Izvestiya vuzov. Yadernaya Energetika

The peer-reviewed scientific and technology journal. ISSN: 0204-3327

Comparative analysis of MCNPX and GEANT4 for fast neutron radiation treatment planning

7/14/2014 2014 - #02 Application of nuclear tech

Solovyev A.N. Fedorov V.V. Kharlov V.I. Stepanova U.A.

DOI: https://doi.org/10.26583/npe.2014.2.08

UDC: 621.039.52:615.849.1

The paper presents a comparative analysis of the MCNPX and GEANT4 simulation codes in radiation treatment planning tasks for fast neutron therapy. Different voxel phantoms were used in this study. A water voxel phantom was used to estimate the secondary particle spectrum. Different homogeneous tissue phantoms were used to compare the dependence of the physical absorbed dose on the tissue type. Finally, two algorithms for voxel aggregation were developed and implemented in the Python programming language to convert medical DICOM images obtained using computer tomography at MRRC, Obninsk, Russia.

MCNPX 2.5e and GEANT-4.9.5p02 were used in this study on the Intel Xeon E5506 2.13 GHz workstation in a single-processor mode. Data preparation and post-simulation analysis were performed using the programs developed by the authors and written in Python with Numpy and Matplotlib Libraries.

The simulation time, physical absorbed dose and dose error were measured during the study. The results showed that the MCNP kerma-evaluation can be faster and more accurate than any other method, but the dose on the surface (i.e. patient’s skin) is assessed incorrectly as the secondary particles and proton equilibrium are not taken into consideration by this method. Homogeneous tissue phantom simulation is much more time-consuming than water phantom simulation, but inhomogeneous structures (i.e. real patient geometry) have comparable simulation time. Work to improve the voxel-based geometry phantom representation will be continued.


  1. Trufanov G.E., Asaturyan M.A., Gharinov G.M. Luchevaya terapiya – Tom 2 [Radiation therapy – Part 2], Moscow, GEOTAR-Media Publ. 2007, 195 p. (in Russian)
  2. Wikipedia, the free encyclopedia. Available at: http://ru.wikipedia.org, http://en.wikipedia.org
  3. Saenko A.S., Mardinskiy Yu.S., Ulyanenko S.E. eds. Otchet o NIR. Razvitie biomedicinskih osnov ispolzovaniya reaktornih neitronov dlya distancionnoi, neutronzahvatnoi i sochetannoi luchevoi terapii [Research results. The biomedical basis development for reactor neutrons usage in external beam radiotherapy, neutron-capture therapy and concomitant therapy.] Obninsk: MRRC, 2004, 300 p. (in Russian).
  4. Tsyb A.F., Ulyanenko S.E., Mardinskiy Yu.S. Neitroni v lechenii zlokachestvennih novoobrazovaniy [Neutron in malignancies treatment]. Obninsk: MRRC, 2004, 94 p. (in Russian).
  5. Brovin A.I., Lityaev V.M., Lichagin A.A., Koryakin S.N., Solovyev A.N., Ulyanenko S.E. Creation of therapeutic facility based on neutron generator NG-24 [Proc. «Portable neutron generators and technologies on their basis»]. Moscow, 2012, pp. 4-5. (in Russian).
  6. Garny Sylvia, Rьhm Werner et al. First steps towards a fast-neutron therapy planning program // Garny et al. Radiation Oncology 2011, 6:163, 2011.
  7. Lityaev V.M., Solovyev A.N. The equipment for creation of therapeutic neutron fields at the neutron generator ng-24. [Proc. «Portable neutron generators and technologies on their basis»]. Moscow, 2012, p. 27. (in Russian).
  8. Lityaev V.M., Ulyanenko S.E., Gorbushin N.G. Ustroistvo dlya luchevoi terapii bistrimi neitronami [The fast neutron radiation treatment facility]. Parent RF, no. 2442620, 2012.
  9. Lityev V.M., Lychagin A.A., Potetnya V.I., Solovyev A.N., Ulyanenko S.E., Harlov V.I. Physical and dosimetric studies for substantiate medical requirements to therapeutic facility based on portable neutron generators [Proc. «Portable neutron generators and technologies on their basis»]. Moscow, 2012, p. 26. (in Russian).
  10. MCNPX Home page. Available at: http://mcnpx.lanl.gov/
  11. Geant4: A toolkit for the simulation of the passage of particles through matter. Available at: http://geant4.cern.ch/
  12. Python. Available at: http://www.python.org/
  13. Numpy. Available at: http://www.numpy.org/
  14. Matplotlib: Python plotting. Available at: http://matplotlib.sourceforge.net/
  15. Stepanov U.A. Solovyev A.N., Prusachenko P.S. Vliyanie elementnogo sostava tkanei s blizkimi plotnostyami na otsenki pogloshennih doz pri planirovanii neitronnoi terapii s ispolzovaniem GEANT4 [The close density tissues and its elemental composition dependence on the absorbed dose evaluation in neutron radiation therapy tasks with GEANT4] «Eksperementalnaya i teoreticheskya biofizika ’13. » Sbornik tezisov [Proc. «Experimental and theoretical biophysics ’13. Books of theses»]. Puschino, Fix-print Publ. 2013, pp. 127-128 (in Russian).
  16. Solovyev A.N. Automated distributed radiation treatment planning system. Informacionnye i telekommuunikatsionnie tehnologii. 2013, no. 17, pp. 48-60 (in Russian).
  17. Python Imaging Library. Available at: http://www.pythonware.com/products/pil/
  18. Moiseenko D.N., Kurachenko U. Analiz tyajelih radiatsionnig avariy s pomoshju vokselnogo antropomorfnogo fantoma [The severe radiation accidents analysis with voxel anthropomorphic phantom]. Izvestiya vuzov. Yadernaya energetika. 2012, no. 4, pp. 152–160.

radiation therapy radiation treatment planning Monte-Carlo method