Mapping neutron biological effectiveness for DNA damage induction as a function of incident energy and depth in a human sized phantom
Jazyk angličtina Země Anglie, Velká Británie Médium electronic
Typ dokumentu časopisecké články
PubMed
39820036
PubMed Central
PMC11739508
DOI
10.1038/s41598-025-85879-2
PII: 10.1038/s41598-025-85879-2
Knihovny.cz E-zdroje
- MeSH
- dvouřetězcové zlomy DNA účinky záření MeSH
- fantomy radiodiagnostické * MeSH
- lidé MeSH
- metoda Monte Carlo * MeSH
- neutrony * MeSH
- poškození DNA * MeSH
- relativní biologická účinnost * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
We present new developments for an ab-initio model of the neutron relative biological effectiveness (RBE) in inducing specific classes of DNA damage. RBE is evaluated as a function of the incident neutron energy and of the depth inside a human-sized reference spherical phantom. The adopted mechanistic approach traces neutron RBE back to its origin, i.e. neutron physical interactions with biological tissues. To this aim, we combined the simulation of radiation transport through biological matter, performed with the Monte Carlo code PHITS, and the prediction of DNA damage using analytical formulas, which ground on a large database of biophysical radiation track structure simulations performed with the code PARTRAC. In particular, two classes of DNA damage were considered: sites and clusters of double-strand breaks (DSBs), which are known to be correlated with cell fate following radiation exposure. Within a coherent modelling framework, this approach tackles the variation of neutron RBE in a wide energy range, from thermal neutrons to neutrons of hundreds of GeV, and reproduces effects related to depth in the human-sized receptor, as well as to the receptor size itself. Besides providing a better mechanistic understanding of neutron biological effectiveness, the new model can support better-informed decisions for radiation protection: indeed, current neutron weighting (ICRP)/quality (U.S. NRC) factors might be insufficient for use in some radiation protection applications, because they do not account for depth. RBE predictions obtained with the reported model were successfully compared to the currently adopted radiation protection standards when the depth information is not relevant (at the shallowest depth in the phantom or for very high energy neutrons). However, our results demonstrate that great care is needed when applying weighting factors as a function of incident neutron energy only, not explicitly considering RBE variation in the target. Finally, to facilitate the use of our results, we propose look-up RBE tables, explicitly considering the depth variable, and an analytical representation of the maximal RBE vs. neutron energy.
ASI Italian Space Agency Rome Italy
Department of Radiation Dosimetry Nuclear Physics Institute Czech Academy of Sciences Prague Czechia
Physics Department University of Roma Tor Vergata Rome Italy
Radiation Biophysics and Radiobiology Laboratory Physics Department University of Pavia Pavia Italy
Zobrazit více v PubMed
Knoll, G. F. Radiation Detection and Measurement/Glenn F. Knoll (Wiley, 1989).
Hall, E. & Giaccia, A. Radiobiology for the Radiologist (Wolters Kluwer Health, 2012).
ICRP, 1991. 1990 recommendations of the international commission on radiological protection. Ann. ICRP21, 60 (1991). PubMed
ICRP, 2007. The 2007 recommendations of the international commission on radiological protection. Ann. ICRP37, 103 (2007). PubMed
ICRP, 2003. Relative biological effectiveness (RBE), quality factor (Q), and radiation weighting factor ([Image: see text]). Ann. ICRP33, 92 (2003). PubMed
United States Nuclear Regulatory Commission. 10 CRF 20.1004, Units of Radiation Dose. Tech. Rep., U.S. NRC (2021).
Ottolenghi, A., Smyth, V. & Trott, K. Assessment of cancer risk from neutron exposure—the ANDANTE project. Radiat. Meas.57, 68–73. 10.1016/j.radmeas.2012.10.017 (2013).
Pihet, P., Menzel, H., Schmidt, R., Beauduin, M. & Wambersie, A. Biological Weighting Function for RBE Specification of Neutron Therapy Beams. Intercomparison of 9 European Centres. Radiat. Protect. Dosim.31, 437–442. 10.1093/oxfordjournals.rpd.a080709 (1990).
Gerlach, R., Roos, H. & M. Kellerer, A. Heavy ion RBE and microdosimetric spectra. Radiat. Protect. Dosim.99, 413–418. 10.1093/oxfordjournals.rpd.a006821 (2002). PubMed
Stewart, R. D. et al. Rapid MCNP simulation of DNA double strand break (DSB) relative biological effectiveness (RBE) for photons, neutrons, and light ions. Phys. Med. Biol.60, 8249–8274. 10.1088/0031-9155/60/21/8249 (2015). PubMed
Baiocco, G. et al. The origin of neutron biological effectiveness as a function of energy. Sci. Rep.6, 34033. 10.1038/srep34033 (2016). PubMed PMC
Montgomery, L., Lund, C. M., Landry, A. & Kildea, J. Towards the characterization of neutron carcinogenesis through direct action simulations of clustered DNA damage. Phys. Med. Biol.66, 205011. 10.1088/1361-6560/ac2998 (2021). PubMed
Zabihi, A. et al. Determination of fast neutron rbe using a fully mechanistic computational model. Appl. Radiat. Isotopes156, 108952. 10.1016/j.apradiso.2019.108952 (2020). PubMed
Sato, T. et al. Features of particle and heavy ion transport code system (PHITS) version 3.02. J. Nucl. Sci. Technol.55, 684–690. 10.1080/00223131.2017.1419890 (2018).
Kundrát, P. et al. Analytical formulas representing track-structure simulations on DNA damage induced by protons and light ions at radiotherapy-relevant energies. Sci. Rep.10, 15775. 10.1038/s41598-020-72857-z (2020). PubMed PMC
Alloni, D., Campa, A., Friedland, W., Mariotti, L. & Ottolenghi, A. Track structure, radiation quality and initial radiobiological events: considerations based on the PARTRAC code experience. IInt. J. Radiat. Biol.88, 77–86. 10.3109/09553002.2011.627976 (2012). PubMed
Friedland, W., Dingfelder, M., Kundrát, P. & Jacob, P. Track structures, DNA targets and radiation effects in the biophysical Monte Carlo simulation code PARTRAC. Mutat. Res.711, 28–40. 10.1016/j.mrfmmm.2011.01.003 (2011). PubMed
Friedland, W. et al. Comprehensive track-structure based evaluation of DNA damage by light ions from radiotherapy-relevant energies down to stopping. Sci. Rep.7, 45161. 10.1038/srep45161 (2017). PubMed PMC
Goodhead, D. T. Initial events in the cellular effects of ionizing radiations: clustered damage in DNA. Int. J. Radiat. Biol.65, 7–17 (1994). PubMed
Ward, J. The complexity of DNA damage: relevance to biological consequences. Int. J. Radiat. Biol.66, 427–432 (1994). PubMed
Georgakilas, A. G., O’Neill, P. & Stewart, R. D. Induction and repair of clustered DNA lesions: what do we know so far?. Radiat. Res.180, 100–109 (2013). PubMed
Hirayama, H. et al. The EGS5 code system. Tech. Rep., United States. Department of Energy (2005).
Iida, K., Kohama, A. & Oyamatsu, K. Formula for proton-nucleus reaction cross section at intermediate energies and its application. J. Phys. Soc. Jpn.76, 044201 (2007).
Ogawa, T., Sato, T., Hashimoto, S. & Niita, K. Development of a reaction ejectile sampling algorithm to recover kinematic correlations from inclusive cross-section data in Monte-Carlo particle transport simulations. Nucl. Instrum. Meth. A763, 575–590. 10.1016/j.nima.2014.06.088 (2014).
International Commission on Radiation Units & Measurements. ICRU Report 44: tissue substitutes in radiation dosimetry and measurement. J. ICRU23, 8596 (1989).
Sato, T., Watanabe, R., Sihver, L. & Niita, K. Applications of the microdosimetric function implemented in the macroscopic particle transport simulation code PHITS. Int. J. Radiat. Biol.88, 143–150. 10.3109/09553002.2011.611216 (2012). PubMed
International Commission on Radiation Units & Measurements. ICRU report 36: microdosimetry. J. ICRU27, 759 (1983).
Kellerer, A. M. Fundamentals of Microdosimetry (Academic Press Inc, 1985).
Nikjoo, H., O’Neill, P., Goodhead, D. & Terrissol, M. Computational modelling of low-energy electron-induced dna damage by early physical and chemical events. Int. J. Radiat. Biol.71, 467–483. 10.1080/095530097143798 (1997). PubMed
Nikjoo, H. & Liamsuwan, T. 9.03—biophysical basis of ionizing radiation. In Comprehensive Biomedical Physics (ed. Brahme, A.) 65–104 (Elsevier, 2014). 10.1016/B978-0-444-53632-7.00921-7.
Kundrát, P., Friedland, W. & Baiocco, G. Track structure-based simulations on DNA damage induced by diverse isotopes. Int. J. Mol. Sci.23, 7859. 10.3390/ijms232213693 (2022). PubMed PMC
Kreipl, M. S., Friedland, W. & Paretzke, H. G. Interaction of ion tracks in spatial and temporal proximity. Radiat. Environ. Biophys.48, 349–359. 10.1007/s00411-009-0234-z (2009). PubMed
Barnard, S., Bouffler, S. & Rothkamm, K. The shape of the radiation dose response for dna double-strand break induction and repair. Genome Integr.4, 1. 10.1186/2041-9414-4-1 (2013). PubMed PMC
Löbrich, M., Rydberg, B. & Cooper, P. K. Repair of x-ray-induced dna double-strand breaks in specific not i restriction fragments in human fibroblasts: joining of correct and incorrect ends. Proc. Natl. Acad. Sci.92, 12050–12054. 10.1073/pnas.92.26.12050 (1995). PubMed PMC
The MathWorks Inc. Optimization Toolbox version: R2022a, Natick, Massachusetts. https://www.mathworks.com (2022).
Geant4. https://geant4.cern.ch/ (2024).
Agostinelli, S. et al. Geant4-a simulation toolkit. Nucl. Instrum. Methods Phys. Res. Sect. A: Acceler. Spectrom. Detect. Assoc. Equip.506, 250–303. 10.1016/S0168-9002(03)01368-8 (2003).
Bellinzona, V. E. et al. Linking microdosimetric measurements to biological effectiveness in ion beam therapy: A review of theoretical aspects of mkm and other models. Front. Phys.8, 7859. 10.3389/fphy.2020.578492 (2021).
Kase, Y. et al. Microdosimetric measurements and estimation of human cell survival for heavy-ion beams. Radiat. Res.166, 629–638. 10.1667/RR0536.1 (2006). PubMed
Friedland, W., Kundrát, P., Schmitt, E., Becker, J. & Li, W. Modeling DNA damage by photons and light ions over energy ranges used in medical applications. Radiat. Protect. Dosimetry183, 84–88. 10.1093/rpd/ncy245 (2018). https://academic.oup.com/rpd/article-pdf/183/1-2/84/28670297/ncy245.pdf. PubMed
Kocher, D. & Hoffman, F. O. Ncrp report 181, evaluation of the relative effectiveness of low-energy photons and electrons in inducing cancer in humans: a critique and alternative analysis. Health Phys.116, 817–827. 10.1097/HP.0000000000001011 (2019). PubMed
ICRP, 2013. Assessment of radiation exposure of astronauts in space. Ann. ICRP42, 123 (2013). PubMed
Cross, W. & Ing, H. Conversion and quality factors relating neutron fluence and dosimetric quantities. Radiation Protection Dosimetry10, 29–42. 10.1093/oxfordjournals.rpd.a079409 (1985).
Stinchcomb, T. G. & Borak, T. B. Neutron quality parameters versus energy below 4 MeV from microdosimetric calculations. Radiat. Res.93, 1–18 (1983). PubMed
Paterson, L. C. et al. High-accuracy relative biological effectiveness values following low-dose thermal neutron exposures support bimodal quality factor response with neutron energy. Int. J. Mol. Sci.23, 1456. 10.3390/ijms23020878 (2022). PubMed PMC
Schneider, U., Hälg, R. A., Baiocco, G. & Lomax, T. Neutrons in proton pencil beam scanning: parameterization of energy, quality factors and RBE. Phys. Med. Biol.61, 6231–6242. 10.1088/0031-9155/61/16/6231 (2016). PubMed
Schneider, U., Hälg, R. A. & Lomax, T. Neutrons in active proton therapy: parameterization of dose and dose equivalent. Zeitschri. Med. Phys.27, 113–123. 10.1016/j.zemedi.2016.07.001 (2017). PubMed