Purpose: Patients who receive proton-beam therapy are exposed to unwanted stray neutrons. Stray radiations increase the risk of late effects in normal tissues, such as second cancers and cataracts, and may cause implanted devices such as pacemakers to malfunction. Compared to therapeutic beams, little attention has been paid to modeling stray neutron exposures. In the past decade, substantial progress was made to develop semi-empirical models of stray neutron dose equivalent, but models to routinely calculate neutron absorbed dose and kerma are still lacking. The objective of this work was to develop a new physics-based analytical model to calculate neutron spectral fluence, kerma, and absorbed dose in a water phantom.
Methods: We developed the model using dosimetric data from Monte Carlo simulations and neutron kerma coefficients from the literature. The model explicitly considers the production, divergence, scattering, and attenuation of neutrons. Neutron production was modeled 120 MeV to 250 MeV proton beams impinging on a variety of materials. Fluence, kerma and dose calculations were performed in a 30 x 180 x 44 cm3 phantom at points up to 43 cm in depth and 80 cm laterally.
Results: Predictions of the analytical model agreed reasonably with corresponding values from Monte Carlo simulations, with a mean difference in average energy deposited of 20%, average kerma coefficient of 21%, and absorbed dose to water of 49%.
Conclusion: The analytical model is simple to implement and use, requires less configuration data that previously reported models, and is computationally fast. Our uncertainty in predicted absorbed dose is about a factor of 10 larger outside the treatment field than inside, i.e., from measurements or treatment planning calculations. This reflects the historical difficulty of predicting stray dose, e.g., despite nearly two decades of research, clinical treatment planning systems still neglect stray radiation.
Modeling, Radiation Dosimetry, Protons
TH- External Beam- Particle/high LET therapy: Neutron computational dosimetry