|
Estimating the relative biological effectiveness of light ions using TOPAS monte carlo simulation
|
M. Arif Efendi   , D. Sakata , Y.C. Keat |
| Department of Biomedical Imaging, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Penang, Malaysia , ckying7@usm.my |
|
|
Abstract: (792 Views) |
Background: This paper presents a Monte Carlo (MC) simulation study estimating Relative Biological Effectiveness at a 10% survival fraction (RBE10) of light ion beams by means of microdosimetric approach. Microdosimetric parameters for estimating Relative Biological Effectiveness (RBE) were determined through the utilisation of the Tool for Particle Simulation (TOPAS) MC simulations. These simulations incorporated a 3D silicon on insulator (SOI) Bridge microdosimeter model. Materials and Methods: The incident 176.8 MeV proton and 176.4 MeV/u helium ion beams were simulated at different depths within a water phantom. The microdosimetric aspects, such as уF ̅ and уD ̅ at different depths along the fields were predicted from simulations. The RBE10 were derived using simulated microdosimetric spectra as inputs to the modified Microdosimetric Kinetic Model (MKM). Results: Simulated уD ̅ distributions for proton and helium ion beams in water were about 4 keV/µm and 4 to 8 keV/µm at the plateau region, respectively and around 7 to 14 keV/µm and 35 to 56 keV/µm at the Bragg peak (BP) region, respectively. In the tail region уD ̅ values were increasing from 5 keV/µm to 10 keV/µm and 7 keV/µm to 14 keV/µm at depths of 224 mm to 250 mm, respectively. Conclusion: The RBE10 for protons exhibit a range of 0.99 to 1.22, which differs from the standard practice of using a fixed RBE of 1.1 in the Treatment Planning System (TPS) for proton therapy. The simulation results in this study may be used as an outlook for radiobiological experiments in the NASA Space Radiation Laboratory (NSRL). |
|
| Keywords: Helium ion, Modified MKM, NSRL, Proton, TOPAS. |
|
|
Full-Text [PDF 1224 kb]
(253 Downloads)
|
|
Type of Study: Original Research |
Subject:
Radiation Biology
|
|
|
|
|
|
|
| References |
|
1. 1. Ekinci F, Bostanci E, Güzel MS, Dagli O (2023) Simulation based analysis of 4He, 7Li, 8Be and 10B ions for heavy ion therapy. International Journal of Radiation Research, 21(1): 131-137. 2. Mohan R (2022) A review of proton therapy - Current status and future directions. Precision Radiation Oncology, 6(2): 164-176. [ DOI:10.1002/pro6.1149] 3. Ebner DK, Frank SJ, Inaniwa T, Yamada S & Shirai T (2021) The Emerging Potential of Multi-Ion Radiotherapy. Frontiers in Oncology, 11. [ DOI:10.3389/fonc.2021.624786] 4. La Tessa C, Sivertz M, Chiang IH, Lowenstein D & Rusek A (2016) Overview of the NASA space radiation laboratory. Life Sciences in Space Research, 11: 18-23. [ DOI:10.1016/j.lssr.2016.10.002] 5. Held KD, Blakely EA, Story MD & Lowenstein DI (2016) Use of the NASA Space Radiation Laboratory at Brookhaven National Laboratory to Conduct Charged Particle Radiobiology Studies Relevant to Ion Therapy. Radiation Research, 185(6): 563-567. [ DOI:10.1667/RR14412.1] 6. Burigo L, Gehrke T, J kel O, Sivertz M, Olsen T, Rusek A, Obcemea C & Greilich S (2020) Beam characterization at NSRL for radiobiological experiments. Phase 1. Journal of Instrumentation, 15(10): T10004. [ DOI:10.1088/1748-0221/15/10/T10004] 7. Kase Y, Kanai T, Matsumoto Y, Furusawa Y, Okamoto H, Asaba T, Sakama M & Shinoda H (2006) Microdosimetric measurements and estimation of human cell survival for heavy-ion beams. Radiation Research, 166(4): 629-638. [ DOI:10.1667/RR0536.1] 8. Newhauser W (2009) International Commission on Radiation Units and Measurements Report 78: Prescribing, Recording and Reporting Proton-beam Therapy. Radiation Protection Dosimetry, 133(1): 60-62. [ DOI:10.1093/rpd/ncp005] 9. Mohan R, Peeler CR, Guan F, Bronk L, Cao W & Grosshans DR (2017) Radiobiological issues in proton therapy. Acta Oncologica, 56(11): 1367-1373 [ DOI:10.1080/0284186X.2017.1348621] 10. Zaider M (1991) Elements of microdosimetry. Medical Physics, 18(6): 1085-1092. [ DOI:10.1118/1.596616] 11. De Nardo L, Cesari V, Donà G, Magrin G, Colautti P, Conte V & Tornielli G (2004) Mini-TEPCs for radiation therapy. Radiation Protection Dosimetry, 108(4): 345-352. [ DOI:10.1093/rpd/nch023] 12. Verona C, Magrin G, Solevi P, Bandorf M, Marinelli M, Stock M & Verona Rinati G (2018) Toward the use of single crystal diamond based detector for ion-beam therapy microdosimetry. Radiation Measurements, 110: 25-31. [ DOI:10.1016/j.radmeas.2018.02.001] 13. Agosteo S, Fallica PG, Fazzi A, Pola A, Valvo G & Zotto P (2005) A feasibility study of a solid-state microdosimeter. Applied Radiation and Isotopes, 63(5-6 SPEC. ISS.): 529-535. [ DOI:10.1016/j.apradiso.2005.05.001] 14. Galer S, Hao L, Gallop J, Palmans H, Kirkby K & Nisbet A (2011) Design concept for a novel SQUID-based microdosemeter. Radiation Protection Dosimetry, 143(2-4): 427-431. [ DOI:10.1093/rpd/ncq475] 15. Bradley PD, Rosenfeld AB, Allen B, Coderre J & Capala J (1999) Performance of silicon microdosimetry detectors in boron neutron capture therapy. Radiation Research, 151(3): 235-243. [ DOI:10.2307/3579934] 16. Nikjoo H (2003). Radiation track and DNA damage. International Journal of Radiation Research, 1(1): 14-17. [ DOI:10.1063/1.1516320] 17. Fassó A, Ferrari A, Sala PR & Ranft J (2001) FLUKA: Status and prospects for hadronic applications. Advanced Monte Carlo for Radiation Physics, Particle Transport Simulation and Applications (pp. 955-960), Springer. [ DOI:10.1007/978-3-642-18211-2_153] 18. Agostinelli S, Allison J, Amako K, Apostolakis J, Araujo H, Arce P, et al. (2003) GEANT4 - A simulation toolkit. Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 506(3): 250-303. [ DOI:10.1016/S0168-9002(03)01368-8] 19. Allison J, Amako K, Apostolakis J, Araujo H, Dubois PA, Asai M, et al. (2006) Geant4 developments and applications. IEEE Transactions on Nuclear Science, 53(1): 270-278. [ DOI:10.1109/TNS.2006.869826] 20. Allison J, Amako K, Apostolakis J, Arce P, Asai M, Aso T, et al. (2016) Recent developments in GEANT4. Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 835: 186-225. [ DOI:10.1016/j.nima.2016.06.125] 21. Ganjeh AZ, Eslami-Kalantari M, Ebrahimi Loushab M, Mowlavi AA (2020) Investigation of the direct DNA damages irradiated by protons of different energies using geant4-DNA toolkit. International Journal of Radiation Research, 18(4): 809-815. [ DOI:10.52547/ijrr.18.4.809] 22. Goorley T, James M, Booth T, Brown F, Bull J, Cox LJ, et al. (2012) Initial MCNP6 release overview. Nuclear Technology, 180(3): 298-315. [ DOI:10.13182/NT11-135] 23. Pshenichnov, I, Mishustin, I, & Greiner, W (2007) MCHIT - Monte Carlo model for proton and Heavy-Ion Therapy. International Conference on Nuclear Data for Science and Technology, 1343-1346. [ DOI:10.1051/ndata:07214] 24. Burigo L, Pshenichnov I, Mishustin I & Bleicher M (2013) Microdosimetry of radiation field from a therapeutic 12C beam in water: A study with Geant4 toolkit. Nuclear Instruments and Methods in Physics Research, Section B: Beam Interactions with Materials and Atoms, 310: 37-53. [ DOI:10.1016/j.nimb.2013.05.021] 25. Zhu H, Chen Y, Sung W, McNamara AL, Tran LT, Burigo LN, et al. (2019) The microdosimetric extension in TOPAS: Development and comparison with published data. Physics in Medicine and Biology, 64(14): 15. [ DOI:10.1088/1361-6560/ab23a3] 26. Bolst D, Guatelli S, Tran LT, Chartier L, Davis J, Biasi G, et al. (2020) Validation of Geant4 for silicon microdosimetry in heavy ion therapy. Physics in Medicine and Biology, 65(4): 045014. [ DOI:10.1088/1361-6560/ab586a] 27. Taddei PJ, Zhao Z & Borak TB (2008) A comparison of the measured responses of a tissue-equivalent proportional counter to high energy heavy (HZE) particles and those simulated using the Geant4 Monte Carlo code. Radiation Measurements, 43(9-10): 1498-1505. [ DOI:10.1016/j.radmeas.2008.09.003] 28. Eulitz J, Lutz B, Wohlfahrt P, Dutz A, Enghardt W, Karpowitz C, et al. (2019) A Monte Carlo based radiation response modelling framework to assess variability of clinical RBE in proton therapy. Physics in Medicine and Biology, 64(22): 225020. [ DOI:10.1088/1361-6560/ab3841] 29. Bronk L, Guan F, Patel D, Ma D, Kroger B, Wang X, et al. (2020) Mapping the relative biological effectiveness of proton, helium and carbon ions with high-throughput techniques. Cancers, 12(12): 1-15. [ DOI:10.3390/cancers12123658] 30. Mein S, Dokic I, Klein C, Tessonnier T, Böhlen TT, Magro G, et al. (2019) Biophysical modeling and experimental validation of relative biological effectiveness (RBE) for 4He ion beam therapy. Radiation Oncology, 14(1): 1-16. [ DOI:10.1186/s13014-019-1295-z] 31. Debrot E, Tra, L, Chartier L, Bolst D, Guatelli S, Vandevoorde C, et al. (2018) SOI microdosimetry and modified MKM for evaluation of relative biological effectiveness for a passive proton therapy radiation field. Physics in Medicine and Biology, 63(23): 235007. [ DOI:10.1088/1361-6560/aaec2f] 32. Lee SH, Mizushima K, Yonai S, Matsumoto S, Mizuno H, Nakaji T, et al. (2022) Predicting the Biological Effects of Human Salivary Gland Tumour Cells for Scanned 4He‐, 12C‐, 16O‐ and 20Ne‐Ion Beams Using an SOI Microdosimeter. Applied Sciences, 12(12): 6148. [ DOI:10.3390/app12126148] 33. Perl J, Shin J, Schümann J, Faddegon B & Paganetti H (2012) TOPAS: An innovative proton Monte Carlo platform for research and clinical applications. Medical Physics, 39(11): 6818-6837. [ DOI:10.1118/1.4758060] 34. Faddegon B, Ramos-Méndez J, Schuemann J, McNamara A, Shin J, Perl J & Paganetti H (2020) The TOPAS tool for particle simulation, a Monte Carlo simulation tool for physics, biology and clinical research. Physica Medica, 72(November 2019): 114-121. [ DOI:10.1016/j.ejmp.2020.03.019] 35. Bolst D, Guatelli S, Tran LT, Chartier L, Lerch MLF, Matsufuji N, Rosenfeld AB (2017) Correction factors to convert microdosimetry measurements in silicon to tissue in 12C ion therapy. Physics in Medicine and Biology, 62(6): 2055-2069. [ DOI:10.1088/1361-6560/aa5de5] 36. Parisi G, Schettino G & Romano F (2022) A systematic study of the contribution of counting statistics to the final lineal energy uncertainty in microdosimetry. Physics in Medicine and Biology, 67(15): 155002. [ DOI:10.1088/1361-6560/ac79fb] 37. Tran LT, Chartier L, Bolst D, Pogossov A, Guatelli S, Petasecca M, et al. (2017) Characterization of proton pencil beam scanning and passive beam using a high spatial resolution solid-state microdosimeter. Medical Physics, 44(11): 6085-6095. [ DOI:10.1002/mp.12563] 38. Horst F, Schardt D, Iwase H, Schuy C, Durante M, Weber U (2021) Physical characterization of 3He ion beams for radiotherapy and comparison with 4He. Physics in Medicine and Biology, 66(9). [ DOI:10.1088/1361-6560/abef88] |
|
| Send email to the article author |
|
|
|
| Add your comments about this article |
|
|
|
|
Arif Efendi M, Sakata D, Keat Y. Estimating the relative biological effectiveness of light ions using TOPAS monte carlo simulation. Int J Radiat Res 2024; 22 (3) :703-709 URL: http://ijrr.com/article-1-5640-en.html
|
