Biomedical Microdevices

, 11:925 | Cite as

Quantifying tumor-selective radiation dose enhancements using gold nanoparticles: a monte carlo simulation study

  • Sean X. Zhang
  • Junfang Gao
  • Thomas A. Buchholz
  • Zhonglu Wang
  • Mohammad R. Salehpour
  • Rebekah A. Drezek
  • Tse-Kuan Yu
Article

Abstract

Gold nanoparticles can enhance the biological effective dose of radiation delivered to tumors, but few data exist to quantify this effect. The purpose of this project was to build a Monte Carlo simulation model to study the degree of dose enhancement achievable with gold nanoparticles. A Monte Carlo simulation model was first built using Geant4 code. An Ir-192 brachytherapy source in a water phantom was simulated and the calculation model was first validated against previously published data. We then introduced up to 1013 gold nanospheres per cm3 into the water phantom and examined their dose enhancement effect. We compared this enhancement against a gold-water mixture model that has been previously used to attempt to quantify nanoparticle dose enhancement. In our benchmark test, dose-rate constant, radial dose function, and two-dimensional anisotropy function calculated with our model were within 2% of those reported previously. Using our simulation model we found that the radiation dose was enhanced up to 60% with 1013 gold nanospheres per cm3 (9.6% by weight) in a water phantom selectively around the nanospheres. The comparison study indicated that our model more accurately calculated the dose enhancement effect and that previous methodologies overestimated the dose enhancement up to 16%. Monte Carlo calculations demonstrate that biologically-relevant radiation dose enhancement can be achieved with the use of gold nanospheres. Selective tumor labeling with gold nanospheres may be a strategy for clinically enhancing radiation effects.

Keywords

Nanoparticle Dose enhancement Monte Carlo simulation modeling 

References

  1. S. Agostinelli, J. Allison, K. Amako et al., Geant4—a simulation toolkit. Nucl. Instrum. Methods Phys. Res. A 506, 250–303 (2003). doi:10.1016/S0168-9002(03)01368-8 CrossRefGoogle Scholar
  2. J. Allison, K. Amako, J. Apostolakis et al., Geant4 developments and applications. IEEE Trans. Nucl. Sci. 53, 270–278 (2006). doi:10.1109/TNS.2006.869826 CrossRefGoogle Scholar
  3. A. Angelopoulos, P. Baras, L. Sakelliou et al., Monte Carlo dosimetry of a new Ir-192 high dose rate brachytherapy source. Med. Phys. 27, 2521–2527 (2000). doi:10.1118/1.1315316 CrossRefGoogle Scholar
  4. F. Ballester, C. Hernández, J. Pèrez-Calatayud et al., Monte Carlo calculation of dose rate distributions around Ir-192 wires. Med. Phys 24, 1221–1228 (1997). doi:10.1118/1.598142 CrossRefGoogle Scholar
  5. F. Ballester, J. Pèrez-Calatayud, V. Puchades et al., Monte Carlo dosimetry of Buchler high dose rate Ir-192 source. Med. Phys 28, 2586–2591 (2001). doi:10.1118/1.1420398 CrossRefGoogle Scholar
  6. K. Bullis, Remotely activated nanoparticles destroy cancer. Technology Review 2007. http://www.technologyreview.com/Nanotech/17956/. Published January 2, 2007. Accessed November 25, 2007
  7. S.H. Cho, Estimation of tumor dose enhancement due to gold nanoparticles during typical radiation treatments: a preliminary Monte Carlo study. Phys. Med. Biol 50, N-163–N-173 (2005)CrossRefGoogle Scholar
  8. S.J. Douglas, S.S. Davis, L. Illum, Nanoparticles in drug delivery. Crit. Rev. Ther. Drug Carrier Syst. 3, 133–161 (1987)Google Scholar
  9. A.M. Gobin, M.H. Lee, N.J. Halas et al., Nano Lett 7, 1929–1934 (2007). doi:10.1021/nl070610y CrossRefGoogle Scholar
  10. D. Granero, J. Pèrez-Calatayud, F. Ballester, Monte Carlo calculation of the TG-43 dosimetric parameters of a new BEBIG Ir-192 HDR source. Radiother. Oncol 76, 79–85 (2005). doi:10.1016/j.radonc.2005.06.016 CrossRefGoogle Scholar
  11. J.F. Hainfeld, D.N. Slatkin, H.M. Smilowitz, The use of gold nanoparticles to enhance radiotherapy in mice. Phys. Med. Biol. 49, 309-N–315 (2004)CrossRefGoogle Scholar
  12. J.F. Hainfeld, D.N. Slatkin, T.M. Focella et al., Gold nanoparticles: a new X-ray contrast agent. Br. J. Radiol. 79, 248–253 (2006). doi:10.1259/bjr/13169882 CrossRefGoogle Scholar
  13. D.M. Herold, I.J. Das, C.C. Stobbe et al., Gold microspheres: a selective technique for producing biologically effective dose enhancement. Int. J. Radiat. Biol 76, 1357–1364 (2000). doi:10.1080/09553000050151637 CrossRefGoogle Scholar
  14. M. Hu, J.Y. Chen, Z.Y. Li et al., Gold nanostructures: engineering their plasmonic properties for biomedical applications. Chem. Soc. Rev 35, 1084–1094 (2006). doi:10.1039/b517615h CrossRefGoogle Scholar
  15. H.E. Johns, J.W. Hunt, S.O. Fedoruk, Surface back-scatter in the 100 kV to 400 kV range. Br. J. Radiol. 27, 443–448 (1954)CrossRefGoogle Scholar
  16. K.L. Kelly, E. Coronado, L.L. Zhao et al., The optical properties of metal nanoparticles: The influences of size, shape, and dielectric environment. J Phys Chem B Condens Matter Mater Surf Interfaces Biophys 107, 668–677 (2003)Google Scholar
  17. C. Loo, A. Lowery, N. Halas, J. West, R. Drezek, Immunotargeted nanoshells for integrated cancer imaging and therapy. Nano Lett. 5(4)), 709–711 (2005). doi:10.1021/nl050127s CrossRefGoogle Scholar
  18. R. Nath, L.L. Anderson, G. Luxton et al., Dosimetry of interstitial brachytherapy source: recommendations of AAPM radiation therapy committee task group No. 43. Med. Phys 22, 209–234 (1995). doi:10.1118/1.597458 CrossRefGoogle Scholar
  19. C. Noguez, Surface plasmons on metal nanoparticles: The influence of shape and physical environment. J. Phys. Chem. C. Nanomaterials Interfaces 111, 3806–3819 (2007)Google Scholar
  20. NuDat 2.4. National Nuclear Data Center. Nuclear data from NuDat, a web-based database maintained by the National Nuclear Data Center. Upton, NY, USA: Brookhaven National Laboratory; http://www.nndc.bnl.gov/nudat2. Accessed November 25, 2007
  21. J. Panyam, V. Labhasetwar, Biodegradable nanoparticles for drug and gene delivery to cells and tissue. Adv. Drug Deliv. Rev 55, 329–347 (2003). doi:10.1016/S0169-409X(02)00228-4 CrossRefGoogle Scholar
  22. Physics Laboratory, National Institute of Standards and Technology., Stopping-power and range tables for electrons. http://physics.nist.gov/PhysRefData/Star/Text/ESTAR.html . Accessed November 25, 2007
  23. M.J. Rivard, B.M. Coursey, L.A. Dewerd et al., Update of AAPM task group No. 43 report: a revised AAPM protocol for brachytherapy dose calculations. Med. Phys. 31, 633–674 (2004). doi:10.1118/1.1646040 CrossRefGoogle Scholar
  24. J.L. Robar, Generation and modeling of megavoltage photon beams for contrast-enhanced radiation therapy. Phys. Med. Biol 51, 5487–5504 (2006). doi:10.1088/0031-9155/51/21/007 CrossRefGoogle Scholar
  25. J.L. Robar, S.A. Riccio, M.A. Martin, Tumor dose enhancement using modified megavoltage photon beams and contrast media. Phys. Med. Biol 47, 2433–2449 (2002). doi:10.1088/0031-9155/47/14/305 CrossRefGoogle Scholar
  26. J.H. Sakamoto, B.R. Smith, B. Xie et al., The molecular analysis of breast cancer utilized targeted nanoparticle based ultrasound contrast agents. Technol. Cancer Res. Treat. 4, 627–636 (2005)Google Scholar
  27. G. Schmid, Nanoparticles: from theory to application (Wiley-Vch Verlag GmbH & Co. KGaA; Weinheim, Germany, 2004)Google Scholar
  28. D.C. Sullivan, M. Ferrari, Nanotechnology and tumor imaging: seizing an opportunity. Mol. Imaging 3, 364–369 (2004). doi:10.1162/1535350042973526 CrossRefGoogle Scholar
  29. F. Verhaegen, B. Reniers, E. Deblois et al., Dosimetric and microdosimetric study of contrast-enhanced radiotherapy with kilovolt X-rays. Phys. Med. Biol 50, 3555–3569 (2005). doi:10.1088/0031-9155/50/15/005 CrossRefGoogle Scholar
  30. J.F. Williamson, Monte Carlo evaluation of kerma at a point for photon transport problems. Med. Phys. 14, 567–576 (1987). doi:10.1118/1.596069 CrossRefGoogle Scholar
  31. X-5 Monte Carlo Team, MCNP-A General Monte Carlo N-Particle Transport Code, Version 5. LA-UR-03-1987. Los Alamos National Laboratory: Los Alamos, NM, 2004Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Sean X. Zhang
    • 1
  • Junfang Gao
    • 1
  • Thomas A. Buchholz
    • 3
  • Zhonglu Wang
    • 1
  • Mohammad R. Salehpour
    • 1
  • Rebekah A. Drezek
    • 2
  • Tse-Kuan Yu
    • 3
  1. 1.Department of Radiation PhysicsThe University of Texas M. D. Anderson Cancer CenterHoustonUSA
  2. 2.Department of Bioengineering and Department of Electric and Computer EngineeringRice UniversityHoustonUSA
  3. 3.Department of Radiation OncologyThe University of Texas M. D. Anderson Cancer CenterHoustonUSA

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