiotherapy Physics, Carleton University, Ottawa, Canada Ottawa Hospital Cancer Center, Ottawa, Canada 3 National Research Council of Canada, Ottawa, Canada 2 When a high accuracy experiment is modelled in great detail using a well-benchmarked Monte Carlo code, the level of agreement between measurements and simulations can be used to investigate the uncertainty in the input cross section data to the Monte Carlo model. In this study, this approach is used to investigate the uncertainty in the NIST XCOM photon cross sections [http://physics.nist.gov/xcom] at megavoltage energies. Exponential attenuation of photon beams in narrow beam geometry was chosen because it is particularly sensitive to small cross section errors. Attenuation measurements were made at the NRCC research linac for 10-30 MV photon beams generated without a flattening filter using Be, Al and Pb targets. The detector was a Farmer chamber, and the attenuators were incremental thicknesses of graphite and lead to reduce the primary signals by roughly two orders of magnitude. The measurement uncertainty on most of the smallest signals was ~0.6%, including the uncertainty in the incident electron parameters. A detailed EGSnrc model of the experiment was created, with the input electron parameters to the model independently known. Two new features had to be added to EGSnrc: modelling photonuclear attenuation, and using the exact XCOM data as input. These features have recently been added to the standard EGSnrc distribution (V4.2.4, 2013). Comparisons between the EGSnrc-calculated transmission data and the measured transmission signals showed discrepancies that are mostly within 2%. With the high accuracy of both the measurements and the Monte Carlo model, it was possible to attribute these discrepancies to errors in the input photon cross sections to the simulations. An energy-independent cross section scaling factor that minimizes these discrepancies was determined and used to deduce the cross section uncertainty. The final material-independent energy-independent 95% upper-bound estimate of the uncertainty on the XCOM mass attenuation coefficients in the energy range from 1 to 30 MeV was found to be 0.5%, with a reduced chi-squared of 1.1 for 139 degrees of freedom. The 0.5% estimate is significantly smaller than the current qualitative estimate of 1 ≈ 2% by Hubbell [1]. This study highlights the role that accurate Monte Carlo simulations can play in quantifying the uncertainty in basic data. [1] Hubbell 1999 Phys. Med. Biol. 44 R1-R22 International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 13 Incorporating Electric and Magnetic Fields into EGSnrc Victor N. Malkov1 and David W. O. Rogers1 1 Carleton Laboratory for Radiotherapy Physics, Carleton University, Ottawa, Canada Electric and magnetic fields (EMFs) influence charged particle trajectories and energies. The introduction of hybrid MRI-radiotherapy machines for guided radiotherapy makes it desirable to perform Monte Carlo simulations of charged particle transport in media under the influence of a magnetic field. Such capabilities provide better understanding of the electron return effect, dose perturbations, and changes in dosimeter sensitivity due to the influence of EMFs. In this study, the Lorentz force on electrons/positrons has been incorporated into EGSnrc, and, although such developments have been previously considered, we aim at providing an efficient and well benchmarked implementation which can be released as part of the official EGSnrc package. EGS4, the predecessor to EGSnrc, included an EMF subroutine, but the transition to a new electron transport algorithm, and the introduction of a single scattering mode required its abandonment. The main ideas of the EGS4 EMF algorithm are maintained, but the new code is now incorporated into the EGSnrc electron transport system, and several optimizations are performed to increase efficiency to accommodate for the larger steps taken in EGSnrc.These improvements are crucial to the overall performance, since, even though the method is convergent under small steps, timing studies reveal that the previously required restrictions can cause nearly a 9 fold increase in the computation time. To verify the validity of the algorithm, comparisons are first made to vacuum solutions of the electron trajectories in EMFs. Next, the influence of magnetic fields of varying amplitude on the central-axis dose of an electron pencil beam on water, and on the dose distributions due to 1.25 MeV and a 6 MV photon beams are analyzed. As seen in Figure of the normalized dose for a parallel 6 MV photon beam with a field size of 4 × 4 cm2 incident on a segmented water slab, significant dose variations occur in the presence of a magnetic field. Further, due to the added curvature of the electron path induced by the EMF a boundary crossing algorithm has been developed to allow for varying geometries. This new approach to boundaries is tested by performing an ion chamber simulation, and determining any step size dependencies. Overall, this work will allow for an efficient incorporation of spatially varying EMFs into simulations. Future development will concentrate on further testing and optimization of the code prior to release for general use. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 14 Comparison between EGSnrc, Geant4, MCNP5 and Penelope for electron beams J. P. Archambault1 and Ernesto Mainegra-Hing1 1 National Research Council of Canada, Ottawa, Canada As the complexity of problems solved using Monte Carlo techniques grows, as in the case of IMRT and IGRT, it becomes more difficult to exactly determine where differences among different MC codes are coming from. A simple geometry is chosen to highlight similarities and differences of electron transport calculations among the most commonly used MC simulation systems in radiation physics. Calculations of energy deposited in water spheres of different radii surrounded by air were compared for EGSnrc, Geant4, MCNP5 and Penelope. An electron source emitting monoenergetic pencil beams of 0.5 MeV, 1.0 MeV and 5.0 MeV was placed 5 cm from the center of the sphere whose radius varied from 0.5 cm to 4.5 cm. The choice of such a simple geometry allows the focus to be placed on the phyics models used by these codes. Three different physics lists for Geant4 were studied; G4Standard the default list designed for high energy particle physics experiments, G4Livermore and G4Penelope, both designed for low energy electromagnetic physics. Three different energy-loss straggling algorithms were used for MCNP5; the default algorithm, the ITS algorithm and the energy- and step-specific algorithm. Simulation results are compared to single-scattering modes for EGSnrc, Geant4 and Penelope and a step-size study performed for MCNP5. Differences of up to a factor of 5 were found for 0.5 MeV electron beams and the smallest radii when using default settings in some of the MC codes. The agreement improves as the radii and the energy increase. All codes tend to agree in SS mode, at the 1% level. The process required to find best parameters reproducing SS results, demonstrates the varying degrees of electron step-size dependency of these codes. - Energy deposition in H2O spheres for 500 keV e Energy deposition ratio Edep/EdepSS 6 EGSnrc Penelope Geant4 (Standard) Geant4 (Penelope) MCNP5 (default) MCNP5 (ITS) 5 4 3 2 1 0 0 0.25 0.5 0.75 1 1.25 1.5 1.75 2 sphere radius r / cm 2.25 2.5 2.75 3 International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 15 A New Monte-Carlo Simulation Tool: Penelope Rewritten From Scratch Aurélien Croc de Suray1 and Juan-Carlos Garcia-Hernandez1 1 CEA List, Gif-sur-Yvette, France Penelope is one of the widely used Monte-Carlo simulators used in the nuclear medicine field. This application simulates and transports electron, positrons and photons of energy between 50 ev and 10 GeV through a geometric scene composed of modules described by quadric surfaces. Different kinds of estimations can be obtained such as the energy or the dose deposition in a module or a customised area. Whereas the implemented physics models are appreciated due to their very good precision another strong point is the presence of some variance reduction algorithms. All these aspects lead to high quality predictions in a short amount of computing time.However the current code presents some drawbacks. As examples: • The geometry code is not optimal for complex scenes and cannot deal with high number of modules; • Most of buffers, in particular detector counters, have a hard-coded maximum size preventing the user from easily going through; • Developing new variance reduction algorithms is not straightforward; • The simulation is not parallelized. In order to improve this simulator it has been completely rewritten from Fortran to C++ with a new object-oriented architecture so that future enhancements will be added readily.On the one hand backward compatibility with the 2006 version lets users to use it without changing their configuration, geometry or material files. On the other hand the architecture of the code offers new opportunities to develop and support other geometries, sources, detectors, variance reduction algorithms, etc. New features are: • Support of voxel geometries; • New variance reduction algorithm which forces photons to interact into a specific geometric module; • Plug-in mechanism in order to load customized geometry, source, detectors etc.; • New and verbose configuration file structure which lets customized plug-ins to grab information from it; • No more limitations in buffer sizes / in detectors number of channels; • New detector counters algorithm to avoid rounding problem when simulating high number of showers; • Code parallelized through MPI. Ideas for the future would be to add the transport of protons. Thus this talk will introduce the Penelope Monte-Carlo simulation tool and its drawbacks. Next the new rewritten version with its different improvements will be presented. Then different simulation results will be showed. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 16 Increasing efficiency of BEAMnrc-simulated Co-60 beams using directional source biasing (DSB) Blake Walters1 and Iwan Kawrakov1 1 National Research Council of Canada, Ottawa, Canada There is ongoing interest in the Monte Carlo simulation of Co-60 treatment beams because of the possibility of accurately calculating ion chamber beam quality correction factors (kQ ), investigations into the use of Co-60 in IMRT and, more recently, the potential of using Co-60 treatment with magnetic resonance imaging (MRI) for image guided radiotherapy (IGRT). Monte Carlo simulations of Co-60 beams have been performed using BEAMnrc, a powerful tool for treatment head simulation using the EGSnrc radiation transport code. However, to obtain reasonable doseprecision, full simulations of the treatment head require ~100 hrs on 15 1.8 GHz CPU’s and are, thus, impractical. This work introduces a variance reduction technique, called directional source biasing (DSB). DSB preferentially generates split, low-weight primary photons from the isotropically-radiating Co-60 source that are directed into the treatment field. These photons are further split and radially redistributed upon entering the primary collimator, thus taking advantage of radial symmetry above the collimator to reduce the initial number of primary photons generated and tracked in the upper portion of the treatment head. Additional computation time is saved by subjecting secondary electrons to Russian Roulette. These high-weight electrons can then be split below the source capsule if the user is interesed in secondary electron effects. Using BEAMnrc simulated Co-60 beams incident on a water phantom (0.5 cm3 voxels), DSB is shown to increase the dose calculation efficiency for doses > 0.5Dmax by a factor of 40 over the highest efficiency previously obtainable [1]. Efficiency depends on the photon splitting number (nbrspl) and is optimized at nbrspl values in the range 20,000-40,000 (See Figure 1). Thus, the ~100 hr Co-60 dose calculation now requires only 2.5 hrs, making accurate Monte Carlo calculation of kQ values and simulations of Co-60 based radiotherapy techniques feasible. Implementationof DSB in beampp, an accelerator simulation code that uses the egs++ geometry package, results in a further 5% increase in dose efficiency (See Figure 1). [1] Mora et al. 1999 Med Phys 26(11) 2494-2502 International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 17 Fast exponential track length estimator for Monte-Carlo simulations of small-animal radiation therapy François Smekens1 , J. M. Létang1 , C. Noblet2 , S. Chiavassa2,3 , G. Delpon2,3 , N. Freud1 , S. Rit1 and D. Sarrut1 1 CREATIS, Université de Lyon, Lyon, France Centre de Recherche en Cancérologie Nantes - Angers, Nantes, France 3 Institut de Cancérologie de l’Ouest, Centre René Gauducheau, Saint-Herbelain, France 2 MC simulation are known to be accurate and time-consuming simulation methods for dosimetric applications. Recently, we proposed the exponential track length estimator (expTLE) method, a kerma-based method mixing MC splitting, ray casting and deterministic dose calculation in order to speed-up low energy photon MC simulations. It provided up to 25-fold gain of speed compared to the "state-ofthe-art" track length estimator method (TLE). However, the method was limited to simulations with punctual photon source irradiating a single voxelised volume, without the ability to cope with structures outside the patient volume. In the field of preclinical studies, small animal radiotherapy (SMART) is appropriate for such MC variance reduction technique. Indeed, SMART implies the simulation of a low photon beam (below 250 keV) taking into account the x-ray tube focal spot heterogeneity in order to irradiate submillimeter resolution volumes. In this work, we propose two improvements to the expTLE method. First, we extended the splitting multiplicity concept to all photon sources: primary (x-ray generator) and secondary (inside and outside the voxelised patient volume). The primary photon source is based on the MC event generator, in contrast to the secondary split photons generated using the process generator (Compton and Rayleigh scattering and fluorescence). Hence, any source type can be taken into account. Then, instead of propagating the split photons as classical MC particles, a mixed navigation system has been implemented. Outside voxelised volume, a virtual MC particle called ’hybridino’ is introduced. Hybridino is associated with a weight decreasing according to the encountered volumes attenuation. Inside voxelised volume, a fast raycasting technique was used to perform the dose calculation by using attenuation and energy absorption coefficients.We validated and analysed the proposed method for two realistic small animal treatment plans. The kerma approximation, consisting in the complete deactivation of electron transport, is discussed. For each simulation, the optimal multiplicity values were identified. Then, the expTLE was compared to analog MC and conventional TLE in terms of dose convergence and efficiency.We found that optimal splitting multiplicities vary from 150 to 400 depending on the dose level of interest and the dose contribution. The weak dependence of the efficiency on the multiplicity allows us to fix this parameter to a single value of 200 with no significant efficiency loss. In all situations, discrepancies in integral dose were below 1%. Using optimal expTLE setting, the speed up factors were about 104 compared to the analogMC and vary from 10 to 15 compared to conventional TLE. Finally, expTLE provide results similar than TLE while reducing the simulation time from about 1 hour to 5 min considering a single CPU for typical small animal radiation therapy applications. A theoretical framework to improve Monte Carlo algorithms coupled to magnetic fields Hugo Bouchard1 and Alex Bielajew2,3 1 Acoustics and Ionising Radiation Team, National Physical Laboratory, Teddington, UK Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor (MI), USA 3 Ionizing Radiation Standards, National Research Council of Canada, Ottawa, Canada 2 The integration of MRI and radiotherapy can provide real-time image guidance, promising major benefits to patients in terms of dose delivery accuracy. However, it has been reported that MRI-strength magnetic fields can have significant effects on dosimetry. These must be modelled using Monte Carlo (MC) codes that combine deterministic Lorentz forces with stochastic interactions as independent processes (e.g., PENELOPE, GEANT4, EGS4). In reality, because of the coupling between the multiple scattering (MS) of charged particles and the Lorentz force, an independent treatment of these processes requires small steps sizes, reducing efficiency. Furthermore, such an implementation lacks rigorous self-consistency validation, since it has not been shown that the conditions required by the Fano cavity test in varying density media can be achieved in the presence of magnetic fields. Herein, we propose a new theoretical framework that couples magnetic fields to radiation transport and suggest two new algorithms for MC calculations. The Boltzmann transport e+ /e− equation is modified to account for the Lorentz force. The applicability of Fano’s theorem using magnetic fields is investigated. Using the same approach as the theory of Lewis, transport equations are reduced using a spherical harmonics expansion to investigate the feasibility of developing a new algorithm accounting for the coupling between MS and magnetic fields. Firstly, we demonstrate that Fano’s theorem does not apply in the presence of magnetic fields. The main consequence is that the standard Fano cavity test cannot be used with varying density media in the presence of magnetic fields, and therefore a new test must be designed to validate the accuracy of charged particle transport simulation under such conditions. Secondly, we demonstrate that the reduced Boltzmann equations can be used to develop an exact MS theory, one that allows larger step- sizes, thereby improving simulation efficiency. However, this development breaks the azimuthal symmetry of conventional MS theories, necessitating the development of new theoretical techniques. The theoretical framework proposed herein, will enable the development of a new accuracy test for MC simulations assesses the influence of magnetic fields. Additionally, the proposed approach will allow the development of a new MS theory, adapted, in a theoretically rigorous fashion, for magnetic fields, allowing the possibility of a new, highly efficient MC algorithm. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 18 Ausgab objects in EGSnrc: Track, dose, and fluence scoring Ernesto Mainegra-Hing1 1 National Research Council of Canada, Ottawa, Canada The generic EGSnrc class EGS_AusgabObject allows interfacing with the electromagnetic shower process from outside any C++ user-code. Ausgab objects can be loaded as dynamic shared objects (DSOs) upon user’s request. The philosophy behind ausgab objects and their implementation in EGSnrc are described in detail. Track, dose and fluence scoring objects are thoroughly discussed and specific practical examples presented. These ausgab objects combined with the egspp source and geometry modules would allow using EGSnrc as a generic application which can be operated via an input file. If one is interested in calculating energy deposited, fluence, energy fluence, or any related quantity such as dose or kerma in an arbitrary source/geometry combination, one can already do this with any of the C++ EGSnrc user-codes that make use of input files. Improving LDR brachytherapy TLD measurements using Monte Carlo techniques David W. O. Rogers1 and M. Rodriguez2 1 2 Carleton Laboratory for Radiotherapy Physics, Carleton University, Ottawa, Canada Princess Margaret Hospital, Toronto, Canada Dose rate constants (DRCs), the ratios of the dose rate 1 cm from a seed per unit air kerma strength, play a central role in dosimetry of Pd-103 and I-125 seeds. Historically they have been measured using TLDs in various plastic phantoms. The TLDs are calibrated in Co-60 rel ) used to extract the absorbed dose to water or 6 MV beams and previously measured or calculated relative absorbed dose sensitivities (SAD in the phantom. A phantom correction factor, Pphant is used to deduce the corresponding absorbed dose to water in water and hence the DRC. Although uncertainties on individual measurements were high (5% or more), the "modern" measured values for 24 different seeds were, on average, a surprising 5% higher than Monte Carlo (MC) calculated values. Much of this is due to use of either measured TLD rel rel SAD values of 1.41 for Pd-103 and I-125 vs megavoltage calibrations or calculated values which were based on the assumption that SAD rel equals the relative absorbed dose energy dependence (f ) of TLD material based on MC calculations of the dose to LiF per unit dose to water at the same point. This assumption, which ignores the relative intrinsic energy dependence of LiF, was justified by experimental data from the 1990s with large uncertainties. Using the BrachyDose code we have calculated f rel values of LiF and find that they vary by up to 8.4% for different isotopes, different TLD shapes and even between different seed models for the same isotope. We remove the rel SAD values and Pphant values from the original measured DRC values, insert our newly calculated values of f rel and Pphant and compare to calculated values of the DRCs. We deduce the value of the relative intrinsic energy dependence (the dose to the LiF per unit reading rel ) which gives the best fit of the revised measured DRCs and the MC values. The average differences are now 1.2% from the TLD, kbq rel and 0.3% vs the original 5% and more importantly, the implied values of kbq for I-125 and Pd-103 are 1.076(15) and 1.095(25) which are in good agreement with the values measured by Davis et al and Nunn et al in x-ray beams. Our calculated Pphant values have much lower statistical uncertainties than previous values but systematic uncertainties from density and composition variations are significant. MC calculated correction factors for TLD detectors are essential for high accuracy measurements in low-energy brachytherapy. These results suggest clinical DRCs, rather than being averaged MC and measured values, could be based on MC calculated values as done with Ir-192. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 19 Recent advances in BrachyDose Martin Martinov1 , David W. O. Rogers1 and Rowan M. Thomson1 1 Carleton Laboratory for Radiotherapy Physics, Carleton University, Ottawa, Canada In recent years, BrachyDose has been developed in the Carleton Laboratory for Radiotherapy Physics (CLRP) as a fast EGSnrc-based Monte Carlo simulation package for brachytherapy. This code has been used to investigate dosimetry for a variety of brachytherapy applications both within the CLRP and with clinical collaborators. This presentation will review several recent updates to BrachyDose towards its future release to the scientific community. A Graphical User Interface (GUI) was built on the Qt4 framework to create a user-friendly environment for BrachyDose use. The GUI enables full access to all aspects of the text-based BrachyDose input file which specifies simulation geometry, source spectrum, run mode, calculation type, simulation parameters, etc; there are tooltips and an error checker for each input. Simulations may be submitted to a cluster and monitored using the GUI. An advanced geometry previewer has been developed within the GUI; it may be used to create images combining BrachyDose geometry, CT data, and isodose contours (see Figure 1). Dose distributions output by BrachyDose are in the 3ddose format from the BEAMnrc system. A stand-alone program, 3ddose_tools, was built for analysis of any files in the 3ddose format (not limited to those produced by BrachyDose). 3ddose_tools includes a reimplementation of all the functionality of statdose (distributed with EGSnrc/BEAMnrc) but with additional features. For example, 3ddose_tools has the ability to analyse multiple dose distributions simultaneously, create DVHs, and extract specified metrics. Analysis may be performed for the whole dose distribution provided in the 3ddose file, or it may be limited to a particular volume (e.g., that containing selected media specified by an egsphant file). The CLRP TG-43 and BrachyDose geometry databases continue to be updated. Three new seed models, the THINSeed 9011, Theragenics AgX100 and IsoRay CS1 have been added and TG-43 parameters computed; several eye plaque models have been developed. Figure 1 shows a simulation comparing the dose distributions of 3 different seed models, one of which was the CS1, used in a standard COMS plaque treatment of Ocular Melanoma. The GUI, 3ddose_tools and the updated geometry database will all be included in the upcoming distribution package of BrachyDose. Once a distribution method and revision system is decided upon, it will be made publicly available under the GNU public license. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 20 Monte Carlo dose calculations for permanent implant brachytherapy: Interdependence of metallic artifact reduction and tissue assignment N. Miksys1 , Luc Beaulieu2,3 , J. E. Cygler4 , C. Xu2,3 , J. M. Caudrelier5 and R. M. Thomson1 1 Carleton Laboratory for Radiotherapy Physics, Carleton University, Ottawa, Canada Département de radio-oncologie and Centre de recherche du CHU de Québec, Centre hospitalier universitaire de Québec, Québec, Canada 3 Département de physique, de génie physique et d’optique and Centre de recherche sur le cancer, Université Laval, Québec, Canada 4 Department of Medical Physics, Ottawa Hospital Cancer Centre, Ottawa, Canada 5 Department of Radiation Medicine, Ottawa Hospital Cancer Centre, Ottawa, Canada 2 Purpose: Monte Carlo (MC) dose calculations for permanent implant brachytherapy (BT) require modelling of the patient geometry. Voxelized MC phantoms can be derived from post-implant CT scans which first require the application of a metallic artifact reduction (MAR) algorithm to mitigate BT seed streaking artifacts before image voxels are mapped to a tissue type and mass density using a tissue assignment scheme (TAS). This work uses clinical prostate and breast BT examples to explore the interdependence of MAR and TAS on MC dose calculations.Methods: MC dose calculations, using EGSnrc user-code BrachyDose, are performed on clinical prostate and breast BT cases using MC phantom models derived using one of four MAR methods (raw sinogram, virtual sinogram, 3D median filter, simple threshold replacement) and one of four site-specific TAS. Dose distributions and clinical metrics are compared to each other and to TG-43 results. Results: In the prostate and breast, failing to apply MAR and using a TAS which accounts for calcifications can decrease the target D90 by over 50% compared to the average of other MC results. Sinogram based MAR methods can leave residual high CT number streaking artifacts which could lead to an increased assignment of calcification producing higher target metrics by several percent and increased local doses by over a factor of five when compared to models which omit calcifications. 3D median filter MAR can cause an over smoothing of CT numbers which has a more significant effect in breast BT where the target volume contains both adipose and fibroglandular tissues. Thresholding-based MAR fails to eliminate low CT number artifacts and can leave residual high CT number artifacts around seeds, but results in no significant difference in metrics or local doses compared to the mean of other MC models. Compared to MC, TG-43 calculated doses overestimate D90 by up to 10% in the prostate and by up to 30% in the breast. Conclusions: Realistic patient models are required for accurate MC dose calculations. In the prostate and breast there is an interdependence of MAR and TAS modelling choices, with unique considerations for each site. MC calculations which consider calcifications yield the most accurate results but are most sensitive to the choice of MAR method. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 21 Fast GPU-based Monte Carlo dose calculations for permanent prostate implant Éric Bonenfant1,2 , Vincent Magnoux3 , Sami Hissoiny4 , Benoît Ozell3 , Luc Beaulieu1,2 and Philippe Després1,2 1 Département de radio-oncologie and Centre de recherche du CHU de Québec, Centre hospitalier universitaire de Québec, Québec, Canada Département de physique, de génie physique et d’optique and Centre de recherche sur le cancer, Université Laval, Québec, Canada 3 Département de génie informatique et génie logiciel, École polytechnique de Montréal, Montréal, Canada 4 Elekta Inc., Maryland Heights (MO), USA 2 Purpose/Objective: As stated in the AAPM report of Task Group 186, model-based dose calculation algorithms (MBDCA) in brachytherapy carry many advantages over traditional frameworks such as the TG-43 formalism. Among MBDCAs, Monte Carlo techniques have been considered the accuracy gold standard for dose calculation in radiation therapy as they rely on fundamental physics principles. However, long computation times still remain an obstacle to the deployment of Monte Carlo dose calculations in the clinic. In recent years, Graphics Processing Units (GPU) have been used to perform general-purpose calculations under massively parallel conditions. This new calculation platform allows for the development of fast dose calculation algorithms, including those based on Monte Carlo techniques. Materials and Methods: In this work, an existing GPU-based Monte Carlo code (bGPUMCD) for LDR brachytherapy was further developed, tested and optimized. The objectives were twofold: first, to evaluate the importance of X-ray fluorescence and Rayleigh scattering on the results and second, to evaluate the calculation times for clinical cases of permanent prostate implants. For this purpose, a Nucletron SelectSeed source model was developed and validated. Simulations were conducted under the TG-186 recommendations regarding radiation transport, material assignment and dose scoring. The bGPUMCD results were compared with others obtained with the well-validated GEANT4 Monte Carlo suite. Results: Simulations of the SelectSeed in TG-43 conditions using bGPUMCD reproduced within 2% the established radial and anisotropy functions of this source. The algorithm was able process more than 14.34 millions of primary photons per second. Dose calculations for permanent prostate implants were performed in less than 30 seconds in bGPUMCD, with uncertainties under 1% and under 7.5 seconds, with uncertainties under 2%, in the target volume using cubic voxels of 1 mm. GPUMCD results, regarding the isodoses distributions, were in almost exact agreement with those obtained with GEANT4 obtained over several hours of computation and dosimetric indices showed a difference of 2.7% or less inside the target. Average voxel-by-voxel comparison showed an average ratio between bGPUMCD and Geant4 between 0.9995 and 1.0005, an absolute average percent difference under 3% and an average 3%/3 mm gamma test passing rate of 96.88% with an average gamma index of 0.53 inside the target volume. Conclusions: Short execution times achieved by bGPUMCD let envision the development of Monte Carlo techniques for clinical brachytherapy. To further accelerate dose calculations, a multi-GPU setup could be considered. This compact yet powerful setup, combined with the rapid evolution of GPUs, might allow the use of accurate MBDCAs in plan optimisation, leading to potentially better solutions. Developments of GPU-based Monte Carlo simulations and their applications in radiotherapy Xun Jia1 1 Department of Radiation Oncology, University of California,San Diego (CA), USA Monte Carlo simulations have been widely used in radiation therapy. The low computational efficiency is a major obstacle preventing them from routine clinical applications. As an emerging high-performance computing hardware, computer graphics processing unit has recently been employed to accelerate Monte Carlo particle transport simulations. While promising speeds have been observed, there are also challenges to be overcome, which are due to the conflicts between the GPU hardware and the Monte Carlo algorithms. Over the years, we have developed a set of Monte Carlo packages for photon, electron, and proton transports. This talk will first present an overview about the current status of these packages. Technical challenges will be discussed, such as GPU thread divergence problem and memory writing conflict problem. The achieved high efficiency on GPU also permits novel applications of the Monte Carlo methods in radiotherapy that were computationally challenging in the past. We will also present a few examples to demonstrate the great impacts of fast Monte Carlo simulations. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 22 Hardware-Accelerated Sub-minute Monte Carlo Methods: Hope or Hype? X. George Xu1 , Tianyu Liu1 , Lin Su1 , Xining Du1 and Peter Caracappa1 1 Rensselaer Polytechnic Institute, St. Troy (NY), USA The Monte Carlo method is taken to be the gold standard for a large body of research work found in nuclear engineering, health physics and medical physics. Given that, the recent attention to circumventing the bottleneck of Monte Carlo calculations using graphics processing units (GPUs) seems to be justified, and the thought of leveraging an extremely successful gaming technology to be innovative. A few studies by the Monte Carlo community have shown the feasibility of unprecedented sub-minute or even few-second Monte Carlo dose calculations. However, early adopters of the GPU technology were criticized for their often biased comparison of performance against CPUs. Some have also noted that many parallel schemes for Monte Carlo acceleration, such as vectorized methods, are not really new. Whether GPU is just hype, and how much hope we should invest in this and other technologies, are issues to be discussed in this paper. We review the so-called “heterogeneous computing” architecture and present ARCHER (Accelerated Radiation-transport Computations in Heterogeneous EnviRonments) - a software testbed designed to support research on Monte Carlo methods under different hardware platforms including multiple-core CPUs, NVIDIA GPUs and the Intel Xeon Phi coprocessors. Results of medical physics applications performed thus far are presented, including: (1) X-ray CT dose calculations and (2) External beam radiation therapy dose verification. We present benchmark results against production codes, MCNP and GEANT4. Calculations were performed on a workstation equipped with a 6-core Intel Xeon X5650 CPU, an NVIDIA KeplerK40 GPU and an Intel Xeon Phi 5110p coprocessor. For the CT dose case, the GPU-based ARCHER code takes only 1.46 minutes, the coprocessor-based ARCHER code takes 3.52 minutes while the CPU-based code takes 11.18 minutes using 12 hyper-threads. In a tomotherapy treatment planning case, we found the GPU-based ARCHER code completed in about 36 seconds while the CPU-based code running on an Intel E5-2620 required 729 seconds using 12 hyper-threads. Finally, a number of questions are addressed that many are perhaps interested in but reluctant to ask. What do these results really mean? Are such comparisons fair to the CPUs, GPUs, and coprocessors? Will GPU technology last, or will it be just be another transitional technology that will soon be outdated? Hybridizing primary histogram-based photon source models with phase-space-lets for GPU-based Monte Carlo dose calculation Reid W. Townson1 and Sergei Zavgorodni1 1 Vancouver Island Cancer Centre, University of Victoria, Victoria, Canada In GPU-based Monte Carlo simulations for radiotherapy dose calculation, source modelling from a phase-space source can be an efficiency bottleneck. Previously, this has been addressed using phase-space-let (PSL) sources, which provided significant efficiency enhancement. We propose that additional speed-up can be achieved through the use of a hybrid primary photon point source model combined with a secondary PSL source. A novel phase-space derived and histogram-based implementation of this model has been integrated into gDPM v3.0. Additionally, a simple method for approximately deriving target photon source characteristics from a phase-space that does not contain inheritable particle history variables (LATCH) has been demonstrated to succeed in selecting ~99% of the true target photons with only ~0.3% contamination (for a Varian 21EX 18MV machine). Total simulation time using a hybrid source instead of PSLs was 2-3 times faster. An array of Varian 21EX and TrueBeam energies were tested using open fields, and all cases achieved greater than 97% chi-test agreement (the mean was 99%) above the 2% isodose with 1%/1 mm criteria. The root mean square differences were less than 1%, with a mean over the cases of 0.5%. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 23 A multi-GPU approach to GPU-based Monte Carlo dose calculations Vincent Magnoux1 , Philippe Després2,3 and Benoît Ozell1 1 Département de génie informatique et génie logiciel, École polytechnique de Montréal, Montréal, Canada Département de radio-oncologie and Centre de recherche du CHU de Québec, Centre hospitalier universitaire de Québec, Québec, Canada 3 Département de physique, de génie physique et d’optique and Centre de recherche sur le cancer, Université Laval, Québec, Canada 2 GPUs were shown to significantly accelerate Monte Carlo codes dedicated to dose calculations. Most of the studies conducted so far were based on a single GPU on a single node. In order to achieve a breakthrough in acceleration factors, multi-GPU strategies must be developed and implemented. Strategies involving CUDA, pthreads and MPI are presented in this work. The software bGPUMCD, a GPU-based Monte Carlo code, was adapted to run on multiple GPUs. Modifications were made on two levels: for multiple GPUs on a single node and for a cluster of nodes. On a single node, each GPU was managed by one thread using the pthreads library. The workload was shared among GPUs by allocating a certain amount of particles to simulate on each GPU. Results from individual GPUs were simply read from the node’s shared memory and added together. This did not affect the precision of the results compared to a single-GPU execution. For multiple nodes, MPI was used to transmit and combine the results from each node. In order to allow for better scalability, the initialization code was completely segregated into two phases: all required input data was first read from files and interpolated when needed, then copied to each GPU. Only the main thread on the master node would read that data and transmit it to the other nodes, eliminating the need for concurrent access to the file system. This scheme was tested by simulating two billion photons on up to 32 GPUs distributed across 16 nodes. Total execution time went down from 260 seconds on a single GPU to 31 seconds with the maximum number of processors. The communication overhead was only a fraction of a second. However, the CUDA context initialization time varied between 3 and 7 seconds across nodes and the gathering of all results was limited by the longest of these times. The remaining serial execution time, required to initialize the simulation and to write its results into a file, was around 9 seconds. There was thus a 16-second section of unavoidable serial or repeated work, while the speedup for the rest of the program scaled linearly with the number of processors. On recent hardware, a single simulation would benefit from up to 8 GPUs, after which serial execution time would be longer than the actual simulation work. A larger cluster would allow for multiple simulations in the same amount of time, for very fast treatment planning or for more complex simulations that include secondary particles and different particle types. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 24 GGEMS platform: GPU Geant4-based Monte Carlo Simulation Julien Bert1 , Y. Lemaréchal1 , E. Garrido1 and D. Visvikis1 1 LaTIM INSERM UMR 1101, CHU Morvan, Brest, France Monte Carlo Simulations (MCS) play a key role in medical applications, both for imaging and radiotherapy by accurately modeling the different physics processes and interactions between particles and matter (tissues and/or detectors). However, MCS are always associated with long execution times, which is one of the major issues preventing their use in routine clinical practice. Recently, graphics processing units (GPU) have become in many different domains a low cost alternative solution for the acquisition of high computation power [1]. Within this context different physics processes extracted from various MCS codes have been used and implemented on GPU targeting specific applications [2-6]. In contrast to these studies, the objective of this work was to develop a potentially unique solution in terms of flexibility and coverage for both therapy and imaging applications. The proposed efficient MCS platform for GPU architectures named GGEMS (GPU GEant4-based Monte Carlo Simulation) is an extension of an implementation framework already proposed by [7] based on the well-validated Geant4 toolkit [8]. This new platform proposes hardware adapted solution for the different components of MCS, including pseudo-random numbers generators, navigators, material definition, dose scoring, etc. Concerning electromagnetic physics effects for photons, electrons and protons there were extracted from Geant4 and implemented on GPU, including the handling of generated secondary particles. As an application example, GGEMS was used to perform brachytherapy simulations accounting for patient tissue heterogeneities and inter-seeds interactions. Within this application context the GGEMS platform allowed realistic implanted seed geometry simulations within a prostate using a hybrid voxelised/analytical navigator and tissue derived parameters using patient specific CT images. A complete dosimetry study using this low dose rate brachytherapy application (see Fig. 1) was nearly real-time using GGEMS (2 secs running on 4*GTX690) compared to several hours of calculation considering the same simulation using standard Geant4 running on a single CPU core. [1] J. Nickolls and W. J. Dally 2010 IEEE Micro 30 56; [2] X. Jia et al. 2010 PMB 55 3077; [3] B. Toth 2010 Conf. on Computer Graphics and Geometry; [4] S. Hissoiny et al. 2011 Med. Phys. 38 754; [5] J. Lippuner and I. Elbakri 2011 PMB 56 7145; [6] L. Jahnke et al. 2012 PMB 57 1217; [7] J. Bert et al. 2013 PMB 58 5593; [8] J. Allison et al. 2006 IEEE TNS 53 270 International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 25 Pre-calculated Monte Carlo on GPU: Performance and Uncertainties Marc-André Renaud1 , David Roberge2 and Jan Seuntjens1 1 2 Medical Physics Unit, McGill University, Montréal, Canada Centre Hospitalier de l’Université de Montréal, Montréal, Canada While significant progress has been made in speeding up Monte Carlo dose calculation methods, they remain too time-consuming for the purpose of inverse planning. To achieve clinically usable calculation speeds, a pre-calculated Monte Carlo (PMC) algorithm for proton and electron transport was developed to run on graphics processing units (GPU). The algorithm utilises pre-generated particle track data from conventional Monte Carlo (MC) codes for different materials such as water, bone and lung to produce dose distributions in voxelised phantoms. While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from the limited number of unique tracks in the pre-generated track bank is missing from the literature. With a proper uncertainty analysis, an optimal pregenerated track bank size can be selected for a desired dose calculation uncertainty. Dose distributions generated using PMC and benchmark MC codes were compared and found to be within 1% of each other in voxels with dose values greater than 50% of the maximum dose. In proton calculations, a small (< 1 mm) distance-to-agreement error was observed at the Bragg Peak. Latent uncertainty was characterised for electrons and found to follow a Poisson distribution with the number of unique tracks per energy. A track bank of 20,000 unique tracks per pre-generated energy in water had a size 800 MB and achieved a latent uncertainty of approximately 1%. Using an NVIDIA GTX 590, Efficiency analysis showed a 937x efficiency increase over DOSXYZnrc for 16 MeV electrons in water, and 508x for 16 MeV electrons in bone. The PMC method can calculate dose distributions for electrons and protons to a statistical uncertainty of 1% with a large efficiency gain over conventional MC codes. Before performing clinical dose calculations, models to calculate dose contributions from uncharged particles must be implemented. Following the successful implementation of these models, the PMC method will be evaluated as a candidate for inverse planning of modulated electron radiation therapy (MERT) and scanned proton beams. Improvements and developments of the GPUMCD platform Sami Hissoiny1 1 Elekta Inc., Maryland Heights (MO), USA The GPUMCD platform was introduced in 2010 as a new GPU-oriented solution to fast Monte Carlo based dose calculations. This presentation will cover recent developments and improvements that have occurred within Elekta to the GPUMCD platform. The presentation will cover a number of software as well as physics aspects. Notably, a new batch statistics method, an improved magnetic field handling and an innovative material indexing as well as an application within a CBCT scatter compensation context will be presented, along with their impact and result. The Use of Monte Carlo Simulations in Nuclear Medicine Anna Celler1 1 Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada Over the years Monte Carlo (MC) simulations have established a strong position in nuclear medicine (NM) research. Applications range from the design and testing of new imaging systems and investigations of their data structures, development and validation of different image reconstruction and data processing programs for both single-photon emission computed tomography (SPECT) and positron emission tomography (PET), include calculations of internal radiation doses from diagnostic procedures and radionuclide therapies, and even extend to the recent studies of cyclotron production of medical radioisotopes. The research program of our Medical Imaging Research Group covers all these areas. In my talk I will review the use of MC simulations in these different NM applications, briefly discuss the codes that have been specifically designed for them and show examples of MC simulations performed by us and others. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 26 The role of GATE Monte Carlo simulations in dynamic studies using a dedicated cardiac SPECT camera Sonoko Nakano1 , Amir Pourmoghaddas2 , Rachel Timmins2 , Manfred Trummer1 , Tony Farnsombe3 , Glenn R. Wells2 and Anna Celler4 1 Simon Fraser University, Vancouver, Canada University of Ottawa, Ottawa, Canada 3 Hamilton Health Sciences, Hamilton, Canada 4 Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada 2 Quantitative dynamic imaging of myocardial blood flow and flow reserve could significantly improve diagnosis of heart disease patients as compared to traditional static myocardial perfusion studies. New cardiac SPECT camera, Discovery NM 530c (GE Healthcare), is a stationary system perfectly suited for such dynamic studies as temporal data inconsistency due to a standard camera rotation is eliminated. The geometry of its 19 pinholes and associated semiconductor (CZT) detectors spans about 180o allowing for simultaneous data acquisition from all angles, but reconstructions of dynamic studies still employ static algorithms. Our goal is to improve the accuracy of Discovery NM 530c dynamic cardiac studies by simultaneous processing of all time-frames with our dynamic SPECT method. The project was performed in three stages. First, we had to exactly model camera geometry and data acquisition, secondly, develop our own static reconstruction algorithm and validate it against experimental data, and then modify it for processing multiple time-frames of dynamic acquisition. In the first part we used Monte Carlo simulation software, GATE version 6.2. Then, the reconstruction algorithm was developed to match camera geometry. To verify the correctness of our model and reconstructions, a series of sources, including one in the shape of letter “F” were simulated and measured and projections and reconstructed images were compared. In addition, images of a healthy and diseased pig heart were reconstructed. Finally, we simulated dynamic acquisitions of a line source with high and low activities changing over time. The time-activity curves (TAC) were obtained using two methods: (1) each time frame was reconstructed individually, and (2) all time-frames were processed concurrently by our new dynamic reconstruction algorithm. Development of this algorithm required exact modeling of camera geometry and acquisition protocol. GATE simulations proved extremely valuable here. They allowed us to investigate camera characteristics (maps of sensitivity and resolution), and to create and validate our static reconstruction algorithm (no proprietary manufacturer software was available). Experimental and simulated projections and images showed good agreement. Next, the algorithm was modified to process dynamic studies. TACs obtained from simultaneous processing of dynamic studies showed significant improvement over those from individual reconstructions; the curves were less noisy and very closely followed the theoretical ones (NMSE for method 1 and 2 were 18% and 3%, and 9% and 2% for low and high statistics data, respectively). For our pig model, TACs from different ROIs defined on heart images reconstructed individually had considerably higher fluctuations than those obtained from simultaneous processing. Next, we will apply this approach to reconstruction of dynamic myocardial blood flow studies. Discovery NM530c GATE simulation of the Discovery NM530c Front view Side view Set of 19 simulated projections corresponding to acquisition of “F” shaped source Head 1 Head 6 Head 15 Head 2 Head 7 Head 8 Head 16 Head 3 Head 9 Head 10 Head 17 Head 4 Head 11 Head 12 Head 5 Head 13 Head 18 Images of “F” shaped source reconstructed from experimental data from simulated data Head 14 Head 19 International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 Personalized calculation of gamma-photon absorbed dose in neuroendocrine tumors with a GPU-based Monte Carlo code 177 27 Lu-octreotate radionuclide therapy of Jean-François Montégiani1,2 , Émilie Gaudin1,2 , Price A. Jackson3 , Jean-Mathieau Beauregard4,5 and Philippe Després1,2 1 Département de radio-oncologie and Centre de recherche du CHU de Québec, Centre hospitalier universitaire de Québec, Québec, Canada Département de physique, de génie physique et d’optique and Centre de recherche sur le cancer, Université Laval, Québec, Canada 3 Department of Molecular Imaging and Targeted Therapeutics, Peter MacCallum Cancer Centre, Melbourne, Australia 4 Département de médecine nucléaire and Centre de recherche du CHU de Québec, Centre hospitalier universitaire de Québec, Québec, Canada 5 Département de radiologie and Centre de recherche sur le cancer, Université Laval, Québec, Canada 2 In peptide receptor radionuclide therapy (PRRT) of neuroendocrine tumors (NET) with 177 Lu-octreotate, two radiation types contribute to absorbed radiation dose: beta particles and gamma photons. For tumors or organs with high uptake, absorbed dose mostly comes from beta particles, which have a maximal tissue range of approximately 2 mm. However, for radiosensitive organs with low uptake, such as the bone marrow, the contribution of gamma photons to absorbed dose may not be negligible. A GPU-based Monte Carlo (MC) dosimetry code was used to assess the proportion of absorbed radiation dose attributable to 177 Lu gamma emissions. The internal radiotherapy GPU MC dosimetry framework (irtGPUMCD) was derived from a low-energy brachytherapy dosimetry code (bGPUMCD). In this code, only photons are transported and can undergo photoelectric effect, Compton effect and Rayleigh scattering. The code was implemented on a Graphics Processing Unit (GPU) to achieve fast results in clinically compatible timeframes. Serial quantitative single-photon emission computed tomography/computed tomography (SPECT/CT) acquisitions were performed 4, 24 and 72 hours after 177 Lu-octreotate administration (approximately 7.4 GBq) in eight NET patients. Images were aligned using a non-rigid deformation of CT volumes, yielding 177 Lu-octreotate 4D quantitative biodistribution with patient-specific anatomical information. irtGPUMCD produced a dose rate map for those time points. 1-cm3 volumes of interest dose rate samples were obtained for the kidney and bone marrow, organs at risk with high and low uptake respectively. Dose rate data were fitted to a bi-exponential curve, which was integrated to derive the absorbed dose for total (beta and gamma) and gamma-photon-only simulations. For the average renal dose, a very low relative contribution of the gamma photons to the total dose was found: 3.4 ± 1.4% of the total dose (range: 1.9-6.5%). For bone marrow, this gamma contribution was more significant: 20.1 ± 7.8% of total dose (range: 9.2-36.1%). These results suggest that for tumor and renal dosimetry calculations, the contribution of gamma radiation to the absorbed doses may be neglected. However, the latter needs to be considered when calculating absorbed radiation dose to the bone marrow, a critical organ with low uptake in PRRT with 177 Lu-octreotate. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 28 Development and validation of a simulation platform to model acoustic waves induced by linear accelerator irradiation Susannah Hickling1,2 , Pierre Leger1,2 and Issam El Naqa1,2 1 2 Medical Physics Unit, McGill University, Montréal, Canada McGill University Health Centre, Montréal, Canada Motivation/Objective: X-ray acoustic computed tomography (XACT) is an emerging branch of photoacoustic (PA) imaging whereby an image of the dose distribution following each pulse of kV or MV irradiation can be reconstructed by detecting radiation-induced acoustic waves. The objective of this work is to develop and validate a simulation workflow that can be used to model XACT in different situations. Methods: Our proposed platform is based on combining Monte Carlo (MC) simulations and PA models. The first step in the proposed simulation workflow uses Geant4 MC simulations to determine the dose distribution following a single LINAC radiation pulse. The dose distribution is then converted into an initial pressure distribution, and the transportation of acoustic waves in media is modeled with the MATLAB toolbox k-Wave. This gives rise to time-varying pressure waves (TVPWs) detected at transducer locations surrounding the region of interest. Computational simulations and corresponding experiments were performed to model and detect the TVPWs arising from LINAC irradiation of a lead rod in a water tank. Beam energies of 6 MV and 18 MV, lead rod depths from 5 to 11 cm, and transducer to rod distances ranging from 8 to 16 cm were investigated. Experimentally, TVPWs were detected with a single element immersion ultrasound transducer. The transducer output was fed into a commercial preamplifier and a customized analog electronic filter to reduce noise and provide further gain prior to read-out on an oscilloscope. Results: Simulated and experimental results both showed that the amplitude of the TVPWs increased with increasing beam energy, decreasing lead rod depth and decreasing lead rod to transducer distance. TVPWs for the lead rod at depths of 5 cm and 9 cm demonstrated that the relative amplitude difference between the two depths for the first peak to valley transition is 73% for the simulated signals and 75% for the experimental measurements (Fig. 1). Additionally, frequency analysis of both the simulated and experimental TVPWs indicated a frequency peak near 50 kHz. Conclusions: We have demonstrated that our simulation platform successfully enables the prediction of the frequency spectrum and relative amplitudes of TVPWs under different irradiation conditions, and can be applied to other more complex situations to model XACT. (a) (b) Fig. 1: Simulated (a) and experimental (b) signals for the induced acoustic waves after irradiation of a lead rod placed at depths of 5 cm and 9 cm in a water tank with an 18 MV LINAC beam. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 29 Monte Carlo simulation of an X-ray Luminescence Optical Tomography scanner prototype Sarahi Rosas-Gonzalez1 , Mercedes Rodriguez-Villafuerte1 and Arnulfo Martinez-Davalos1 1 Instituto de Fisica, Universidad Nacional Autonoma de Mexico, Mexico, Mexico A new hybrid imaging modality, x-ray luminescence optical tomography (XLOT), has been proposed to study problems related to deeptissue small-animal imaging. In this technique luminescent nanoparticles emit optical photons when irradiated with a collimated x-ray beam. XLOT combines the high sensitivity of optical imaging and the high spatial resolution of x-ray imaging. We are currently building an XLOT prototype using SiPM photodetectors and a low energy x-ray tube. It uses submillimeter diameter collimators to produce an X-ray pencil beam to achieve high spatial localization of the luminescent nanoparticles. The use of this technique for small-animal imaging applications requires the determination of the dose delivered to the subject. Also, accurate knowledge of the energy deposition map inside the subject is useful for optimization of the optical imaging model used in the tomographic reconstruction. However, the use of a narrow beam of low energy X-rays complicates the use of traditional methods for the determination of the absorbed dose. In this work we report the calculation of the deposited energy distribution map by means of Monte Carlo simulation (PENELOPE v.2011) using an energy range of 30-90 kVp, W target and 1.0 mm Al filtration. The results show that the dose scales linearly with kVp for a fixed concentration of luminescent nanoparticles and air-kerma rate and that the dose ratio for a 3 mm diameter insert containing 10 mg/ml Gd2O2S embedded in a 30 mm diameter water phantom is 6:1. This ratio drops to less than 2:1 for a 1 mg/ml concentration. The imaging performance of the system has been evaluated by means of simulations of the NEMA NU4 image quality and micro-Derenzo phantoms. The results indicate that quantification of the luminescent particle concentration deteriorates with object size, up to 80% when going from 5 to 1 mm diameter objects at 1 mg/ml concentration. The optical spatial resolution using 1 mm step size and 10 degrees angular step is of the order of 2 mm. Acknowledgements: Project PAPIIT IN105913, DGAPA-UNAM, and PAEP-UNAM. The application of Monte Carlo techniques in patient imaging dose calculations and imaging dose reductions George Ding1 1 Department of Radiation Oncology, Vanderbilt University School of Medicine, Nashville (TN), USA The increased utilization of x-ray imaging in patient treatment positioning significantly improves the accuracy of radiation treatment delivery. Image-guided radiation therapy represents a new paradigm in the field of high-precision radiation medicine Image-guided radiation therapy (IGRT) represents a new paradigm in the field radiation oncology for cancer treatment. Daily imaging procedures for patient setup also add additional dose to the treatment target as well as normal tissues. Knowledge of these additional imaging doses to patients is important for patient treatment management as well as for imaging dose reductions. Monte Carlo techniques play an essential role in obtaining xray beam characteristics from different image devices and in calculating radiation dose to patients resulting from an imaging procedure. This talk summarizes beam characteristics from different image devices, provides an overview of radiation dose to patients resulting from different imaging procedures including electronic portal imaging, MVCT, MV-CBCT, kV radiographs, kV-CBCT, and Novalis TX ExacTrac acquisitions and discuss techniques to reduce the imaging doses to patient sensitive organs in clinical applications. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 30 Transport-theoretic variance reduction tools for Monte Carlo simulation of kilovoltage photon fields Jeffrey F. Williamson1 and Andrew J. Sampson1 1 Department of Radiation Oncology, Virginia Commonwealth University, Richmond (VA), USA Discrete-event Monte Carlo simulation is widely used for the simulation of kilovoltage photon fields in broad array of medical applications including brachytherapy dosimetry and treatment planning and computation of patient dose, scatter sinograms, and image quality for x-ray transmission CT and other radiographic imaging modalities. Unlike condensed-history transport of charged-particle fields, photon Monte Carlo can be shown to be an unbiased but statistically imprecise partial solution of the Boltzmann transport equation (BTE). The BTE is an integral-differential equation in 7 independent variables which completely characterizes the distribution of ionizing radiation in terms of the angular flux, given a complete description of the problem geometry, sources, and boundary conditions. Integration of Monte Carlo tools into clinical practice often requires substantial acceleration of these simulations so that low-uncertainty results can be obtained in a logistically acceptable timeframe, which in turn requires use of advanced variance reduction (VR) tools. The hypothesis argued in this talk is that describing the problem in the terms of the BTE leads to more robust and optimally designed VR tools than the commonly used heuristic approach. We will illustrate application of these principles by two innovative approaches we have introduced to the field. 1. Generalized correlated sampling for subminute 3D Monte Carlo calculations for brachytherapy planning [1,2]. CMC tallies the dose difference, ∆D, between highly correlated histories in homogeneous and heterogeneous geometries. The heterogeneous geometry histories were derived from photon collisions sampled in a geometrically identical but purely homogeneous medium geometry, by altering their particle weights to correct for bias. In low-energy seed implants for prostate and breast cancer, average efficiency gains in the clinical target volume of 40 and 60, respectively, were observed. The design problem to be solved was determination of heterogeneous-to-homogeneous geometry weight correction factors, given that the original homogeneous geometry random walk also used VRTs (forced collision and survival biasing), and that both were scored with expected-value track-length estimation. Once the problem is formulated in terms of the integral BTE, computation of correction factors is an obvious consequence of the biased sampling theorem. In addition, the BTE literature demonstrates that no general proof of efficiency improvement is possible. 2. Acceleration of Monte Carlo cone-beam CT (CBCT) scatter-projection estimation with adjoint-driven importance sampling implemented via weight windowing [3]. Monte Carlo is a promising approach for estimation of patient-specific CBCT scatter projections for reducing cupping and streaking artifacts. Without advance VR, sufficiently smoothed and resolved 2D scatter distributions (300-600 projections) can consume many hours of CPU time. Our acceleration strategy was to adopt importance sampling, where importance, I(β) where β = (r, Ω, E), of a point in phase space is understood to be the expected contribution of the particle at β and all its possible progeny to the detector response (here defined as the total flat panel detector signal integrated over all pixels). Insights from transport theory include: (a) I(β) is proportional to the adjoint fluence, Φ∗ (β) (a BTE-like solution describing virtual transport of particles from the detector to the source); (b) splitting and Russian roulette by a weight window centered at W (β) ∝ 1/Φ∗ (β) is equivalent to sampling histories from the biased kernel, K (β|β 0 ) (Φ∗ (β)|Φ∗ (β 0 )), and source, S(β)Φ∗ (β); (c) under certain conditions, e.g., scoring detector response by a next flight estimate, adjoint-driven importance sampling results in a zero variance estimate of the true flux. In our implementation, the adjoint MC source was a uniform rectangular prism (equal in size to the flat panel detector) with energy and angular distributions given by the track-length estimator while the forward MC source was either point source or phase-space (PS) source below the bow-tie filter. Importance functions were calculated by “on-the-fly” by MC, precalculated by MC, or derived from precalculated adjoint solution (discrete ordinates (DO) code DANTSYS). The PS source increased efficiency 14.5-fold, while precalculated importance function increased efficiency by additional factors ranging from 10 to 26. Overall, scatter projection computing time (1 cm pixels, 10% uncertainty, and single AMD X6 1090T processor). Mathematical derivation and theoretical characterization of advanced VR techniques is a mature nuclear engineering research area with a substantial literature. The transport-theory applications literature is a rich source of computational strategies for addressing clinical problems in imaging and dosimetry, especially those involving neutral particle transport. [1] H. Hedtjärn et al. 2002 Phys. Med. Biol. 47, 351; [2] A. Sampson et al. 2012 Med. Phys. 39(2); 1058-1068; [3] 2013 Med. Phys. 40, 513-513 International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 31 Modelling spectra and HVL of a miniature low-energy x-ray source using EGSnrc Peter Watson1 and Jan Seuntjens1 1 Medical Physics Unit, McGill University, Montréal, Canada The INTRABEAM system (Carl Zeiss, Oberkochen, Germany) is a miniature x-ray tube for use in intraoperative radiotherapy and brachytherapy. The device accelerates electrons to up to 50 keV, which are then steered down an evacuated needle probe to strike a gold target. For accurate dosimetry of the INTRABEAM system, it is important that the photon spectrum be well understood. In this work, we have developed an EGSnrc-based monte carlo (MC) model of the INTRABEAM system to study the source photon spectra and half-value layer (HVL). The influence of various MC parameters, such as electron impact ionization, was investigated. The effect of spherical applicators on the HVL was also studied. These results were compared with spectra and HVL measurements taken from literature.The INTRABEAM source probe was modeled using cavity, an EGSnrc user code. Two different probe material and geometry specifications [1-2] were modeled. Two 50 keV electron sources were considered: a parallel beam covering the entire gold target; and a swept hollow cone beam which more accurately describes the true source. Outside of the probe, photon fluence spectra was scored across a circular region (r = 0.5 cm) situated 1 cm from the probe tip (or applicator surface), both along and orthogonal to the probe axis. From the simulated spectra, HVL was determined analytically by calculating the attenuation of air-kerma for a given thickness of aluminum and source-to-detector air gap.To help validate the EGSnrc simulation, the photon spectrum was compared with published Geant4 simulation data [2]. The major difference between these two codes is in how atomic relaxations are treated. In EGSnrc, transitions to and from the M and N shells are treated in an average way, whereas in Geant4 they are considered explicitly. The effect of M and N shell averaging is evident in comparing the gold L-lines predicted by EGSnrc and Geant4. The results of the HVL calculations from simulated spectra for the bare probe and spherical applicators were consistent with literature reported measured values, in considering measurement uncertainties and the assumption of no scatter in the HVL calculation. No significant difference in HVL was found between either of the two probe specifications or electron sources. [1] Yanch and Harte 1996 Med. Phys. 23, 9; [2] Nwankwo et al. 2013, Phys. Med. Biol. 58, 7 International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 32 Monte Carlo simulations to assess the accuracy of low-energy electron beam reference dosimetry Bryan R. Muir1 and David W. O. Rogers2 1 2 Measurement Science and Standards, National Research Council of Canada, Ottawa, Canada Carleton Laboratory for Radiotherapy Physics, Carleton University, Ottawa, Canada The AAPM is updating their protocol for electron beam calibration and hence, there is interest in determining the appropriate choice of ion chamber type for such reference dosimetry. Historically, cylindrical chambers have not been recommended for use in low-energy electron beams because of large replacement corrections for these chambers in low-energy electron beams. Of late, the assumptions needed to determine perturbation corrections for cylindrical chambers have been questioned and issues have been raised regarding the measurement performance of plane-parallel chambers, the detector of choice for low-energy electron beam calibration. In this work, kQ factors are calculated for the commonly used plane-parallel PTW Roos and cylindrical NE2571 ion chambers as well as for the small-volume cylindrical Exradin A1SL ion chamber. The absorbed dose to water and the response of ionization chamber models are calculated with the EGSnrc egs_chamber user-code. Cobalt-60 and electron beam sources are modelled using collimated point sources from spectra or BEAMnrc accelerator models. The suitability of different chamber types for practical reference dosimetry is evaluated by considering how precisely kQ factors can be selected given reasonable (1 mm) uncertainties associated with the establishment of the beam quality specifier, R50, and ion chamber positioning. These results show that using the smaller cylindrical A1SL chamber can improve the accuracy of calibration of low-energy electron beams with R50 as low as 2.8 cm. If results for the PTW Roos or NE2571 chambers are considered, uncertainties become unacceptable for beams with R50 smaller than 4.59 cm and 3.37 cm, respectively, although the uncertainty associated with the use of the PTW Roos chamber increases much less dramatically with decreasing R50 than for the NE2571 chamber. To explain these effects, calculated kQ factors are dissected using individual chamber perturbation calculations with specific emphasis on the influence of replacement corrections. These results suggest that cylindrical Farmer-type chambers allow more accurate calibration of electron beams with lower incident energies (~5.5 MeV) than if plane-parallel chambers are used, although larger uncertainties are possible if Farmer-type chambers are used in very low-energy beams. It is found that small-volume cylindrical chambers might be the best choice of detector for the calibration of low-energy electron beams. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 33 Modelling interactions in radiotherapy by photon activation of high-Z nanoparticles Mathieu Agelou1 , Rachel Delorme1 , Hélène Elleaume2 and Florence Taupin2 1 2 Laboratoire Modélisation, Simulation et Systèmes, CEA List, Gif-sur-Yvette, France European Synchrotron Radiation Facility, Grenoble, France Malignant brain tumours represent a few percents of adult cancers and are the most frequent for children. Because of their location, the radio sensitivity of healthy brain tissue and the presence of the blood brain barrier, the current treatments for some of these cancers are not efficient. An innovative approach using X-rays in addition with heavy elements, as iodine, gold or gadolinium nanoparticles, seems to open a promising way. Such technique is developed at the medical beam line of European Synchrotron Radiation Facility using monochromatic X-rays in the 50-100 keV range for the treatment of resistant solid tumours such as high-grade gliomas.With this approach, a localized dose enhancement can be obtained from photoelectric effect on heavy elements introduced in the target volume. However, the physical processes and biological impact of the photon activation of heavy elements are not well understood. The experimental results can not be explained from macroscopic dose calculations only, the radio-induced damages at the cell level have to be considered in more details. The aim of this work is to model and simulate, with a Monte Carlo transport code, the interaction between radiations and cells or DNA in presence of heavy elements and to compare the results with experimental measurements carried out with a partner laboratory: the INSERM team of the beam line dedicated to medical studies at ESRF. Clonogenic assays have been performed on F98 cells to measure the “Sensitizer Enhancement Ratio” which is compared to our simulated “Dose Enhancement Ratio” (DEF).To this end, we first started to study the characteristics of the high-Z nanoparticles under various conditions of irradiation, for instance looking at the spectra of secondary electrons created and the deposited dose at a micrometer level around a nanoparticle. In a second hand, we will look into a more realistic model close to the experimental conditions in order to see potential correlation between a physical process modelled and a radiobiological result obtained with the experiments made at ESRF. Two well-known and widely used Monte Carlo codes have been utilized for their respective advantages: PENELOPE and GEANT4.The attached figures are examples of results obtained: 2D DEF maps for different gadolinium distributions, comparison between DEF and SER for a given conditions of gadolinium nanoparticles localization and beam energies. Comparison between DEF at membrane and SER4Gy in the case of internalized gadolinium nanoparticles (GdNP) K-shell threshold DEF = Dose Enhancement Ratio DEF = Dose (Gd) Dose (water) SER = Sensitizer enhancement ratio SER4GY = Survival à 4Gy (control sample) Survival à 4Gy (with Gd) International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 34 The Geant4-DNA project: overview and recent developments Sébastien Incerti1 1 Université Bordeaux 1, Centre d’Études Nucléaires de Bordeaux, Gradignan, France Understanding and prediction of adverse effects of ionizing radiation at the cellular and sub-cellular scale remains a challenge of today’s radiobiology research. In this context, a large experimental and modeling activity is currently taking place, aimed at better understanding the biological effects of ionizing radiation at the sub-cellular scale. The “Geant4-DNA” project was initiated by the European Space Agency. It aims to develop an experimentally validated simulation platform for the modeling of DNA damage induced by ionizing radiation, using modern computing tools and techniques. The platform is based on the general-purpose and open-source “Geant4” Monte Carlo simulation toolkit, and benefits from the toolkit’s full transparency and free availability.This project proposes to develop specific functionalities in Geant4 allowing: 1. The modeling of elementary physical interactions between ionizing particles and biological media, during the so-called "physical" stage; 2. The modeling of the "physico-chemical and chemical" stages corresponding to the production, the diffusion and the chemical reactions occurring between chemical species. During the “physico-chemical” stage, the water molecules that have been excited and ionized during the physics stage may de-excite and dissociate into initial water radiolysis products. In the "chemical stage", these chemical species diffuse in the medium surrounding the DNA. They may eventually react among themselves or with the DNA molecule; 3. The introduction of detailed biological target geometry models, where the two above stages are combined with a geometrical description of biological targets (such as chromatin segments, cell nuclei...). The Geant4-DNA physics processes and models are fully integrated into the Geant4 toolkit and can be combined with Geant4 geometry modeling capabilities. In particular, it becomes possible to implement the geometry of biological targets with a high resolution at the submicrometer scale and fully track particles within these geometries using the Geant4-DNA physics processes. These geometries represent a significant improvement of the geometrical models used so far for dosimetry studies with the Geant4 toolkit at the biological cell scale. The current status of the project will be presented, as well as on-going developments. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 35 Clusters of energy deposit sites after simulating irradiation by light ions with the track structure MC code LIonTrack Gloria Bäckström1 , Nina Tilly1,2 , José M. Fernandez-Varea3 and Anders Ahnesjö1 1 Department of Radiology, Oncology and Radiation Science, Uppsala University, Uppsala, Sweden Elekta Instrument, Uppsala, Sweden 3 Facultat de Fisica, Universitat de Barcelona, Barcelona, Spain 2 An important feature of radiotherapy with protons and other light ions is the increased RBE as compared to conventional photon radiotherapy. RBE is difficult to determine due to its dependency on a number of variables. For a specific cell line and biological endpoint, LET is not sufficient as a predictor of the RBE because of the different dose deposition profiles on a microscopic scale for different particles. The study of energy deposit (ED) site patterns at the cell-nucleus level is important for the characterization of RBE variations, because such patterns might correlate to clinical endpoints. A track structure MC code, LIonTrack, was developed to generate the ED site patterns by protons and other light ions in liquid water with accuracy at the nanometre scale [1]. The continuum distorted-wave formalism with the eikonal initial state approximation (CDW-EIS) is employed to sample the initial energy and angle of the electrons emitted in ionizing collisions of the light ions with water molecules. The transport simulation of the ejected electrons is performed with an extended version of the PENELOPE/penEasy code to which the model of Dingfelder et al. [2] for the inelastic scattering of electrons has been linked. One code application in microdosimetry is to generate the ED sites by a radiation quality and thereafter group the ED sites in clusters. The frequencies of each cluster order, where the order is given by the number of ED sites within the cluster, can be computed. Clusters of ED sites and their cluster orders were computed for various radiation qualities with the clustering method presented by Bäckström et al. [3]. The frequencies of cluster orders for ED sites by proton, helium, lithium and carbon ions with the same LET, 25.7 eV/nm, were larger for clusters of higher orders (four and up) for protons than for the ions with higher atomic number. The reported RBE of these radiation qualities for cell survival of V79 cells is higher for protons than for the other ions. Therefore, distributions of cluster order frequencies of ED sites seem to follow the general trends of light ion RBE. The distribution of cluster order frequencies might be a better descriptor of radiation impact than LET. [1] Bäckström et al. 2013 Med. Phys. 40 064101; [2] Dingfelder et al 1998 Radiat. Phys. Chem. 53 1-18; [3] Bäckström et al. 2014 Spatial energy deposit site patterns generated by light ions and 60Co photons in cell nucleus-sized targets (manuscript) International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 36 Monte Carlo calculated cluster patterns for energy deposition sites for low and high energy brachytherapy sources Fernanda Villegas1 , Nina Tilly2 and Anders Ahnesjö1 1 2 Department of Radiology, Oncology and Radiation Science, Uppsala University, Uppsala, Sweden Elekta Instrument, Uppsala, Sweden Damage to DNA due to exposure to ionizing radiation plays an important role for the response of living tissue to radiation. The spatial pattern of energy deposition (ED) sites that is formed by the interactions of the primary particle and its secondary electrons has been shown to correlate with relative biological effectiveness (RBE) between ion and photon beams. The latter kind of radiation is generally considered to be of low linear energy transfer (LET) and taken as the reference radiation. Furthermore, the weighting factor is set to equal one for radiation protection purposes. Nonetheless, variation in RBE values among different photon sources used in brachytherapy have been reported. The aim of this work is to analyse the cluster patterns of EDs formed by five of the most frequently used brachytherapy sources, 103 Pd, 125 I, 192 Ir, 137 Cs and 60 Co. Event-by-event Monte Carlo simulations were carried out with the PENELOPE/penEasy code to obtain the track structure of the mentioned sources. Distances to the nearest neighbouring EDs were calculated in order to obtain a frequency distribution of distances between EDs. The results suggest that there is a non-uniform random component due to track correlated EDs and a uniform random component due to EDs stemming from uncorrelated tracks. The uniform random component increases as dose is increased while the non-uniform random component remains the same. The clustering of EDs were analysed with in-house developed programs. The ratio of frequency distribution of cluster order shows that the two lower mean photon energy sources (103 Pd, and 125 I) differ by as much as 15% with respect to 60 Co, while the ratio differs by only 2% for the two sources with higher mean photon energy (192 Ir, and 137 Cs). This cluster pattern information will be joined with ion data in order to find if cluster frequency distributions can function as a better surrogate than dose to describe the radiation impact on the modelling of cell survival. Peripheral dose estimation with pseudo-deterministic transport in C++ version of PENELOPE Juan-Carlos Garcia-Hernandez1 , I. Bessières1 , J.-M. Bordy2 and B. Poumarède1 1 2 Laboratoire Modélisation, Simulation et Systèmes, CEA List, Gif-sur-Yvette, France Laboratoire National Henri-Becquerel, CEA List, Gif-sur-Yvette, France With the improvements in radiotherapy techniques and the resulting increase in life expectancy after initial treatment, the problem of secondary cancers due to peripheral dose becomes an issue of tomorrow’s radiotherapy. The objective of this work is to develop a computational tool based on Monte Carlo (MC) to determine precisely the dose to healthy organs distant from the tumor area and not exposed to the radiation field in radiotherapy. This dose estimation will allow the clinician to choose the most suitable treatment technique as well as its associated ballistics aiming a dose reduction to the most sensitive and healthy organs, it might also provide a dosimetric data base essential for epidemiological studies.The most effective method for peripheral dose estimation is the so called pseudo-deterministic transport method. Our laboratory, through the experience gained by the intensive use of PENELOPE code, decided to develop its own version of this code by translating it into C++. It is in this new version that was implemented this variance reduction technique. The pseudo-deterministic transport is applied when a region is insufficiently sampled because particles have a very low probability of reaching it. A sphere surrounding this region is defined by the user. During transport, the pseudo-deterministic process takes place for all photons undergoing an interaction outside the sphere. This process replaces analog interaction dividing photons into two counterparts: a photon called real or non-deterministic and a virtual one (or deterministic). The non-deterministic photon is sampled in the normal way keeping its weight unchanged. However, it is "killed" if it reaches the area of interest during his transportation. For deterministic photon, a direction pointing to the sphere is specially sampled; the associated energy and the probability of being sampled in this direction are calculated. Then it is transported to the entrance of the area of interest taking into account the attenuation by crossed materials.Validation tests will be presented on basic examples to evaluate gains in efficiency. Examples of more specific applications will be discussed: calculation of peripheral dose in the case of radiotherapy and calculation of received dose by physician during interventional radiology. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 37 A Monte Carlo Model of an 18 MV Varian Linac to Simulate Neutron Spectra Robert Maglieri1 , Angel Licea2 , Jan Seuntjens1 and J. Kildea1 1 2 Medical Physics Unit, McGill University, Montréal, Canada Canadian Nuclear Safety Commission, Ottawa, Canada With the advent of flattening filter free beams and door-less bunkers, neutron measurements around radiotherapy linacs are once again gaining importance. Recently, a new neutron spectrometer, the Nested Neutron Spectrometer (NNS) by Detec (Gatineau, Quebec), appeared on the market. It can be operated in current mode (not unlike an ion chamber) to detect neutrons in high dose-rate environments such as pulsed-beam radiotherapy. However, the feasibility of using the current-mode operated NNS in radiotherapy must be evaluated. In this work, a Monte Carlo model of a Varian 21EX linac and treatment room was used to provide an insight to the characteristics of the neutron spectrum at various locations in the linac bunker. All Monte Carlo simulations were carried out in MCNP6. The geometry and shielding of the linac were based on the published model of a Varian 2300C [1]. The beam shaping components, as well as some shielding, were modified to fit those of a Varian 21EX running at 18 MV. Simulations were run with 5 x 108 electrons incident on a tungsten target. Through Bremsstrahlung and subsequent photonuclear reactions, neutrons are produced in the linac head and scored by various point detector (F5) tallies across the treatment room. ENDF60 and LA150U cross sections were used for neutron and photonuclear interactions. To evaluate the accuracy of the Monte Carlo, a number of tests were carried out in MCNP. The effect of the bunker walls was studied by successively extending the walls and then removing them altogether. A thermal neutron peak appears when the walls are present, but is absent when they are removed. Wood (8 cm cellulose) was also added to the bunker walls to mimic the furnishings in the treatment room. The increase in hydrogen content from the cellulose caused the thermal peak to increase by ~30% around the linac head. Moreover, the effect of shielding material (lead, iron, and tungsten) in the linac was studied by changing the bulk components. There was a negligible change in the fast neutron peak between lead and iron. However, tungsten decreased the fast neutron peak by ~20%. Finally, MCNP-simulated spectra were compared with the NNS-measured spectra. There was good agreement at all locations in the bunker with the exception of the larger fast neutron peak in the case of the MC as shown in the attached figure. This contributes to an overall increase of neutron fluence in the maze.Apart from some discrepancies in peak heights, there was reasonable agreement between NNS-measured and Monte Carlo-simulated spectra. This demonstrates, in part, the feasibility of using the Nested Neutron Spectrometer in high dose-rate radiotherapy environments. Further comparison with alternate measurements should be carried out to increase confidence in the NNS. Neutron Spectrum at 140 cm from Isocenter 4 12 x 10 NNS MCNP Fluence Rate [n/cm2/s] 10 8 6 4 2 0 −10 10 −8 10 [1] K. R. Kase et al. 1998 Health physics 74(1) 38-47. −6 10 −4 10 Energy [MeV] −2 10 0 10 2 10 International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 38 Monte Carlo in clinical practice: patient-specific QA, 4D phase-space predictions, and in-vivo EPID dosimetry Tony Popescu1,2 1 2 British Columbia Cancer Agency, Victoria, Canada University of British Columbia, Vancouver, Canada A fully automated, patient-specific, Monte Carlo based QA process has been used at the BC Cancer Agency for more than 2000 VMAT patients and 1000 IMRT patients. This process is fast, maximally efficient in terms of departmental resources, and capable of simulating any plan in a single run, regardless of its complexity. The core of this system is source 20 of DOSXYZnrc, developed by Lobo and Popescu for 4D Monte Carlo simulations of continuously-variable beam configurations, with arbitrary degrees of freedom. I will present several enhanced capabilities for source 20, recently introduced in order to address specific challenges presented by TrueBeam simulations (the unavailability of a full linac model and the fact that input IAEA phase spaces may be non-planar). These new features have been released as part of BEAMnrc/DOSXYZnrc (V4-2.4.0). I will present applications to a variety of clinical cases, including jaw-tracking, non-coplanar, and multiple-arc VMAT, for both standard and flattening filter free (FFF) photon beams. While pre-treatment VMAT QA is currently a clinical mainstay, there is growing interest in the use of QA methods that are more relevant to the actual patient treatment and are, in fact, capable of providing in vivo dosimetry. To this end, a new general research tool has been recently introduced for VMAT Monte Carlo QA, simultaneously providing dose deposition in both the patient CT data set and any type of planar (entrance or exit) detector. By enabling DOSXYZnrc to optionally output a 4D IAEA phase space, it is now possible to collect the particles exiting the patient during a VMAT simulation. This phase space can be used for further synchronized simulations of EPID and/or CBCT dose or images, either globally, incrementally, or per control point, allowing comparisons of the 4D phase space EPID prediction with the actual EPID data acquired with the patient on treatment. Such a process that could monitor the patient dose delivered during the entire course of treatment (possibly in an adaptive manner, in conjunction with in vivo CBCT data and linac log files) would be more deserving of the name "patient-specific QA" than a pre-treatment phantom-based QA process. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 39 4D Monte Carlo simulations of gated and free-breathing dose delivery with a Varian TrueBeam linac Emily Heath1 , T. Karan2 and I. Popescu1 1 2 Department of Physics, Carleton University, Ottawa, Canada Department of Medical Physics, British Columbia Cancer Agency, Vancouver, Canada Verification of the three-dimensional dose distribution delivered to the patient is highly desirable for quality assurance of complex radiotherapy treatments such as VMAT and gated treatments. We previously developed a 4D Monte Carlo simulation tool using EGSnrc/BEAMnrc which synchronizes the delivery of particles from the linac model to the patient’s respiratory motion state. The patient respiratory motion is modeled using the defDOSXYZnrc Monte Carlo code which deforms voxels to match the geometry of a particular respiratory phase. Recently, we have extended our 4D Monte Carlo simulation method to be able to simulate treatments delivered using a Varian TrueBeam linac. By incorporating the beam hold status from the delivery log files gated treatments can be simulated. The beam settings from the log file are combined with motion amplitude or phase information from an RPM respiratory trace measured using the RPM system to model variations in patient respiratory motion. This new approach was validated by comparing simulations of dose delivered from a RapidArc plan with and without gating to film measurements in a motion phantom. The current patient motion model uses a single set of deformation vectors between the exhale and inhale phases which are scaled according the isocenter motion as a function of phase. The accuracy of this approach was investigated by modifying defDOSXYZnrc to interpolate motion from multiple sets of deformation vectors to better account for hysteresis. Dose distributions from a RapidArc plan delivered on a lung patient with approximately 1 cm motion amplitude were compared for simulations using only exhale-inhale deformation vectors vs. using three sets of vectors (exhale-30% inhaled , exhale-inhale, exhale-30% exhaled). Good agreement was obtained between measurements and simulations for the free-breathing and gated simulations (see Fig. 1). For a 2 mm voxel resolution, comparison of the dose distributions using a single set of deformation vectors vs. 3 sets of vectors with a gamma criterion of 2%/2 mm showed a passing rate of 99.8% (D > 5%) and 95% (D > 50%). A 4D Monte Carlo method has been developed which enables the calculation of the delivered dose using plan or delivery log files while accounting for the individual patient respiratory motion characteristics. We are currently developing a fast 4DMC code by implementing our approach into VMC++ using an efficient tetrahedron-based geometry. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 40 Development of a new virtual source model for portal image prediction using the Monte Carlo code PENELOPE Isabelle Chabert1 , Delphine Lazaro1 , Eric Barat1 , Thomas Dautremer1 , Thierry Montagu1 , Mathieu Agelou1 , Aurélien Croc de Suray1 , Juan-Carlos Garcia-Hernandez1 , Mohamed Benkreira2 , M. Nigoul2 , S. Gempp2 and Loïc De Carlan1 1 2 CEA List, Gif-sur-Yvette, France Assistance Publique - Hôpitaux de Marseille, Marseille, France Purpose: Electronic Portal Imaging Devices (EPIDs) are widely used for quality assurance and dosimetric verifications in radiotherapy. To highlight dose delivery errors, the image acquired during the treatment session can be compared to a pre-calculated reference image, which can be predicted at high-resolution with a recently developed Monte Carlo (MC)-based method. However, using this method in clinical routine is still hampered by the necessity to store huge phase space files (PSF). This study aims at developing a new and accurate virtual source model (VSM) to describe in a compact way the irradiation beam by keeping all the correlations between particle characteristics stored in the PSF. Material/methods: The VSM was built upon a commissioned model of a Synergy linac (Elekta) developed using the PENELOPE code. Using this model, a reference PSF was calculated for an uncollimated beam after the flattening filter (FF), and particles were sorted out in three sub-sources according to the position of their last interaction in the linac head (target, primary collimator or FF). Each particle is described by its radial position (r) in the PSF, its energy (E), and its polar and azimuthal angles (phi, th), representing the particle deviation compared to its direction after bremsstrahlung, and the orientation of this deviation. For each sub-source, a 4D histogram was built by storing the particle distributions according to their r, E, phi, th values. Our VSM hence contains all correlations between these four variables. This new VSM was implemented in PENELOPE, and was validated by comparing physical characteristics from the reference PSF and from the VSM. Then calculated dose distributions in a water phantom were compared for an uncollimated beam using the VSM and the reference PSF. Results: A PS file of 240 Go is compressed in 4D histograms of 10 Mo. Energy spectra and angular distributions in PENELOPE coordinate system obtained for each sub-source with the reference PSF and with the VSM are compared. The VSM reproduces with an overall good agreement the energy and angular distributions of the reference PSF. Figure 1 shows for each sub-source depth dose and lateral dose profiles in the water tank located just after the flattening filter. Good agreements are observed between the dose distributions calculated with the VSM and the reference PSF. Results remain sensitive to the chosen binning for the correlated histograms, and binning optimization is under study to provide the most accurate results. Conclusion: A new VSM taking into account for all correlations between particle characteristics was developed and implemented in PENELOPE. Its accuracy will make it usable to calculate high-resolution reference portal images and dose distributions for quality assurance in radiotherapy. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 41 Monte Carlo Simulation of Cherenkov Emission by High-Energy Radiotherapy Beams: Investigating a Novel Optical Approach to Dosimetry and Online Imaging in Radiotherapy Yana Zlateva1 and Issam El Naqa1 1 Medical Physics Unit, McGill University, Montréal, Canada Background/Objective: X-ray imaging, commonly used to localize a lesion in radiotherapy (RT), increases patient exposure. In addition, current RT dosimeters are made of non-water materials, requiring conversion to dose to water and limiting resolution. Yet, Cherenkov emission (CE) by charged particles traveling faster than the phase speed of light in a dielectric medium is inherent to all high-energy RT beams, consists of (non-ionizing) optical photons, and can be detected outside the beam. This work validates the potential for application of Cherenkov emission in radiotherapy dosimetry, and online imaging by analysis of its correlation with radiation dose. Materials/Methods: Dose-CE correlation was investigated via both simulation and experiment. A Monte Carlo (MC) CE simulator was designed using the Geant4 simulation toolkit. The optical spectrometry system consists of a multi-mode step-index optical fiber (numerical aperture = 0.22), connected to a diffraction grating spectrometer incorporating a front- or back-illuminated charge-coupled device (CCD). The MC CE simulator was used to investigate the 3D correlation between radiation dose and CE, optimize the acquisition geometry, and simulate the acquisition for validation of the experimental findings. Results: 3D MC analyses indicate a strong linear correlation between radiation dose and CE (Pearson correlation coefficient greater than 0.99). A beam incidence angle of 50◦ relative to the surface normal produced a CE maximum along a horizontal fiber. This angle was adopted for experimental studies in order to maximize the signal-to-noise. Dose-CE correlation was investigated via water tank ion chamber scans along the beam central axis and optical fiber scans with the fiber tip positioned at the field edge. With all data sets normalized to 1, the effective point of measurement of dose by our optical system for 18, 12 and 6 MeV clinical electron beams was found to be at 1.7, 0.8 and 0.1 cm, respectively, downstream from the fiber axis (greater than 0.99). Conclusions: Our work validates the potential for application of CE in RT dosimetry and online imaging for patient setup and treatment verification, since CE is intrinsic to the beam, non-ionizing, and can be detected outside the beam. Future work involves upgrades to the CE simulator to include tissue material properties and imaging functionalities. It is expected that the proposed technique will be applicable to high-resolution 3D dose mapping by means of diffuse optical tomography, online CE imaging and localization during radiotherapy, and beam modulation based on tumor microenvironment information. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 42 Imaging and Radiation Therapy: GATE Monte Carlo Simulation of a 6 MV photon beam LINAC and its MV-CBCT Flat Panel for IMRT applications Saadia Benhalouche1 , Julien Bert1,2 , Nicolas Boussion1,2 , Awen Autret1 , Olivier Pradier1,2 and Dimitris Visvikis1,2 1 2 LaTIM INSERM UMR 1101, CHU Morvan, Brest, France Radiotherapy Department, CHRU de Brest, Brest, France The context of the present work is the Monte Carlo GATE simulation of a linear accelerator (LINAC) in radiotherapy, equipped with a 6 MV X-ray photon beam and a flat panel detector allowing to perform Mega Volt Cone Beam Computed Tomography (MV-CBCT). As a first step a comprehensive modeling of the LINAC (Oncor Impression from Siemens) was done according to its physical and geometrical properties. Validation was done as a second step by means of a dosimetric study comparing simulated and measured data. This digital platform was used for simulating two clinical applications. In the first one, an Intensity Modulated Radiation Therapy (IMRT) treatment plan was simulated using complex field shapes designed from a multileaf collimator (160 leaves). Validation was performed by comparing absolute and relative dosimetric data, simulated and measured inside a dedicated quality control phantom. In the second application, the flat panel of the electronic portal imaging device (EPID) was used for: • Simulating acquisitions of 2D images from a patient and an anthropomorphic phantom, and then 3D reconstruction in order to obtain MV-CBCT images; • Calculating dose distributions delivered during the MV-CBCT process to both patient and phantom; • Reconstructing IMRT dose at the isocenter for a known target using EPID signal. For IMRT simulations considering eleven patient datasets with very complex and heterogeneous fields, GATE provided good results with a relative error of 0.43% ± 0.25% on absolute dose between simulated and measured beams. Planar dose comparisons were performed using gamma-index analysis. For the whole set of beams 95.20% ± 5.23% of the evaluated dose points satisfied the 5%/4 mm criterion. MVCBCT volumes obtained with GATE showed a good agreement with the CT of a patient and an anthropomorphic phantom. Mean uncertainty for deposited doses at the phantom isocenter was 0.010 Gy ± 0.003 Gy while mean statistical uncertainty in the anthropomorphic phantom was 0.010 Gy ± 0.004 Gy. For IMRT dose reconstruction, the comparison between GATE calculation and measurements gave 92% of dose points passing 3%/3 mm criterion. This preliminary result was obtained for one IMRT plan only, with relatively large, simple and homogeneous fields. We conclude that we have successfully modeled the complete LINAC platform inside GATE, for both imaging and dosimetric applications. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 43 Least Restrictive Assignment of Dose-Distance Differences (LRAD) in comparing radiotherapy dose distributions Bruce A. Faddegon1 and Peng Dong1 1 University of California San Francisco, San Francisco (CA), USA Purpose: To formalize a method to compare dose distributions based on the least restrictive of dose and distance differences, to evaluate the method for IMRT QA on a conventional linac, and to demonstrate the clinical relevance of LRAD in comparing radiotherapy dose distributions calculated with Monte Carlo simulation to measurement or calculations done with different simulation parameters, Monte Carlo systems, or algorithms. Methods: Lrad is defined as the least restrictive of the dose difference at each point in the distributions being compared (%D), with dose normalized by the same factor, and the distance to agreement (DTA in millimeters). The DTA is limited to orthogonal directions such as parallel and perpendicular to MLC motion. If %DLo, Lrad=DTA, else Lrad=%D. Lrad fails at any point when Lrad > DTAo or Lrad > %Do. We compared LRAD (Lo=1%/mm, DTAo=2 mm, %Do=2%) with Gamma index tool (2%/2 mm pass/fail criteria) for IMRT QA with 2D detector arrays. Dose distribution measured for 6 MV and 18 MV x-rays for various field sizes and shapes, including 6 IMRT plans, were compared to measurements made with output, beam flatness, beam symmetry, MLC leaf positions, and detector array translation and rotation adjusted at up to twice published acceptable tolerance. Published application of methods similar to LRAD used to validate Monte Carlo simulation is reviewed to demonstrate clinical relevance. Results: LRAD was more effective than Gamma in detecting a 2% drift in output (dose per monitor unit), 1-2 mm drifts in MLC leaf position for 1-8 leaves in the field, and beam flatness and symmetry drifts that resulted in a 3% change in the off-axis ratio. LRAD and Gamma were equally effective for larger output changes and for detector translations and rotations. For all ~400 measurements performed, LRAD detected 78% of the error and Gamma detected 52% of the errors. By using a color scale to display dose differences and grey scale for spatial errors, the reason for failure was self evident, whether it be beam or mechanical changes. Similar approaches have proven effective in comparing measurements and different calculation approaches to Monte Carlo simulation. Conclusion: LRAD proved to be advantageous in its ability to detect and distinguish between realistic changes in beam and mechanical settings in comparison to the Gamma Index. LRAD provides a clinically relevant, formal methodology for comparing radiotherapy dose distributions including those calculated with Monte Carlo simulation. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 44 The use of Monte Carlo beam models in the design of optimized scattering foils for Modulated Electron Radiation Therapy Tanner Connell1 and Jan Seuntjens1 1 Medical Physics Unit, McGill University, Montréal, Canada Modulated Electron Radiation Therapy continues to be an area of interest to various groups, however, the scattering foils used in beam flattening have not been optimized for this modality as fully flattened beams are not a requirement for intensity modulated deliveries. The clinical foils therefore produce an excess of bremsstrahlung dose that unnecessarily deposits dose in distal healthy tissues of the patient. By reducing this bremsstrahlung dose through redesign of the clinical foils, this photon contamination can be reduced, further increasing the main benefit of electron therapy which is the sparing of distal healthy tissue. In this work, the feasibility of novel scattering foils specifically designed for Modulated Electron Radiation Therapy is investigated using Monte Carlo methods. An accurate beam model that was tuned using measurements with the scattering foils removed was employed from previous work. Different foil parameters such as material, shape and thickness were analyzed to find the ideal combination for MERT applications using a hypothetical electron MLC. It was shown that low atomic-number materials such as aluminum were optimal, while shaped foils such as those employed in current dual foil designs were not necessary. As shown in Figure 1 (a), aluminum foil-thickness between 0.36 and 1.50 mm were capable of sufficiently broadening beams with energies between 12 and 20 MeV respectively, with beams of lower energies receiving sufficient scatter from the treatment head components and air scatter. As seen in Figure 1 (b), the bremsstrahlung dose from the custom foils is markedly reduced from the clinical foils and is only slightly higher than the beamlines with the foil removed. Finally, custom foils were manufactured based upon the simulated designs and were placed into the beamline of the 2100EX accelerator that the beam model was based on, and showed excellent agreement between the simulated and measured PDDs and profiles. Custom foils achieved higher dose rates on the central axis compared to the clinical foils by factors of 5.4, 4.9 and 4.5 for 12, 16 and 20 MeV respectively. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 45 Application of Monte Carlo dose and effect calculations in proton therapy Harald Paganetti1 1 Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston (MA), USA Monte Carlo simulations have a long history in proton therapy but only recently has code efficiency and computer power enabled the routine use of Monte Carlo simulations in the clinic. So far, Monte Carlo based dose calculation is only done retroactively, i.e. outside of the treatment planning optimization loop. This is expected to change based on fast Monte Carlo on GPU units. This presentation focuses on two aspects, (a) the potential clinical impact of Monte Carlo dose calculation in proton therapy and (b) the use of Monte Carlo for biological treatment optimization. (a) It has been demonstrated that there are considerable uncertainties in predicting the end of range of proton beams in patients. A large part of these range uncertainties are due to approximations in analytical dose calculation routines (such as in the handling of multiple Coulomb scattering) implemented in commercial treatment planning systems. It has been demonstrated that the use of Monte Carlo could reduce current generic range margins significantly and allow the definition of treatment site or even patient specific range margins. As a consequence, Monte Carlo dose calculation will enable us use beam angles in proton therapy that are currently avoided. (b) Although protons are considered low-LET (linear energy transfer) particles, the variation in LET values is nevertheless considerable. Elevated LET values are believed to show a significant increase in biological effectiveness for some tissues. The use of Monte Carlo allows accurate prediction of LET and effect distributions in patients. Consequently, we can now correlate areas of increased and decreased efficiency to side effects and treatment failures, respectively. Furthermore, Monte Carlo generated LET distributions can be the basis for biological treatment plan optimization. Accuracy of proton interactions below 20 MeV in Geant4 Shirin A. Enger1 , Valerio Giusti1 and Pedro Arce1 1 McGill University, Montréal, Canada Geant4 is a Monte Carlo (MC) toolkit with an increasing use in the field of medical physics. Electromagnetic processes are well validated, but for hadronic interactions of charged particles at energies of the order of a few MeV, particularly for low Z materials, there are no physics models able to reproduce the experimental data. With the default version of Geant4, the cross sections and production of secondary particles for proton-nucleus interactions at an energy below 20 MeV are not satisfactory. Radionuclide yield in reaction with protons below 20 MeV are studied with the default version of Geant4 and compared with MCNPX and measurements. A new Geant4 package has been developed as well using the data on reaction cross sections and production of secondary particles contained in evaluated nuclear databases. The new package has been tested making use of the TENDL-2009 and TENDL-2012 databases. The neutron and gamma production obtained with the new Geant4 package and TENDL- libraries are significant from 4 MeV, while with the standard Geant4 physics there is no production of neutrons for energy below 8 MeV for some radionuclides, while above 8 MeV the gamma and neutron production shows a wrong yield. However, due to the object oriented design and modular architecture of Geant4 the new physics model and cross section libraries can successfully be added to the Geant4 toolkit for particle energies below 20 MeV. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 46 Status of the TOPAS Monte Carlo System for Proton Therapy J. Perl1 , J. Schümann2 , J. Shin3 , J. Ramos-Méndez4 . Bruce A. Faddegon4 and Harald Paganetti2 1 SLAC National Accelerator Laboratory, Menlo Park (CA), USA Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston (MA), USA 3 St. Jude Children’s Research Hospital, Memphis (TN), USA 4 University of California San Francisco, San Francisco (CA), USA 2 We will present an overview of the TOPAS - TOol for PArticle Simulation. TOPAS makes Monte Carlo simulation more readily available for research and clinical physicists. TOPAS can model a passive scattering or scanning beam treatment head, model a patient geometry based on CT images, score dose, fluence, etc., save and replay a phase space, provides advanced graphics, and is fully four-dimensional (4D) to handle variations in beam delivery and patient geometry during treatment. TOPAS users configure pre-built components (nozzle, patient handling, dosimetry or imaging components) to simulate a wide variety of particle therapies with no required knowledge of its underlying Geant4 Simulation Toolkit or any programming languages. Advanced Geant4 features such as nested parameterizations, parallel worlds and "layered mass geometry" become easy to use. All aspects of the simulation, including all 4D behaviors, are controlled from a unique, TOPAS Parameter Control System. TOPAS was engineered from the ground up to be flexible, yet easy to use, reliable and repeatable. The code includes a strong focus on "engineering-in" safety, employing a variety of techniques to make it harder for users to make mistakes. After reviewing the goals and feature set of TOPAS, we will present a quick survey of TOPAS applications from a variety of users. Applications have demonstrated complex simulations involving multiple time-dependent quantities. At the University of California San Francisco Eye Treatment Facility, TOPAS has accurately simulated the treatment head including wire chamber, collimators, ion chambers, a rotating range modulation propeller and a water column of variable thickness. Simulations included simultaneous variation of beam current, propeller motion and even the filling over time of a variable water column. At the Francis H. Burr Proton Therapy Center, double scattering proton therapy has been simulated with all components of the IBA universal nozzle, including the rotating modulator wheels and time-dependent beam current modulation. At St. Jude Children’s Research Hospital, scanning beam proton treatments have been simulated including timedependent steering fields. 187 users from 59 institutions in 19 countries have participated in TOPAS Beta testing since January 2013. TOPAS functionality continues to grow in response to user needs. Recent additions have included variance reduction capabilities, automated read-in of RT Structure set data, automated creation of dose volume histograms, increased flexibility in user-written scorers, increased options for user control of physics settings, and the addition of optical physics (including optical surface properties). The talk will close with comments on TOPAS future development. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 47 Biological modeling in TOPAS J. Schümann1 , Bruce A. Faddegon2 , D. Giantsoudi1 , A. McNamura1 , J. Perl3 , L. Polster1 , J. Ramos-Méndez2 , I. Rinaldi1 , J. Shin4 and Harald Paganetti1 1 Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston (MA), USA University of California San Francisco, San Francisco (CA), USA 3 SLAC National Accelerator Laboratory, Menlo Park (CA), USA 4 St. Jude Children’s Research Hospital, Memphis (TN), USA 2 TOPAS, Tool for Particle Simulation, makes Monte Carlo (MC) simulations for proton therapy accessible to a large user base. Up to now, TOPAS has focused on physics. At the same time, radiation therapy research does focus more and more on the boundary between physics and biology. Consequently, TOPAS is expanding to meet a new user base in radiation biology. We will present our new efforts and implementations to bridge the divide between these two research domains by extending TOPAS to include biophysical modeling, culminating in TOPAS-Bio. Biology in TOPAS-Bio is considered on two scales: modeling organ effects and modeling cellular effects. Our approach integrates outcome modeling directly into the TOPAS framework so that TOPAS-Bio will provide a single unified tool from physics simulations to biological outcome modeling at multiple scales.Organ effect modeling relies on the capability to read organ contours from the patient treatment plan. We have developed a DICOM interface for TOPAS to assign voxels of patients to any number of organs. We have implemented the following organ effect models: the Lyman-Kutcher-Burman model, the critical element model, the population based critical volume model, the relative seriality model, the EUD model and the Poisson model. Thus, TOPAS-Bio allows the calculation of tumor control probability (TCP) and normal tissue complication probability (NTCP) directly based on its Monte Carlo dose calculation framework.On the cellular scale, biological modeling TOPAS-Bio is now capable of calculating relative biological effects (RBE) or cell survival curves. This is particularly important due to the increasing effort on biological treatment planning optimization for proton therapy. Three linear-energy transfer (LET) based models, the microdosimetric kinetic model (MKM), the repair misrepair fixation (RMF) model and the local effect model (LEM) version 1 and 4 are included in TOPAS-Bio, with additional models under way.By combining full Monte Carlo simulation based radiation transport with biological modeling, TOPAS-Bio is providing a platform for clinical research on outcome as well as radiobiology research for the development of models as well as for designing experiments. For example, being able to model the physics of the radiation environment precisely will play a crucial role in designing cell experiments. Furthermore, the availability of multiple models allows direct comparison of the model predictions with the consistent underlying physical properties. We expect that the extended TOPAS-Bio will be a valuable asset for radiobiological and biophysical research. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 48 Improving carbon relative stopping power estimates for patients, using daily carbon imaging with pretreatment single or dual energy CT. Marta F. Dias1,2 , Charles-Antoine Collins Fekete2,3 , David C. Hansen2,4 , Marco Riboldi1 and Joao Seco2 1 Dipartamento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy Francis H. Burr Proton Therapy Center, Massachusetts General Hospital, Boston (MA), USA 3 Département de physique, de génie physique et d’optique et Centre du recherche sur le cancer, Université Laval, Québec, Canada 4 Aarhus University, Aarhus, Denmark 2 Purpose: The number of centers using carbon particles for cancer treatment has been growing remarkably over the last years. Clinically, the range of the incident particles in the patient’s body is calculated using information from X-ray computed tomography (CT) images, which can lead to uncertainties around 1% to 3%. The aim of this work is to investigate the use of carbon imaging combine with single-energy (SECT) or dual-energy (DECT) to better estimate and reduce uncertainties in carbon relative stopping power (RSP) calculation. Methods: A Gammex phantom is used as reference throughout the whole study. ImaSim Pro provides CT images of the Gammex phantom at 80, 120 and 140 kVP. To obtain the RSP values from the SECT a new calibration curve to convert HU into carbon RSP is determined using the Bethe-Bloch formula and experimental RSP values for a proton beam. For the DECT it is used the Yang approach. Carbon radiographs of the Gammex are produced as reference using a Geant4 v.4.9.6 Monte Carlo simulations over multiple angles. A GPU-based carbon propagation method is implemented using a NVIDIA GeForce GTX 680. A carbon digitally reconstructed radiography (CDRR) is generated using spline-interpolation to propagate each carbon from its origin through the Gammex phantom. The energy loss of each carbon over each step is calculated using RSP tables obtained from SECT or DECT. These RSP values are iteratively changed using a gradient descent optimization whose goal is to minimize the difference between the CDRR energy output and the MC reference value. To reduce the optimization time, RSP values are binned based on HU threshold (SECT) or atomic effective number threshold (DECT). The optimized RSP values are compared with the experimentally obtained RSP values. The need to use information from multiple angles is also investigated as a method to decrease statistical uncertainties. Results/Conclusions: Preliminary results using SECT information shows that for bone materials, such as inner bone and CACO50%, the RSP uncertainties can be reduced from 1.26% and 1.54% to 0.35% and 0.85% respectively. Based on these preliminary results, carbon RSP uncertainties can be reduced using information from both carbon radiographs and SECT. Experimental RSP for a carbon beam will be obtained and the possibility to use this method on alpha particles will also be considered. The next step is to use DECT and information from multiple angle carbon radiographs to better estimate RSP values from different tissue materials. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 49 Improved Efficiency in Monte Carlo Simulation for Passive-Scattering Proton Therapy J. Ramos-Méndez1 , J. Perl2 , J. Schümann3 , J. Shin4 , Harald Paganetti3 and Bruce A. Faddegon1 1 Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco (CA), USA SLAC National Accelerator Laboratory, Menlo Park (CA), USA 3 Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston (MA), USA 4 St. Jude Children’s Research Hospital, Memphis (TN), USA 2 We have developed variance reduction techniques (VRTs) for the specific needs of proton therapy in passive-scattering mode. We focus our attention to the tracking of protons through the treatment head, which consumes more than a half of the total simulation time. The TOPAS application was used to simulate two treatment heads: one at the Francis H. Burr Proton Therapy Center (S1), the other the eye treatment beam line at UC Davis Crocker Lab used by UC San Francisco (S2). We studied the geometrical particle splitting (GPS) technique combined with Russian roulette based on geometry considerations. In addition, for S1, the threshold value (in distance units) for the production of secondary particles (hereafter referred as the production cut or PC) such as electrons, positrons and gammas was tuned to find the optimal value. For both treatment heads, two split planes were located at strategic locations. Once a proton (primary or secondary) reaches either of the planes, Russian roulette is played if its directed outside a user-defined region, otherwise it is split 8 times for S1 or 16 times for S2. The split planes are located in a parallel geometry, thus with parallel navigation the particle "knows" if it has crossed such planes. Phase spaces (PHSPs) were scored at the end of each treatment head and saved in binary format. After that, the particle tracks were stopped. For analysis consideration, the PHSPs were divided into concentric rings of equal area to calculate the planar energy fluence per ring and its corresponding statistical uncertainty. Subsequently the computational efficiency was calculated as the inverse of the squared statistical uncertainty of the energy fluence multiplied by the simulation time. The effect of the efficiency improvement on the simulation accuracy was determined by comparing dose distributions calculated from PHSPs created with and without the VRT and PC for homogenous phantoms and a patient.For S1 computational efficiency increased by a factor of about 80. For dose calculations (with GPS approximately 12 million of histories to achieve a statistical uncertainty lower than 2%), by considering those voxels with values larger than 20% of the maximum dose, 28% ± 5% of such that voxels show a systematic difference of 0.32±0.12 which correspond to 0.61% of the maximum dose. 21% ± 4% of voxels show a systematic difference -0.58 ± 0.06 that corresponds to 1.1% of the maximum dose. Alternative calculations show that the percentage of voxels that passed the gamma index test was of 98.85% for the 2% and 2 mm criteria.For S2 computational efficiency increased by a factor of about 57. For dose calculation (with GPS approximately 2 million of histories to achieve a statistical uncertainty lower than 2%), by considering those voxels with values larger than 20% of the maximum dose, 12% ± 1% of such that voxels show a systematic difference of 1.11 ± 0.11 which correspond to 1.2% of the maximum dose. 22% ± 2% of voxels show a systematic difference 1.12 ± 0.06 that corresponds to 1.23% of the maximum dose. Alternative calculations show that the percentage of voxels that passed the gamma index test was of 99.79% for the 2% and 2 mm criteria.In simulations of passive scattering proton therapy, the combination of VRT and PC lead to a significantly reduction in CPU time without compromising the dosimetric accuracy. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 50 A sub-millimeter experimental benchmark of a 67.5 MeV proton depth dose curve in water Bruce A. Faddegon1 , J. Shin2 , Carlos M. Castenada3 and Inder K. Daftari1 1 University of California San Francisco, San Francisco (CA), USA St. Jude Children’s Research Hospital, Memphis (TN), USA 3 Crocker Nuclear Laboratory, University of California, Davis (CA), USA 2 Purpose/Objectives: To measure a pristine proton Bragg Peak for a 67.5 MeV proton beam with depth known to a few tenths of a millimeter and energy known with better accuracy than the depth. Materials/Methods: A time of flight (TOF) system was previously used to establish the energy of the proton beam exiting the cyclotron used for the benchmark measurement within 0.1 MeV and is also used routinely to verify the beam energy. The width of the peak was limited to 0.4 MeV FWHM based on previous CsI measurements. The beam was incident on 2 different Ta scattering foils, 101.6 µm and 381 µm thick, followed by a wire chamber, secondary electron emission monitor and 127 µm thick Kapton exit window. This is minimal material of accurately known composition and density as required for measurement of the benchmark pristine Bragg Peak. The beam was collimated to a diameter of 111 mm at the exit window with a water tank oriented perpendicular to the beam axis placed 300 mm from the exit window. Radiochromic film was used to measure beam flatness, symmetry and divergence and to verify the beam axis was coincident with alignment lasers. Diodes for charged particle dosimetry from 2 different manufacturers were centered on the beam axis with depth determined to 0.2 mm, including a discrepancy of 0.2 mm in the manufacturer specification of the sensitive volume depth in the detector. A motorized stage with 3 µm reproducibility was used to step the detectors from the water tank window through the Bragg Peak. The dose rate was low enough that the measured percent depth dose curves were independent of dose rate. Parallel plate chambers with a positioning accuracy of 0.2 mm and 0.5 mm were used to verify the diode measurements. Measurement was compared to Monte Carlo simulation done with Geant4 using TOPAS. Results: The diode and parallel plate chamber depth dose curves agree within the least restrictive of the accuracy of the detector positioning and 1.5% in dose, within the repeatability of the measurement. The experimental benchmarks for the 67.5 MeV proton beam shown in the Figure has 0.2% accuracy in the beam energy and 0.5% accuracy in depth of the Bragg Peak. To our knowledge this accuracy exceeds that of published benchmarks. The 80% dose at the distal side of the Bragg Peak for the thinner foil was at 37.2 ± 0.2 mm, compared to the simulated value of 37.1 mm. The 80% dose for the thicker foil was at 35.0 ± 0.2 mm, compared to the simulated value of 34.8 mm. The result has ramifications on the accuracy of the mean ionization potential needed to calculate stopping powers for the Monte Carlo simulation, with the resulting stopping power in water marginally high by 0.3 ± 0.5%. Conclusions: The experimental benchmark met the accuracy objective. The sub-millimeter accuracy of the simulation will facilitate achieving 1-2 mm accuracy in range estimation in treatment planning for proton therapy, a worthwhile clinical goal. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 51 Tissue Identification by Dual Energy Computed Tomography for Brachytherapy Mathieu Gaudreault1,2,3 , Guillaume Landry3,4 , Luc Beaulieu1,2 and Frank Verhaegen3,5 1 Département de radio-oncologie and Centre de recherche du CHU de Québec, Centre hospitalier universitaire de Québec, Québec, Canada Département de physique, de génie physique et d’optique and Centre de recherche sur le cancer, Université Laval, Québec, Canada 3 Department of Radiation Oncology (MAASTRO), GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, the Netherlands 4 Division of Medical Physics, Ludwig-Maximilians-Universität, Munich, Germany 5 Medical Physics Unit, McGill University Health Centre and Department of Oncology, McGill University, Montréal, Canada 2 Objectives: Dual Energy CT imaging (DECT) is a known technology in diagnostic radiology. The tissue-differentiating capabilities of DECT for radiotherapy have only recently been explored. DECT provides the CT numbers at two energies (80 kVp and 140 kVp) of the geometry. This technology is expected to improve tissue segmentation in brachytherapy as opposed to Single Energy CT imaging (SECT). Materials and methods: Tissue assignment is performed on DECT scans reconstructed using sinogram affirmed iterative reconstruction (SAFIRE, Siemens) of the Gammex RMI 467 phantom for 4 values of CTDIvol. Tissue identification is performed through the calculation of the Mahalanobis distance between the measured HU80kVp and HU140kVp and distributions of the reference CT numbers of each voxel. The assignment scheme is tested by calculating the dose distributions of a heterogeneous phantom made of the materials resulting from assignment. The dose distributions are calculated with Monte Carlo (MC) simulations using GEANT4 with an I-125 point source. The voxel by voxel dose differences in a sphere with 2 cm radius are calculated with respect to the dose distributions of a homogeneous phantom made of the reference parameters of the material under study. The exercise is repeated for two datasets of human tissues (a list of 15 tissues appropriate for prostate brachytherapy and a list of 10 tissues representing the interval of the effective atomic number of 73 human tissues) for which the CT numbers are calculated by the stoichiometric method. Results are compared to tissue assignment based on SECT. Results: The dose differences are below 3% for all inserts of the calibration Gammex phantom. The dose differences obtained from the human tissue validation datasets are below 10% for all tissues considered. Lower dose differences are obtained for the human tissue dataset if the list of possible assigned tissues (initially 73 tissues) is restricted to the number of tissues considered (10 tissues). It is observed that the dose differences are larger if the image dose is lowered for all datasets. DECT leads in general to better results than SECT. Conclusions: Tissue assignment is feasible by calculating the Mahalanobis distance between the measured HU80kVp and HU140kVp and reference tissue distributions for the Gammex RMI 467 phantom and two human tissue datasets. The resulting dose distributions show a good agreement with the reference dose distributions. However, image noise alters the results of the assignment. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 52 Evaluation of the performance of a dual energy CT segmentation method using a Monte Carlo imaging simulation environment Anthony Di Salvio1 , S. Bedwani1 , Hugo Bouchard2 and Jean-François Carrier1 1 2 Département de radio-oncologie, Centre hospitalier de l’Université de Montréal, Montréal, Canada Acoustics and Ionising Radiation Team, National Physical Laboratory, Teddington, UK Purpose: To simulate dose distributions using Monte Carlo, the patient geometry can, in most cases, be described using two physical properties for each voxel: • Electron density (ED); • Energy-dependent electron cross-sections (ECS). While ED is extracted from conventional CT (SECT) HU-ED curves, ECS are usually assumed from the properties of known media being associated to curve segments. Dual energy CT (DECT) should improve this characterization method by providing additional information, such as the effective atomic number (EAN), on a single acquisition. Methods: The projection of a numerical head phantom is simulated with the EGSnrc user code egs_cbct with monoenergetic sources (57 keV, 68 keV, and 77 keV) to evaluate projections equivalent to 90 kV, 120 kV, and 140 kV exempt of beam hardening effects. Images are reconstructed using a Feldkamp-Davis-Kress (FDK) algorithm. A DECT stoichiometric calibration is used to obtain ED and EAN in each voxel and further obtain the most likely tissue corresponding to both values assigned. The performance of the tissue segmentation of the presented DECT method is compared with SECT and the original phantom. The SECT method assigns the most likely material based on a segmentation of CT numbers. Results: The numerical phantom and the reconstructed data are segmented into 6 different materials: vacuum, adipose tissue, muscle, cartilage, spongiosa, and cortical bone. DECT and SECT data were compared to the original phantom in two parts: 1) all tissues, from adipose tissue to cortical bone, and 2) tissues of higher density, comparing cartilage, spongiosa, and cortical bone. Data overall is similar for both methods. The proportion of correctly assigned voxels - other than vacuum - goes from 62.4% for DECT to 63.6% for SECT. Most errors are attributed to partial volume effects and to filtering from reconstruction. Assignment of tissues of higher density is improved using DECT data as it assigns correctly 55.2% of this type of tissue against 48.2% using SECT. Figure shows different material segmentations on a single slice. Conclusion: Assigning tissues of higher density correctly is important in evaluating dose distributions, especially for brachytherapy as interactions vary more between those tissues than between soft tissues. Further developments in reconstruction and segmentation parameters should increase the efficiency of both methods. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 53 Application of Monte Carlo dose calculations for on-line replanning for the hybrid MRI radiotehrapy accelerator Bas W. Raaymakers1 , G. H. Bol1 , C. Kontaxis1 , J. J. E. Kleijnen1 , J. Wolthaus1 , B. Van Asselen1 , S. P. M. Crijns1 , A. N. T. J. Kotte1 and J. J. W. Lagendijk1 1 Department of Radiotherapy, UMC Utrecht, Utrecht, the Netherlands In the UMC Utrecht, The Netherlands, we have prototyped a hybrid 1.5T MRI and a 6 MV radiotherapy system in collaboration with Elekta AB, Sweden and Philips, The Netherlands. This system allows simultaneous MR imaging and dose delivery for more precise tumor targeting. Exploiting on-line and real-time MRI based anatomical updates for treatment optimization requires on-line and ultimately realtime plan adaptations or re-planning. The dose delivery is done in the presence of a transverse 1.5 T magnetic field. The photon beam is not affected by the magnetic field, however the secondary electrons are. The impact is an asymmetric dose kernel in homogeneous tissue and an Electron Return Effect at tissue-air interfaces, i.e. electrons in air will return back to the exiting surface due the Lorenz force. This impact should be taken into account in dose calculations and inverse optimization to determine the optimal intensity modulated radiotherapy treatment (IMRT) dose distribution. This mandates the use of a Monte Carlo dose engine in the IMRT module. In Utrecht the GPUMCD code [1] is used. This dose engine is coupled to an inverse optimization algorithm in order to have a flexible IMRT planning system (MRLTP) to develop and prototype on-line plan adaptation and re-planning strategies. A few strategies will be presented such as automated on-line re-planning and on-line plan adaptations by means of a so called virtual couch shift. For the latter the pre-treatment IMRT dose distribution is moved along with a translation or rotation of the patient rather than moving the patient back to the pre-treatment position. Also a segment-by-segment optimization is used to account for intra-fraction anatomical updates. The results from MRLTP are experimentally validated according to our clinical QA protocol using the Delta4 system (Scandidos, Sweden). On-line plan adaptations that are accounting for the impact of the magnetic field require a fast Monte Carlo based dose engine. By doing so, on-line and potentially intra-fraction plan adaptations and re-planning are feasible which opens the way for a more adaptive, precise radiotherapy. This will improve the existing radiotherapy patient population but also opens the door towards an effective radiotherapy for highly mobile tumor sites that require such extensive on-line plan adaptation. Part of this work is financially supported by Elekta AB, Sweden. [1] S. Hissoiny et al. 2011 Phys. Med. Biol. 56 (16). p.5119 International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 54 A study of the limitation of radiation detectors in nonstandard conditions using EGSnrc Yuji Kamio1 and Hugo Bouchard2 1 2 Département de radio-oncologie, Centre hospitalier de l’Université de Montréal, Montréal, Canada Acoustics and Ionising Radiation Team, National Physical Laboratory, Teddington, UK Purpose: Small and composite IMRT fields produced by SBRT/IMRT modalities are known to require an additional correction factor to accurately convert a dosimeter’s response to dose absorbed in water [1]. While it is not possible evaluate these factors explicitly due the endless possibility of fields, we can attempt to design worst case scenarios to evaluate the robustness of a variety of radiation detectors to nonstandard conditions. Methods: The following detectors are modelled using the egs++ library according to the manufacturers’ specifications by Exradin for the A12, A1SL and A14 ionization chambers as well as the W1 scintillation detector, Nuclear Enterprises for the NE2571 chamber and PTW for the PTW31018 microLion, PTW60012 unshielded diode and PTW60003 natural diamond detectors. Dose response function [2] d(x,y) are first sampled in the transverse and longitudinal direction by scoring the dose absorbed from a pencil beam crossing the isocenter plane at the position (x,y) using the Monte Carlo code egs_chamber [3]. These functions suggest the following special cases: a) a dimensionless pencil beam incident on the centroid of the sensitive volume, a field incident only on b) the contour the central electrode and c) the contour of the sensitive volume. Results: The A12 and NE2571 correction factors at 6 MV are found to deviate significantly from unity with values varying between 0.2 and 32 for cases a) and c) respectively when the dose is reported to a point-like structure of water and 0.4 and 1.3 when the dose is reported to the sensitive volume filled with water. Fields incident only on the contour of the central electrode produce volume-dose correction factors slightly more important for the A12, NE2571 and A1SL chambers. Worst case correction factors are found to be reduced at 25 MV which could be explained by a less significant mass density effects at higher energies. Conclusion: This work illustrates which spatial features of nonstandard fields give rise to correction factors above/below unity. The illustrated fields can be used to test how robust a given dosimeter is in nonstandard conditions. For instance, the scintillation detector do not produce volume-dose correction factors that deviated by more than 1.5% from unity in these limiting cases. [1] R. Alfonso et al. 2008 Med. Phys. 35 (11), p.5179-5186; [2] H. Bouchard et al. 2004 Med. Phys. 31(9), p. 2454-2465; [3] J. Wulff et al. 2008 Med. Phys. 35(4), p. 1328-1336. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 55 Characterization of the response of nine radiation detectors in small fields and IMRT beams using EGSnrc Yuji Kamio1 and Hugo Bouchard2 1 2 Département de radio-oncologie, Centre hospitalier de l’Université de Montréal, Montréal, Canada Acoustics and Ionising Radiation Team, National Physical Laboratory, Teddington, UK Purpose: The aim of this work is to compare the response of various dosimeters in nonstandard beams using Monte Carlo methods. Methods: Detailed models of nine radiation detectors are built from manufacturers’ specifications using the egs++ library. These include four ionization chambers (A12, A1SL, A14 and NE2571), an unshielded diode (PTW60012), a liquid-filled chamber (PTW 31018), a natural diamond detector (PTW60003), an alanine pellet as well as a scintillation detector (W1). Small beams of field sizes between 2 and 40 mm are modeled using the egs++ library and 13 IMRT fields [1] are generated with a BEAMnrc [2] model of a Varian Clinac 21EX linac. The efficiency of the simulations is improved with the use of variance reduction techniques available with the usercode egs_chamber [3]. Underwood et al. [4] recently introduced four variations on the nonstandard field correction factor needed to determine the absorbed dose to water. These factors are used to determine how significant the dosimeter’s non-sensitive components, sensitive volume and mass density are in nonstandard fields. Results: Nonstandard beam correction factors can be significantly reduced in both small and IMRT beams by reporting the dose to the sensitive volume filled with water. Once volume averaging effects are eliminated, mass density effects are found to be the dominant factor with high-density detectors (e.g. diode) over-responding and low-density detectors (e.g. ion chambers) under-responding in small fields. The non-sensitive components are found to significantly influence the detector’s response. This is namely the case with the microLion where the high-density graphite electrode can overcompensates its low-density sensitive volume. The unshielded diode is also found to under-respond in intermediate fields (2 to 4 cm2 ) and IMRT field segments due to the sensitivity its high-Z volume to the increased keV scattered photons of the reference field. The influence of the detector’s orientation on the response is also studied. Conclusion: This work suggests that nonstandard field correction factors can be avoided by using either density-compensated detectors or near water-equivalent dosimeters such as the scintillation detector whose correction factors deviate from unity by less than 1%. [1] H. Bouchard et al. 2004 Med. Phys. 31(9), p. 2454-2465; [2] D. W. O. Rogers et al. 1995 Med. Phys. 22 (5), p. 503-524; [3] J. Wulff et al. 2008 Med. Phys. 35(4), p. 1328-1336, 2008; [4] T. Underwood et al. 2013 Med. Phys. 40(8). International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 56 On-axis and off-axis correction factors for modern detectors in small field dosimetry Pavlos Papaconstadopoulos1 , F. Tessier2 and Jan Seuntjens1 1 2 Medical Physics Unit, McGill University, Montréal, Canada Ionizing Radiation Standards, National Research Council of Canada, Ottawa, Canada Introduction: In recent years several investigators have targeted the problematic nature of dose measurements in stereotactic fields, which often results in erroneous output factors. These factors will propagate as systematic errors to the treatment planning system during the commissioning procedure. Not many researchers have investigated the need for off-axis corrections in the penumbra region of stereotactic profiles. These regions will also suffer by conditions of non-charged particle equilibrium. In this work we aim to investigate the on-axis and off-axis corrections for modern dosimeters including a liquid ion chamber, an unshielded diode and a scintillator. Methods: As a first step, the Varian Novalis Tx linear accelerator was modeled using the EGSnrc/BEAMnrc code. A rigorous commissioning process was followed using 2 small-field detectors: the PTW microLION 31018 (ML) and the SI, Exradin D1V unshielded diode. The detectors were explicitly modeled using the egs_chamber code and technical sketches provided by the manufacturers. Measurements and simulations were also performed for the SI, Exradin scintillator W1 in both horizontal (res=3 mm) and vertical (res=0.5 mm) orientations to the water surface. As a second step, on-axis and off-axis correction factors were derived for all the detectors and for field sides of 0.5, 1 and 2 cm according to the Alfonso formalism. For this work a cylindrical volume of radius = 0.15 mm and length = 0.3 mm was used for the reference dose in a point in water. Results and Discussion: The commissioning process resulted in a source size of FWHM(x)=1.25 mm, FWHM(y)= 1.1 mm, energy=6.1 MeV and angular spread = 1 deg. The output factors agreed within 0.5% for the ML, 1.5% for the D1V and 0.5% for the W1 measurements. All detectors exhibited minimal output factor corrections down to a field side of 1 cm. For the smallest field side of 0.5 cm, large discrepancies were observed for the D1V (+4%) and W1/horizontal (+5.4%), while small corrections were needed for the ML (+2%) and W1/vertical (+0.2%). On the off-axis positions all detectors exhibited negligible corrections within the field (50% dose level). Discrepancies started appearing within the 50% - 10% dose levels mainly for the ML and diode D1V (up to 15%). Small corrections (up to 3%) were required for the W1/vertical. Conclusions: The scintillator W1 exhibited promising results for relative small field dosimetry. If used with the highest resolution (0.5 mm), small corrections were needed for both on-axis and off-axis positions. For the horizontal orientation, which can be performed in solid water, the scintillator exhibited large discrepancies at the smallest field mainly due to volume averaging. Large corrections were observed for the rest of the detectors either on-axis (D1V) or off-axis (ML, D1V). Future work will focus in evaluating the Cherenkov calibration method required for the scintillator measurements. 1 0.98 1.2 1 kfclin(x),fclin(0) Qclin(x),Qclin(0) fmsr kfclin, Qclin, Qmsr 1.02 1.2 kfclin(x),fclin(0) Qclin(x),Qclin(0) diode d1v microLION 31018 scintillator w1 (//) scintillator w1 dose in water 1.04 0.8 0.6 0.4 1 0.8 0.6 0.4 0.2 0.2 0 0.96 0.5 2 Inplane profile (0.5 × 0.5 cm ) Crossplane profile (0.5 × 0.5 cm2) Output factor corrections 1.06 1 1.5 field side (cm) 2 0 0 1 2 3 4 offïaxis (mm) 5 0 2 4 offïaxis (mm) 6 International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 57 Depth and off-axis dose perturbation effects in water in an 18 MV photon beam for a liquid ionization chamber and an air-filled ionization chamber Kyle O’Grady1 , Stephen D. Davis1 , Pavlos Papaconstadopoulos1 and Jan Seuntjens1 1 Medical Physics Unit, McGill University, Montréal, Canada Using the egs_chamber user code of the EGSnrc Monte Carlo system, a PTW microLion liquid ionization chamber and an Exradin A1SL air-filled ionization chamber have been modeled to investigate their perturbation effects in water in a 5 × 5 cm2 18 MV photon beam. BEAMnrc was used to construct a model of a Varian CL21EX linear accelerator according to vendor specifications. Tuning of the beam model was performed by comparing microLion chamber measurements to calculations that included a full model of the chamber. The tuning process included tweaking the energy, radial intensity, and angular spread of the electron beam incident on the target. This tuned model was validated by comparing measured PDDs and profiles from the A1SL chamber to calculated results that included a detailed model of the chamber.The effects of both detectors’ material compositions were investigated using the egs_chamber correlated sampling technique to compare a full chamber model to dose calculations in water. The ratio of dose to water in a region with the same dimensions as the chamber cavity relative to dose in the active volume for the full chamber model was calculated for both chambers. A1SL chamber PDD simulations were used to determine the chamber’s effective point of measurement using the methodology presented by Tessier and Kawrakow [1]. The effective point of measurement was 0.29 mm upstream, consistent with the published results. Once shifted, the dose ratio was nearly independent of depth and was consistent with the stopping-power ratio of water to air. As a function of off-axis distance, the dose ratio in both detectors was nearly constant inside the field and consistent with the stopping power ratios of water to detector material, but varied up to 3.3% near the field edge due to fluence perturbation effects. To determine the effect of volume averaging of the A1SL chamber relative to an idealized point detector, the dose ratio calculations were repeated at 1 mm increments with the water scoring region reduced to a 0.3 mm × 1 mm × 0.3 mm voxel (see Figure). The dose ratio results were the same as earlier within the field, but now varied up to 13.2% near the field edge. Ideally, once the effects of detector perturbation and spatial resolution are fully characterized for more field sizes and detectors, they could be applied to clinical water tank measurements for improved dosimetric accuracy. [1] Tessier and Kawrakow 2010 Med. Phys. 37, 96-107 International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 58 A comparison of field factors for small field x-ray dosimetry with Gachromic EBT3 film and Monte Carlo simulations for a Novalis linear accelerator Johnny E. Morales1,2 , Scott B. Crowe1,2 , R. Hill1,2 and J. V. Trapp1,2 1 2 Department of Radiation Oncology, Chris O’Brien Lifehouse Sydney, Sydney, Australia School of Chemistry, Physics and Mechanical Engineering, Queensland University of Technology, Brisbane, Australia Aim: The aim of this project was to compare the suitability of Gafchromic EBT3 film for dosimetry of small x-ray fields in Novalis Tx equipped with circular cones. Introduction: Small field dosimetry remains a challenge due to the limitations of current dosimetry detectors. These limitations include a lack of charged particle equilibrium between water and the detector material, source occlusion, either under-response or over-response of detector material in broad beams and volume averaging effects due to detector size. Radiochromic film shows great possibility for small field dosimetry due to high spatial resolution, ease of use and near tissue equivalence. A Novalis Trilogy linear accelerator equipped with BrainLab circular cones in the range of 4 to 30 mm diameter was modelled using the BEAMnrc/DOSYZnrc package. This model was used ,fmsr to calculate field factors, (ΩfQclin ), for a range of small field sizes [1]. A comparison was then made between the field factors measured clin ,Qmsr with Gafchromic EBT3 film and the Monte Carlo calculations. fclin ,fmsr Results: Table shows the results from the Monte Carlo calculations for field factors, ΩQ , and the Gafchromic EBT3 measurements. clin ,Qmsr The uncertainty for the EBT3 measurements was 2% (1SD) and 0.5% for the BEAMnrc/DOSXYZnrc calculations. Cone Diameter (mm) Depth (cm) EBT3 film Monte Carlo Difference (%) 4 1.5 0.646 0.649 -0.4 4 10 0.357 0.356 0.2 7.5 1.5 0.816 0.811 0.6 7.5 10 0.451 0.452 -0.3 10 1.5 0.872 0.870 0.3 10 10 0.496 0.488 0.6 20 1.5 0.945 0.955 -1.1 20 10 0.543 0.551 -1.5 30 1.5 0.976 0.959 1.8 30 10 0.578 0.570 1.4 Discussion and Conclusion: We found excellent agreement between the field factors measured with Gafchromic EBT3 film and Monte Carlo calculations. For field diameters of 4 to 10 mm we found a maximum deviation of 0.6%. But we found a difference of up to 1.8% for fields greater than 10 mm. A comparison is made between our results and those by other groups with similar megavoltage equipment [2]. fclin ,fmsr We conclude that Gafchromic EBT3 film is a suitable detector for measurements of field factors, ΩQ , for small x-ray beams in a clin ,Qmsr Novalis equipped with circular cones. [1] R. Alfonso et al. 2008 Med. Phys 35, 5179-5186; [2] C. Bassinet et al. 2013 Med. Phys. 40, 071725. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 59 Poster abstracts On-line relative stopping power optimisation using multiple angle proton radiography and SECT/DECT prior-knowledge information Charles-Antoine Collins Fekete1,2 , Marta F. Dias2,3 , David C. Hansen2,4 , Luc Beaulieu1,5 and Joao Seco1 1 Département de physique, de génie physique et d’optique and Centre de recherche sur le cancer, Université Laval, Québec, Canada Department of Radiation Oncology, Francis H. Burr Proton Therapy Center, Massachusetts General Hospital, Boston (MA), USA 3 Dipartamento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy 4 Department of Clinical Medicine, Aarhus University, Aarhus, Denmark 5 Département de radio-oncologie and Centre de recherche du CHU de Québec, Centre hospitalier universitaire de Québec, Québec, Canada 2 Purpose/Objectives: Standard proton therapy practice deals with proton stopping power uncertainty of 3.5%, strongly affecting the ability to place the proton Bragg peak at the edge of the tumour. The clinical stoichiometric calibration curve is directly related to these uncertainties. This project tackles the problem with a new innovative method, i.e. approaching the relative stopping power (RSP) problem by using combined information from single-energy CT (SECT) or dual-energy CT (DECT) images with proton radiography energy output from a few angles. Materials and Methods: Monte Carlo (MC) algorithm Geant4 v.4.9.6 is used for Monte Carlo processing in this code. NVIDIA GeForce GTX 680 graphics is used for GPU processing. The reference phantom throughout the whole study is a Gammex phantom. ImaSim algorithm allows us to produce a CT image of the Gammex phantom at 80, 120 and 140 kVp. Yang method is used to extract RSP from combined 80-140 kVp CT (DECT) and the stoichiometric method serves to extract RSP from the 120 kVp CT (SECT). Geant4 MC algorithm is used to produce a reference proton radiography energy output for multiple angles (180 degrees separated by 5 degrees steps). Each proton is propagated from is origin through the Gammex phantoms using ray tracing, calculating the energy loss with the RSP tables (SECT, DECT), to produce a proton digitally reconstructed radiography (PDRR). A gradient descent optimisation is then done on the RSP values to converge the PDRR energy output to the MC reference value. To reduce the optimization time, RSP values are binned based on HU threshold (SECT) or atomic effective number threshold (DECT). Proton radiography at multiple angles allows us to decrease statistical uncertainty. Cauchy variable step sizes are used. Optimized RSP tables from both imaging method are compared to the MC reference. Results: Preliminary results using the SECT table shows that CB2-50% CaCO3 and LN-450 material RSP are optimized towards the reference value with a final difference of respectively -4.2% (initially -13.8%) and 0.83% (initially 1.95%). Calculation time is 0.98 s per 100 000 protons propagated on a single GPU core, within clinical tolerance. Conclusions: Based on these results, ray tracing optimization, using information from proton radiography at multiple angles and RSP tables extracted from SECT, demonstrates a potential to improve the proton range accuracy in a clinical environment. The next step is to include DECT method to optimize RSP values. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 60 AVOQA : Application for Voxelization Optimized by Quadtree Algorithm, New CT-scan voxelization tool for MCNPX Virgile Letellier1 , E. Constant1 , L. De Marzi1 , J. Argaud1 , N. Fournier-Bidoz1 and A. Mazal1 1 Curie Institute Proton Therapy Center in Orsay, Curie Institute, Paris, France Introduction: The Curie Institute Proton Therapy Center in Orsay (ICPO), attempt to switch part of its patients dosimetry quality controls to Monte Carlo simulations. In order to decrease occupancy rooms for quality control and to treat new cancer localization. In parallel, a study has been carried out in order to work on the patient CT images directly in the Monte Carlo code MCNPX. The purpose is to verify the TPS dosimetry with an independent Monte Carlo code and to compare them. Material and Methods: The ICPO has for two of these three treatment lines, MCNPX Monte Carlo modelization validated for all the workable ballistic treatment options. MCNPX is used in its 2.6 version on 128 cores Intel Xeon 2690 cluster.The interface and the algorithm to convert images into Dicom MCNPX geometry were performed on MATLAB 2012b. The algorithm purpose is to segment the images by regions of homogeneity and to create lattices allocated recursively by the different components: • Materials; • Hounsfield; • Density with CT-scan calibration curves application. The isocenter of the treatment room (IEC) is used as reference. Results: Segmentation permits to decrease the number of voxels generated by a factor 100. Memory gain allows to voxelize with more layers or higher resolution. The plug-and-play voxelization has a millimetric precision and can be directly operated into MCNPX without any errors or additional modifications. Matrix dose in tissues are exported to Dicom matrix (RT dose) in water dose, recognized by the commercial TPS for easier comparison.-Conclusion Software based on this study was created and was called AVOQA (Application for Voxelization by Optimized Quadtree Algorithm). Compared to alternative applications, AVOQA creates a voxelization for MCNPX directly from CT-scan without using the organs contours; in addition it applies the CT-can calibrations. Thus AVOQA is a great MCNPX voxelization tool for CT-scan images, and it is the most accurate and faithful. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 61 Impact of correlation between CT numbers and tissue parameters on Monte Carlo simulations: dosimetric aspects Nicolas Garnier1,2 , Dyaa Amer1,2 , Rémy Villeneuve1 , Éric Franchisseur1 , Mourad Benabdesselam2 , Cécile Ortholan1 and Benjamin Serrano1 1 2 Medical physics and radiotherapy department, Princess Grace Hospital, Monaco, Monaco Laboratoire de physique et de la matière condensée, Sophia Antipolis University, Nice, France Purpose: Monte Carlo (MC) simulation in radiotherapy is well known to be the reference for patient deposit dose estimation. Correlation between CT images and MC tissue parameters is a major step before the estimation of the deposit dose. It requires transforming the CT dicom images in the geometry input of MC code, and depends on the chosen samplings, which modify the CT number. However the CT number determine the density and the chemical composition of each voxel. The purpose of this study is to highlight the dosimetric impact of the density and the chemical composition variation. Methods: This study was performed with PENELOPE MC code (2011 version). Interactions of monoenergetic (2 MeV) and monodirectional photon beam in a cubic voxel (1cc) in an air environment were simulated with MC. We investigated the absorbed energy in the voxel by changing density and chemical composition. Nine ICRP (publication 110) elements were simulated: air, lung, adipose, breast, water, liver, muscle, spongiosa bone and mineral bone. Because the water is used as reference in the Treatment Planning System (TPS) our results were normalized by energy deposit in water with the same density: 100 x (Energy deposit in the element - Energy deposit in water) / (Energy deposit in water). The standard deviation was estimated as the statistical error. Results: For density in the interval 0.5 to 1.1 g/cm3 the maximum variation between energy deposit in lung, adipose, breast, liver, muscle and energy deposit in water is -1.3%. Concerning the spongiosa bone in a range density of 1 to 1.5 g/cm3 the difference do not exceed -3.2%. The difference with water for mineral bone in a range density of 1.5 to 2.2 g/cm3 is about -9%. In air medium (density close to 0.001 g/cm3 ) the variation goes up to -18%. The attached figure illustrates these variations. Conclusion: Following the energy deposit with MC simulation in different elements for the same density shows the impact of the chemical composition as a crucial point, which strongly influences the accuracy of patient dose calculations in MC treatment planning. It is particularly important to differentiate lung from air (17.5% for density at 0.3 g/cm3 ), bone from soft tissue (3% for density at 1.1 g/cm3 ) and different bone compositions (6.5% for density at 1.26 g/cm3 ). International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 62 Scatter correction with Monte Carlo pre-calculated kernels Benjamin Auer1 , Virgile Bekaert1 , Jean-Michel Gallone1 , David Brasse1 and Ziad El Bitar1 1 Université de Strasbourg, Strasbourg, France In Emission Tomography (ET), attenuation and scatter introduce an important artefact in the reconstructed images biasing the diagnosis and the follow-up of the imaged patient. Photoelectric effect and Compton scattering are at the origin of the above-mentioned effects and require to be considered for if an accurate quantification of the reconstructed images is required, otherwise signal-to-noise ratio, contrast recovery and spatial resolution will be degraded.Using Monte Carlo Simulation (MCS), physical effects undergone by photons during the ET exam can be precisely modelled and considered for during image reconstruction, which improve the image quality. However, MCS are large time consuming and therefore inappropriate for the rate of daily exams performed in clinical routine. In this work we propose to accelerate the modelling of the physical effects occurring in the patient making it adequate for clinical routine. The photons’ propagation will be modelled by successive convolution of pre-calculated kernels in order to model photons’ propagation though matter. We take advantage that patients are composed of identical biological tissues and that photon propagation in an element volume of a given tissue is similar and reproducible from one patient to another. This leads us to calculate a propagation kernel per element volume and per biological tissue. The calculated kernels will hence model emission and transmission though an element volume (voxel) of different biological tissues and will be stored in a database in order to be used later for photon propagation without a need for a full MCS. This will make possible a patientdependent attenuation and scatter correction for clinical routine.The kernels are calculated using Geant4 (http://geant4.cern.ch), version 9.10.00.p01.The simulation set-up to compute the emission kernels will be a voxel filled with a homogeneous activity. For the transmission kernels, the calculation will consist to target the entry of the voxel with various energy and incidence photons beams. Photons’ information at the exit of the voxel whether in emission or transmission will be used to calculate the kernels. Photons’ propagation though kernels convolution will be very adequate for a GPU implementation. Calculation of solid-state track-etched detectors response in 290 MeV/u and 400 MeV/u carbon-12 ion beams using Geant4 Martin Šefl1,2 , V. Štěpán 2,3 , K. Pachnerová Brabcová2,4 , I. Ambrožová2 , O. Ploc2 , Sébastien Incerti3 and M. Davídková2 1 Department of Dosimetry and Application of Ionizing Radiation, Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University of Prague, Prague, Czech Republic 2 Department of Radiation Dosimetry, Nuclear Physics Institute ASCR, Prague, Czech Republic 3 Université Bordeaux 1, Centre d’Études Nucléaires de Bordeaux, Gradignan, France 4 Department of Applied Physics, Chalmers University of Technology, Göteborg, Sweden Solid state track etched detectors can work as linear energy transfer (LET) spectrometers for charged particles with LET above detection threshold, while electrons and other particles are not detected. We have applied the Geant4 Monte Carlo simulation toolkit version 4.9.6p01 [1,2] to reproduce the beamline geometry [3] and experimental setup used for experimental measurements [4, 5] of LET spectra of 290 MeV/u and 400 MeV/u carbon ion beams at Heavy Ion Medical Accelerator in Chiba, Japan. The spectra were measured with track-etched detector TD1 (Japan Fukuvi Chemical Industry Co. Ltd), which is under our evaluation conditions sensitive to charged particles of LET between 8 and 500 keV/µm. The dose and LET spectra of the beam attenuated by several thicknesses of PMMA filters had been calculated in water and were compared with the experimental data. Calculations and measurements were in a good agreement within the detectors LET sensitivity range. [1] J. Allison et al. 2006 IEEE Transactions on Nuclear Science, 53 270-278; [2] S. Agostinelli et al. 2003 Nuclear Instruments and Methods in Physics Research, A 506, 250-303; [3] S. Yonai et al. 2009 Med. Phys., 36 4830-4839; [4] K. Pachnerová Brabcová et al. 2011 Radiat. Prot. Dosim., 143 440-444; [5] F. Spurný et al. 2011 Radiat. Prot. Dosim., 143 519-522. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 63 Challenges in implementing a GPU-based Monte Carlo transport code for proton dose calculations Daniel Maneval1,2 , Benoît Ozell3 and Philippe Després1,2 1 Département de radio-oncologie and Centre de recherche du CHU de Québec, Centre hospitalier universitaire de Québec, Québec, Canada Département de physique, de génie physique et d’optique and Centre de recherche sur le cancer, Université Laval, Québec, Canada 3 Département de génie informatique et génie logiciel, École polytechnique de Montréal, Montréal, Canada 2 Hadron therapy is an advanced technique of external radiation therapy. Ions have a finite path in matter and present a maximum in their energy deposition profile in their distal range called the Bragg peak. This allows a better ballistic treatment than conventional techniques with better sparing of organs at risk and healthy tissues. Currently, hadron therapy uses low Linear Energy Transfer (LET) ions such as protons or high-LET ones such as carbon ions.The most accurate dose calculations in proton therapy stem from Monte Carlo algorithms. However, their clinical implementation remains problematic due to long computation times. Recently, Graphics Processing Units (GPU) were used to significantly accelerate dose calculation algorithms in external beam radiation therapy and brachytherapy. While GPUs offer unprecedented parallel computing capabilities, implementing a Monte Carlo code on these devices remains challenging. GPUMCD was used as the foundation of this work which is a validated GPU Monte Carlo code for photons and electrons. Proton physics is currently being integrated into GPUMCD based on a class II condensed history scheme with a continuous slowing down approximation. Later, nuclear reactions will be incorporated using an empirical model. Geant4 serves as a gold standard for comparison in the work presented. Moreover, Geant4 is also used to statistically predict thread divergence and race conditions, paving the way for counteract these significant problems in GPU-based calculations.Preliminary results suggest that an optimal number of steps can be derived from the incident proton energy, that limits thread divergence. Race conditions can also be mitigated by using a position-dependant thread management. The ultimate objective of this work is to allow the clinical use of Monte Carlo methods for dose calculations in order to improve the treatment control and quality in proton therapy. Effects of the position variation of an inhomogeneous material in water using Monte Carlo simulation Guilherme Franco Inocente1 , Ana Flavia Vidotti Roder1 and Joel Mesa1 1 Instituto de Biociências de Botucatu, UNESP, Sao Paulo, Brazil Nowadays the treatment planning in radiation therapy with protons beam are done based on Computed Tomography (XCT) and Nuclear Magnetic Resonance imaging. With the treatment planning completed the patient is taken to the therapy facility and positioned such that the tumor is centered within the field of the proton beam. This step is carried out with the aid of radiography of the tumor region in order to adjust the correct positioning of the patient. Unfortunately, the high precision that can be achieved by proton can be compromised in the positioning process of the tumor within the radiation field driven radiographs. As a way to overcome this difficulty, the idea of uniting in the same equipment for proton therapy a CT system able to take the inherent characteristics of the proton beam interaction with the patient to generate the image of the region of medical interest. There is a great effort to study the feasibility of reconstructing images generated from the irradiation with proton beams, and thus reduce some inaccuracies, as it will be the same type of radiation as treatment planning, and also to drastically reduce some errors location, since the design can be done at the same site and just before where the patient is treated. The goal of this study was estimate the most like path of the proton inside a cylinder with depth 12 cm containing water and an inhomogeneity (plastic simulated bone) of 2 cm in different positions for energies between 100 MeV and 250 MeV that are the energies of radiological interest. So was calculated the behavior of the Bragg Peak and calculated the angle and lateral deflection for the proton trajectory that will allows study the impact of this results in the image reconstruction. The calculation was done with the code MCNPX and compared with an analytical calculation based on Moliere’s. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 64 Fast Monte-Carlo simulation of Cone-Beam X-ray image formation using GPUMCD Dmitri Matenine1,2 , Yves Goussard3 and Philippe Després1,2 1 Département de radio-oncologie and Centre de recherche du CHU de Québec, Centre hospitalier universitaire de Québec, Québec, Canada Département de physique, de génie physique et d’optique and Centre de recherche sur le cancer, Université Laval, Québec, Canada 3 Département de génie électrique, École Polytechnique de Montréal, Montréal, Canada 2 Purpose: X ray imaging has numerous applications in medical diagnostics and assistance in medical treatment. It is also the basis of the Computed Tomography (CT), an imaging modality which estimates the three-dimensional (3D) distribution of the subject’s radio-density. Currently, there is much interest in the development of accessible quantitative CT imaging. It requires an accurate measurement of the linear attenuation coefficients along the X-ray paths joining the radiation source and the detector. In practice, this measurement is biased in part due to the polychromaticity of the X-ray beam, and in part due to scattered photons reaching the detector. The effect of scatter is severe for wide cone-beam acquisition geometries. The current work proposes a fast Monte-Carlo photon transport code which simulates X-ray image formation by a polychromatic X-ray beam partially attenuated by a scattering medium. It may be used as a research tool for controlled simulation of the imaging process. Moreover, it may be integrated in a CT reconstruction algorithm to estimate scatter and to allow for an accurate quantitative cone-beam CT. Methods: The GPUMCD code is taken as a working basis for the development of the projection simulator. It is a fast Monte-Carlo code developed for the NVIDIA CUDA graphics processing architecture. A version called bGPUMCD simulating the transport of low-energy (1-150 keV) photons is used. It is designed to use a radio-density phantom or a CT volume as input. Certain simplifying hypotheses are used in order to accelerate simulations. Their validity will be evaluated by comparison to a more sophisticated model and an independent code (e.g. GEANT4). Photons are generated at a point source and deterministically transported at the faces of the CT volume. Inside the CT volume, Rayleigh, Compton and photoelectric interactions are simulated by Monte-Carlo. Photons exiting the volume with appropriate energy and direction are deterministically transported to the detector panel and are absorbed by the detector. Results: A source at a 120 kV potential was simulated using a spectrum with 0.5 keV energy bins. The photons propagated in a 320 × 320 × 320 water block phantom, and were absorbed by a 768 × 768 detector. The simulation initialization requires 2 min, while the photon tracking requires 10 s per billion of photons. This lets envision the integration of a scatter correction step in iterative reconstruction methods dedicated to quantitative measurements. International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 Index Šefl, M., 62 Štěpán, V., 62 Agelou, M., 33, 40 Ahnesjö, A., 35, 36 Ali, E. S. M., 12 Ambrožová, I., 62 Amer, D., 61 Arce, P., 45 Archambault, J. P., 14 Argaud, J., 60 Auer, B., 62 Autret, A., 42 Barat, E., 40 Beaulieu, L., 20, 21, 51, 59 Beauregard, J.-M., 27 Bedwani, S., 52 Bekaert, V., 62 Benabdesselam. M., 61 Benhalouche, S., 42 Benkreira, M., 40 Bert, J., 11, 24, 42 Bessières, I., 36 Bielajew, A., 17 Bol, G. H., 53 Bonenfant, É., 21 Bordy, J.-M., 36 Bouchard, H., 17, 52, 54, 55 Boussion, N., 42 Brasse, D., 62 Bäckström, G., 35 Caracappa, P., 22 Carrier, J.-F., 52 Castenada, C. M., 50 Caudrelier, J. M., 20 Celler, A., 25, 26 Chabert, I., 40 Chiavassa, S., 17 Collins Fekete, C.-A., 48, 59 Connell, T., 44 Constant, E., 60 Crijns, S. P. M., 53 Croc de Suray, A., 15, 40 Crowe, S. B., 58 Cygler, J. E., 20 Daftari, I. K., 50 Dautremer, T., 40 Davídková, M., 62 Davis, S. D., 57 De Carlan, L., 40 De Marzi, L., 60 Delorme, R., 33 Delpon, G., 17 Després, P., 21, 23, 27, 63, 64 Di Salvio, A., 52 Dias, M. F., 48, 59 Ding, G., 29 Dong, P., 43 Du, X., 22 Dubois, L., 10 El Bitar, Z., 62 El Naqa, I., 28, 41 Elleaume, H., 33 Enger, S. A., 45 Faddegon, B. A., 43, 46, 47, 49, 50 Farnsombe, T., 26 Fernandez-Varea, J. M., 35 Fournier-Bidoz, N., 60 Franchisseur, É., 61 Freud, N., 17 Gallone, J.-M., 62 Garcia-Hernandez, J.-C., 15, 36, 40 Garnier, N., 61 Garrido, E., 24 Gaudin, É., 27 Gaudreault, M., 51 Gempp, S., 40 Giantsoudi, D., 47 Giusti, V., 45 Goussard, Y., 64 Granton, P., 10 Hansen, D. C., 48, 59 Heath, E., 39 Hickling, S., 28 Hill, R., 58 Hissoiny, S., 21, 25 Incerti, S., 34, 62 Inocente, G. F., 63 Jackson, P. A., 27 Jia, X., 21 Kamio, Y., 54, 55 Karan, T., 39 Kawrakov I., 16 Kildea, J., 37 Kleijnen, J. J. E., 53 65 International Workshop on Monte Carlo Techniques in Medical Physics – Quebec City, June 17-20th 2014 Kontaxis, C., 53 Kotte, A. N. T. J., 53 Lagendijk, J. J. W., 53 Landry, G., 51 Lazaro, D., 40 Leger, P., 28 Lemaréchal, Y., 11, 24 Letellier, V., 60 Licea, A., 37 Liu, T., 22 Létang, J. M., 17 Maglieri, R., 37 Magnoux, V., 21, 23 Mainegra-Hing, E., 14, 18 Makano, S., 26 Malkov, V. N., 13 Maneval, D., 63 Martinez-Davalos, A., 29 Martinov, M., 19 Matenine, D., 64 Mazal, A., 60 McEwen, M. R., 12 McNamura, A., 47 Mesa, J., 63 Miksys N., 20 Montagu, T., 40 Montégiani, J.-F., 27 Morales, J. E., 58 Muir, B. R., 32 Nigoul, M., 40 Noblet, C., 17 O’Grady, K., 57 Ortholan, C., 61 Ozell, B., 21, 23, 63 Pachnerová Brabcová, K., 62 Paganetti, H., 45–47, 49 Papaconstadopoulos, P., 56, 57 Perl, J., 46, 47, 49 Ploc, O., 62 Polster, L., 47 Popescu, I., 39 Popescu, T., 38 Poumarède, B., 36 Pourmoghaddas, A., 26 Pradier, O., 42 Raaymakers, B. W., 53 Ramos-Méndez, J., 46, 47, 49 Renaud, M.-A., 25 Riboldi, M., 48 Rinaldi, I., 47 Rit, S., 17 Roberge, D., 25 Roder, A. F. R., 63 Rodriguez, M., 18 Rodriguez-Villafuerte, M., 29 Rogers, D. W. O., 12, 13, 18, 19, 32 Rosas-Gonzalez, S., 29 Sampson, A. J., 30 Sarrut, D., 17 Schümann, J., 46, 47, 49 Seco, J., 48, 59 Serrano, B., 61 Seuntjens, J., 25, 31, 37, 44, 56, 57 Shin, J., 46, 47, 49, 50 Smekens, F., 17 Su, L., 22 Taupin, F., 33 Tessier, F., 56 Thomson, R. M., 19, 20 Tilly, N., 35, 36 Timmins, R., 26 Townson, R. W., 22 Trani, D., 10 Trapp, J. V., 58 Trummer, M., 26 Van Asselen, B., 53 Van Hoof, S., 10 Verhaegen, F., 10, 51 Villegas, F., 36 Villeneuve, R., 61 Visvikis, D., 11, 24, 42 Walters B., 16 Watson, P., 31 Wells, G., 26 Williamson, J. F., 30 Wolthaus, J., 53 Xu, C., 20 Xu, X. G., 22 Zavgorodni, S., 22 Zlateva, Y., 41 66
