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At least 19 records

Application of multi-method-multi-model inference to radiation related solid cancer excess risks models for astronaut risk assessment

The impact of including model-averaged excess radiation risks (ER) into a measure of radiation attributed decrease of survival (RADS) for the outcome all solid cancer incidence and the impact on the uncertainties is demonstrated. It is shown that RADS applying weighted model averaged ER based on AIC weights result in smaller risk estimates with narrower 95% CI than RADS using ER based on BIC weights. Further a multi-method-multi-model inference approach is introduced that allows calculating one general RADS estimate providing a weighted average risk estimate for a lunar and a Mars mission. For males the general RADS estimate is found to be 0.42% (95% CI: 0.38%; 0.45%) and for females 0.67% (95% CI: 0.59%; 0.75%) for a lunar mission and 2.45% (95% CI: 2.23%; 2.67%) for males and 3.91% (95% CI: 3.44%; 4.39%) for females for a Mars mission considering an age at exposure of 40 years and an attained age of 65 years. It is recommended to include these types of uncertainties and to include model-averaged excess risks in astronaut risk assessment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

HUMAN FACTORS AND BEHAVIORAL PERFORMANCE EXPLORATION MEASURES: ASSESSING ASTRONAUT RISK

INTRODUCTION: The Human Factors and Behavioral Performance Exploration Measures (HFBP-EM) suite is a set of standardized measures to assess behavioral health and performance risk related to future exploration class missions, and to support reduction of the Human Research Program’s (HRP) Behavioral Medicine (BMed), Team, Sleep, and Human Systems Integration Architecture (HSIA) risks. This presentation will provide an overview of the HFBP-EM program, describe its implementation across spaceflight analogs and the international space station (ISS), and discuss its applicability to audience members. TOPIC: HFBP-EM is a research program designed to develop a standard set of measures that can be used in space and space-analog research to characterize BMed, Team, Sleep, and HSIA risks. It is an ongoing research project that is used examine the validity and reliability of HFBP measures, as well as their shorter forms. It also serves as a test bed for HFBP measures being considered for the spaceflight standard measures. The suite of measures is used to test the efficacy of countermeasures. To date, HFBP-EM has been collected in Human Exploration Research Analogs campaigns 4 and 5, and the SIRIUS 19 mission in the Russian Ground Based Experiment Complex. A subset of the HFBP-EM suite was collected during spaceflight as part of HRP’s Standard Measures in Spaceflight Project. Data was collected from a total of 55 multinational astronaut and astronaut-like crewmembers (mean age: 39.5, SD = 7.6; 31% female; 91% with advanced degrees). Three broad categories of HFBP-EM measures and their relevance to HRP risks will be discussed: 1) surveys that assess team functioning (Teams risk) as well as mood and affect (Bmed risk), 2) performance-based tasks of cognitive functioning and operationally relevant performance (Bmed risk), and 3) physiological biomarkers of sleep (sleep risk) and heart rate (Bmed risk). We will provide an overview of the background of the HFBP-EM program, what the suite currently includes, and next steps in its future development. We will also discuss the application to aerospace practitioners and researchers. APPLICATION: Astronaut teams selected for future space exploration missions will face several challenges that pose significant yet still unknown risks to the behavioral health and performance of astronauts. The HFBP-EM suite provides a comprehensive assessment of behavioral health and performance in space analog and spaceflight settings. This suite can be applied to both operational and research settings to advance risk reduction research for long duration space exploration missions.

S T Bell↗

Ensemble Cancer Risk Model for Astronaut Risk Assessment

A new approach to NASA space radiation risk modeling has successfully extended the current NASA probabilistic cancer risk model to an ensemble framework able to consider sub-model parameter uncertainty (e.g. uncertainty in a radiation quality parameter) as well as model-form uncertainty associated with differing theoretical or empirical formalisms (e.g. combined dose-rate and radiation quality effects). Ensemble methodologies are already widely used in weather prediction, modeling of infectious disease outbreaks, and certain terrestrial radiation protection applications to better understand how uncertainty may influence risk decision-making. Applying ensemble methodologies to space radiation risk projections offers the potential to efficiently incorporate emerging research results, allow for the incorporation of future (including international) models, improve uncertainty quantification for underlying sub-models developed against sparse experimental data, and reduce the impact of subjective bias on risk projections. Moreover, risk forecasting across an ensemble of multiple predictive models can provide stakeholders additional information on risk acceptance if current health/medical standards cannot be met or the level of knowledge doesn’t permit a specific risk or exposure limit to be developed for future space exploration missions. In this work, ensemble risk projections implementing multiple sub-models of radiation quality, dose and dose-rate effectiveness factors, excess risk, and latency as ensemble members are presented. Initial consensus methods for ensemble model weights and correlations to account for individual model bias are discussed. In these analyses, the ensemble forecast compares well to results from NASA's current operational cancer risk projection model used to assess permissible exposure limits and permissible mission durations for astronauts. However, a large range of projected risk values are obtained at the upper 95th confidence level where models must extrapolate beyond available biological data sets; closer agreement is seen at the median + one sigma due to the inherent similarities in available models. Future work, including the addition of new models and methods for statistical correlation between predictive members are discussed to define alternate ways of thinking about risk and ‘acceptable’ uncertainty with respect to NASA’s current permissible exposure limits.

Lisa C Simonsen↗

Getting to the Heart of Cardiovascular Risk Assessment in Astronauts for Exploration Class Missions

Since the beginning of manned spaceflight, NASA has recognized the potential risk of cardiovascular decrements due to stressors in the space environment. Of particular concern is the effect of space radiation on cardiovascular disease since astronauts will be exposed to higher levels of galactic cosmic rays outside the Earth's protective magnetosphere. To date, only a few studies have examined the effects of heavy ion radiation on cardiovascular disease, and at lower, space-relevant doses, the association between radiation exposure and cardiovascular pathology is more varied and unclear. Furthermore, other spaceflight conditions such as microgravity, circadian shifts, and confinement stress pose unique challenges in estimating the health risks that can be attributed to exposure to ionizing radiations. In this work, we review age, cause of mortality, and radiation exposure amongst early NASA astronauts in selection groups and discuss the limitations of assessing such a cohort when attempting to characterize the risk of space flight, including stressors such as space radiation and microgravity exposure, on cardiovascular health. METHODS: NASA astronauts in selection groups 1-7 were chosen and the comparison population was white men of the same birth cohort as drawn from data from the CDC Wonder Database and CDC National Center for Health Statistics Life Tables. Cause of death information was obtained from the Lifetime Surveillance of Astronaut Health program and deceased astronauts were classified based on ICD-10 codes: ischemic heart disease (IHD), stroke, cancer, acute occupational events, non-NASA accidents, and other/unknown. Expected years of life left and expected age at death were calculated for the cohort. RESULTS AND CONCLUSIONS: There were 32 deaths in this early astronaut population, 12 of which were due to accidents or acute occupational events that impacted lifespan considerably. The average age at death from these causes is 30 years lower than the average expected ~70 years of age in the general population. Remarkably, all 41 living early astronauts outlived our calculated expected age at death for members of their birth cohort; furthermore, 13 of the 20 deceased astronauts who did not die in NASA/non-NASA accidents exceeded this age. There was no difference in IHD between the astronaut cohort and the comparison population; therefore, it is not possible to associate IHD mortality with radiation in that astronaut cohort. As NASA looks toward future exploration-class missions, early astronaut cohorts provide a convenient option for assessing these risks and for developing mitigation strategies. However, many challenges still exist when assessing such limited evidence, including small cohort size, health and lifestyle confounders (such as smoking and drinking), the high accident mortality rate, and the fact that many of these astronauts are still alive, outliving many of their birth-cohort peers. Future analysis should include a longitudinal study, monitoring cases as they occur in the cohort. As this cohort is currently followed-up over time, and as more IHD cases are anticipated in a population of this age, this type of study is not as resource-intensive as would normally be the case.

Elgart, S. R.↗

Probabilistic Risk Assessment for Astronaut Post Flight Bone Fracture

Introduction: Space flight potentially reduces the loading that bone can resist before fracture. This reduction in bone integrity may result from a combination of factors, the most common reported as reduction in astronaut BMD. Although evaluating the condition of bones continues to be a critical aspect of understanding space flight fracture risk, defining the loading regime, whether on earth, in microgravity, or in reduced gravity on a planetary surface, remains a significant component of estimating the fracture risks to astronauts. This presentation summarizes the concepts, development, and application of NASA's Bone Fracture Risk Module (BFxRM) to understanding pre-, post, and in mission astronaut bone fracture risk. The overview includes an assessment of contributing factors utilized in the BFxRM and illustrates how new information, such as biomechanics of space suit design or better understanding of post flight activities may influence astronaut fracture risk. Opportunities for the bone mineral research community to contribute to future model development are also discussed. Methods: To investigate the conditions in which spaceflight induced changes to bone plays a critical role in post-flight fracture probability, we implement a modified version of the NASA Bone Fracture Risk Model (BFxRM). Modifications included incorporation of variations in physiological characteristics, post-flight recovery rate, and variations in lateral fall conditions within the probabilistic simulation parameter space. The modeled fracture probability estimates for different loading scenarios at preflight and at 0 and 365 days post-flight time periods are compared. Results: For simple lateral side falls, mean post-flight fracture probability is elevated over mean preflight fracture probability due to spaceflight induced BMD loss and is not fully recovered at 365 days post-flight. In the case of more energetic falls, such as from elevated heights or with the addition of lateral movement, the contribution of space flight quality changes is much less clear, indicating more granular assessments, such as Finite Element modeling, may be needed to further assess the risks in these scenarios.

Risk Analysis↗

Ensemble Methodologies for Astronaut Cancer Risk Assessment in the face of Large Uncertainties

A new approach to NASA space radiation risk modeling has successfully extended the current NASA probabilistic cancer risk model to an ensemble framework able to consider sub-model parameter uncertainty (e.g. uncertainty in a radiation quality parameter) as well as model-form uncertainty associated with differing theoretical or empirical formalisms (e.g. combined dose-rate and radiation quality effects). Ensemble methodologies are already widely used in weather prediction, modeling of infectious disease outbreaks, and certain terrestrial radiation protection applications to better understand how uncertainty may influence risk decision-making. Applying ensemble methodologies to space radiation risk projections offers the potential to efficiently incorporate emerging research results, allow for the incorporation of future (including international) models, improve uncertainty quantification for underlying sub-models developed against sparse experimental data, and reduce the impact of subjective bias on risk projections. Moreover, risk forecasting across an ensemble of multiple predictive models can provide stakeholders additional information on risk acceptance if current health/medical standards cannot be met or the level of knowledge doesn’t permit a specific risk or exposure limit to be developed for future space exploration missions. In this work, ensemble risk projections implementing multiple sub-models of radiation quality, dose and dose-rate effectiveness factors, excess risk, and latency as ensemble members are presented. Initial consensus methods for ensemble model weights and correlations to account for individual model bias are discussed. In these analyses, the ensemble forecast compares well to results from NASA's current operational cancer risk projection model used to assess permissible exposure limits and permissible mission durations for astronauts. However, a large range of projected risk values are obtained at the upper 95th confidence level where models must extrapolate beyond available biological data sets; closer agreement is seen at the median + one sigma due to the inherent similarities in available models. Future work, including the addition of new models and methods for statistical correlation between predictive members are discussed to define alternate ways of thinking about risk and ‘acceptable’ uncertainty with respect to NASA’s current permissible exposure limits.

space radiation↗

Utility of Terrestrial Cardiovascular Disease Data in Astronaut Radiation Risk Assessment – A Case Study Showing Increased Risk with Clonal Hematopoiesis of Indeterminate Potential

Cardiovascular disease (CVD) is associated with high doses of radiation and is are cognized health risk for astronauts on multiple or long duration exploration missions to the Moon or Mars. Currently, radiation risk assessment is based on background population disease rates and does not consider individual risk factors that may modify analysis, especially at lower radiation doses.

Zarana S Patel↗

Improvements to the Ionizing Radiation Risk Assessment Program for NASA Astronauts

To perform dosimetry and risk assessment, NASA collects astronaut ionizing radiation exposure data from space flight, medical imaging and therapy, aviation training activities and prior occupational exposure histories. Career risk of exposure induced death (REID) from radiation is limited to 3 percent at a 95 percent confidence level. The Radiation Health Office at Johnson Space Center (JSC) is implementing a program to integrate the gathering, storage, analysis and reporting of astronaut ionizing radiation dose and risk data and records. This work has several motivations, including more efficient analyses and greater flexibility in testing and adopting new methods for evaluating risks. The foundation for these improvements is a set of software tools called the Astronaut Radiation Exposure Analysis System (AREAS). AREAS is a series of MATLAB(Registered TradeMark)-based dose and risk analysis modules that interface with an enterprise level SQL Server database by means of a secure web service. It communicates with other JSC medical and space weather databases to maintain data integrity and consistency across systems. AREAS is part of a larger NASA Space Medicine effort, the Mission Medical Integration Strategy, with the goal of collecting accurate, high-quality and detailed astronaut health data, and then securely, timely and reliably presenting it to medical support personnel. The modular approach to the AREAS design accommodates past, current, and future sources of data from active and passive detectors, space radiation transport algorithms, computational phantoms and cancer risk models. Revisions of the cancer risk model, new radiation detection equipment and improved anthropomorphic computational phantoms can be incorporated. Notable hardware updates include the Radiation Environment Monitor (which uses Medipix technology to report real-time, on-board dosimetry measurements), an updated Tissue-Equivalent Proportional Counter, and the Southwest Research Institute Radiation Assessment Detector. Also, the University of Florida hybrid phantoms, which are flexible in morphometry and positioning, are being explored as alternatives to the current NASA computational phantoms.

Semones, E. J.↗

Comparison of chromosome aberration frequencies in pre- and post-flight astronaut lymphocytes irradiated in vitro with gamma rays

If radiosensitivity is altered in a microgravity environment, it will affect the accuracy of assessing astronauts' risk from exposure to space radiation. To investigate the effects of space flight on radiosensitivity, we exposed a crewmember's blood to gamma rays at doses ranging from 0 to 3 Gy and analyzed chromosome aberrations in mitotic lymphocytes. The blood samples were collected 10 days prior to an 8-day Shuttle mission, the day the flight returned, and 14 days after the flight. After exposure, lymphocytes were stimulated to grow in media containing phytohaemagglutinin (PHA) and mitotic cells were harvested for chromosome analysis using a fluorescence in situ hybridization (FISH) with whole chromosome specific probes. The dose response of total exchanges showed no changes in the radiosensitivity after the mission.

manned↗

Impact of AMS-02 Measurements on Reducing GCR Model Uncertainties

For vehicle design, shield optimization, mission planning, and astronaut risk assessment, the exposure from galactic cosmic rays (GCR) poses a significant and complex problem both in low Earth orbit and in deep space. To address this problem, various computational tools have been developed to quantify the exposure and risk in a wide range of scenarios. Generally, the tool used to describe the ambient GCR environment provides the input into subsequent computational tools and is therefore a critical component of end-to-end procedures. Over the past few years, several researchers have independently and very carefully compared some of the widely used GCR models to more rigorously characterize model differences and quantify uncertainties. All of the GCR models studied rely heavily on calibrating to available near-Earth measurements of GCR particle energy spectra, typically over restricted energy regions and short time periods. In this work, we first review recent sensitivity studies quantifying the ions and energies in the ambient GCR environment of greatest importance to exposure quantities behind shielding. Currently available measurements used to calibrate and validate GCR models are also summarized within this context. It is shown that the AMS-II measurements will fill a critically important gap in the measurement database. The emergence of AMS-II measurements also provides a unique opportunity to validate existing models against measurements that were not used to calibrate free parameters in the empirical descriptions. Discussion is given regarding rigorous approaches to implement the independent validation efforts, followed by recalibration of empirical parameters.

Slaba, T. C.↗

The Local Tissue Environment During the September 29, 1989 Solar Particle Event

The solar particle event (SPE) of September 29, 1989, produced an iron-rich spectrum with energies approaching 1 GeV/amu with an energy power index of 2.5. These high charge and energy (HZE) ions of the iron-rich SPEs challenge conventional methods of SPE shield design and assessment of astronaut risks. Shield and risk assessments are evaluated using the HZETRN code with computerized anatomical man (CAM) model for astronaut s body tissues. Since the HZE spectra decline rapidly with energy and HZE attenuation in materials is limited by their penetration power, details of the mass distributions about the sensitive tissues (shielding materials and the astronaut's body) are important determining factors of the exposure levels. Typical space suit and lightly shielded structures allow significant contributions from HZE components to some critical body tissues and have important implications on the models for risk assessment. Only a heavily shielded equipment room of a space vehicle or habitat provides sufficient shielding for the early response at sensitive organs from this event. The February 23, 1956 event of similar spectral characteristics and ten times this event may have important medical consequences without a well-shielded region.

Kim, M.-H. Y.↗

Radiation Risk Assessment of the Individual Astronaut: A Complement to Radiation Interests at the NIH

Predicting human risks following exposure to space radiation is uncertain in part because of unpredictable distribution of high-LET and low-dose-derived damage amongst cells in tissues, unknown synergistic effects of microgravity upon gene- and protein-expression, and inadequately modeled processing of radiation-induced damage within cells to produce rare and late-appearing malignant cancers. Furthermore, estimation of risks of radiogenic outcome within small numbers of astronauts is not possible using classic epidemiologic study. It therefore seems useful to develop strategies of risk-assessment based upon large datasets acquired from correlated biological models useful for resolving radiogenic risk-assessment for irradiated individuals. In this regard, it is suggested that sensitive cellular biodosimeters that simultaneously report 1) the quantity of absorbed dose after exposure to ionizing radiation, 2) the quality of radiation delivering that dose, and 3) the biomolecular risk of malignant transformation be developed in order to resolve these NASA-specific challenges. Multiparametric cellular biodosimeters could be developed using analyses of gene-expression and protein-expression whereby large datasets of cellular response to radiation-induced damage are analyzed for markers predictive for acute response as well as cancer-risk. A new paradigm is accordingly addressed wherein genomic and proteomic datasets are registered and interrogated in order to provide statistically significant dose-dependent risk estimation in individual astronauts. This evaluation of the individual for assessment of radiogenic outcomes connects to NIH program in that such a paradigm also supports assignment of a given patient to a specific therapy, the diagnosis of response of that patient to therapy, and the prediction of risks accumulated by that patient during therapy - such as risks incurred by scatter and neutrons produced during high-energy Intensity-Modulated Radiation Therapy. Value of assessment of radiogenic outcome for individuals exposed to radiation is suggested to be common to both NASA and NIH.

Richmond, Robert C.↗

Resolving Risks in Individual Astronauts: A New Paradigm for Critical Path Exposures

The limited number of astronauts available for risk-assessment prevents classic epidemiologic study, and thereby requires alternative approach to assessing risks within individual astronauts exposed to toxic agents identified within the Bioastronautics Critical Path Roadmap (BCPR). Developing a system of noninvasive real-time biodosimetry that provides large datasets for analyses before, during, and after missions for simultaneously determining 1) the kinds of toxic insult, 2) the degree of that insult, both within tissues absorbing that insult, would be usehl for resolving statistically significant risk-assessment in individual astronauts. Therefore, a currently achievable multiparametric paradigm is presented for use in analyzing gene-expression and protein-expression so as to establish predictive outcomes.

Richmond, Robert C.↗

A Shielding Model for an Inflatable Vehicle, TransHab, and the Associated Astronaut Space Radiation Risk Assessment

TransHab, a habitable inflatable structure, has been proposed as a possible module for the International Space Station that provides significant increase in the available volume compared with the US Hab module and fo r a human Mars mission . A study was undertaken to understand and provide design inputs for crew radiation exposures. The results show that the current design provides sufficient shielding to assure that the crew exposures are below the crew exposure limits currently adopted for the ISS. In addition, the shielding provides adequate protection from the largest solar particle events (SPEs) observed during the last 40 years.

Atwell, William↗