Abstract

This work presents the CPU implementation of GMC ['gimik]: a fast yet accurate one-variable Monte Carlo dose algorithm for proton therapy to be incorporated into our in-house treatment planning system, Astroid. GMC is based on a simple mathematical model using the formulated proton scattering power and tabulated data of empirical depth-dose distributions. These Bragg peaks determine the energy deposited along the particle's track. The polar scattering angle is based on the particle's local energy and the voxel's density, while the azimuthal component of that scattering angle is the single variable in GMC, uniformly distributed from 0 to 2π. The halo effect of the beam, currently not implemented, will consider large scattering angles and secondary protons for a small percentage of the incident histories. GMC shows strong agreement with both the empirical data and GEANT4-based simulations. Its current CPU implementation runs at ~300 m.s−-1, approximately ten times faster than GEANT4. Significant speed improvement is expected with the upcoming implementation of multi-threading and the portage to the GPU architecture. In conclusion, a one-variable Monte Carlo dose algorithm was produced for proton therapy dose computations. Its simplicity allows for fast dose computation while conserving accuracy against heterogeneities, hence drastically improving the current algorithms used in treatment planning systems.

Details

Title
GMC ['gimik]: a one-variable Monte Carlo dose algorithm for proton therapy
Author
Depauw, N 1 ; Clasie, B 2 ; Madden, T 2 ; Rosenfeld, A 3 ; Kooy, H 2 

 Francis H. Burr Proton Therapy Center, Department of Radiation Oncology, Massachusetts General Hospital (MGH), Boston MA 02114, USA; Centre for Medical Radiation Physics, University of Wollongong, Australia 
 Francis H. Burr Proton Therapy Center, Department of Radiation Oncology, Massachusetts General Hospital (MGH), Boston MA 02114, USA 
 Centre for Medical Radiation Physics, University of Wollongong, Australia 
Publication year
2014
Publication date
Mar 2014
Publisher
IOP Publishing
ISSN
17426588
e-ISSN
17426596
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2576602534
Copyright
© 2014. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.