Flying without a Net: Space Radiation Cancer Risk Predictions without a Gamma-ray Basis

Abstract

The biological effects of high linear energy transfer (LET) radiation show both a qualitative and quantitative difference when compared to low-LET radiation. However, models used to estimate risks ignore qualitative differences and involve extensive use of gamma-ray data, including low-LET radiation epidemiology, quality factors (QF), and dose and dose-rate effectiveness factors (DDREF). We consider a risk prediction that avoids gamma-ray data by formulating a track structure model of excess relative risk (ERR) with parameters estimated from animal studies using high-LET radiation. The ERR model is applied with U.S. population cancer data to predict lifetime risks to astronauts. Results for male liver and female breast cancer risk show that the ERR model agrees fairly well with estimates of a QF model on non-targeted effects (NTE) and is about 2-fold higher than the QF model that ignores NTE. For male or female lung cancer risk, the ERR model predicts about a 3-fold and more than 7-fold lower risk compared to the QF models with or without NTE, respectively. We suggest a relative risk approach coupled with improved models of tissue-specific cancers should be pursued to reduce uncertainties in space radiation risk projections. This approach would avoid low-LET uncertainties, while including qualitive effects specific to high-LET radiation.