Based on previous publications on a triple Gaussian analytical pencil beam model and on Monte Carlo calculations using Monte Carlo codes GEANT-Fluka, versions 95, 98, 2002, and BEAMnrc/EGSnrc, a three-dimensional (3D) superposition/convolution algorithm for photon beams (6 MV, 18 MV) is presented. Tissue heterogeneity is taken into account by electron density information of CT images. A clinical beam consists of a superposition of divergent pencil beams. A slab-geometry was used as a phantom model to test computed results by measurements. An essential result is the existence of further dose build-up and build-down effects in the domain of density discontinuities. These effects have increasing magnitude for field sizes < or =5.5 cm(2) and densities < or = 0.25 g cm(-3), in particular with regard to field sizes considered in stereotaxy. They could be confirmed by measurements (mean standard deviation 2%). A practical impact is the dose distribution at transitions from bone to soft tissue, lung or cavities.

In this work, a novel three-dimensional superposition algorithm for photon dose calculation is presented. The dose calculation is performed as a superposition of pencil beams, which are modified based on tissue electron densities. The pencil beams have been derived from Monte Carlo simulations, and are separated into lateral and depth-directed components. The lateral component is modeled using exponential functions, which allows accurate modeling of lateral scatter in heterogeneous tissues. The depth-directed component represents the total energy deposited on each plane, which is spread out using the lateral scatter functions. Finally, convolution in the depth direction is applied to account for tissue interface effects. The method can be used with the previously introduced multiple-source model for clinical settings. The method was compared against Monte Carlo simulations in several phantoms including lung- and bone-type heterogeneities. Comparisons were made for several field sizes for 6 and 18 MV energies. The deviations were generally within (2%, 2 mm) of the field central axis d(max). Significantly larger deviations (up to 8%) were found only for the smallest field in the lung slab phantom for 18 MV. The presented method was found to be accurate in a wide range of conditions making it suitable for clinical planning purposes.

Accurate modelling of the radiation output of a medical linear accelerator is important for radiotherapy treatment planning. The major challenge is the adjustment of the model to a specific treatment unit. One approach is to use a multiple-source model containing a set of physical parameters. In this work, the parameters were derived from standard beam data measurements using optimization methods. The source model used includes sub-sources for bremsstrahlung radiation from the target, extra-focal photon radiation and electron contamination. The cost function includes a gamma error measure between measurements and current dose calculations. The procedure was applied to six beam data sets (6 MV to 23 MV) measured with accelerators from three vendors, but the results focus primarily on Varian accelerators. The obtained average gamma error (1%, 1 mm) between dose calculations and measurements used in optimization was smaller than 0.7 for each studied treatment beam and field size, and a minimum of 83% of measurement points passed the gamma < 1 criterion. For experiments made at different SSDs and for asymmetric fields, the average gamma errors were smaller than 1.1. For irregularly shaped MLC apertures, the differences in point doses were smaller than 1.0%. This work demonstrates that the source model parameters can be automatically derived from simple measurements using optimization methods. The developed procedure is applicable to a wide range of accelerators, and has an acceptable accuracy and processing time.

Purpose: To determine the parameters of a multiple‐source model for an arbitrary linear accelerator using optimization methods. Method and Materials: A multiple‐source model describing the energy fluence output of a linear accelerator was developed in this study. A point source modeled radiation from the target, a finite‐size source all extra‐focal radiation, and an electron source contaminant particles. The parameters determined were the mean energy curve (for off‐axis softening), intensity profile curve (for non‐uniform photon energy fluence), electron source values, extra‐focal source size, energy, and intensity. The parameters were optimized by minimizing the gamma error between the dose calculation results and the beam data measurements by applying a non‐linear optimization technique not requiring gradient information. The dose was calculated by an algorithm based on superposition/convolution of Monte Carlo determined scatter kernels. The beam data measurements required were depth dose curves, lateral profiles, and diagonal profiles for multiple field sizes. The model requires minimal data about the internal dimensions and construction of the accelerator head. Results: The method was applied to 231 realistic data sets of varying quality and consistency for Elekta, Siemens and Varian accelerators. The gamma error (1%, 3 mm) for an average optimized model was lower than 1.0 for 98% of the measurement points. Typical duration of the optimization to derive the model parameters was 5–15 minutes. In cases where the measurements contained inconsistencies, the resulting gamma errors were significant, which indicates that the method could be useful in quality assurance of measurement data. Conclusion: This study demonstrated that the parameters for a multiple‐source model can be determined in an efficient and stable manner using optimization methods. The model is applicable to an arbitrary accelerator and has clinically acceptable accuracy and execution time. Conflict of Interest: This work was supported by Varian Medical Systems.

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