A multiple source model for 6 MV photon beam dose calculations using Monte Carlo

Abstract

A multiple source model (MSM) for the 6 MV beam of a Varian Clinac 2300 C/D was developed by simulating radiation transport through the accelerator head for a set of square fields using the GEANT Monte Carlo (MC) code. The corresponding phase space (PS) data enabled the characterization of 12 sources representing the main components of the beam defining system. By parametrizing the source characteristics and by evaluating the dependence of the parameters on field size, it was possible to extend the validity of the model to arbitrary rectangular fields which include the central 3 x 3 cm2 field without additional precalculated PS data. Finally, a sampling procedure was developed in order to reproduce the PS data. To validate the MSM, the fluence, energy fluence and mean energy distributions determined from the original and the reproduced PS data were compared and showed very good agreement. In addition, the MC calculated primary energy spectrum was verified by an energy spectrum derived from transmission measurements. Comparisons of MC calculated depth dose curves and profiles, using original and PS data reproduced by the MSM, agree within 1% and 1 mm. Deviations from measured dose distributions are within 1.5% and 1 mm. However, the real beam leads to some larger deviations outside the geometrical beam area for large fields. Calculated output factors in 10 cm water depth agree within 1.5% with experimentally determined data. In conclusion, the MSM produces accurate PS data for MC photon dose calculations for the rectangular fields specified.

A Monte Carlo study of a flattening filter-free linear accelerator verified with measurements

“…The filter is a major contributor of scattered radiation in the treatment head (Chaney et al 1994, Fix et al 2001 and can lead to higher doses outside the treatment field , Kry et al 2010, O'Brien et al 1991.. Due to the non-uniform shape of the flattening filter, the beam energy distribution will vary with off-axis distance, creating challenges for dose calculation algorithms. One way of removing these unfavourable properties of conventional clinical radiation beams would be to remove the flattening filter.…”

Monte Carlo source model for photon beam radiotherapy: photon source characteristics

“…3,4,[21][22][23] It has been shown that if the electron beam above the target is modeled accurately and the particles are accurately transported through the beam-generating devices to the PS plane, the dose calculation using that PS file is able to match measured dose. 9,16,18,23,24,[36][37][38] One limitation of directly using the PS file is the lack of flexibility to adjust the data for use with accelerators with slightly different outputs. A second limitation is the introduction of a systematic error, termed latent or remnant variance, as recently mentioned by Sichani and Sohrabpour 25 and Fippel et al 34 and described in detail by Sempau et al 39 This systematic error is due to the limited size of the PS file, which results in a finite variance for a calculated quantity, e.g., dose, using a finite-sized PS file as input.…”

“…Apart form using analytical source models or the PS file itself as a source model, another approach, which overcomes these limitations, is to create a histogram-based source model based on the PSD. 8,[12][13][14][15][16][17] By sampling the initial parameters of a particle from these histogram distributions, virtually no particle is reused, thereby reducing the latent variance. A further advantage of histogram-based source models is that the sampling is faster than reading particles from a PS file.…”

“…Previously developed histogram-based source models are closely related to the underlying accelerator. 8,[15][16][17] These source models reconstruct the photon beam below the secondary collimator, i.e., they make use of information about the collimator jaws. Therefore, it will be difficult to use such models if, for example, one pair of jaws is replaced by a multileaf collimator.…”

“…This benchmark allows investigating the shape of the dose distribution for each individual source, e.g., the change in depth for the dose maximum for each subsource, compared with other published studies in which the total dose distribution is shown. 11,12,[15][16][17]20 Furthermore, the subsource dose characterization has the potential to ease the commissioning procedure, since information about which subsource needs to be tuned can be obtained by comparing measured dose distributions with those calculated for the individual sources. Dose distribution comparisons are performed for SSDs of 50, 75, 100, and 200 cm to validate the source model for a large range of conditions.…”