Neutron Ambient Dose From Proton Irradiation of ICRU Tissue Calculated Via Monte Carlo Simulation
A Gearhardt*, Y Chen, S Ahmad, M Newpower, University of Oklahoma Health Sciences Center, Oklahoma City, OK
Presentations
PO-GePV-T-136 (Sunday, 7/10/2022) [Eastern Time (GMT-4)]
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Purpose: To determine the neutron dose radially and along the central axis of proton beams of two clinical energies in ICRU tissue.
Methods: The Monte Carlo toolkit TOPAS was used with the default modular physics list to simulate proton beams of 80 and 220 MeV passing through a phantom of ICRU tissue. Cylindrical detectors of 1 cm width and radial bins of 1 cm were used to score the energy dependent fluence of secondary neutrons produced from the entrance of the beam in the phantom to 10 cm beyond the Bragg peak for each energy. The energy was scored in 1 MeV bins from 0 MeV to the incident proton energy. The energy fluence spectra were used with the ambient dose coefficients reported in ICRP-74 to calculate neutron dose in each radial sector for each depth.
Results: Neutron dose for all proton energies is significantly decreased at 15 cm radially from the central axis of the proton beam. Dose is significantly decreased at a depth of 10 cm beyond the Bragg peak, even along the central axis. The fast neutron fluence peak dissipates by 15 cm radially from the central axis of the proton beam for all energies. However, the thermal neutron fluence remains relatively high for all radial distances from the proton beam.
Conclusion: Fast neutrons are produced just after the proton beam enters the phantom. The fast neutrons peak in fluence around half of the depth of the proton Bragg peak, causing a peak in neutron dose. Neutron dose generally decreases radially from the central axis of the proton beam. Future work will utilize phase spaces of beams from the Mevion s250i Hyperscan proton scanning system to evaluate neutron dose from a clinical beam.
Keywords
Taxonomy
TH- External Beam- Particle/high LET therapy: Proton therapy – computational dosimetry-Monte Carlo
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