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Applications of MCNP simulation in treatment planning: a comparative study

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Abstract

Monte Carlo codes have been used for approximately 80 years to solve various problems in medical physics. In this paper, the importance of the MCNPX code in treatment planning is highlighted. As illustrative examples of the role of MCNPX in this field, some dosimetric parameters, isodose distribution curves, and figures of merit (FOMs) were considered for photon beams of various energies. To the best of the authors’ knowledge, such a systematic study has not been done before. Tissue-air ratio values were obtained as a function of depth in tissue as well as field size. The results of the simulations were in agreement within 3.5% with experimental results reported in the literature. Backscatter factor values were calculated as a function of beam energy, and found to be in agreement with published experimental values within 5.9%. The isodose curves for different conditions and beam arrangements were also simulated. Besides, FOMs were calculated for different radiation energies. All the results were in agreement with related data in the literature. It is concluded that the MCNPX code and the models developed in the present study can be used in different conditions where these parameters are involved, improving individualized treatment planning for individual patients.

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References

  • Alavian H, Tavakoli-Anbaran H (2019) Study on gamma shielding polymer composites reinforced with different sizes and proportions of tungsten particles using MCNP code. Prog Nucl Energy 115:91–98

    Article  Google Scholar 

  • Beilla S, Chauveau N, Laprie A, Bardiès M, Franceries X (2016) Which impact of tumor density variations on absorbed dose in external radiotherapy. Phys Med 32:301

    Article  Google Scholar 

  • Bushberg JT, Seibert JA, Jr Leidholdt EM, Boone JM (2012) The essential physics of medical imaging, 3rd edn. Lippincott Williams & Wilkins, Philadelphia

    Google Scholar 

  • Chibani O, Li XA (2002) Monte Carlo dose calculations in homogeneous media and at interfaces: a comparison between GEPTS, EGSnrc, MCNP, and measurements. Med Phys 29:835–847

    Article  Google Scholar 

  • DeMarco JJ, Solberg TD, Wallace RE, Smathers JB (1995) A verification of the Monte Carlo code MCNP for thick target bremsstrahlung calculations. Med Phys 22:11–16

    Article  Google Scholar 

  • Du Y, Frey EC, Wang WT, Tocharoenchai C, Baird WH, Tsui BMW (2002) Combination of MCNP and SimSET for Monte Carlo simulation of SPECT with medium-and high-energy photons. IEEE Trans Nucl Sci 49:668–674

    Article  ADS  Google Scholar 

  • Faria FP, Reynaldo S, Fonseca TCF, Lacerda MAS, Da Silva TA (2015) Monte Carlo simulation applied to the characterization of an extrapolation chamber for beta radiation dosimetry. Radiat Phys Chem 116:226–230

    Article  ADS  Google Scholar 

  • Forster RA, Little RC, Briesmeister JF, Hendricks JS (1990) MCNP capabilities for nuclear well logging calculations. IEEE Trans Nucl Sci 37:1378–1385

    Article  ADS  Google Scholar 

  • Joel GSC, Maurice NM, Jilbert NME, Ousmanou M, David S (2018) Monte Carlo method for gamma spectrometry based on GEANT4 toolkit: efficiency calibration of BE6530 detector. J Environ Radioact 189:109–119

    Article  Google Scholar 

  • Johns HE, Cunningham JR (1984) Physics of radiology, 4th edn. Charles C Thomas, Springfield

    Google Scholar 

  • Juste B, Miró R, Campayo JM, Díez S, Verdú G (2010) Comparison of experimental 3D dose curves in a heterogeneous phantom with results obtained by MCNP5 simulation and those extracted from a commercial treatment planning system. Appl Radiat Isot 68:913–917

    Article  Google Scholar 

  • Khan FM, Gibbons JP (2014) Khan’s the physics of radiation therapy, 5th edn. Lippincott Williams & Wilkins, Philadelphia

    Google Scholar 

  • Leelanoi P, Buranurak S, Sangaroon S (2018) Investigating a proton beam-based neutron source for BNCT using the MCNP simulation, in: Journal of Physics: Conference Series. IOP Publishing, Bristol

    Google Scholar 

  • Lewis RD, Ryde SJS, Hancock DA, Evans CJ (1999) An MCNP-based model of a linear accelerator x-ray beam. Phys Med Biol 44:1219

    Article  Google Scholar 

  • Mendes BM, Trindade BM, Fonseca TCF, de Campos TPR (2017) Assessment of radiation-induced secondary cancer risk in the Brazilian population from left-sided breast-3D-CRT using MCNPX. Br J Radiol 90:20170187

    Article  Google Scholar 

  • Musarudin M, Saripan MI, Mashohor S, Saad WHM, Hashim S, Nordin AJ (2012) Preliminary results from attenuation correction for MCNP-generated PET image, in: 2012 IEEE-EMBS conference on biomedical engineering and sciences. IEEE, pp. 907–910

  • Ören Ü, Hiller M, Andersson M (2016) IDACstar: a MCNP application to perform realistic dose estimations from internal or external contamination of radiopharmaceuticals. Radiat Prot Dosim 174:406–411

    Google Scholar 

  • Pelowitz DB (2008) MCNPXTM user’s manual version 2.6.0. Los Alamos, NM: Los Alamos National Laboratory. LA-CP-07–1473

  • Podgorsak EB (2005) Radiation oncology physics: a handbook for teachers and students. International Atomic Energy Agency, Vienna

    Google Scholar 

  • Rogers DWO (2006) Fifty years of Monte Carlo simulations for medical physics. Phys Med Biol 51:R287

    Article  ADS  Google Scholar 

  • Sechopoulos I, Rogers DWO, Bazalova-Carter M, Bolch WE, Heath EC, McNitt-Gray MF, Sempau J, Williamson JF (2018) RECORDS: improved Reporting of montE CarlO RaDiation transport Studies: report of the AAPM Research Committee Task Group 268. Med Phys 45:e1–e5

    Article  Google Scholar 

  • Shdeed TA, Nahili M, Issa NA, Bitar A (2016) Study of absorbed dose in important organs during helical CT chest scan using MCNP code and MIRD phantom. Egypt J Radiol Nucl Med 47:1649–1663

    Article  Google Scholar 

  • Shultis JK, Faw RE (2011) An MCNP Primer. Department of Mechanical and Nuclear Engineering, Kansas State University, Manhattan

    Google Scholar 

  • Solberg TD, DeMarco JJ, Chetty IJ, Mesa AV, Cagnon CH, Li AN, Mather KK, Medin PM, Arellano AR, Smathers JB (2001) A review of radiation dosimetry applications using the MCNP Monte Carlo code. Radiochim Acta 89:337–355

    Article  Google Scholar 

  • Walters BRB, Kawrakow I, Rogers DWO (2002) History by history statistical estimators in the BEAM code system. Med Phys 29:2745–2752

    Article  Google Scholar 

  • Zaker N, Zehtabian M, Sina S, Koontz C, Meigooni AS (2016) Comparison of TG-43 dosimetric parameters of brachytherapy sources obtained by three different versions of MCNP codes. J Appl Clin Med Phys 17:379–390

    Article  Google Scholar 

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This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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  1. Department of Energy Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran

    Seyed Milad Vahabi & Mojtaba Shamsaie Zafarghandi

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  1. Seyed Milad Vahabi
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  2. Mojtaba Shamsaie Zafarghandi
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Correspondence to Seyed Milad Vahabi.

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Vahabi, S.M., Shamsaie Zafarghandi, M. Applications of MCNP simulation in treatment planning: a comparative study. Radiat Environ Biophys 59, 307–319 (2020). https://doi.org/10.1007/s00411-020-00841-2

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