Monte Carlo evaluation of a photon pencil kernel algorithm applied to fast neutron therapy treatment planning
2003 (English)In: Physics in Medicine and Biology, ISSN 0031-9155 (print) 1361-6560 (online), Vol. 48, no 20, 3327-3344 p.Article in journal (Refereed) Published
When dedicated software is lacking, treatment planning for fast neutron therapy is sometimes performed using dose calculation algorithms designed for photon beam therapy. In this work Monte Carlo derived neutron pencil kernels in water were parametrized using the photon dose algorithm implemented in the Nucletron TMS (treatment management system) treatment planning system. A rectangular fast-neutron fluence spectrum with energies 0–40 MeV (resembling a polyethylene filtered p(41)+ Be spectrum) was used. Central axis depth doses and lateral dose distributions were calculated and compared with the corresponding dose distributions from Monte Carlo calculations for homogeneous water and heterogeneous slab phantoms. All absorbed doses were normalized to the reference dose at 10 cm depth for a field of radius 5.6 cm in a 30 × 40 × 20 cm3 water test phantom. Agreement to within 7% was found in both the lateral and the depth dose distributions. The deviations could be explained as due to differences in size between the test phantom and that used in deriving the pencil kernel (radius 200 cm, thickness 50 cm). In the heterogeneous phantom, the TMS, with a directly applied neutron pencil kernel, and Monte Carlo calculated absorbed doses agree approximately for muscle but show large deviations for media such as adipose or bone. For the latter media, agreement was substantially improved by correcting the absorbed doses calculated in TMS with the neutron kerma factor ratio and the stopping power ratio between tissue and water. The multipurpose Monte Carlo code FLUKA was used both in calculating the pencil kernel and in direct calculations of absorbed dose in the phantom.
Place, publisher, year, edition, pages
2003. Vol. 48, no 20, 3327-3344 p.
Medical and Health Sciences
IdentifiersURN: urn:nbn:se:liu:diva-14361DOI: 10.1088/0031-9155/48/20/005OAI: oai:DiVA.org:liu-14361DiVA: diva2:23331