Ant colony algorithm implementation in electron and photon Monte Carlo transport: application to the commissioning of radiosurgery photon beams.
OBJECTIVE
In this work, the authors describe an approach which has been developed to drive the application of different variance-reduction techniques to the Monte Carlo simulation of photon and electron transport in clinical accelerators.


METHODS
The new approach considers the following techniques: Russian roulette, splitting, a modified version of the directional bremsstrahlung splitting, and the azimuthal particle redistribution. Their application is controlled by an ant colony algorithm based on an importance map.


RESULTS
The procedure has been applied to radiosurgery beams. Specifically, the authors have calculated depth-dose profiles, off-axis ratios, and output factors, quantities usually considered in the commissioning of these beams. The agreement between Monte Carlo results and the corresponding measurements is within approximately 3%/0.3 mm for the central axis percentage depth dose and the dose profiles. The importance map generated in the calculation can be used to discuss simulation details in the different parts of the geometry in a simple way. The simulation CPU times are comparable to those needed within other approaches common in this field.


CONCLUSIONS
The new approach is competitive with those previously used in this kind of problems (PSF generation or source models) and has some practical advantages that make it to be a good tool to simulate the radiation transport in problems where the quantities of interest are difficult to obtain because of low statistics.
García-Pareja
S
S
Servicio de Radiofísica Hospitalaria, Hospital Regional Universitario Carlos Haya, Avda. Carlos Haya s/n, E-29010 Málaga, Spain.
Galán
P
P
Manzano
F
F
Brualla
L
L
Lallena
A M
AM
D000465:Algorithms; D000818:Animals; D001000:Ants; D004583:Electrons; D009010:Monte Carlo Method; D017785:Photons / Q000627:therapeutic use*; D011829:Radiation Dosage; D016634:Radiosurgery; D013997:Time Factors