| Popis: |
Monte Carlo (MC) methods are considered the gold-standard approach to dose estimation for normal tissues outside the treatment field (out-of-field) in proton therapy. However, the physics of secondary particle production from high-energy protons are uncertain, particularly for secondary neutrons, due to challenges in performing accurate measurements. Instead, various physics models have been developed over the years to reenact these high-energy interactions based on theory. It should thus be acknowledged that MC users must currently accept some unknown uncertainties in out-of-field dose estimates. In the present study, we compared three MC codes (MCNP6, PHITS, and TOPAS) and their available physics models to investigate the variation in out-of-field normal tissue dosimetry for pencil beam scanning proton therapy patients. Total yield and double-differential (energy and angle) production of two major secondary particles, neutrons and gammas, were determined through irradiation of a water phantom at six proton energies (80, 90, 100, 110, 150, and 200 MeV). Out-of-field normal tissue doses were estimated for intracranial irradiations of 1-, 5-, and 15-year-old patients using whole-body computational phantoms. Notably, the total dose estimates for each out-of-field organ varied by approximately 25% across the three codes, independent of its distance from the treatment volume. Dose discrepancies amongst the codes were linked to the utilized physics model, which impacts the characteristics of the secondary radiation field. Using developer-recommended physics, TOPAS produced both the highest neutron and gamma doses to all out-of-field organs from all examined conditions; this was linked to its highest yields of secondary particles and second hardest energy spectra. Subsequent results when using other physics models found reduced yields and energies, resulting in lower dose estimates. Neutron dose estimates were the most impacted by physics model choice, and thus the variation in out-of-field dose estimates may be even larger than 25% when considering biological effectiveness. |
