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Probalistic Assessment of Radiation Risk for Solar Particle Events

For long duration missions outside of the protection of the Earth's magnetic field, exposure to solar particle events (SPEs) is a major safety concern for crew members during extra-vehicular activities (EVAs) on the lunar surface or Earth-to-moon or Earth-to-Mars transit. The large majority (~90%) of SPEs have small or no health consequences because the doses are low and the particles do not penetrate to organ depths. However, there is an operational challenge to respond to events of unknown size and duration. We have developed a probabilistic approach to SPE risk assessment in support of mission design and operational planning. Using the historical database of proton measurements during the past 5 solar cycles, the functional form of hazard function of SPE occurrence per cycle was found for nonhomogeneous Poisson model. A typical hazard function was defined as a function of time within a non-specific future solar cycle of 4000 days duration. Distributions of particle fluences for a specified mission period were simulated ranging from its 5th to 95th percentile. Organ doses from large SPEs were assessed using NASA's Baryon transport model, BRYNTRN. The SPE risk was analyzed with the organ dose distribution for the given particle fluences during a mission period. In addition to the total particle fluences of SPEs, the detailed energy spectra of protons, especially at high energy levels, were recognized as extremely important for assessing the cancer risk associated with energetic particles for large events. The probability of exceeding the NASA 30-day limit of blood forming organ (BFO) dose inside a typical spacecraft was calculated for various SPE sizes. This probabilistic approach to SPE protection will be combined with a probabilistic approach to the radiobiological factors that contribute to the uncertainties in projecting cancer risks in future work.

Kim, Myung-Hee Y.↗

Probabilistic Assessment of Cancer Risk for Astronauts on Lunar Missions

During future lunar missions, exposure to solar particle events (SPEs) is a major safety concern for crew members during extra-vehicular activities (EVAs) on the lunar surface or Earth-to-moon transit. NASA s new lunar program anticipates that up to 15% of crew time may be on EVA, with minimal radiation shielding. For the operational challenge to respond to events of unknown size and duration, a probabilistic risk assessment approach is essential for mission planning and design. Using the historical database of proton measurements during the past 5 solar cycles, a typical hazard function for SPE occurrence was defined using a non-homogeneous Poisson model as a function of time within a non-specific future solar cycle of 4000 days duration. Distributions ranging from the 5th to 95th percentile of particle fluences for a specified mission period were simulated. Organ doses corresponding to particle fluences at the median and at the 95th percentile for a specified mission period were assessed using NASA s baryon transport model, BRYNTRN. The cancer fatality risk for astronauts as functions of age, gender, and solar cycle activity were then analyzed. The probability of exceeding the NASA 30- day limit of blood forming organ (BFO) dose inside a typical spacecraft was calculated. Future work will involve using this probabilistic risk assessment approach to SPE forecasting, combined with a probabilistic approach to the radiobiological factors that contribute to the uncertainties in projecting cancer risks.

Kim, Myung-Hee Y.↗

3D Visualization of Monte-Carlo Simulation's of HZE Track Structure and Initial Chemical Species

Heavy ions biophysics is important for space radiation risk assessment [1] and hadron-therapy [2]. The characteristic of heavy ions tracks include a very high energy deposition region close to the track (<20 nm) denoted as the track core, and an outer penumbra region consisting of individual secondary electrons (6-rays). A still open question is the radiobiological effects of 6- rays relative to the track core. Of importance is the induction of double-strand breaks (DSB) [3] and oxidative damage to the biomolecules and the tissue matrix, considered the most important lesions for acute and long term effects of radiation. In this work, we have simulated a 56Fe26+ ion track of 1 GeV/amu with our Monte-Carlo code RITRACKS [4]. The simulation results have been used to calculate the energy depiction and initial chemical species in a "voxelized" space, which is then visualized in 3D. Several voxels with dose >1000 Gy are found in the penumbra, some located ~0.1 mm from the track core. In computational models, the DSB induction probability is calculated with radial dose [6], which may not take into account the higher RBE of electron track ends for DSB induction. Therefore, these simulations should help improve models of DSB induction and our understanding of heavy ions biophysics.

Plante, Ianik↗

Probabilistic Assessment of Cancer Risk from Solar Particle Events

For long duration missions outside of the protection of the Earth s magnetic field, space radiation presents significant health risks including cancer mortality. Space radiation consists of solar particle events (SPEs), comprised largely of medium energy protons (less than several hundred MeV); and galactic cosmic ray (GCR), which include high energy protons and heavy ions. While the frequency distribution of SPEs depends strongly upon the phase within the solar activity cycle, the individual SPE occurrences themselves are random in nature. We estimated the probability of SPE occurrence using a non-homogeneous Poisson model to fit the historical database of proton measurements. Distributions of particle fluences of SPEs for a specified mission period were simulated ranging from its 5 th to 95th percentile to assess the cancer risk distribution. Spectral variability of SPEs was also examined, because the detailed energy spectra of protons are important especially at high energy levels for assessing the cancer risk associated with energetic particles for large events. We estimated the overall cumulative probability of GCR environment for a specified mission period using a solar modulation model for the temporal characterization of the GCR environment represented by the deceleration potential (^). Probabilistic assessment of cancer fatal risk was calculated for various periods of lunar and Mars missions. This probabilistic approach to risk assessment from space radiation is in support of mission design and operational planning for future manned space exploration missions. In future work, this probabilistic approach to the space radiation will be combined with a probabilistic approach to the radiobiological factors that contribute to the uncertainties in projecting cancer risks.

Kim, Myung-Hee Y.↗

Monte-Carlo Simulation of Radiation Track Structure and Calculation of Dose Deposition in Nanovolumes

INTRODUCTION: The radiation track structure is of crucial importance to understand radiation damage to molecules and subsequent biological effects. Of a particular importance in radiobiology is the induction of double-strand breaks (DSBs) by ionizing radiation, which are caused by clusters of lesions in DNA, and oxidative damage to cellular constituents leading to aberrant signaling cascades. DSB can be visualized within cell nuclei with gamma-H2AX experiments. MATERIAL AND METHODS: In DSB induction models, the DSB probability is usually calculated by the local dose obtained from a radial dose profile of HZE tracks. In this work, the local dose imparted by HZE ions is calculated directly from the 3D Monte-Carlo simulation code RITRACKS. A cubic volume of 5 micron edge (Figure 1) is irradiated by a (Fe26+)-56 ion of 1 GeV/amu (LET approx.150 keV/micron) and by a fluence of 450 H+ ions, 300 MeV/amu (LET approx. 0.3 keV/micron). In both cases, the dose deposited in the volume is approx.1 Gy. The dose is then calculated into each 3D pixels (voxels) of 20 nm edge and visualized in 3D. RESULTS AND DISCUSSION: The dose is deposited uniformly in the volume by the H+ ions. The voxels which receive a high dose (orange) corresponds to electron track ends. The dose is deposited differently by the 56Fe26+ ion. Very high dose (red) is deposited in voxels with direct ion traversal. Voxels with electron track ends (orange) are also found distributed around the path of the track. In both cases, the appearance of the dose distribution looks very similar to DSBs seen in gammaH2AX experiments, particularly when the visualization threshold is applied. CONCLUSION: The refinement of the dose calculation to the nanometer scale has revealed important differences in the energy deposition between high- and low-LET ions. Voxels of very high dose are only found in the path of high-LET ions. Interestingly, experiments have shown that DSB induced by high-LET radiation are more difficult to repair. Therefore, this new approach may be useful to understand the nature of DSB and oxidative damage induced by ionizing radiation.

Plante, I.↗

Calculation of Dose Deposition in 3D Voxels by Heavy Ions

The biological response to high-LET radiation is very different from low-LET radiation, and can be partly attributed to the energy deposition by the radiation. Several experiments, notably detection of gamma-H2AX foci by immunofluorescence, has revealed important differences in the nature and in the spatial distribution of double-strand breaks (DSB) induced by low- and high-LET radiations. Many calculations, most of which are based on amorphous track models with radial dose, have been combined with chromosome models to calculate the number and distribution of DSB within nuclei and chromosome aberrations. In this work, the Monte-Carlo track structure simulation code RITRACKS have been used to calculate directly the energy deposition in voxels (3D pixels). A cubic volume of 5 micrometers of side was irradiated by 1) 450 (1)H+ ions of 300 MeV (LET is approximately 0.3 keV/micrometer) and 2) by 1 (56)Fe26+ ion of 1 GeV/amu (LET is approximately 150 keV/micrometer). In both cases, the dose deposited in the volume is approximately 1 Gy. All energy deposition events are recorded and dose is calculated in voxels of 20 micrometers of side. The voxels are then visualized in 3D by using a color scale to represent the intensity of the dose in a voxel. This simple approach has revealed several important points which may help understand experimental observations. In both simulations, voxels which receive low dose are the most numerous, and those corresponding to electron track ends received a dose which is in the higher range. The dose voxels are distributed randomly and scattered uniformly within the volume irradiated by low-LET radiation. The distribution of the voxels shows major differences for the (56)Fe26+ ion. The track structure can still be seen, and voxels with much higher dose are found in the region corresponding to the track "core". These high-dose voxels are not found in the low-LET irradiation simulation and may be responsible for DSB that are more difficult to repair. By applying a threshold on the dose visualization, voxels corresponding to electron track ends are evidenced and the spatial distribution of voxels is very similar to the distribution of DSB observed in gamma H2AX experiments, even if no chromosomes have been included in the simulation. Furthermore, this work has shown that a significant dose is deposited in voxels corresponding to electron track ends. Since some delta-rays from iron ion can travel several millimeters, they may also be of radiobiological importance.

Plante, Ianik↗

Uncertainties in Estimates of the Risks of Late Effects from Space Radiation

The health risks faced by astronauts from space radiation include cancer, cataracts, hereditary effects, and non-cancer morbidity and mortality risks related to the diseases of the old age. Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Within the linear-additivity model, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain a Maximum Likelihood estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including ISS, lunar station, deep space outpost, and Mar's missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time, and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative objective's, i.e., the number of days in space without exceeding a given risk level within well defined confidence limits.

Cucinotta, F. A.↗

Calculation of Dose Deposition in 3D Voxels by Heavy Ions and Simulation of gamma-H2AX Experiments

The biological response to high-LET radiation is different from low-LET radiation due to several factors, notably difference in energy deposition and formation of radiolytic species. Of particular importance in radiobiology is the formation of double-strand breaks (DSB), which can be detected by -H2AX foci experiments. These experiments has revealed important differences in the spatial distribution of DSB induced by low- and high-LET radiations [1,2]. To simulate -H2AX experiments, models based on amorphous track with radial dose are often combined with random walk chromosome models [3,4]. In this work, a new approach using the Monte-Carlo track structure code RITRACKS [5] and chromosome models have been used to simulate DSB formation. At first, RITRACKS have been used to simulate the irradiation of a cubic volume of 5 m by 1) 450 1H+ ions of 300 MeV (LET 0.3 keV/ m) and 2) by 1 56Fe26+ ion of 1 GeV/amu (LET 150 keV/ m). All energy deposition events are recorded to calculate dose in voxels of 20 m. The dose voxels are distributed randomly and scattered uniformly within the volume irradiated by low-LET radiation. Many differences are found in the spatial distribution of dose voxels for the 56Fe26+ ion. The track structure can be distinguished, and voxels with very high dose are found in the region corresponding to the track "core". These high-dose voxels are not found in the low-LET irradiation simulation and indicate clustered energy deposition, which may be responsible for complex DSB. In the second step, assuming that DSB will be found only in voxels where energy is deposited by the radiation, the intersection points between voxels with dose > 0 and simulated chromosomes were obtained. The spatial distribution of the intersection points is similar to -H2AX foci experiments. These preliminary results suggest that combining stochastic track structure and chromosome models could be a good approach to understand radiation-induced DSB and chromosome aberrations.

Plante, I.↗

Radiation Risk Projections for Space Travel

Space travelers are exposed to solar and galactic cosmic rays comprised of protons and heavy ions moving with velocities close to the speed of light. Cosmic ray heavy ions are known to produce more severe types of biomolecular damage in comparison to terrestrial forms of radiation, however the relationship between such damage and disease has not been fully elucidated. On Earth, we are protected from cosmic rays by atmospheric and magnetic shielding, and only the remnants of cosmic rays in the form of ground level muons and other secondary radiations are present. Because human epidemiology data is lacking for cosmic rays, risk projection must rely on theoretical understanding and data from experimental models exposed to space radiation using charged particle accelerators to simulate space radiation. Although the risks of cancer and other late effects from cosmic rays are currently believed to present a severe challenge to space travel, this challenge is centered on our lack of confidence in risk projections methodologies. We review biophysics and radiobiology data on the effects of the cosmic ray heavy ions, and the current methods used to project radiation risks . Cancer risk projections are described as a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Risk projections for space travel are described using Monte-Carlo sampling from subjective error di stributions that represent the lack of knowledge in each factor that contributes to the projection model in order to quantify the overall uncertainty in risk projections. This analysis is applied to space mi ssion scenarios including lunar colony, deep space outpost, and a Mars mission. Results suggest that the number of days in space where cancer mortality risks can be assured at a 95% confidence level to be below the maximum acceptable risk for radi ation workers on Earth or the International Space Station is only on the order of 100-200 days. Approaches to reduce these unceI1ainties and mitigate risks are described.

Cucinotta, Francis↗

Step-by-Step Simulation of Radiation of Radiation Chemistry Using Green Functions for Diffusion-Influenced Reactions

The irradiation of biological systems leads to the formation of radiolytic species such as H(raised dot), (raised dot)OH, H2, H2O2, e(sup -)(sub aq), etc.[1]. These species react with neighboring molecules, which result in damage in biological molecules such as DNA. Radiation chemistry is there for every important to understand the radiobiological consequences of radiation[2]. In this work, we discuss an approach based on the exact Green Functions for diffusion-influenced reactions which may be used to simulate radiation chemistry and eventually extended to study more complex systems, including DNA.

Plante, Ianik↗

What Threats to Human Health Does Space Radiation Pose in Orbit

The Space Shuttle program spanned more than the entire length of a solar cycle. Investigations aimed towards understanding the health risks of the astronauts from exposures to space radiation involved mostly physical measurements of the dose and the linear energy transfer (LET) spectrum. Measurement of the dose rate on the Shuttle provided invariable new data for different periods of the solar cycle, whereas measurement of the LET spectrum using the tissue equivalent proportional counter (TEPC) produced the most complete mapping of the radiation environment of the low Earth orbits (LEO). Exposures to the Shuttle astronauts were measured by the personal dosimeter worn by the crewmembers. Analysis of over 300 personal dosimeter readings indicated a dependence on the mission duration, the altitude and inclination of the orbit, and the solar cycle, with the crewmembers on the launch and repair of the Hubble telescope receiving the highest doses due to the altitude of the mission. Secondary neutrons inside the Shuttle were determined by recoil protons or with Bonner spheres, and may contribute significantly to the risks of the crewmembers. In addition, the skin dose and the doses received at different organs were compared using a human phantom onboard a Shuttle mission. A number of radiobiology investigations wer e also performed. The biological doses were determined on six astronauts/cosmonauts on long-duration Shuttle/Mir missions and on two crewmembers on a Hubble repair mission by analyzing the damages in the chromosomes of the crewmembers? white blood cells. Several experiments were also conducted to address the question of possible synergistic effects of spaceflight, microgravity in particular, on the repair of radiation-induced DNA damages. The experimental design included exposure of cells before launch, during flight, or after landing. These physical and biological studies were invaluable in predicting the health risks for astronauts on ISS and future exploration missions. Educational Objectives: A group of high school students flew color negative films on tw o Shuttle missions to detect the radiation environment in orbit. This and other experiments onboard of the Shuttle were aimed at educating the general public of the space program.

Wu, Honglu↗

Uncertainty Analysis in Space Radiation Protection

Space radiation is comprised of high energy and charge (HZE) nuclei, protons, and secondary radiation including neutrons. The uncertainties in estimating the health risks from galactic cosmic rays (GCR) are a major limitation to the length of space missions, the evaluation of potential risk mitigation approaches, and application of the As Low As Reasonably Achievable (ALARA) principle. For long duration space missio ns, risks may approach radiation exposure limits, therefore the uncertainties in risk projections become a major safety concern and methodologies used for ground-based works are not deemed to be sufficient. NASA limits astronaut exposures to a 3% risk of exposure induced death (REID) and protects against uncertainties in risks projections using an assessment of 95% confidence intervals in the projection model. We discuss NASA s approach to space radiation uncertainty assessments and applications for the International Space Station (ISS) program and design studies of future missions to Mars and other destinations. Several features of NASA s approach will be discussed. Radiation quality descriptions are based on the properties of radiation tracks rather than LET with probability distribution functions (PDF) for uncertainties derived from radiobiology experiments at particle accelerators. The application of age and gender specific models for individual astronauts is described. Because more than 90% of astronauts are never-smokers, an alternative risk calculation for never-smokers is used and will be compared to estimates for an average U.S. population. Because of the high energies of the GCR limits the benefits of shielding and the limited role expected for pharmaceutical countermeasures, uncertainty reduction continues to be the optimal approach to improve radiation safety for space missions.

Cucinotta, Francis A.↗

Probability of Causation for Space Radiation Carcinogenesis Following International Space Station, Near Earth Asteroid, and Mars Missions

Cancer risk is an important concern for International Space Station (ISS) missions and future exploration missions. An important question concerns the likelihood of a causal association between a crew members radiation exposure and the occurrence of cancer. The probability of causation (PC), also denoted as attributable risk, is used to make such an estimate. This report summarizes the NASA model of space radiation cancer risks and uncertainties, including improvements to represent uncertainties in tissue-specific cancer incidence models for never-smokers and the U.S. average population. We report on tissue-specific cancer incidence estimates and PC for different post-mission times for ISS and exploration missions. An important conclusion from our analysis is that the NASA policy to limit the risk of exposure-induced death to 3% at the 95% confidence level largely ensures that estimates of the PC for most cancer types would not reach a level of significance. Reducing uncertainties through radiobiological research remains the most efficient method to extend mission length and establish effective mitigators for cancer risks. Efforts to establish biomarkers of space radiation-induced tumors and to estimate PC for rarer tumor types are briefly discussed.

Cucinotta, Francis A.↗

Technical Evaluation of the NASA Model for Cancer Risk to Astronauts Due to Space Radiation

At the request of NASA, the National Research Council's (NRC's) Committee for Evaluation of Space Radiation Cancer Risk Model1 reviewed a number of changes that NASA proposes to make to its model for estimating the risk of radiation-induced cancer in astronauts. The NASA model in current use was last updated in 2005, and the proposed model would incorporate recent research directed at improving the quantification and understanding of the health risks posed by the space radiation environment. NASA's proposed model is defined by the 2011 NASA report Space Radiation Cancer Risk Projections and Uncertainties--2010 . The committee's evaluation is based primarily on this source, which is referred to hereafter as the 2011 NASA report, with mention of specific sections or tables. The overall process for estimating cancer risks due to low linear energy transfer (LET) radiation exposure has been fully described in reports by a number of organizations. The approaches described in the reports from all of these expert groups are quite similar. NASA's proposed space radiation cancer risk assessment model calculates, as its main output, age- and gender-specific risk of exposure-induced death (REID) for use in the estimation of mission and astronaut-specific cancer risk. The model also calculates the associated uncertainties in REID. The general approach for estimating risk and uncertainty in the proposed model is broadly similar to that used for the current (2005) NASA model and is based on recommendations by the National Council on Radiation Protection and Measurements. However, NASA's proposed model has significant changes with respect to the following: the integration of new findings and methods into its components by taking into account newer epidemiological data and analyses, new radiobiological data indicating that quality factors differ for leukemia and solid cancers, an improved method for specifying quality factors in terms of radiation track structure concepts as opposed to the previous approach based on linear energy transfer, the development of a new solar particle event (SPE) model, and the updates to galactic cosmic ray (GCR) and shielding transport models. The newer epidemiological information includes updates to the cancer incidence rates from the life span study (LSS) of the Japanese atomic bomb survivors, transferred to the U.S. population and converted to cancer mortality rates from U.S. population statistics. In addition, the proposed model provides an alternative analysis applicable to lifetime never-smokers (NSs). Details of the uncertainty analysis in the model have also been updated and revised. NASA's proposed model and associated uncertainties are complex in their formulation and as such require a very clear and precise set of descriptions. The committee found the 2011 NASA report challenging to review largely because of the lack of clarity in the model descriptions and derivation of the various parameters used. The committee requested some clarifications from NASA throughout its review and was able to resolve many, but not all, of the ambiguities in the written description.

Source record↗

Computational Transport Modeling of High-Energy Neutrons Found in the Space Environment

The high charge and high energy (HZE) particle radiation environment in space interacts with spacecraft materials and the human body to create a population of neutrons encompassing a broad kinetic energy spectrum. As an HZE ion penetrates matter, there is an increasing chance of fragmentation as penetration depth increases. When an ion fragments, secondary neutrons are released with velocities up to that of the primary ion, giving some neutrons very long penetration ranges. These secondary neutrons have a high relative biological effectiveness, are difficult to effectively shield, and can cause more biological damage than the primary ions in some scenarios. Ground-based irradiation experiments that simulate the space radiation environment must account for this spectrum of neutrons. Using the Particle and Heavy Ion Transport Code System (PHITS), it is possible to simulate a neutron environment that is characteristic of that found in spaceflight. Considering neutron dosimetry, the focus lies on the broad spectrum of recoil protons that are produced in biological targets. In a biological target, dose at a certain penetration depth is primarily dependent upon recoil proton tracks. The PHITS code can be used to simulate a broad-energy neutron spectrum traversing biological targets, and it account for the recoil particle population. This project focuses on modeling a neutron beamline irradiation scenario for determining dose at increasing depth in water targets. Energy-deposition events and particle fluence can be simulated by establishing cross-sectional scoring routines at different depths in a target. This type of model is useful for correlating theoretical data with actual beamline radiobiology experiments. Other work exposed human fibroblast cells to a high-energy neutron source to study micronuclei induction in cells at increasing depth behind water shielding. Those findings provide supporting data describing dose vs. depth across a water-equivalent medium. This poster presents PHITS data suggesting an increase in dose, up to roughly 10 cm depth, followed by a continual decrease as neutrons come to a stop in the target.

Cox, Brad↗

Technical Evaluation of the NASA Model for Cancer Risk to Astronauts Due to Space Radiation

At the request of NASA, the National Research Council's (NRC's) Committee for Evaluation of Space Radiation Cancer Risk Model reviewed a number of changes that NASA proposes to make to its model for estimating the risk of radiation-induced cancer in astronauts. The NASA model in current use was last updated in 2005, and the proposed model would incorporate recent research directed at improving the quantification and understanding of the health risks posed by the space radiation environment. NASA's proposed model is defined by the 2011 NASA report Space Radiation Cancer Risk Projections and Uncertainties 2010 (Cucinotta et al., 2011). The committee's evaluation is based primarily on this source, which is referred to hereafter as the 2011 NASA report, with mention of specific sections or tables cited more formally as Cucinotta et al. (2011). The overall process for estimating cancer risks due to low linear energy transfer (LET) radiation exposure has been fully described in reports by a number of organizations. They include, more recently: (1) The "BEIR VII Phase 2" report from the NRC's Committee on Biological Effects of Ionizing Radiation (BEIR) (NRC, 2006); (2) Studies of Radiation and Cancer from the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR, 2006), (3) The 2007 Recommendations of the International Commission on Radiological Protection (ICRP), ICRP Publication 103 (ICRP, 2007); and (4) The Environmental Protection Agency s (EPA s) report EPA Radiogenic Cancer Risk Models and Projections for the U.S. Population (EPA, 2011). The approaches described in the reports from all of these expert groups are quite similar. NASA's proposed space radiation cancer risk assessment model calculates, as its main output, age- and gender-specific risk of exposure-induced death (REID) for use in the estimation of mission and astronaut-specific cancer risk. The model also calculates the associated uncertainties in REID. The general approach for estimating risk and uncertainty in the proposed model is broadly similar to that used for the current (2005) NASA model and is based on recommendations by the National Council on Radiation Protection and Measurements (NCRP, 2000, 2006). However, NASA's proposed model has significant changes with respect to the following: the integration of new findings and methods into its components by taking into account newer epidemiological data and analyses, new radiobiological data indicating that quality factors differ for leukemia and solid cancers, an improved method for specifying quality factors in terms of radiation track structure concepts as opposed to the previous approach based on linear energy transfer, the development of a new solar particle event (SPE) model, and the updates to galactic cosmic ray (GCR) and shielding transport models. The newer epidemiological information includes updates to the cancer incidence rates from the life span study (LSS) of the Japanese atomic bomb survivors (Preston et al., 2007), transferred to the U.S. population and converted to cancer mortality rates from U.S. population statistics. In addition, the proposed model provides an alternative analysis applicable to lifetime never-smokers (NSs). Details of the uncertainty analysis in the model have also been updated and revised. NASA's proposed model and associated uncertainties are complex in their formulation and as such require a very clear and precise set of descriptions. The committee found the 2011 NASA report challenging to review largely because of the lack of clarity in the model descriptions and derivation of the various parameters used. The committee requested some clarifications from NASA throughout its review and was able to resolve many, but not all, of the ambiguities in the written description.

Source record↗

Space Radiation Cancer Risks and Uncertainities for Different Mission Time Periods

Space radiation consists of solar particle events (SPEs), comprised largely of medium energy protons (less than several hundred MeV); and galactic cosmic ray (GCR), which includes high energy protons and high charge and energy (HZE) nuclei. For long duration missions, space radiation presents significant health risks including cancer mortality. Probabilistic risk assessment (PRA) is essential for radiation protection of crews on long term space missions outside of the protection of the Earth s magnetic field and for optimization of mission planning and costs. For the assessment of organ dosimetric quantities and cancer risks, the particle spectra at each critical body organs must be characterized. In implementing a PRA approach, a statistical model of SPE fluence was developed, because the individual SPE occurrences themselves are random in nature while the frequency distribution of SPEs depends strongly upon the phase within the solar activity cycle. Spectral variability of SPEs was also examined, because the detailed energy spectra of protons are important especially at high energy levels for assessing the cancer risk associated with energetic particles for large events. An overall cumulative probability of a GCR environment for a specified mission period was estimated for the temporal characterization of the GCR environment represented by the deceleration potential (theta). Finally, this probabilistic approach to space radiation cancer risk was coupled with a model of the radiobiological factors and uncertainties in projecting cancer risks. Probabilities of fatal cancer risk and 95% confidence intervals will be reported for various periods of space missions.

Kim,Myung-Hee Y.↗

Space Radiation Cancer Risk Projections and Uncertainties - 2010

Uncertainties in estimating health risks from galactic cosmic rays greatly limit space mission lengths and potential risk mitigation evaluations. NASA limits astronaut exposures to a 3% risk of exposure-induced death and protects against uncertainties using an assessment of 95% confidence intervals in the projection model. Revisions to this model for lifetime cancer risks from space radiation and new estimates of model uncertainties are described here. We review models of space environments and transport code predictions of organ exposures, and characterize uncertainties in these descriptions. We summarize recent analysis of low linear energy transfer radio-epidemiology data, including revision to Japanese A-bomb survivor dosimetry, longer follow-up of exposed cohorts, and reassessments of dose and dose-rate reduction effectiveness factors. We compare these projections and uncertainties with earlier estimates. Current understanding of radiation quality effects and recent data on factors of relative biological effectiveness and particle track structure are reviewed. Recent radiobiology experiment results provide new information on solid cancer and leukemia risks from heavy ions. We also consider deviations from the paradigm of linearity at low doses of heavy ions motivated by non-targeted effects models. New findings and knowledge are used to revise the NASA risk projection model for space radiation cancer risks.

Cucinotta, Francis A.↗