Last Published:  07/30/21 01:05:31 PM (Central)
Responsible Element: Space Radiation (SR)
Status: Open
Description

The predominant factor contributing the most uncertainty to risk of exposure-induced death (REID) estimates is radiation quality. Space radiation exposure differs from that experienced by humans in the terrestrial environment, specifically in the type of radiation. Whereas terrestrial exposures are comprised predominately of photons and radioactive decay emission (X- or γ-rays, α-particles, β-particles), space radiation exposure encompasses a mixture of different ion species ranging from hydrogen and neutrons to gold and larger. The impact of these mixed fields on carcinogenesis and related adverse outcomes are not well characterized. Evidence from animal models indicates that high-energy and charge particle (HZE) irradiation increases tumor incidence in a dose- and species-dependent manner when compared to photon irradiation with relative biological effectiveness (RBE) values ranging from 1 to over 50 in some solid tumor types. Additional evidence suggests that HZE irradiation may shorten the time to tumor malignancy and produce tumors that are more aggressive. Furthermore, it is not known how a mixed field made of multiple ions contributes to carcinogenic risk compared to individual ions. Therefore, research characterizing the effect of radiation quality on radiation carcinogenesis is critical for appropriate extrapolation of excess risk from available human epidemiological data. Characterization of the role radiation quality plays in space radiation associated carcinogenesis will also provide potential targets for countermeasures and mitigation strategies.

Approach

Ground-based research using appropriate in vitro and in vivo models to acquire the necessary datasets for accurate estimation of radiation quality effects for protons, heavy ions, and secondary neutrons. NASA Space Radiation Laboratory (NSRL) at Brookhaven National Laboratory (BNL) supports multiple ion and mixed field studies with fast ion switching for more complex mixed-field GCR simulations. Additional approaches also include advanced biostatistical methods to combine past, current, and future research results into data-driven models.

Target for Closure
  • Data-driven models of radiation quality effects that can be implemented to accurately scale low-LET excess cancer risk estimates to the space radiation environment.

     

  • Strategies to translate impacts to human populations where scaling from epidemiological data is either not possible or not appropriate.
Mappings
Risk Risk of Radiation Carcinogenesis
You are here! Gap Cancer-103: Determine the effects of radiation quality on cancer initiation, promotion, and progression.
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