José Ramos-Méndez1, Wook-Geun Shin2,3, Mathieu Karamitros4, Jorge Domínguez-Kondo5, Ngoc Hoang Tran2, Sebastien Incerti2, Carmen Villagrasa6, Yann Perrot6, Václav Štěpán7, Shogo Okada8, Eduardo Moreno-Barbosa5, Bruce Faddegon1. 1. Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, 94115, USA. 2. Centre d'Études Nucléaires de Bordeaux Gradignan, Université de Bordeaux, CNRS/IN2P3, UMR5797, Gradignan, 33175, France. 3. Department of Radiation Convergence Engineering, Yonsei University, Wonju, 26493, Korea. 4. Radiation Laboratory, University of Notre Dame, Notre Dame, IN, 46556, USA. 5. Facultad de Ciencias Físico Matemáticas, Benemérita Universidad Autónoma de Puebla, Puebla PUE, 72000, Mexico. 6. Institut de Radioprotection et de Sûreté Nucléaire, IRSN, BP17, Fontenay-aux-Roses, 92262, France. 7. Department of Radiation Dosimetry, Nuclear Physics Institute of the CAS, Prague, Czech Republic. 8. KEK, 1-1, Oho, Tsukuba, Ibaraki, 305-0801, Japan.
Abstract
PURPOSE: The simulation of individual particle tracks and the chemical stage following water radiolysis in biological tissue is an effective means of improving our knowledge of the physico-chemical contribution to the biological effect of ionizing radiation. However, the step-by-step simulation of the reaction kinetics of radiolytic species is the most time-consuming task in Monte Carlo track-structure simulations, with long simulation times that are an impediment to research. In this work, we present the implementation of the independent reaction times (IRT) method in Geant4-DNA Monte Carlo toolkit to improve the computational efficiency of calculating G-values, defined as the number of chemical species created or lost per 100 eV of deposited energy. METHODS: The computational efficiency of IRT, as implemented, is compared to that from available Geant4-DNA step-by-step simulations for electrons, protons and alpha particles covering a wide range of linear energy transfer (LET). The accuracy of both methods is verified using published measured data from fast electron irradiations for • OH and e aq - for time-dependent G-values. For IRT, simulations in the presence of scavengers irradiated by cobalt-60 γ-ray and 2 MeV protons are compared with measured data for different scavenging capacities. In addition, a qualitative assessment comparing measured LET-dependent G-values with Geant4-DNA calculations in pure liquid water is presented. RESULTS: The IRT improved the computational efficiency by three orders of magnitude relative to the step-by-step method while differences in G-values by 3.9% at 1 μs were found. At 7 ps, • OH and e aq - yields calculated with IRT differed from recent published measured data by 5% ± 4% and 2% ± 4%, respectively. At 1 μs, differences were 9% ± 5% and 6% ± 7% for • OH and e aq - , respectively. Uncertainties are one standard deviation. Finally, G-values at different scavenging capacities and LET-dependent G-values reproduced the behavior of measurements for all radiation qualities. CONCLUSION: The comprehensive validation of the Geant4-DNA capabilities to accurately simulate the chemistry following water radiolysis is an ongoing work. The implementation presented in this work is a necessary step to facilitate performing such a task.
PURPOSE: The simulation of individual particle tracks and the chemical stage following water radiolysis in biological tissue is an effective means of improving our knowledge of the physico-chemical contribution to the biological effect of ionizing radiation. However, the step-by-step simulation of the reaction kinetics of radiolytic species is the most time-consuming task in Monte Carlo track-structure simulations, with long simulation times that are an impediment to research. In this work, we present the implementation of the independent reaction times (IRT) method in Geant4-DNA Monte Carlo toolkit to improve the computational efficiency of calculating G-values, defined as the number of chemical species created or lost per 100 eV of deposited energy. METHODS: The computational efficiency of IRT, as implemented, is compared to that from available Geant4-DNA step-by-step simulations for electrons, protons and alpha particles covering a wide range of linear energy transfer (LET). The accuracy of both methods is verified using published measured data from fast electron irradiations for • OH and e aq - for time-dependent G-values. For IRT, simulations in the presence of scavengers irradiated by cobalt-60 γ-ray and 2 MeV protons are compared with measured data for different scavenging capacities. In addition, a qualitative assessment comparing measured LET-dependent G-values with Geant4-DNA calculations in pure liquid water is presented. RESULTS: The IRT improved the computational efficiency by three orders of magnitude relative to the step-by-step method while differences in G-values by 3.9% at 1 μs were found. At 7 ps, • OH and e aq - yields calculated with IRT differed from recent published measured data by 5% ± 4% and 2% ± 4%, respectively. At 1 μs, differences were 9% ± 5% and 6% ± 7% for • OH and e aq - , respectively. Uncertainties are one standard deviation. Finally, G-values at different scavenging capacities and LET-dependent G-values reproduced the behavior of measurements for all radiation qualities. CONCLUSION: The comprehensive validation of the Geant4-DNA capabilities to accurately simulate the chemistry following water radiolysis is an ongoing work. The implementation presented in this work is a necessary step to facilitate performing such a task.
Authors: Dousatsu Sakata; Nathanael Lampe; Mathieu Karamitros; Ioanna Kyriakou; Oleg Belov; Mario A Bernal; David Bolst; Marie-Claude Bordage; Vincent Breton; Jeremy M C Brown; Ziad Francis; Vladimir Ivanchenko; Sylvain Meylan; Koichi Murakami; Shogo Okada; Ivan Petrovic; Aleksandra Ristic-Fira; Giovanni Santin; David Sarramia; Takashi Sasaki; Wook-Geun Shin; Nicolas Tang; Hoang N Tran; Carmen Villagrasa; Dimitris Emfietzoglou; Petteri Nieminen; Susanna Guatelli; Sebastien Incerti Journal: Phys Med Date: 2019-05-17 Impact factor: 2.685
Authors: José Ramos-Méndez; Lucas N Burigo; Reinhard Schulte; Cynthia Chuang; Bruce Faddegon Journal: Phys Med Biol Date: 2018-11-28 Impact factor: 3.609
Authors: J Ramos-Méndez; J A LaVerne; N Domínguez-Kondo; J Milligan; V Štěpán; K Stefanová; Y Perrot; C Villagrasa; W-G Shin; S Incerti; A McNamara; H Paganetti; J Perl; J Schuemann; B Faddegon Journal: Phys Med Biol Date: 2021-09-03 Impact factor: 4.174