Validation and study of different parameters in the simulation of diagnostic X-ray spectra using the MCNPX code
DOI:
https://doi.org/10.15392/2319-0612.2023.2119Keywords:
X-ray spectrum, Monte Carlo simulation, MCNPXAbstract
In radiology, knowing the X-ray spectrum characteristics makes it possible to estimate the absorbed dose in the patient and to improve image quality. In this study, an X-ray generator was proposed using the MCNPX code and to validate it, the simulated spectrum was compared to the data provided from AAPM Task Group 195, which resulted in a percentage difference of 8.7%. Furthermore, several X-ray spectra were generated and compared to the spectra obtained from commercially available softwares as xpecgen and SpekCalc. The percentage differences were of the order of 13% in comparison with SpekCalc and 8% with xpecgen. The major differences obtained between those spectra were concentrated in the region of characteristic peaks, independently if variations in electron beam energy, target angle or filtration thickness were performed.
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SECHOPOULOS, I. et al. Monte Carlo reference data sets for imaging research: Executive summary of the report of AAPM Research Committee Task Group 195. Medical Physics, 42, 5679-5691, 2015. DOI: https://doi.org/10.1118/1.4928676
PARK, H. et al. Monte Carlo methods for device simulations in radiation therapy. Phys Med Biol, 66 18TR01, 2021. DOI: https://doi.org/10.1088/1361-6560/ac1d1f
YORIYAZ, H. Método de Monte Carlo: princípios e aplicações em Física Médica. Revista Brasileira de Física Médica, 3(1):141-9, 2009.
TRAN, K. A. et al. Study on the characteristics of X-ray spectra in imaging diagnosis using Monte Carlo simulations. Journal of the Korean Physical Society, Vol. 69, No. 7. 2016. DOI: https://doi.org/10.3938/jkps.69.1168
REYNOSO, F. J. et al. Comparison of filtered X-ray spectra and depth doses derived from a hybrid Monte Carlo model of an orthovoltage X-ray unit with experimental measurements. Biomed Phys Eng Express 2 045011, 2016. DOI: https://doi.org/10.1088/2057-1976/2/4/045011
CHUSIN, T.; MATSUBARA, K.; TAKEMURA, A.; OKUBO, R.; OGAWA, Y. Validation of mammographic x-ray spectra generated using Particle and Heavy Ion Transport code System. Phys Med Biol, 18;65(6):065004, 2020. DOI: https://doi.org/10.1088/1361-6560/ab735c
AY, MR. ; SHAHRIARI, M.; SARKAR, S.; ADIB, M.; ZAIDI, H. Monte carlo simulation of X-ray spectra in diagnostic radiology and mammography using MCNP4C. Phys Med Biol, 7;49(21):4897-917, 2004. DOI: https://doi.org/10.1088/0031-9155/49/21/004
GALLARDO, S.; RÓDENAS, J.; VERDÚ, G. Monte carlo simulation of the compton scattering technique applied to characterize diagnostic x-ray spectra. Med Phys, 31(7):2082-90, 2004. DOI: https://doi.org/10.1118/1.1759827
GALLARDO, S.; QUEROL, A.; RÓDENAS, J.; VERDÚ G. Uncertainty Analysis in the Simulation of X-ray Spectra in the Diagnostic Range using the MCNP5 code. In: Proceedings of the 33rd Annual International Conference of the IEEE-Engineering in Medicine and Biology Society (EMBS), Boston, USA, 2011. DOI: https://doi.org/10.1109/IEMBS.2011.6090125
BUJILA, R.; OMAR, A.; & POLUDNIOWSKI, G. A validation of SpekPy: A software toolkit for modeling X-ray tube spectra. Physica Medica, 75, 44–54, 2020. DOI: https://doi.org/10.1016/j.ejmp.2020.04.026
GHAMMRAOUI, B.; MAKEEV, A.; & GLICK, S. J. High-rate x-ray spectroscopy in mammography with photon counting detectors using a limited number of energy bins. Radiation Measurements, 138, 106444, 2020. DOI: https://doi.org/10.1016/j.radmeas.2020.106444
POLUDNIOWSKI, G.; LANDRY, G.; DEBLOIS, F.; EVANS, P. M. & VERHAEGEN, F. SpekCalc: a program to calculate photon spectra from tungsten anode x-ray tubes. Phys Med Biol, 54(19):N433, 2009. DOI: https://doi.org/10.1088/0031-9155/54/19/N01
CRANLEY, K.; GILMORE, B. J.; FOGARTY, G. W. A. & DEPONDS, L. Catalogue of diagnostic x-ray spectra and other data. IPEM Report No. 78, The Institute of Physics and Engineering in Medicine, 1997.
PELOWITZ, D. B. MCNPX User’s Manual Version 2.7.0. Los Alamos, LANL, 2011.
HERNÁNDEZ, G. & FERNÁNDEZ, F. A model of tungsten anode X-ray spectra. Med Phys., 43(8):4655, 2016. DOI: https://doi.org/10.1118/1.4955120
OMAR, A.; ANDREO, P. & POLUDNIOWSKI, G. A model for the energy and angular distribution of X rays emitted from an X-ray tube. Part II. Validation of X-ray spectra from 20 to 300 kV. Med Phys. 47 (9), 2020. DOI: https://doi.org/10.1002/mp.14360
SHULTIS, J. K. & FAW, R. E. An MNCP Primer. Kansas State University. Manhattan. 2011.
VAN RIPER, K. A. MORITZ Geometry Tool User's Guide - Windows Version (Manual). White Rock Science, 2008.
MCCONN JR, R. J.; GESH, C. J.; PAGH, R. T.; RUCKER, R. A.; WILLIANS III, R. G. Compendium of Material Composition Data for Radiation Transport Modeling, Report PNNL-15870, Rev. 1. Pacific Northwest National Laboratory, Washington, 2011. DOI: https://doi.org/10.2172/1023125
FITZGERALD P, ARAUJO S, WU M, DE MAN B. Semiempirical, parameterized spectrum estimation for x-ray computed tomography. Med Phys, 48(5):2199-2213, 2021. DOI: https://doi.org/10.1002/mp.14715
ZHAO, W.; NIU, K.; SCHAFER, S.; & ROYALTY, K. An indirect transmission measurement-based spectrum estimation method for computed tomography. Phys Med Biol, 60(1), 339–357, 2014. DOI: https://doi.org/10.1088/0031-9155/60/1/339
O’CONNELL, J et al. Next generation high resolution perovskite direct conversion detector: Monte Carlo design optimisation and virtual clinical trial. Phys Med Biol, 68 025016, 2023. DOI: https://doi.org/10.1088/1361-6560/acae15
KUNERT, P.; TRINKL, S.; GIUSSANI, A.; REICHERT, D.; BRIX, G. Tissue equivalence of 3D printing materials with respect to attenuation and absorption of X-rays used for diagnostic and interventional imaging. Med Phys, 49(12):7766-7778, 2022. DOI: https://doi.org/10.1002/mp.15987
KUSK, M. W. et al. Anode heel effect: Does it impact image quality in digital radiography? A systematic literature review. Radiography (Lond), 27(3):976-981, 2021. DOI: https://doi.org/10.1016/j.radi.2021.02.014
OMAR, A.; ANDREO, P. and POLUDNIOWSKI, G. A model for the emission of K and L X rays from an x-ray tube. Nucl Instrum Methods Phys Res B, 437:36–47, 2018. DOI: https://doi.org/10.1016/j.nimb.2018.10.026
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