Encyclopedia of Bioastronautics

Living Edition
| Editors: Laurence R. Young, Jeffrey P. Sutton

Particle Track Structure and Biological Implications

  • Dudley T. GoodheadEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-10152-1_29-1


The track structure of an ionizing charged particle is the stochastic spatial pattern of the inelastic interactions of the particle and all associated secondary charged particles as they pass through matter and impart energy to the molecules or atoms with which they interact. It is this track structure pattern of interactions that sets the initial conditions from which follow the subsequent physico-chemical, chemical, biochemical, and biological consequences of the radiation. Differences in track structure between different types and energies of ionizing radiation can lead to differences in biological consequences, quantitatively and qualitatively.


Track structure is the key property that gives ionizing radiation its considerable potency in causing biological effects and determines the relative effectiveness of different types of radiation for a wide variety of effects. The tracks are the stochastic patterns of the interactions of the charged particles as they...

This is a preview of subscription content, log in to check access.


  1. Alloni D, Mariotti LG, Ottolenghi A (2014) Early events leading to radiation-induced biological effects. In: Brahme A (ed) Comprehensive biomedical physics, vol 7. Elsevier, Amsterdam, pp 1–22Google Scholar
  2. Alp M, Parihar VK, Limoli CL, Cucinotta FA (2015) Irradiation of neurons with high-energy charged particles: an in silico modelling approach. PLoS Comput Biol 11(8):e1004428.  https://doi.org/10.1371/journal.pcbi.1004428CrossRefGoogle Scholar
  3. Anderson RA, Stevens DL, Goodhead DT (2002) M-FISH analysis shows that complex chromosome aberrations induced by α-particle tracks are cumulative products of localized rearrangements. Proc Natl Acad Sci 99:12167–12172CrossRefGoogle Scholar
  4. Berger MJ, Coursey JS, Zucker MA, Chang J (2005) ESTAR, PSTAR, and ASTAR: computer programs for calculating stopping-power and range tables for electrons, protons, and helium ions (version 1.2.3). National Institute of Standards and Technology. http://physics.nist.gov/Star. Accessed 19 Aug 2015
  5. Bichsel H, Groom DE, Klein SR (2014) Passage of charged particles through matter. Chapter 32 of Olive KA et al (Particle Data Group) Review of particle physics. Chinese Physics C38: 090001. IOP Publishing, Bristol, UKGoogle Scholar
  6. Cucinotta FA (2015) Review of NASA approach to space radiation risk assessments for Mars exploration. Health Phys 108:131–142CrossRefGoogle Scholar
  7. Cucinotta FA, Durante M (2006) Cancer risk from exposure to galactic cosmic rays: implications for space exploration by human beings. Lancet Oncol 7(5):431–435CrossRefGoogle Scholar
  8. Cucinotta FA, Nikjoo N, Goodhead DT (1999) Applications of amorphous track models in radiation biology. Radiat Environ Biophys 38:81–92CrossRefGoogle Scholar
  9. Cucinotta FA, Nikjoo H, Goodhead DT (2000) Model for radial dependence of frequency distributions for energy imparted in nanometer volumes from HZE particles. Radiat Res 153:459–468CrossRefGoogle Scholar
  10. Cucinotta FA, Plante I, Ponomarev AL, Kim MH (2011) Nuclear interactions in heavy ion transport and event-based risk models. Radiat Prot Dosim 143:384–390CrossRefGoogle Scholar
  11. Cucinotta FA, Kim M-HY, Chappell LJ (2013) Space radiation cancer risk projections and uncertainties – 2012. NASA TP-2013-217375. National Aeronautics and Space Administration, Washington, DCGoogle Scholar
  12. Cucinotta FA, Alp M, Sulzman FM, Wang M (2014) Space radiation risks to the central nervous system. Life Sci Space Res 2:54–69CrossRefGoogle Scholar
  13. Curtis SB (2013) Fluence rates, delta rays and cell nucleus hit rates from galactic cosmic rays. The Health Risks of Extraterrestrial Environments. http://three.jsc.nasa.gov/articles/TracksinSpace.pdf. Posted 2/28/2013. Accessed 28 Aug 2015
  14. Dingfelder M (2012) Track-structure simulations for charged particles. Health Phys 103:590–595CrossRefGoogle Scholar
  15. Dingfelder M (2014) Monte Carlo track simulations. The Health Risks of Extraterrestrial Environments. http://three.jsc.nasa.gov/articles/monte-carlo-Dingfelder.pdf. Posted 2/6/14. Accessed 28 Aug 2015
  16. Durante M, Cucinotta FA (2008) Heavy ion carcinogenesis and human space exploration. Nat Rev 8:465–472CrossRefGoogle Scholar
  17. Durante M, Cucinotta FA (2011) Physical basis of radiation protection in space travel. Rev Mod Phys 83:1245–1281CrossRefGoogle Scholar
  18. Friedland W, Dingfelder M, Kundrat P, Jacob P (2011) Track structures, DNA targets and radiation effects in the biophysical Monte Carlo simulation code PARTRAC. Mutat Res 711:28–40CrossRefGoogle Scholar
  19. Goodhead DT (1987) Relationship of microdosimetric techniques to applications in biological systems. In: Kase KR, Bjarngard BE, Attix FH (eds) The dosimetry of ionizing radiation, vol 2. Academic, New York, pp 1–89Google Scholar
  20. Goodhead DT (1988) Spatial and temporal distribution of energy. Health Phys 55:231–240CrossRefGoogle Scholar
  21. Goodhead DT (1992) Track structure considerations in low dose and low dose rate effects of ionizing radiation. In: Nygaard OF, Sinclair WK (eds) Advances in radiation biology, Vol. 16: Low level radiation effects. Academic, Orlando, pp 7–44Google Scholar
  22. Goodhead DT (1999) Mechanisms for the biological effectiveness of high-LET radiations. J Radiat Res (Japan) 40(Suppl):1–13Google Scholar
  23. Goodhead DT (2009) Fifth Warren K. Sinclair keynote address: issues in quantifying the effects of low-level radiation. Health Phys 97:394–406CrossRefGoogle Scholar
  24. Goodhead DT (2015) Classical approaches to microdosimetry, with examples of use in radiation protection, medicine and mechanistic understanding. Radiat Prot Dosim 166:276–281.  https://doi.org/10.1093/rpd/ncv194CrossRefGoogle Scholar
  25. Goodhead DT (2018) Track structure and the quality factor for space radiation cancer risk. http://three.jsc.nasa.gov/articles/Track_QF_Goodhead.pdf. Posted 9/28/2018. Accessed 10 Dec 2018
  26. Nikjoo H, Charlton D, Goodhead DT (1994) Monte Carlo track structure studies of energy deposition and calculation of initial DSB and RBE. Adv Space Res 14:161–180CrossRefGoogle Scholar
  27. Plante I, Cucinotta FA (2008) Ionization and excitation cross sections for the interaction of HZE particles in liquid water and application to Monte-Carlo simulation of radiation tracks. New J Phys 10.  https://doi.org/10.1088/1367-2630/10/12/125020CrossRefGoogle Scholar
  28. Plante I, Cucinotta FA (2009) Cross sections for the interactions of 1 eV-100 MeV electrons in liquid water and application to Monte-Carlo simulation of HZE tracks. New J Phys 11.  https://doi.org/10.1088/1367-2630/11/6/063047CrossRefGoogle Scholar
  29. Sridharan DM, Chappell LJ, Whalen MK, Cucinotta FA, Pluth JM (2015) Defining the biological effectiveness of components of high-LET track structure. Radiat Res 184:105–119CrossRefGoogle Scholar
  30. Tavernier S (2010) Experimental techniques in nuclear and particle physics. Springer, BerlinCrossRefGoogle Scholar
  31. Toburen L (2014) Development of Monte Carlo track structure codes. The Health Risks of Extraterrestrial Environmnents. http://three.jsc.nasa.gov/articles/Monte-Carlo-Track-Structure-Toburen.pdf. Posted 2/6/14. Accessed 28 Aug 2015

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Medical Research Council, HarwellDidcotUK

Section editors and affiliations

  • Kathryn D. Held
    • 1
  1. 1.Radiation OncologyMassachusetts General Hospital/Harvard Medical SchoolBostonUSA