Mechanistic bases for modelling space radiation risk and
planning radiation protection of astronauts
A. Ottolenghi, F. Ballarini, M. Biaggi
Dipartimento di Fisica -Università degli Studi di Milano and INFN -Sezione di Milano, via
Celoria 16, 20133 Milano (Italy)
Abstract
The approaches generally adopted for planning radiation protection in ground-based facilities
cannot be applied straightforward for astronaut protection in space. Indeed in such extreme
conditions, modelling methods and shielding design must be based on a detailed mechanistic
knowledge of the peculiar astronauts irradiation conditions. Great help can derive from
mechanistic modelling, generally aimed to better understand the intermediate steps leading from
the initial energy depositions to different biological endpoints, up to organ and organism level. In
the present work, criteria will be illustrated for using mechanistic approaches in developing
practical tools for astronauts radioprotection, once the external field and the interaction cross
sections with the spacecraft walls are known; particular attention will be given to the treatment of
mixed fields. Techniques for integrating into condensed-history codes stochastic information
provided by event-by-event simulations will be presented.
KEY WORDS: mechanistic models, radiobiological damage, astronauts radioprotection, mixed
fields.
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1. Introduction
Space radiation consists mainly of high energy ions originating from Van Allen belts, Galactic
Cosmic Radiation (GCR) and Solar Particle Events (SPE), which are injections of charged
particles associated with solar flare; SPE are quite rare, but their effects can be extremely severe
and their prediction is very difficult. Detailed information on space radiation features can be
found in [1]; the main aspects will be summarised below. While Van Allen belts consist
essentially of electrons and protons trapped in the Earth's geomagnetic field, both GCR and SPE
are formed mostly of high energy protons, with smaller components of helium and heavier nuclei
such as carbon and iron ions. More specifically, GCR consist of 87% protons, 12% alpha
particles and about 1% HZE particles, i.e. particles with Z > 2 and energies high enough to
penetrate at least 1 mm of the spacecraft walls; although HZE particles give a small contribution
to radiation flux, they can represent up to 50% of dose. The maximum energy of such particles is
of the order of 1000 GeV/n (but the spectrum is peaked around 1 GeV/n), and the maximum total
particle fluence of GCR (at solar minimum) is about 4 cm-2 s-1. Solar Particle Events can generate
more than 108 particles/cm2, with energies up to 1 GeV/n; it has been estimated that the large
solar flare occurred in August 1972 would be lethal for an unprotected crew on the lunar surface.
While SPE can induce acute, high-dose exposures, cosmic rays provide chronic exposures of the
order of 1 mSv/day. Such complicated irradiation conditions - mixed fields including heavy ions
incoming at both low dose rates (GCR) and high dose rates (SPE) - make it difficult to predict
long term biological effects induced by space radiation, due to the main following reasons: a)
radiobiology of heavy ions is still not known in detail; b) the effects of mixed fields cannot be
simply calculated as the sum of the effects of the different components; c) dose protraction can
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induce an increased repair capacity of cells and tissues in longer times, thus leading to a decrease
of the effects with respect to acute irradiation [2] (on this subject, it is worthy to report that there
is some contradiction on the effects of low dose rates: an increase of neoplastic transformation
has been observed following protracted exposures to low doses of high-LET radiation [3-5]); d)
the interaction with the spacecraft walls and shielding structures can significantly modify the
composition of the external field. This scenario is made even more complicated by microgravity,
whose interaction with radiation has not yet been clarified: an extensive review on this topic can
be found in [6], where it is reported that 50% of the experiments showed independent action of
radiation and microgravity, whereas 47% of the experiments showed a synergistic effect; an
antagonist action was observed in the remaining 3% of the experiments analised in the paper.
Moreover, recent experiments suggest that DNA double-strand break repair can be delayed under
microgravity conditions [7].
2. Estimating space radiation risk
Astronauts are classified as radiation exposed workers. In the International Commission on
Radiological Protection (ICRP) report n. 60 [8], a semi-empirical approach is adopted and health
risk and exposure limits are calculated on the basis of average quantities such as absorbed dose
(D), Linear Energy Transfer (LET) and Relative Biological Effectiveness (RBE). In terms of
practical applications, the risk for a given organ or tissue is assumed to be proportional to the
equivalent dose (H), which is defined as the product between D and the quality factor Q; the risk
for fatal cancer in the case of adult workers was set to 4% per Sv. Significant uncertainties affect
these estimates, since health risks calculations are based on extrapolations to low doses/dose-rates
of data obtained after exposures to higher doses/dose-rates. A phenomenological approach to
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perform estimates of heavy ion effects was adopted by Katz [9], who developed a track structure
model based on the hypothesis that radiation biological effectiveness is determined by the local
spatial distribution of the dose within the cell nucleus. Furthermore, the authors assumed that the
effects of local dose depositions due to charged particles do not significantly differ from those
induced by X rays. According to this model, charged particle fields are described through an
"amorphous" track structure, where only the radial dose distribution is taken into account. On the
basis of such distribution and using experimental data on cell survival following X ray
irradiation, the authors derive RBE values for cell inactivation induced by heavy ions.
In the case of radiation exposure on Earth, where in principle there are no limitations for
shielding design and construction, quality factors can be used to perform prudential risk
estimates. The question is much more complicated in space, where astronauts can be protected
only by the spacecraft walls and thin shielding structures of specific materials. In such extreme
conditions, different approaches need to be introduced to describe radiobiological damage
induction, which is a stochastic process involving a large number of inter-related intermediate
steps. A schematic representation of this process, from the initial physical interactions of
radiation with matter down to the induction of biological damage at organ and organism level, is
reported in the left side of figure 1. In the right side of the figure, the main information needed for
modelling each single step is reported, i.e.: the radiation type and energy of the different
components of the space radiation field; cross sections for nuclear reactions with the spacecraft
walls, the shielding structures and the human body; excitation and ionisation cross sections for
interactions with cellular targets such as water molecules and DNA; diffusion coefficients and
reaction rate constants of free radicals. Furthermore, phenomena whose role is still unclear are
reported, such as: interphase chromatin organisation in the nucleus; kinetics cell-cycle
perturbation; genomic instability; intercellular communication; local and systemic response to
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biological damage, such as apoptosis, adaptive response, cell repopulation and tissue
vascularisation . Mechanistic models and track-structure-based simulation codes represent a
necessary approach to these problems. Such models, which can provide overall descriptions from
the initial energy depositions to specific biological endpoints, allow one to better understand the
underlying mechanisms and thus to perform more reliable interpretations and extrapolations of
data, including biodosimetry measurements, which are of particular interest in case of space
radiation exposure. This can provide the bases for developing practical predictive tools able to
quantify health risk for specific space missions and to give indications on the appropriate
shielding design. An overview on the general features of mechanistic models and their
differences with respect to phenomenological approaches can be found elsewhere [10]; in this
paper, examples of both partial and overall mechanistic models of biological damage at different
levels will be reported and possible practical applications to radioprotection in space will be
discussed.
3. Mechanistic models of radiobiological damage: modelling single stages and the whole
process
3.1 Single-stage modelling
In this section two examples of single-stage models are reported, i.e. models that describe a
specific sub-process involved in biological damage induction by radiation. The first example
(water radiolysis) deals with the very early stages of the radiation action, up to 10 -6 s after
irradiation, whereas the second one (chromosome aberrations) is related to events occurring
within a few hours after the initial radiation insult.
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3.1.1 WATER RADIOLYSIS The time-dependent evolution of radiation tracks in water plays a
non-negligible role in the early stages of biological damage induction, since free radicals - mainly
the OH radical - produced after radiation interaction with water molecules can attack the DNA
constituents, leading to different damage types at the double-helix level. However, large
uncertainties still affect the main parameters governing water radiolysis, i.e interaction crosssections between radiation and H2O molecules in the liquid state, dissociation patterns of ionised
and excited water molecules, diffusion coefficients of the chemical species produced, reaction
rate constants between pairs of chemical species. Most experimental data on time-dependent
yields of chemical species are obtained after irradiation with high energy electrons (1 MeV or
more), whereas simulation codes show higher sensitivities at lower energies, thus implying that
equally acceptable results can be obtained from different research groups by adopting different
parameter sets and assumptions.
A study on the role of such uncertainties can be found in [11], in which water radiolysis was
simulated with the track-structure modules of PARTRAC, a biophysical Monte Carlo code able
to transport photons and electrons in liquid water with an event-by-event technique; proton cross
sections are already available [12] and their implementation in the code will be soon completed.
Starting from the physical module of PARTRAC, which provides a spatial distribution of excited
and ionised water molecules, in [11] two modules for the explicit simulation of the production,
diffusion and interaction of water radicals and molecular products were developed. This study
clearly indicated that the parameter values used by different groups are model-dependent, thus
emphasising the need of new, independently-derived information - from both experimental and
theoretical studies - to be included in this kind of simulations. This will allow one to describe the
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process on more mechanistic bases, thus providing a reliable starting point for simulations of
radical-induced DNA damage. In particular, the track structure modules of PARTRAC can be
coupled with a module describing interphase chromatin organisation, which allows "overall"
modelling of specific damage types up to cell level; a few examples will be presented in section
3.2.1.
3.1.2 CHROMOSOME ABERRATIONS Chromosome aberrations are a particularly interesting
endpoint when dealing with radiation health risk, since there is some evidence that certain
aberration types, such as reciprocal translocations, are correlated with cell conversion to
malignancy [13, 14]. Furthermore, in the specific case of astronaut exposure to the mixed fields
of space radiation, comparisons between pre-flight gamma calibration curves and post-flight
aberration scoring (typically dicentrics or translocations) can provide information on the radiation
quality absorbed by the crew members; an extensive review on this topic can be found in [15].
Chromosome aberrations can also provide dose estimates after exposure to a known radiation
field (retrospective dosimetry), and, more generally, health risk estimates in case of accidental
exposure to radiation fields whose composition is not known. In this sense mechanistic models
can be of great help, since they can be used to interpret available data and to perform
extrapolations to low dose/dose-rate regions, where data are extremely scarce. Moreover,
simulated dose-response curves for aberration induction can provide quantitative predictions in
case of exposure to different doses of different radiation types.
When modelling chromosome aberration induction, assumptions must be adopted on some
aspects of the process that are still under debate, such as the nature of the DNA lesions able to
give rise to aberrations and the laws governing the interaction among such lesions. Many authors
assume that all double-strand breaks (dsb) can potentially lead to chromosome aberrations, and
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that those dsb that actually interact are selected on the basis of their initial distance. This kind of
approach is well represented by [16], in which it was assumed that the interaction probability
between two dsb is a continuously-decreasing function of their initial distance. An alternative,
someway opposite approach can be found in [17], in which aberration induction by light ions was
modelled starting from the assumption that only DNA "Complex Lesions" (CL, defined as
clustered dsb) can lead to aberrations. The authors took into account interphase chromosomes
localisation and assumed that in case of light ion irradiation, chromosome free ends interact
randomly. In figure 2 the calculated yields of different exchange types are reported as a function
of both the particle LET and the yield of CL per cell, which was taken from a previous work on
DNA damage modelling [18]. Figure 2 provides a quantitative evaluation of the role played by
the spatial distribution of the lesions: for each given CL yield, intrachanges (centric rings)
increase with the radiation LET, whereas interchanges (dicentrics, reciprocal exchanges and
complex exchanges) show an opposite trend, thus reflecting the differences between high LET
tracks and low LET tracks in the spatial distribution of energy depositions. In this sense figure 2
can also be regarded as a tool to interpret biodosimetry data obtained after exposure to different
radiation qualities.
3.2 Modelling the whole process (from physics to biology)
3.2.1 DAMAGE UP TO CELLULAR LEVEL (EVENT-BY-EVENT SIMULATIONS) Monte
Carlo biophysical codes based on event-by-event track structure simulations allow detailed
descriptions of damage induction to the cellular structures. This kind of approach is well
represented by the PARTRAC code, whose track-structure modules have been presented above
(see section 3.1.1). Such modules can be coupled with a "geometrical" module reproducing
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different levels of interphase chromatin organisation, from nucleotides and nucleosomes up to
fibre loops and chromosome territories, starting from an atom-by-atom model of the DNA
molecule; both direct energy depositions in the atoms of the target and OH attack to the
nucleobases and the sugar-phosphate moiety can be reproduced. Up to now, PARTRAC has
successfully been applied to investigate DNA fragmentation induced by X and gamma rays [19]
and hprt gene mutations [20]; the description of similar studies can be found in [21]. A possible
future development of this kind of works consists in simulating a large number of cells, each of
them with its 46 chromosomal territories; this will allow simulation of specific endpoints (such as
gene mutations and chromosome aberrations) in realistic cell populations, thus taking into
account cell-by-cell variability (e.g. differences in the relative positions of the various
chromosome territories).
These studies confirm that event-by-event simulations are a very powerful tool, since they
allow reproduction of the stochastic aspects of the radiation action, which cannot be neglected
when dealing with rare endpoints (e.g. cancer induction) initiated by such a large number of
events (i.e. the initial energy depositions). Indeed one of the main features of event-by-event
simulations consists in providing descriptions in terms of distributions (rather than average
values), which can subsequently be integrated in models of damage induction up to organ and
organism level.
3.2.2 DAMAGE UP TO ORGAN AND ORGANISM LEVEL (INTEGRATED CONDENSEDHISTORY CODES) Most models of radiation damage evolution up to organ and organism level
are currently based on phenomenological approaches. Large uncertainties still characterise some
of the mechanisms involved in these processes: for istance, little is known on the mechanisms
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underlying cell conversion to malignancy, and the role played by factors such as apoptosis,
genomic instability, intercellular communication (by-stander effect) and tissue vascularisation is
still unclear. Overall mechanistic models could be of great help; however, due to the large target
volumes involved, event-by-event codes cannot be directly applied to simulate the radiation
interaction with the human body, since unreasonable amounts of CPU time would be required.
On the other side, the use of condensed-history codes, alone, can be misleading, because the
information on the stochastic aspects of these processes might be loss.
A possible solution is represented by "mixed" approaches, consisting in integrating in
condensed-history codes information - in terms of distributions - obtained from event-by-event
simulations. An example can be found in [22], where this kind of approach was adopted to
characterise the physical and biophysical features of the proton beam used at the Paul Scherrer
Institut (Villigen, Switzerland) for the treatment of ocular tumours. Radiation interaction with
matter, including nuclear reactions, was simulated with FLUKA, a condensed-history code able
to transport photons and hadrons of different energies [23]. Radiation track features at the
nanometer scale were taken into account by integrating in FLUKA the yield of DNA "Complex
Lesions" (details on such lesions can be found in section 3.1.2 on chromosome aberrations), thus
obtaining a spatial distribution of a quantity that can be regarded as a "biological" dose in targets
having linear dimensions of the order of centimetres. Excellent agreement was found between the
(calculated) ratio of proton-induced CL to X-induced CL and the (measured) ratio of protoninduced lethal lesions to X-induced lethal lesions after 2 Gy irradiation experiments.
Since complex lesions increase linearly with dose, this approach would not allow reproduction
of the dose-dependence of radiation effectiveness. For this reason, a pragmatic, semi-empirical
approach similar to that introduced in [24], taking into account the linear-quadratic feature of
dose-response curves observed for various endpoints, was adopted in modelling chromosome
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aberration induction by neutron fields of different energies. More specifically, the values of the
linear coefficient and the quadratic coefficient determining dicentric yields after neutron
irradiation of human lymphocytes were calculated by integrating in FLUKA available
experimental values of such coefficients for different monochromatic fields of charged particles;
a detailed description of this work can be found in [25].
However, it has to be pointed out that the approach adopted in [25], although it can provide a
pragmatic tool to estimate radiation risk, cannot be regarded as mechanistic, since the simulation
of the biological stage (i.e. aberration production) mainly relies on phenomenological bases such
as the linear-quadratic shape of dose-response curves. Tests are under development to identify the
most significant radiobiological information to be integrated in FLUKA, similarly to what
reported in [22]; this will allow us to deal at macroscopic level with mechanistic information
obtained at cellular and subcellular level.
4. Discussion and Conclusions
An analysis of the peculiar aspects of space radiation (presence of high energy ions, low dose
rate, microgravity etc.) indicated that approaches based exclusively on average quantities such as
dose and RBE are not adequate for estimating health risk after space radiation exposure and
planning astronauts radioprotection (e.g. shielding design). In this context, mechanistic models
and Monte Carlo simulations can be of great help, since a) they allow one to take into account the
highly-stochastic aspects characterising space radiation, including nuclear interactions with the
spacecraft walls; b) they allow one to better understand the intermediate steps leading from the
initial physical interactions to observable biological damage, and therefore to perform reliable
interpretations and extrapolations of in vitro and in vivo measurements; c) integration into
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condensed-history codes of information provided by event-by-event simulations can provide
spatial distributions of both particle fluences and specific damage yields (e.g. chromosome
aberrations) for each radiation type and energy ("overall" modelling); such "mixed" approaches
represent the bases for the development of practical tools allowing quantitative prediction of
health risks in specific space missions.
Indeed the mechanisms involved in damage induction after space radiation exposure are still
not know in detail, and there is a strong need of further information to be included in overall
simulations as independently-derived data. For instance, further measurements of heavy-ion
nuclear cross sections have to be performed and implemented in transport codes; modelling of
damage induction up to cell level must be extended to different radiation types, in order to
provide distributions to be integrated in condensed-history codes; available data (e.g. neutron
data) on chromosome aberration induction have to be revised on the basis of such mixed
approaches; mechanistic models of damage evolution up to organ and organism level must be
developed, taking into account effects such as cell-cycle perturbation, apoptosis, genomic
instability, intercellular communication and tissue vascularisation; the role of microgravity in
damage induction and evolution needs to be further investigated; simulation of human phantoms
has to be improved, by using anthropomorphic voxel phantoms [26].
Acknowledgements
This work was partially supported by the EU contract no. FIGH-CT1999-00005 ("Low dose risk
models").
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FIGURE CAPTIONS
Fig.1: fundamental stages of the process leading to radiobiological damage (left side) and basic
information needed for mechanistic modelling and simulations (right side).
Fig. 2: effects of the spatial distribution of complex DNA lesions (CL): yields of different
chromosome aberrations induced by alpha particles of different LET as a function of the mean
number of CL per cell. See text for details.
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