Design of a Boron Neutron Capture Enhanced Fast Neutron Therapy Assembly
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A boron neutron capture enhanced fast neutron therapy assembly has been designed for the Fermilab Neutron Therapy Facility (NTF). This assembly uses a tungsten filter and collimator near the patient¡¯s head, with a graphite reflector surrounding the head to significantly increase the dose due to boron neutron capture reactions. The assembly was designed using Monte Carlo radiation transport code MCNP version 5 for a standard 20x20 cm2 treatment beam. The calculated boron dose enhancement at 5.7-cm depth in a water-filled head phantom in the assembly with a 5x5 cm2 collimation was 21.9% per 100-ppm B-10 for a 5.0-cm tungsten filter and 29.8% for an 8.5-cm tungsten filter. The corresponding dose rate for the 5.0-cm and 8.5-cm thick filters were 0.221 and 0.127 Gy/min, respectively. To validate the design calculations, a simplified BNCEFNT assembly was built using four lead bricks to form a 5x5 cm2 collimator. Five 1.0-cm thick 20x20 cm2 tungsten plates were used to obtain different filter thicknesses and graphite bricks/blocks were used to form a reflector. Measurements of the dose enhancement of the simplified assembly in a water-filled head phantom were performed using a pair of tissue-equivalent ion chambers. One of the ion chambers is loaded with 1000-ppm natural boron (184-ppm 10B) to measure dose due to boron neutron capture. The measured dose enhancement at 5.0-cm depth in the head phantom for the 5.0-cm thick tungsten filter is (16.6 ¡À 1.8)%, which agrees well with the MCNP simulation of the simplified BNCEFNT assembly, (16.4¡À 0.5)%. The error in the calculated dose enhancement only considers the statistical uncertainties. The total dose rate measured at 5.0-cm depth using the non-borated ion chamber is (0.765 ¡À 0.076) Gy/MU, about 61% of the fast neutron standard dose rate (1.255Gy/MU) at 5.0-cm depth for the standard 10x10 cm2 treatment beam. The increased doses to other organs due to the use of the BNCEFNT assembly were calculated using MCNP5 and a MIRD phantom.