Abstract
Variance reduction techniques (VRTs) have been tremendously successful when applied to Monte Carlo radiation transport codes for which the computation time constitutes an important and a problematic parameter. In fact, many Monte Carlo calculations absolutely require variance reduction methods to achieve practical computation times. The MCNPX code has a fairly rich set of variance reduction techniques; the most known are transport cutoffs, interaction forcing, Bremsstrahlung splitting and Russian roulette. Also, the use of a phase space seems to be appropriate to reduce enormously the computing time. This work deals with the use of VRTs provided by MCNPX code for the simulation of a clinical linear electron accelerator (LINAC). Differences between various sets of VRTs are investigated. Combination between VRTs and PS is also analyzed during this study. Analysis showed that the use of VRTs and PS improve the simulation efficiency by a factor greater than 700. Finally, experimental curves of depth-dose and dose profile performed in a homogeneous water phantom are compared to dose distributions computed by use of MCNPX Monte Carlo code.
Highlights
IntroductionMonte Carlo (MC) methods are considered to provide the best calculation engine available today in medical radiation physics [1,2]
Monte Carlo (MC) methods are considered to provide the best calculation engine available today in medical radiation physics [1,2].The Monte Carlo method is, by its nature, very time consuming which constitutes the main disadvantage to their use in radiotherapy
Photon Energy Spectra As a very good agreement has been obtained between calculation and measurement for depth dose and dose profile curves, we propose a computed photon spectrum that could be simulated by use of MCNPX code and our model of linac head
Summary
Monte Carlo (MC) methods are considered to provide the best calculation engine available today in medical radiation physics [1,2]. The Monte Carlo method is, by its nature, very time consuming which constitutes the main disadvantage to their use in radiotherapy. The computation time depends on the number of particles generated, their energy, their type and the medium in which they are transported. To obtain good statistics it is required to track hundreds or thousands of millions of particles. The development of advanced computers with special capabilities for parallel calculations has opened new issues for Monte Carlo researchers. Parallel computers are becoming increasingly accessible to medical physicists. For many medical applications this is not enough, because CPU time is still large [3,4]
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