Radiobiological quantities in proton-therapy: Estimation and validation using Geant4-based Monte Carlo simulations

Petringa, Giada; Romano, F.; Manti, Lorenzo; Pandola, L.; Attili, A.; Cammarata, Francesco Paolo; Cuttone, G.; Forte, Giusi Irma; Manganaro, L.; Pipek, J.; Pisciotta, Pietro; Russo, G.; Cirrone, G.A.P.

doi:10.1016/j.ejmp.2019.01.018

Cited by 10 publications

(12 citation statements)

References 37 publications

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“…The χ 2 test confirmed the good agreement between the two distributions even if, as expected, at doses greater than 3 Gy the differences become more evident (well above the 20%) [27]. Table XI is intended to provide a summary of the main results of the electromagnetic physics tests, subject of Section III.…”

Section: Resultssupporting

confidence: 63%

“…The v 2 test confirmed the good agreement between the two distributions even if, as expected, at doses >3 Gy the differences become more evident (well above the 20%). 27…”

Section: E2 Results and Discussionmentioning

confidence: 99%

“…Fragment production cross section (mb) Haettner et al 2013 [120] 400 MeV/u 12 C QGSP BIC HP for hadrons fragmentation yield BIC and QMD: < 25% , INCL:< 40% Hadrontherapy Petringa et al 2019 [27] Cell survival test QGSP BIC HP 62 MeV proton beam < 20% for DU145 > 20% for MDA-MB-231…”

Section: Fragment Totalmentioning

confidence: 99%

“…This test is focused on evaluating the capability of Geant4 to reproduce in‐vitro cell survival curves, also referred to as surviving fraction (SF), against experimental measurements, 120 performed at the CATANA facility radiating the radio‐responsive prostate DU145 cells and breast cancer cell line MDA‐MB‐231, 27 at 20 mm depth in water, corresponding to the mid of a clinical 62 MeV modulated clinical proton beam. The test is called Hadrontherapy in the geant‐val web interface 12…”

Section: Electromagnetic and Hadronic Physics Benchmarking Testsmentioning

confidence: 99%

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Report on G4‐Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group

et al. 2020

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Geant4 is a Monte Carlo code extensively used in medical physics for a wide range of applications, such as dosimetry, micro-and nano-dosimetry, imaging, radiation protection and nuclear medicine. Geant4 is continuously evolving, so it is crucial to have a system that benchmarks this Monte Carlo code for medical physics against reference data and to perform regression testing. To respond to these needs, we developed G4-Med, a benchmarking and regression testing system of Geant4 for medical physics, that currently includes 18 tests. They range from the benchmarking of fundamental physics quantities to the testing of Monte Carlo simulation setups typical of medical physics applications. Both electromagnetic and hadronic physics processes and models within the pre-built, Geant4 physics lists are tested. The tests included in G4-Med are executed on the CERN computing infrastructure via the use of the geant-val web application, developed at CERN for Geant4 testing. The physical observables can be compared to reference data for benchmarking and to results of previous Geant4 versions for regression testing purposes. This paper describes the tests included in G4-Med and shows the results derived from the benchmarking of Geant4 10.5 against reference data. The results presented and discussed in this paper will aid users in tailoring physics lists to their particular application.

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Section: Resultssupporting

confidence: 63%

“…The v 2 test confirmed the good agreement between the two distributions even if, as expected, at doses >3 Gy the differences become more evident (well above the 20%). 27…”

Section: E2 Results and Discussionmentioning

confidence: 99%

Section: Fragment Totalmentioning

confidence: 99%

Section: Electromagnetic and Hadronic Physics Benchmarking Testsmentioning

confidence: 99%

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Report on G4‐Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group

et al. 2020

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“…The investigation of this particular aspect, usually not considered so far, requires both experimental activity and MC simulations. This is also a theme where the importance of modeling nuclear interactions, as discussed in Section 2, is emerging [202,203].…”

Section: Future Directions and Developmentsmentioning

confidence: 99%

Challenges in Monte Carlo Simulations as Clinical and Research Tool in Particle Therapy: A Review

2020

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The use and interest in Monte Carlo (MC) techniques in the field of medical physics have been rapidly increasing in the past years. This is the case especially in particle therapy, where accurate simulations of different physics processes in complex patient geometries are crucial for a successful patient treatment and for many related research and development activities. Thanks to the detailed implementation of physics processes in any type of material, to the capability of tracking particles in 3D, and to the possibility of including the most important radiobiological effects, MC simulations have become an essential calculation tool not only for dose calculations but also for many other purposes, like the design and commissioning of novel clinical facilities, shielding and radiation protection, the commissioning of treatment planning systems, and prediction and interpretation of data for range monitoring strategies. MC simulations are starting to be more frequently used in clinical practice, especially in the form of specialized codes oriented to dose calculations that can be performed in short time. The use of general purpose MC codes is instead more devoted to research. Despite the increased use of MC simulations for patient treatments, the existing literature suggests that there are still a number of challenges to be faced in order to increase the accuracy of MC calculations for patient treatments. The goal of this review is to discuss some of these remaining challenges. Undoubtedly, it is a work for which a multidisciplinary approach is required. Here, we try to identify some of the aspects where the community involved in applied nuclear physics, radiation biophysics, and computing development can contribute to find solutions. We have selected four specific challenges: i) the development of models in MC to describe nuclear physics interactions, ii) modeling of radiobiological processes in MC simulations, iii) developments of MC-based treatment planning tools, and iv) developments of fast MC codes. For each of them, we describe the underlying problems, present selected examples of proposed solutions, and try to give recommendations for future research.

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Searching for optimized selection of Monte Carlo dose calculation parameters for scanned beam proton therapy in RayStation

Kim

Chung

Han

et al. 2023

J. Korean Phys. Soc.

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Radiobiological quantities in proton-therapy: Estimation and validation using Geant4-based Monte Carlo simulations

Cited by 10 publications

References 37 publications

Report on G4‐Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group

Report on G4‐Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group

Challenges in Monte Carlo Simulations as Clinical and Research Tool in Particle Therapy: A Review

Searching for optimized selection of Monte Carlo dose calculation parameters for scanned beam proton therapy in RayStation

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