Abstract
Monte Carlo techniques are widely employed in internal dosimetry to obtain better estimates of absorbed dose distributions from irradiation sources in medicine. Accurate 3D absorbed dosimetry would be useful for risk assessment of inducing deterministic and stochastic biological effects for both therapeutic and diagnostic radiopharmaceuticals in nuclear medicine. The goal of this study was to experimentally evaluate the use of Geant4 application for tomographic emission (GATE) Monte Carlo package for 3D internal dosimetry using the head portion of the RANDO phantom. GATE package (version 6.1) was used to create a voxel model of a human head phantom from computed tomography (CT) images. Matrix dimensions consisted of 319 × 216 × 30 voxels (0.7871 × 0.7871 × 5 mm3). Measurements were made using thermoluminescent dosimeters (TLD-100). One rod-shaped source with 94 MBq activity of 99mTc was positioned in the brain tissue of the posterior part of the human head phantom in slice number 2. The results of the simulation were compared with measured mean absorbed dose per cumulative activity (S value). Absorbed dose was also calculated for each slice of the digital model of the head phantom and dose volume histograms (DVHs) were computed to analyze the absolute and relative doses in each slice from the simulation data. The S-values calculated by GATE and TLD methods showed a significant correlation (correlation coefficient, r 2 ≥ 0.99, p < 0.05) with each other. The maximum relative percentage differences were ≤14 % for most cases. DVHs demonstrated dose decrease along the direction of movement toward the lower slices of the head phantom. Based on the results obtained from GATE Monte Carlopackage it can be deduced that a complete dosimetry simulation study, from imaging to absorbed dose map calculation, is possible to execute in a single framework.
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References
Xu XG, Eckerman KF (2010) Handbook of anatomical models for radiation dosimetry. Taylor & Francis, New York, pp 389–409
Zubal IG, Harrell CR, Smith EO, Rattner Z, Gindi G, Hoffer PB (1994) Computerized three-dimensional segmented human anatomy. Med Phys 21(2):299–302
Parach AA, Rajabi H (2011) A comparison between GATE4 results and MCNP4B published data for internal radiation dosimetry. Nuklearmedizin 50(3):122–133
Parach AA, Rajabi H, Askari MA (2011) Assessment of MIRD data for internal dosimetry using the GATE Monte Carlo code. Radiat Environ Biophys 50(3):441–450
Saito K, Wittmann A, Koga S, Ida Y, Kamei T, Funabiki J et al (2001) Construction of a computed tomographic phantom for a Japanese male adult and dose calculation system. Radiat Environ Biophys 40(1):69–75
Caon M, Bibbo G, Pattison J (1999) An EGS4-ready tomographic computational model of a 14-year-old female torso for calculating organ doses from CT examinations. Phys Med Biol 44(9):2213–2225
Zankl M, Wittmann A (2001) The adult male voxel model “Golem” segmented from whole-body CT patient data. Radiat Environ Biophys 40(2):153–162
Caon M, Mohyla J (2001) Automating the segmentation of medical images for the production of voxel tomographic computational models. Australas Phys Eng Sci Med 24(4):185–190
The consortium of computational human phantoms. http://www.virtualphantoms.org/phantoms.htm. Accessed 5 Oct 2014
The phantom library. http://www.phantomlab.com/rando.html. Accessed 5 Oct 2014
Computerized Imaging Reference Systems (CIRS). Available at:http://www.cirsinc.com Accessed 20 Dec 2014
United Nations. Scientific Committee on the Effects of Atomic Radiation (2009) Effects of ionizing radiation: UNSCEAR 2006 Report to the General Assembly, with scientific annexes (Vol. 2) United Nations Publications
Hendricks J, Briesmeister J (1992) Recent MCNP developments. IEEE Trans Nucl Sci 39(4):1035–1040
Rogers D (1984) Low energy electron transport with EGS. Nucl Instrum Meth A 227(3):535–548
Sempau J, Acosta E, Baro J, Fernández-Varea J, Salvat F (1997) An algorithm for Monte Carlo simulation of coupled electron-photon transport. Nucl Instrum Methods Phys Res B 132(3):377–390
Agostinelli S, Allison J, Ka Amako, Apostolakis J, Araujo H, Arce P et al (2003) GEANT4—a simulation toolkit. Nucl Instrum Meth A 506(3):250–303
Pia M (2003) The Geant4 toolkit: simulation capabilities and application results. Nucl Phys B 125:60–68
The OpenGate Collaboration. http://www.opengatecollaboration.org. Accessed 2 Mar 2014
Visvikis D, Bardies M, Chiavassa S, Danford C, Kirov A, Lamare F et al (2006) Use of the GATE Monte Carlo package for dosimetry applications. Nucl Instrum Meth A 569(2):335–340
Parach AA, Rajabi H, Askari MA (2011) Paired organs-should they be treated jointly or separately in internal dosimetry? Med Phys 38(10):5509–5521
Papadimitroulas P, Loudos G, Nikiforidis GC, Kagadis GC (2012) A dose point kernel database using GATE Monte Carlo simulation toolkit for nuclear medicine applications: comparison with other Monte Carlo codes. Med Phys 39(8):5238–5247
Sarrut D, Bardiès M, Boussion N, Freud N, Jan S, Létang J-M et al (2014) A review of the use and potential of the GATE Monte Carlo simulation code for radiation therapy and dosimetry applications. Med Phys 41(6):064301–064314
Hickson KJ, O’Keefe GJ (2014) Effect of voxel size when calculating patient specific radionuclide dosimetry estimates using direct Monte Carlo simulation. Australas Phys Eng Sci Med 37(3):495–503
Segars W, Tsui B (2009) MCAT to XCAT: the evolution of 4-D computerized phantoms for imaging research. Proc IEEE 97(12):1954–1968
Deloar HM, Fujiwara T, Shidahara M, Nakamura T, Yamadera A, Itoh M (1999) Internal absorbed dose estimation by a TLD method for-FDG and comparison with the dose estimates from whole body PET. Phys Med Biol 44(2):595–606
Yorke ED, Williams LE, Demidecki AJ, Heidorn DB, Roberson PL, Wessels BW (1993) Multicellular dosimetry for beta-emitting radionuclides: autoradiography, thermoluminescent dosimetry and three-dimensional dose calculations. Med Phys 20(2 Pt 2):543–550
Giap HB, Macey DJ, Bayouth JE, Boyer AL (1995) Validation of a dose-point kernel convolution technique for internal dosimetry. Phys Med Biol 40(3):365–381
Chu KH, Lin YT, Hsu CC, Chen CY, Pan LK (2012) Evaluation of effective dose for a patient under Ga-67 nuclear examination using TLD, water phantom and a simplified model. J Radiat Res 53(6):989–998
Bicron H (1993) Model 3500 Manual TLD Reader. Bicorn, Saint-Gobain/Norton Industrial Ceramics Corporation, Solon
Loevinger R, Budinger TF, Watson EE (1991) MIRD primer for absorbed dose calculations. Society of Nuclear Medicine, New York
Yaşar D, Tuǧrul AB (2003) A comparison of TLD measurements to MIRD estimates of the dose to the testes from Tc-99 m in the liver and spleen. Radiat Meas 37(2):113–118
Sahebnasagh A, Adinehvand K, Azadbakht B (2012) Determination and comparison of absorbed dose of ovaries and uterus in heart scan from TC-99 m, by three methods: TLD measurement, MCNP simulation and MIRD calculation and estimation of its risks. Res J Appl Sci Eng Technol 4(22):4572–4575
Mayles P, Nahum AE, Rosenwald JC (2007) Handbook of radiotherapy physics: theory and practice. Taylor & Francis Publishing Group, Boca Raton, pp 305–314
Stabin MG (2008) Uncertainties in internal dose calculations for radiopharmaceuticals. J Nucl Med 49(5):853–860
Pacilio M, Lanconelli N, Meo SL, Betti M, Montani L, Aroche LT et al (2009) Differences among Monte Carlo codes in the calculations of voxel S values for radionuclide targeted therapy and analysis of their impact on absorbed dose evaluations. Med Phys 36(5):1543–1552
Hindorf C, Ljungberg M, Strand S-E (2004) Evaluation of parameters influencing S values in mouse dosimetry. J Nucl Med 45(11):1960–1965
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This work was financially supported by Mashhad University of Medical Sciences with funding number of 920325. The authors declare that they have no conflict of interest.
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Ghahraman Asl, R., Nasseri, S., Parach, A.A. et al. Monte Carlo and experimental internal radionuclide dosimetry in RANDO head phantom. Australas Phys Eng Sci Med 38, 465–472 (2015). https://doi.org/10.1007/s13246-015-0367-0
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DOI: https://doi.org/10.1007/s13246-015-0367-0