Volume 48, Number 3, Juillet-Septembre 2013
|Page(s)||317 - 339|
|Published online||19 March 2013|
Monte Carlo simulation of a proton therapy beamline for intracranial treatments
IRSN, Laboratoire de Dosimétrie des Rayonnements Ionisants,
PRP-HOM/SDE/LDRI - BP17, 92262
2 Centre Antoine Lacassagne (CAL) - Cyclotron biomédical, 227 avenue de la Lanterne, 06200 Nice, France
3 Institut Curie – Centre de Protonthérapie d’Orsay (ICPO) - Campus universitaire bâtiment 101, 91898 Orsay, France
4 IBA, 1348 Louvain-la-Neuve, Belgium
Accepted: 19 December 2012
A radiation transport code based on a Monte Carlo tool is used to simulate a proton therapy beamline designed to treat paediatric patients with intracranial tumours. The treatments are performed using the IBA gantry at the Proton Therapy Centre of the Institut Curie. The treatment is undertaken at 178.16 MeV using the double scattering technique. The aim of this study is to present the Monte Carlo model of the transported proton beam, beamline and treatment room, as well as the experimental validation of the proton dose distributions calculated by this model. The beamline components and the treatment room are accurately modelled using the Monte Carlo code MCNPX. The proton source at the beamline entrance is defined on the basis of IBA data, measurements and calculations. Measured and calculated relative proton dose distributions in a water phantom are compared for the validation. Depth dose profiles, including pristine Bragg peaks and a spread–out Bragg peak, and lateral dose profiles are studied. A general good agreement was found between calculated and measured distributions with discrepancies of less than 2 mm. Relative proton dose distributions are therefore considered to be correctly described by our simulated geometry and proton source parameters. The Monte Carlo simulation will be used subsequently for radiation protection purposes: calculation of secondary neutron doses received by treated patients of different ages.
Key words: proton therapy / dosimetry / Monte Carlo
© EDP Sciences, 2013
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