9 March 2017 Monte Carlo investigation of backscatter point spread function for x-ray imaging examinations
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Abstract
X-ray imaging examinations, especially complex interventions, may result in relatively high doses to the patient’s skin inducing skin injuries. A method was developed to determine the skin-dose distribution for non-uniform x-ray beams by convolving the backscatter point-spread-function (PSF) with the primary-dose distribution to generate the backscatter distribution that, when added to the primary dose, gives the total-dose distribution. This technique was incorporated in the dose-tracking system (DTS), which provides a real-time color-coded 3D-mapping of skin dose during fluoroscopic procedures. The aim of this work is to investigate the variation of the backscatter PSF with different parameters. A backscatter PSF of a 1-mm x-ray beam was generated by EGSnrc Monte-Carlo code for different x-ray beam energies, different soft-tissue thickness above bone, different bone thickness and different entrance-beam angles, as well as for different locations on the SK-150 anthropomorphic head phantom. The results show a reduction of the peak scatter to primary dose ratio of 48% when X-ray beam voltage is increased from 40 keV to 120 keV. The backscatter dose was reduced when bone was beneath the soft tissue layer and this reduction increased with thinner soft tissue and thicker bone layers. The backscatter factor increased about 21% as the angle of incidence of the beam with the entrance surface decreased from 90° (perpendicular) to 30°. The backscatter PSF differed for different locations on the SK-150 phantom by up to 15%. The results of this study can be used to improve the accuracy of dose calculation when using PSF convolution in the DTS.
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Zhenyu Xiong, Zhenyu Xiong, Sarath Vijayan, Sarath Vijayan, Stephen Rudin, Stephen Rudin, Daniel R. Bednarek, Daniel R. Bednarek, } "Monte Carlo investigation of backscatter point spread function for x-ray imaging examinations ", Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 1013243 (9 March 2017); doi: 10.1117/12.2254064; https://doi.org/10.1117/12.2254064
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