Open AccessA phase space model of a Versa HD linear accelerator for application to Monte Carlo dose calculation in a real‐time adaptive workflow
Author(s) -
Bedford James L.,
Nilawar Rahul,
Nill Simeon,
Oelfke Uwe
Publication year - 2022
Publication title -
journal of applied clinical medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.83
H-Index - 48
ISSN - 1526-9914
DOI - 10.1002/acm2.13663
Subject(s) - monte carlo method , linear particle accelerator , imaging phantom , phase space , physics , radiation treatment planning , computational physics , photon , computer science , medical physics , simulation , optics , mathematics , beam (structure) , statistics , radiation therapy , medicine , thermodynamics
Abstract Purpose This study aims to develop and validate a simple geometric model of the accelerator head, from which a particle phase space can be calculated for application to fast Monte Carlo dose calculation in real‐time adaptive photon radiotherapy. With this objective in view, the study investigates whether the phase space model can facilitate dose calculations which are compatible with those of a commercial treatment planning system, for convenient interoperability. Materials and methods A dual‐source model of the head of a Versa HD accelerator (Elekta AB, Stockholm, Sweden) was created. The model used parameters chosen to be compatible with those of 6‐MV flattened and 6‐MV flattening filter‐free photon beams in the RayStation treatment planning system (RaySearch Laboratories, Stockholm, Sweden). The phase space model was used to calculate a photon phase space for several treatment plans, and the resulting phase space was applied to the Dose Planning Method (DPM) Monte Carlo dose calculation algorithm. Simple fields and intensity‐modulated radiation therapy (IMRT) treatment plans for prostate and lung were calculated for benchmarking purposes and compared with the convolution‐superposition dose calculation within RayStation. Results For simple square fields in a water phantom, the calculated dose distribution agrees to within ±2% with that from the commercial treatment planning system, except in the buildup region, where the DPM code does not model the electron contamination. For IMRT plans of prostate and lung, agreements of ±2% and ±6%, respectively, are found, with slightly larger differences in the high dose gradients. Conclusions The phase space model presented allows convenient calculation of a phase space for application to Monte Carlo dose calculation, with straightforward translation of beam parameters from the RayStation beam model. This provides a basis on which to develop dose calculation in a real‐time adaptive setting.