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From radiobiology to radiotherapy: dose homogeneity in cells after alpha irradiation in measurements and Monte Carlo simulations

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Introduction: Proton radiotherapy offers an advantage in sparing healthy tissue compared to photon therapy due to the specific interaction of protons with the patient’s body. In radiobiological experiments, alpha sources are commonly used instead of proton accelerators for convenience, but ensuring a uniform dose distribution is challenging. Properly designing the cell irradiation setup is crucial to reliably measure the average cellular response in such experiments. The objective of this research is to underscore the importance of dosimetric validation in radiobiological investigations. While Monte Carlo (MC) simulations offer valuable insights, their accuracy needs experimental confirmation. Once consistent results are obtained, the reliance on simulations becomes viable, as they are more efficient and less cumbersome compared to experimental procedures. Material and methods: The simulations are performed with three MC code-based tools: Geant4-DNA, GATE, and SRIM to model the alpha radiation source and calculate dose distributions for various cell irradiation scenarios. Dosimetric verification of the experimental setup containing a 241Am source is performed using radiochromic films. Additionally, a clonogenic cell survival assay is carried out for the DU145 cell line. Results: The study introduces a novel source simulation model derived from dosimetric measurements. The comparison between dosimetric results obtained with simulations and measured experimentally yields a gamma (3%/3mm) parameter value exceeding 99%. Furthermore, the LQ model parameters fitted to survival data of DU145 cells irradiated with particles emitted from 241Am source demonstrate consistency with previously published findings. Conclusions: Radiobiological experiments investigate cellular responses to various irradiation scenarios. Challenges arise with densely ionizing radiation used in clinical practice, particularly in ensuring uniform dose delivery for reliable experiments. MC codes aid in simulating dose distribution and designing irradiation systems for consistent cell treatment. However, experimental validation is essential before relying on simulation results. Once confirmed, these results offer a cost-effective and time-efficient approach to planning radiobiological experiments compared to traditional laboratory work.
Rocznik
Strony
79--89
Opis fizyczny
Bibliogr. 21 poz., rys.
Twórcy
  • Biomedical Physics Division, Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Poland
  • Biomedical Physics Division, Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Poland
  • Biomedical Physics Division, Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Poland
  • Biomedical Physics Division, Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Poland
  • Heavy Ion Laboratory, University of Warsaw, Poland
  • Biomedical Physics Division, Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Poland
Bibliografia
  • 1. Yan S; Ngoma TA; Ngwa W, Bortfeld TR. Global democratisation of proton radiotherapy. The Lancet Oncology. 2023;24(6):e245-e254. https://doi.org/10.1016/S1470-2045(23)00184-5
  • 2. Lee KH, Shin JY, Kim EH. Measurement of activity distribution in an Am-241 disc source using peeled-off Gafchromic EBT3 films. Applied Radiation and Isotopes. 2018;135:192-200. https://doi.org/10.1016/j.apradiso.2018.01.037
  • 3. UNSCEAR. Sources and effects of ionizing radiation, ANNEX B, Exposures from natural radiation sources. UNSCEAR 2000 REPORT, New York 2000, 1, 97-99.
  • 4. Bernstein C; Bernstein H; Payne CM; Garewal H. DNA repair/pro-apoptotic dual-role proteins in five major DNA repair pathways: fail-safe protection against carcinogenesis. Mutation Research/Reviews in Mutation Research. 2002;511(2):145-178. https://doi.org/10.1016/S1383-5742(02)00009-1
  • 5. Szeflinski Z, Filipek M, Gotlib J, Kazmierczak U. Radiobiological research and dosimetry using a flat alpha source. RAP 2019 Conference Proceedings. https://doi.org/10.37392/RapProc.2019.02
  • 6. Wojcik A, Thierry-Chef I, Friedl AA, Rühm W. Minimum reporting standards about dosimetry of radiation sources used in radiation research studies. Radiat Environ Biophys. 2024;63:181-183. https://doi.org/10.1007/s00411-024-01063-6
  • 7. Wronska A, Jonas K, Arshiya AA, et al. Prompt-gamma emission in GEANT4 revisited and confronted with experiment. Physica Medica. 2021;88:250-261. https://doi.org/10.1016/j.ejmp.2021.07.018
  • 8. Incerti S, Ivanchenko A, Karamitros, et al. Comparison of GEANT4 very low energy cross section models with experimental data in water. Medical Physics. 2010;37:4692-4708. https://doi.org/10.1118/1.3476457
  • 9. Incerti S, Baldacchino G, Bernal M, et al. The Geant4-DNA project. International Journal of Modeling, Simulation, and Scientific Computing. 2010;10(2):157-178. https://doi.org/10.1142/S1793962310000122
  • 10. Incerti S, Kyriakou I, Bernal M, et al. Geant4-DNA example applications for track structure simulations in liquid water: a report from the Geant4-DNA Project. Medical Physics. 2018;45(8):e722-e739. https://doi.org/10.1002/mp.13048
  • 11. Bernal MA, Bordage MC, Brown JMC, 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. Physica Medica. 2015;31(8):861-874. https://doi.org/10.1016/j.ejmp.2015.10.087
  • 12. Strulab D, Santin G, Lazaro D, Breton V, Morel C. GATE (Geant4 Application for Tomographic Emission): a PET/SPECT general-purpose simulation platform. Nuclear Physics B-Proceedings Supplements. 2003;128:75-79. https://doi.org/10.1016/S0920-5632(03)90969-8
  • 13. Ziegler JF, Ziegler MD, Biersack JP. SRIM-The stopping and range of ions in matter. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms. 2010;268(11-12):1818-1823. https://doi.org/10.1016/j.nimb.2010.02.091
  • 14. Winberg M, Garcia R. National low-level waste management program radionuclide report series, Volume 14: Americium-241. Technical report, EG and G Idaho, 1995. https://doi.org/10.2172/130651
  • 15. Grilj V, Brenner DJ. LET dependent response of GafChromic films investigated with MeV ion beams. Physics in Medicine and Biology. 2018;63(24):245021. https://doi.org/10.1088/1361-6560/aaf34a
  • 16. Low DA, Harms WB, Mutic S, Purdy JA. A technique for the quantitative evaluation of dose distributions. Medical Physics. 1998;25(5):656-661. https://doi.org/10.1118/1.598248
  • 17. Brzozowska B, Gałecki M, Tartas A, Ginter J, Kaźmierczak U, Lundholm L. Freeware tool for analysing numbers and sizes of cel colonies. Radiation and Environmental Biophysics. 2019:58:109-117. https://doi.org/10.1007/s00411-018-00772-z
  • 18. Elgqvist J, Timmermand O, Larsson E, Strand SE. Radiosensitivity of Prostate Cancer Cell Lines for Irradiation from Beta Particle-emitting Radionuclide Lu-177 Compared to Alpha Particles and Gamma Rays. Anticancer Research. 2016;36(1):103-109.
  • 19. Nilsson J, Bauden MP, Nilsson JM, Strand SE, Elgqvist J. Cancer Cell Radiobiological Studies Using In-House-Developed –Particle Irradiator. Cancer Biotherapy and Radiopharmaceuticals. 2015;30(9):386-394. https://doi.org/10.1089/cbr.2015.1895
  • 20. Stenerlöw B, Pettersson OA, Essand M, Blomquist E, Carlsson, J. Irregular variations in radiation sensitivity when the linear Energy transfer is increased. Radiotherapy and Oncology. 1995;36(2):133-142. https://doi.org/10.1016/0167-8140(95)01591-4
  • 21. Hussein M, Rowshanfarzad P, Ebert M, Nisbet A, Clark C. A comparison of the gamma index analysis in various commercial IMRT/VMAT QA systems. Radiology and Oncology. 2013;109(3):370-376. https://doi.org/10.1016/j.radonc.2013.08.048
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-13d6eae3-67d8-4c1d-8ce9-0cf9cf87ba22
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