Adaptation of GEANT4 to Monte Carlo dose calculations based on CT data.
The GEANT4 Monte Carlo code provides many powerful functions for conducting particle transport simulations with great reliability and flexibility. However, as a general purpose Monte Carlo code, not all the functions were specifically designed and fully optimized for applications in radiation therapy. One of the primary issues is the computational efficiency, which is especially critical when patient CT data have to be imported into the simulation model. In this paper we summarize the relevant aspects of the GEANT4 tracking and geometry algorithms and introduce our work on using the code to conduct dose calculations based on CT data. The emphasis is focused on modifications of the GEANT4 source code to meet the requirements for fast dose calculations. The major features include a quick voxel search algorithm, fast volume optimization, and the dynamic assignment of material density. These features are ready to be used for tracking the primary types of particles employed in radiation therapy such as photons, electrons, and heavy charged particles. Recalculation of a proton therapy treatment plan generated by a commercial treatment planning program for a paranasal sinus case is presented as an example.
Jiang
H
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Department of Radiation Oncology, Massachusetts General Hospital & Harvard Medical School, Boston, Massachusetts 02114, USA.
Paganetti
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H
D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D009010:Monte Carlo Method; D009369:Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D011874:Radiometry / Q000379:methods*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D014057:Tomography, X-Ray Computed / Q000379:methods*