The Effect of Nucleus Size on the Cell Dose in Targeted Radionuclide Therapy - A Monte Carlo Study

Ebrahim Kouhkan, Nahid Chegeni, Amjad Hussain

DOI: 10.4103/jmss.JMSS_21_19

Abstract


Background: Nowadays, the use of radiopharmaceuticals in medicine is unavoidable. Depending on the distribution of the radiopharmaceutical in the cells, the nucleus absorbed dose changes by the variations in their geometry size. Therefore, this study aims to investigate the S-value by the variation of nucleus size using Geant4 toolkit. Methods: Two spherical cells with a variety of nucleus size have been considered as the cancerous cell. Monoenergetic electrons ranging from 5 to 300 keV are distributed uniformly. The S-value for four target-source components (including Nucleus-Cytoplasm, Nucleus-Cell surface, Nucleus-Nucleus, and Nucleus-Nucleus surface) is computed and plotted. Then, the obtained data are compared with analytical Medical Internal Radiation Dose (MIRD) data. Results: In Nucleus-Cytoplasm compartment for electrons below 10 keV, obtained S-values show a slight decrease for the nucleus in the radii of around half of the cell radius and then S-values increase with the increase in the nucleus radii. In the S-value of Nucleus-Cell surface, for all electron energy levels, a slight decrease observed with the increase of nucleus radii. For Nucleus-Nucleus and Nucleus-Nucleus surface cases, with an increase in the size of the cell nucleus, a sharp reduction in the S-values is detected. Conclusion: It can be concluded that for the beta emitters with low-energy radiation (<40 keV), the S-value is heavily dependent on the nucleus size which may affect the treatment of small tumors. While for the beta emitters with higher-energy radiation (>100 keV), the size of the nucleus is not very noticeable in the induced S-value.

Keywords


Beta-emitting radiopharmaceutical, Geant4-DNA, nuclear medicine, S-value

Full Text:

PDF

References


Stabin M, Xu XG. Basic principles in the radiation dosimetry of nuclear medicine. Semin Nuclear Med 2014;44:162-71. Back to cited text no. 1

Held KD, Kawamura H, Kaminuma T, Paz AE, Yoshida Y, Liu Q, et al. Effects of charged particles on human tumor cells. Front Oncol 2016;6:23. Back to cited text no. 2

Larson SM, Carrasquillo JA, Cheung NK, Press OW. Radioimmunotherapy of human tumours. Nat Rev Cancer 2015;15:347-60. Back to cited text no. 3

Strand SE, Jönsson BA, Ljungberg M, Tennvall J. Radioimmunotherapy dosimetry – A review. Acta Oncol 1993;32:807-17. Back to cited text no. 4

Murray D, McEwan AJ. Radiobiology of systemic radiation therapy. Cancer Biother Radiopharm 2007;22:1-23. Back to cited text no. 5

Goddu SM, Howell RW, Rao DV. Cellular dosimetry: Absorbed fractions for monoenergetic electron and alpha particle sources and S-values for radionuclides uniformly distributed in different cell compartments. J Nucl Med 1994;35:303-16. Back to cited text no. 6

Sefl M, Incerti S, Papamichael G, Emfietzoglou D. Calculation of cellular S-values using Geant4-DNA: The effect of cell geometry. Appl Radiat Isot 2015;104:113-23. Back to cited text no. 7

Cole A. Absorption of 20-eV to 50,000-eV electron beams in air and plastic. Radiat Res 1969;38:7-33. Back to cited text no. 8

Bichsel H. Monte Carlo Calculations of Track Structures, in Office of Scientific and Technical Information Technical Reports 1995, Washington University, Seattle, WA (United States): Nuclear Physics Laboratory; 1995. p. 2-7. Back to cited text no. 9

Rogers DW. Fifty years of monte carlo simulations for medical physics. Phys Med Biol 2006;51:R287-301. Back to cited text no. 10

El Naqa I, Pater P, Seuntjens J. Monte carlo role in radiobiological modelling of radiotherapy outcomes. Phys Med Biol 2012;57:R75-97. Back to cited text no. 11

Hugtenburg RP. Track-structure monte carlo modelling in X-ray and megavoltage photon radiotherapy. In: Gómez-Tejedor GG, Fuss MC, editors. Radiation Damage in Biomolecular Systems. Dordrecht: Springer Netherlands; 2012. p. 301-11. Back to cited text no. 12

Incerti S, Douglass M, Penfold S, Guatelli S, Bezak E. Review of geant4-DNA applications for micro and nanoscale simulations. Phys Med 2016;32:1187-200. Back to cited text no. 13

Tajik-Mansoury MA, Rajabi H, Mozdarani H. A comparison between track-structure, condensed-history monte carlo simulations and MIRD cellular S-values. Phys Med Biol 2017;62:N90-106. Back to cited text no. 14

Webster M, Witkin KL, Cohen-Fix O. Sizing up the nucleus: Nuclear shape, size and nuclear-envelope assembly. J Cell Sci 2009;122:1477-86. Back to cited text no. 15

Gorski S, Misteli T. Systems biology in the cell nucleus. J Cell Sci 2005;118:4083. Back to cited text no. 16

Karp G, Iwasa J, Marshall W. Cell and Molecular Biology: Concepts and Experiments. Hoboken: John Wiley and Sons, Inc.; 2015. Back to cited text no. 17

Cai Z, Pignol JP, Chan C, Reilly RM. Cellular dosimetry of (111) In using monte carlo N-particle computer code: Comparison with analytic methods and correlation within vitro cytotoxicity. J Nucl Med 2010;51:9. Back to cited text no. 18

Moradi MS, Bidabadi BS. Micro-dosimetry calculation of auger-electron-emitting radionuclides mostly used in nuclear medicine using GEANT4-DNA. Appl Radiat Isot 2018;141:73-9. Back to cited text no. 19

Cai Z, Kwon YL, Reilly RM. Monte carlo N-particle (MCNP) modeling of the cellular dosimetry of 64Cu: Comparison with MIRDcell S values and implications for studies of its cytotoxic effects. J Nucl Med 2017;58:339-45. Back to cited text no. 20

Nikjoo H, Uehara S. Comparison of various monte carlo track structure codes for energetic electrons in gaseous and liquid water. Basic Life Sci 1994;63:167-84. Back to cited text no. 21

Turner JE, Hamm RN, Ritchie RH, Bolch WE. Monte carlo track-structure calculations for aqueous solutions containing biomolecules. Basic Life Sci 1994;63:155-66. Back to cited text no. 22

Bernal MA, Bordage MC, Brown JM, Davídková M, Delage E, El Bitar Z, et al. Track structure modeling in liquid water: A review of the Geant4-DNA very low energy extension of the geant4 monte carlo simulation toolkit. Phys Med 2015;31:861-74. Back to cited text no. 23

Casella G, Robert CP, Wells MT. Generalized accept-reject sampling schemes. Lecture Notes Monogr Ser 2004;45:342-7. Back to cited text no. 24

Heinrich L, Körner R, Mehlhorn N, Muche L. Numerical and Analytical Computation of Some Second-Order Characteristics of Spatial Poisson-Voronoi Tessellations. A Journal of Theoretical and Applied Statistics 1998;31:235-59. Back to cited text no. 25

Goerg SJ, Kaiser J. Nonparametric testing of distributions—the Epps-Singleton two-sample test using the empirical characteristic function. Stata J 2009;9:454-65. Back to cited text no. 26

Yap BW, Sim CH. Comparisons of various types of normality tests. J Stat Comput Simul 2011;81:2141-55. Back to cited text no. 27

Bernhardt P, Forssell-Aronsson E, Jacobsson L, Skarnemark G. Low-energy electron emitters for targeted radiotherapy of small tumours. Acta Oncol 2001;40:602-8. Back to cited text no. 28


Refbacks

  • There are currently no refbacks.


 

  https://e-rasaneh.ir/Certificate/22728

https://e-rasaneh.ir/

ISSN : 2228-7477