When a carbon beam interacts with human tissues, many secondary fragments are produced into the tumor region and the surrounding healthy tissues. Therefore, in hadrontherapy precise dose calculations require Monte Carlo tools equipped with complex nuclear reaction models. To get realistic predictions, however, simulation codes must be validated against experimental results; the wider the dataset is, the more the models are finely tuned.Since no fragmentation data for tissue-equivalent materials at Fermi energies are available in literature, we measured secondary fragments produced by the interaction of a 55.6MeVu(-1) (12)C beam with thick muscle and cortical bone targets. Three reaction models used by the Geant4 Monte Carlo code, the Binary Light Ions Cascade, the Quantum Molecular Dynamic and the Liege Intranuclear Cascade, have been benchmarked against the collected data. In this work we present the experimental results and we discuss the predictive power of the above mentioned models.

When a carbon beam interacts with human tissues, many secondary fragments are produced into the tumor region and the surrounding healthy tissues. Therefore, in hadrontherapy precise dose calculations require Monte Carlo tools equipped with complex nuclear reaction models. To get realistic predictions, however, simulation codes must be validated against experimental results; the wider the dataset is, the more the models are finely tuned.Since no fragmentation data for tissue-equivalent materials at Fermi energies are available in literature, we measured secondary fragments produced by the interaction of a 55.6MeVu(-1) (12)C beam with thick muscle and cortical bone targets. Three reaction models used by the Geant4 Monte Carlo code, the Binary Light Ions Cascade, the Quantum Molecular Dynamic and the Liege Intranuclear Cascade, have been benchmarked against the collected data. In this work we present the experimental results and we discuss the predictive power of the above mentioned models.

Nuclear reaction measurements on tissue-equivalent materials and GEANT4 Monte Carlo simulations for hadrontherapy.

CAPPUZZELLO, FRANCESCO;MUSUMARRA, Agatino;
2014-01-01

Abstract

When a carbon beam interacts with human tissues, many secondary fragments are produced into the tumor region and the surrounding healthy tissues. Therefore, in hadrontherapy precise dose calculations require Monte Carlo tools equipped with complex nuclear reaction models. To get realistic predictions, however, simulation codes must be validated against experimental results; the wider the dataset is, the more the models are finely tuned.Since no fragmentation data for tissue-equivalent materials at Fermi energies are available in literature, we measured secondary fragments produced by the interaction of a 55.6MeVu(-1) (12)C beam with thick muscle and cortical bone targets. Three reaction models used by the Geant4 Monte Carlo code, the Binary Light Ions Cascade, the Quantum Molecular Dynamic and the Liege Intranuclear Cascade, have been benchmarked against the collected data. In this work we present the experimental results and we discuss the predictive power of the above mentioned models.
2014
When a carbon beam interacts with human tissues, many secondary fragments are produced into the tumor region and the surrounding healthy tissues. Therefore, in hadrontherapy precise dose calculations require Monte Carlo tools equipped with complex nuclear reaction models. To get realistic predictions, however, simulation codes must be validated against experimental results; the wider the dataset is, the more the models are finely tuned.Since no fragmentation data for tissue-equivalent materials at Fermi energies are available in literature, we measured secondary fragments produced by the interaction of a 55.6MeVu(-1) (12)C beam with thick muscle and cortical bone targets. Three reaction models used by the Geant4 Monte Carlo code, the Binary Light Ions Cascade, the Quantum Molecular Dynamic and the Liege Intranuclear Cascade, have been benchmarked against the collected data. In this work we present the experimental results and we discuss the predictive power of the above mentioned models.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/35231
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