Radiation Physics and Engineering
A peer-reviewed journal published by K. N. Toosi University of Technology

‎Microscopic RBE estimation in proton therapy using TOPAS-nBio‎: ‎Impact of physics models and DNA damage energy threshold

Document Type : Research Article

Authors

Hadi Nakhzari Moghadam
Mohammad Mohammadzadeh

Department of Radiation in Medicine‎, ‎Shahid Beheshti University‎, ‎Tehran‎, ‎Iran

https://doi.org/10.22034/rpe.2025.542780.1294
Abstract
Relative Biological Effectiveness (RBE) is a key factor in proton therapy, yet its current fixed clinical value of 1.1 may not adequately represent biological effects at the microscopic level. In this study, we employed the TOPAS-nBio Monte Carlo toolkit to simulate DNA damage and calculate RBE based on various biological endpoints, including direct and indirect double-strand breaks (DSBs), and simple versus complex DSBs. Simulations were performed across multiple proton energies (1-64 MeV) using three physics constructors and two energy threshold models for strand break induction. Validation against reference and experimental data showed less than 5% deviation, with "DNA Physics Option 2" and a linear energy threshold of 5-37.5 eV yielding the most consistent results. Similarly, "DNA Physics Option 4 and 6" with a fixed energy threshold of 17.5 eV align well with experimental and simulation reference data. RBE values were found to vary significantly with damage type and simulation parameters, with total DSBs providing the most biologically relevant estimates, reaching a maximum of 1.9 for low-energy protons. The study also revealed that both direct and indirect damage alone may underestimate biological effectiveness. Differences in RBE across physics constructors reached up to 30.8%, emphasizing the need for careful model selection. These findings support replacing the fixed RBE with a more nuanced, DNA damage-based approach in treatment planning systems. Incorporating microscopic RBE modeling could enhance the biological accuracy of proton therapy and ultimately improve patient outcomes.

Highlights

  • Proton RBE varies up to nearly 2.8 at low energies.
  • Physics model choice causes RBE differences up to 30.8%.
  • Total DSBs are the most reliable RBE endpoint.
  • Linear SSB threshold (5-37.5 eV) yields robust results.
  • Microscopic modeling can improve proton therapy planning.

Keywords

Proton therapy
RBE
DNA damage
Monte Carlo simulation
TOPAS

Copyright
RPE is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).

Conflict of Interest
The authors declare no potential conflict of interest regarding the publication of this work‎.

Funding
‎The authors declare that no funds‎, ‎grants‎, ‎or other financial support were received during the preparation of this manuscript‎.

Belli, M., Cherubini, R., Dalla Vecchia, M. a., et al. (2001). DNA fragmentation in mammalian cells exposed to various light ions. Advances in Space Research, 27(2):393–399.
Bernal, M. A., Bordage, M. C., Brown, J. M. C., et al. (2015). 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, 31(8):861–874.
Bordage, M., Bordes, J., Edel, S., et al. (2016). Implementation of new physics models for low energy electrons in liquid water in Geant4-DNA. Physica Medica, 32(12):1833–1840.
Campa, A., Dini, V., and Esposito, G. o. (2003). DNA dsb induced in mammalian cells by charged particles and gamma rays: experimental results and theoretical approaches. In 9th HCPBM Workshop and ENLIGHT Meeting, pages 5–5.
Chappuis, F., Grilj, V., Tran, H. N., et al. (2023). Modeling of scavenging systems in water radiolysis with Geant4-DNA. Physica Medica, 108:102549.
Chattaraj, A. and Selvam, T. P. (2024). Calculation of biological effectiveness of SOBP proton beams: a TOPAS Monte Carlo study. Biomedical Physics & Engineering Express, 10(3):035004.
Chatzipapas, K. P., Tran, N. H., Dordevic, M., et al. (2023). Simulation of DNA damage using Geant4-DNA: an overview of the “molecularDNA” example application. Precision Radiation Oncology, 7(1):4–14.
Chaudhary, P., Marshall, T. I., Currell, F. J., et al. (2016). Variations in the processing of DNA double-strand breaks along 60-MeV therapeutic proton beams. International Journal of Radiation Oncology* Biology* Physics, 95(1):86–94.
Friedland, W., Kundrát, P., and Jacob, P. (2012). Stochastic modelling of DSB repair after photon and ion irradiation. International Journal of Radiation Biology, 88(1-2):129–136.
Friedland, W., Schmitt, E., Kundrát, P., et al. (2017). Comprehensive track-structure based evaluation of DNA damage by light ions from radiotherapy-relevant energies down to stopping. Scientific Reports, 7(1):45161.
Incerti, S., Baldacchino, G., Bernal, M., et al. (2010). The GEANT4-DNA project. International Journal of Modeling, Simulation, and Scientific Computing, 1(02):157–178.
Incerti, S., Kyriakou, I., Bernal, M., et al. (2018). Geant4-DNA example applications for track structure simulations in liquid water: a report from the Geant4-DNA Project. Medical Physics, 45(8):e722–e739.
Karamitros, M., Luan, S., Bernal, M. A., et al. (2014). Diffusion-controlled reactions modeling in Geant4-DNA. Journal of Computational Physics, 274:841–882.
Kyriakou, I., Incerti, S., and Francis, Z. (2015). Improvements in geant4 energy-loss model and the effect on low-energy electron transport in liquid water. Medical Physics, 42(7):3870–3876.
Lampe, N., Karamitros, M., Breton, V., et al. (2018). Mechanistic DNA damage simulations in Geant4-DNA part 1: A parameter study in a simplified geometry. Physica Medica, 48:135–145.
McMahon, S. J. (2021). Proton RBE models: commonalities and differences.
Physics in Medicine & Biology, 66(4):04NT02.
McNamara, A. L., Ramos-Méndez, J., Perl, J., et al. (2018). Geometrical structures for radiation biology research as implemented in the TOPAS-nBio toolkit. Physics in Medicine & Biology, 63(17):175018.
Nikjoo, H., Taleei, R., Liamsuwan, T., et al. (2016). Perspectives in radiation biophysics: from radiation track structure simulation to mechanistic models of DNA damage and repair. Radiation Physics and Chemistry, 128:3–10.
Paganetti, H. (2014). Relative biological effectiveness (RBE) values for proton beam therapy. variations as a function of biological endpoint, dose, and linear energy transfer. Physics in Medicine & Biology, 59(22):R419.
Paganetti, H., Niemierko, A., Ancukiewicz, M., et al. (2002). Relative biological effectiveness (RBE) values for proton beam therapy. International Journal of Radiation Oncology* Biology* Physics, 53(2):407–421.
Parisi, A., Furutani, K. M., and Beltran, C. J. (2025). The Abridged Microdosimetric Distribution Methodology for flexible and efficient relative biological effectiveness calculations in ion radiotherapy. Physics in Medicine & Biology, 70(21):215027.
Perl, J., Shin, J., Schümann, J., et al. (2012). TOPAS: an innovative proton Monte Carlo platform for research and clinical applications. Medical Physics, 39(11):6818–6837.
Plante, I. and Devroye, L. (2017). Considerations for the independent reaction times and step-by-step methods for radiation chemistry simulations. Radiation Physics and Chemistry, 139:157–172.
Rafiepour, P., Sina, S., Amoli, Z. A., et al. (2024). A mechanistic simulation of induced DNA damage in a bacterial cell by X-and gamma rays: a parameter study. Physical and Engineering Sciences in Medicine, 47(3):1015–1035.
Ramos-Méndez, J., Shin, W.-g., Karamitros, M., et al. (2020). Independent reaction times method in Geant4-DNA: Implementation and performance. Medical Physics, 47(11):5919–5930.
Sakata, D., Hirayama, R., Shin, W.-G., et al. (2023). Prediction of DNA rejoining kinetics and cell survival after proton irradiation for V79 cells using Geant4-DNA. Physica Medica, 105:102508.
Schuemann, A. J., Mcnamara, A., Perl, J., et al. (2019). TOPAS-nBio: An Extension to the TOPAS Simulation Toolkit for Cellular and Sub-cellular Radiobiology TOPAS-nBio: An Extension to the TOPAS Simulation Toolkit for Cellular and Sub-cellular Radiobiology.
Shin, W.-G., Ramos-Mendez, J., Faddegon, B., et al. (2019). Evaluation of the influence of physical and chemical parameters on water radiolysis simulations under MeV electron irradiation using Geant4-DNA. Journal of Applied Physics, 126(11).
Sotiropoulos, M., Taylor, M., Henthorn, N., et al. (2017). Geant4 interaction model comparison for dose deposition from gold nanoparticles under proton irradiation. Biomedical Physics & Engineering Express, 3(2):025025.
Tommasino, F. and Durante, M. (2015). Proton radiobiology. Cancers, 7(1):353–381.
Tung, C.-J. (2015). Microdosimetric relative biological effectiveness of therapeutic proton beams. Biomedical Journal, 38(5).
Vafapour, H., Rafiepour, P., Moradgholi, J., et al. (2025). Evaluating the biological impact of shelters on astronaut health during different solar particle events: A Geant4-DNA simulation study. Radiation and Environmental Biophysics, 64(1):137–150.
Wang, C.-C., Hsiao, Y., Lee, C.-C., et al. (2012). Monte Carlo simulations of therapeutic proton beams for relative biological effectiveness of double-strand break. International Journal of Radiation Biology, 88(1-2):158–163.
Zhu, H., McNamara, A. L., McMahon, S. J., et al. (2020a). Cellular response to proton irradiation: a simulation study with TOPAS-nBio. Radiation Research, 194(1):9–21.
Zhu, H., McNamara, A. L., Ramos-Mendez, J., et al. (2020b). A parameter sensitivity study for simulating DNA damage after proton irradiation using TOPAS-nBio. Physics in Medicine & Biology, 65(8):085015.
Radiation Physics and Engineering
Volume 7, Issue 1
Winter 2026
Pages 27-38

  • Receive Date 22 August 2025
  • Revise Date 27 October 2025
  • Accept Date 16 November 2025

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