Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
권호 표지
DOI QR코드

DOI QR Code

Development and verification of a novel system for computed tomography scanner model construction in Monte Carlo simulations

  • Ying Liu (School of Health Science and Engineering, University of Shanghai for Science and Technology) ;
  • Ting Meng (School of Health Science and Engineering, University of Shanghai for Science and Technology) ;
  • Haowei Zhang (School of Health Science and Engineering, University of Shanghai for Science and Technology) ;
  • Qi Su (Department of Medical Equipment, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University) ;
  • Hao Yan (Department of Medical Equipment, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University) ;
  • Heqing Lu (Department of Medical Equipment, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University)
  • Received : 2021.07.21
  • Accepted : 2022.07.04
  • Published : 2022.11.25
Download PDF
⟨ Previous Next ⟩

Abstract

The accuracy of Monte Carlo (MC) simulations in estimating the computed tomography radiation dose is highly dependent on the accuracy of CT scanner model. A system was developed to observe the 3D model intuitively and to calculate the X-ray energy spectrum and the bowtie (BT) filter model more accurately in Monte Carlo N-particle (MCNP). Labview's built-in Open Graphics Library (OpenGL) was used to display basic surfaces, and constructive solid geometry (CSG) method was used to realize Boolean operations. The energy spectrum was calculated by simulating the process of electronic shooting and the BT filter model was accurately modeled based on the calculated shape curve. Physical data from a study was used as an example to illustrate the accuracy of the constructed model. RMSE between the simulation and the measurement results were 0.97% and 0.74% for two filters of different shapes. It can be seen from the comparison results that to obtain an accurate CT scanner model, physical measurements should be taken as the standard. The energy spectrum library should be established based on Monte Carlo simulations with modifiable input files. It is necessary to use the three-segment splicing modeling method to construct the bowtie filter model.

Keywords

Acknowledgement

This work was supported by the National Natural Science Foundation of China (No. 82073474) and the Planning Project of Shanghai Science and Technology (No. 21S31902100). We would like to thank Weihai Zhuo and Haikuan Liu (Institute of Radiation Medicine, Fudan University, Shanghai, China) for their suggestions with regard to writing.

References

  1. F.B. Brown, MCNPdA General Monte Carlo N-Particle Transport Code, Version 5, LA-UR-03-1987, Los Alamos, Los Alamos National Laboratory, 2003. 
  2. X Monte Carlo Team, MCNP - A General Monte Carlo N-Particle Transport Code, Version 5,Volume II: User's Guide, Los Alamos National Laboratory, Los Alamos, NM, 2003. 
  3. G. Jarry, J.J. DeMarco, U. Beifuss, C.H. Cagnon, M.F. McNittGray, A Monte Carlo-based method to estimate radiation dose from spiral CT: from phantom testing to patient-specific models, Phys. Med. Biol. 48 (2003) 2645-2663.  https://doi.org/10.1088/0031-9155/48/16/306
  4. A.C. Turner, D. Zhang, H.J. Kim, J.J. DeMarco, C.H. Cagnon, E. Angel, D.D. Cody, D.M. Stevens, A.N. Primak, C.H. McCollough, M.F. McNitt-Gray, A method to generate equivalent energy spectra and filtration models based on measurement for multidetector CT Monte Carlo dosimetry simulations, Med. Phys. 36 (2009) 2154-2164.  https://doi.org/10.1118/1.3117683
  5. J.W. Gu, B. Bednarz, X.G. Xu, S.B. Jiang, Assessment of patient organ doses and effective doses using the VIP-Man adult male phantom for selected conebeam CT imaging procedures during image guided radiation therapy, Radiat. Protect. Dosim. 131 (2008) 431-443.  https://doi.org/10.1093/rpd/ncn200
  6. C. Lee, K.P. Kim, D. Long, R. Fisher, C. Tien, S.L. Simon, A. Bouville, W.E. Bolch, Organ doses for reference adult male and female undergoing computed tomography estimated by Monte Carlo simulations, Med. Phys. 38 (2011) 1196-1206.  https://doi.org/10.1118/1.3544658
  7. S.E. McKenney, A. Nosratieh, D. Gelskey, K. Yang, S.Y. Huang, L. Chen, J.M. Boone, Experimental validation of a method characterizing bowtie filters in CT scanners using a real-time dose probe, Med. Phys. 38 (2011) 1406-1415.  https://doi.org/10.1118/1.3551990
  8. K. McMillan, M. McNitt-Gray, D. Ruan, Development and validation of a measurement-based source model for kilovoltage cone-beam CT Monte Carlo dosimetry simulations, Med. Phys. 40 (2013), 111907. 
  9. A.P. Colijn, W. Zbijewski, A. Sasov, F.J. Beekman, Experimental validation of a rapid Monte Carlo based micro-CT simulator, Phys. Med. Biol. 49 (2004) 4321-4333.  https://doi.org/10.1088/0031-9155/49/18/009
  10. M. Randazzo, M. Tambasco, A rapid noninvasive characterization of CT x-ray sources, Med. Phys. 42 (2015) 3960-3968.  https://doi.org/10.1118/1.4921805
  11. J.M. Boone, Method for evaluating bowtie filter angle-dependent attenuation in CT: theory and simulation results, Med. Phys. 37 (2010) 40-48.  https://doi.org/10.1118/1.3264616
  12. A.I. Hassan, M. Skalej, H. Schlattl, C. Hoeschen, Determination and verification of the x-ray spectrum of a CT scanner, J. Med. Imaging 5 (2018), 013506. 
  13. K. Cranley, B.J. Gilmore, G.W.A. Fogarty, L. Deponds, Catalogue of Diagnostic X-Ray Spectra and Other Data IPEM, IPEM, York, 1997. Report No. 78. 
  14. R. Birch, M. Marshall, Computation of bremsstrahlung x-ray spectra and comparison with spectra measured with a Ge(Li) detector, Phys. Med. Biol. 24 (1979) 505-517.  https://doi.org/10.1088/0031-9155/24/3/002
  15. D.W.O. Rogers, C.M. Ma, G.X. Ding, B. Walters, D. Sheikh-Bagheri, G.G. Zhang, NRCC Report PIRS-0509(A)revK: BEAMnrc Users Manual, NRCC, Ottawa, 2004. 
  16. G. Poludniowski, G. Landry, F. DeBlois, P.M. Evans, F. Verhaegen, SpekCalc: a program to calculate photon spectra from tungsten anode x-ray tubes, Phys. Med. Biol. 54 (2009) 433-438.  https://doi.org/10.1088/0031-9155/54/2/017
  17. N. Zaker, M. Zehtabian, S. Sina, C. Koontz, A.S. Meigooni, Comparison of TG-43 dosimetric parameters of brachytherapy sources obtained by three different versions of MCNP codes, J. Appl. Clin. Med. Phys. 17 (2016) 379-390. 
  18. D. Barbesi, V.V. Vicente, S. Millet, M. Sandow, J.Y. Colle, D.L.H.L. Aldave, A LabVIEW®-based software for the control of the AUTORAD platform: a fully automated multisequential flow injection analysis Lab-on-Valve (MSFIA-LOV) system for radiochemical analysis, J. Radioanal. Nucl. Chem. 313 (2017) 217-227.  https://doi.org/10.1007/s10967-017-5282-2
  19. G.G. Poludniowski, P.M. Evans, Calculation of x-ray spectra emerging from an x-ray tube. Part I. electron penetration characteristics in x-ray targets, Med. Phys. 34 (2007) 2164-2174.  https://doi.org/10.1118/1.2734725
  20. Y. Kong, W. Zhuo, B. Chen, C. Zhao, MCNP simulations of medical diagnostic X-ray spectra, Nuclear Technioues 42 (2019) 11. 
  21. X-5 Monte Carlo Team, MCNPdA General Monte Carlo N-Particle Transport Code, Version 5 Volume I: MCNP Overview and Theory, Los Alamos National Laboratory, NM, 2003. Report No. LA-UR-03-1987. 
  22. M.G. David, E.J. Pires, M.A. Bernal, J.G. Peixoto, C.E. Dealmeida, Experimental and Monte Carlo-simulated spectra of standard mammography-quality beams, Br. J. Radiol. 85 (2012) 629-635.  https://doi.org/10.1259/bjr/73088072
  23. S.M. Seltzer, Calculation of photon mass energy-transfer and mass energyabsorption coefficients, Radiat. Res. 136 (1993) 147-170.  https://doi.org/10.2307/3578607
  24. J. Gu, B. Bednarz, P.F. Caracappa, X.G. Xu, The development, validation and application of a multi-detector CT (MDCT) scanner model for assessing organ doses to the pregnant patient and the fetus using Monte Carlo simulations, Phys. Med. Biol. 54 (2009) 2699-2717.  https://doi.org/10.1088/0031-9155/54/9/007
  25. M. Cros, R.M.S. Joemai, J. Geleijns, D. Molina, M. Salvado, SimDoseCT: dose ꠑ reporting software based on Monte Carlo simulation for a 320 detector-row cone-beam CT scanner and ICRP computational adult phantoms, Phys. Med. Biol. 62 (2017) 6304-6321.  https://doi.org/10.1088/1361-6560/aa77ea
  26. H. Zhang, S. Sun, H. Lu, Y. Liu, Construction and application of BREP phantom for Chinese women of childbearing age in radiation protection, Radiat. Protect. Dosim. 189 (2020) 407-419.  https://doi.org/10.1093/rpd/ncaa056
  27. H. Koivunoro, T. Siiskonen, P. Kotiluoto, I. Auterinen, E. Hippelainen, S. Savolainen, Accuracy of the electron transport in mcnp5 and its suitability for ionization chamber response simulations: a comparison with the egsnrc and penelope codes, Med. Phys. 39 (2012) 1335-1344. https://doi.org/10.1118/1.3685446