Monte Carlo investigation of backscatter point spread function for x-ray imaging examinations

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.

[1]  S Rudin,et al.  SU-E-CAMPUS-I-04: Automatic Skin-Dose Mapping for An Angiographic System with a Region-Of-Interest, High-Resolution Detector. , 2014, Medical physics.

[2]  Daniel R. Bednarek,et al.  A system to track skin dose for neuro-interventional cone-beam computed tomography (CBCT) , 2016, SPIE Medical Imaging.

[3]  Daniel R. Bednarek,et al.  Integration of kerma-area product and cumulative air kerma determination into a skin dose tracking system for fluoroscopic imaging procedures , 2016, SPIE Medical Imaging.

[4]  C. Martin.  Measurement of patient entrance surface dose rates for fluoroscopic x-ray units. , 1995, Physics in medicine and biology.

[5]  Stephen Rudin,et al.  Incorporating corrections for the head-holder and compensation filter when calculating skin dose during fluoroscopically guided interventions , 2015, Medical Imaging.

[6]  N Petoussi-Henss,et al.  Calculation of backscatter factors for diagnostic radiology using Monte Carlo methods. , 1998, Physics in medicine and biology.

[7]  Stephen Rudin,et al.  Skin dose mapping for non-uniform x-ray fields using a backscatter point spread function , 2017, Medical Imaging.

[8]  S Rudin,et al.  Clinical application of region-of-interest techniques to radiologic imaging. , 1996, Radiographics : a review publication of the Radiological Society of North America, Inc.

[9]  Stephen Rudin,et al.  Verification of the performance accuracy of a real-time skin-dose tracking system for interventional fluoroscopic procedures , 2011, Medical Imaging.

[10]  Daniel R. Bednarek,et al.  TH‐AB‐201‐01: A Real‐Time Skin‐Dose Mapping System for Region‐Of‐Interest (ROI) Fluoroscopy , 2015 .

[11]  S Rudin,et al.  A tracking system to calculate patient skin dose in real-time during neurointerventional procedures using a biplane x-ray imaging system. , 2016, Medical physics.

[12]  S Rudin,et al.  TU-D-209-02: A Backscatter Point Spread Function for Entrance Skin Dose Determination. , 2016, Medical physics.

[13]  Hugo Bouchard,et al.  Backscatter factors and mass energy-absorption coefficient ratios for diagnostic radiology dosimetry , 2011, Physics in medicine and biology.

[14]  Stephen Rudin,et al.  Lens of the eye dose calculation for neuro-interventional procedures and CBCT scans of the head , 2016, SPIE Medical Imaging.

[15]  Daniel R. Bednarek,et al.  MO-F-CAMPUS-I-01: A System for Automatically Calculating Organ and Effective Dose for Fluoroscopically-Guided Procedures , 2015 .

[16]  S Rudin,et al.  Region of interest fluoroscopy. , 1992, Medical physics.