A virtual source model for Kilo‐voltage cone beam CT: Source characteristics and model validation

Abstract

The purpose of this investigation was to study the source characteristics of a clinical kilo-voltage cone beam CT unit and to develop and validate a virtual source model that could be used for treatment planning purposes. We used a previously commissioned full Monte Carlo model and new bespoke software to study the source characteristics of a clinical kilo-voltage cone beam CT (CBCT) unit. We identified the main particle sources, their spatial, energy and angular distribution for all the image acquisition presets currently used in our clinical practice. This includes a combination of two energies (100 and 120 kVp), two filters (neutral and bowtie), and eight different x-ray beam apertures. We subsequently built a virtual source model which we validated against full Monte Carlo calculations. We found that the radiation output of the clinical kilo-voltage cone beam CT unit investigated in this study could be reproduced with a virtual model comprising of two sources (target and filtration cone) or three sources (target, filtration cone and bowtie filter) when additional filtration was used. With this model, we accounted for more than 97% of the photons exiting the unit. Each source in our model was characterised by a origin distribution in both X and Y directions, a fluence map, a single energy spectrum for unfiltered beams and a two dimensional energy spectrum for bowtie filtered beams. The percentage dose difference between full Monte Carlo and virtual source model based dose distributions was well within the statistical uncertainty associated with the calculations ( ± 2%, one standard deviation) in all cases studied. The virtual source that we developed is accurate in calculating the dose delivered from a commercial kilo-voltage cone beam CT unit operating with routine clinical image acquisition settings. Our data have also shown that target, filtration cone, and bowtie filter sources needed to be all included in the model in order to accurately replicate the dose distribution from the clinical radiation beam.