RBE and radiation weighting factors as applied in the context of protection of the environment from ionising radiation

نویسندگان

  • K. A. Higley
  • D. C. Kocher
  • A. G. Real
  • D. B. Chambers
چکیده

It has long been recognized that the degree of biological impact on an organism resulting from a given absorbed dose of ionising radiation can vary depending upon the type of radiation involved. This difference has been experimentally quantified and reported as the “relative biological effectiveness” (RBE) of specific radiation types. RBE values have been measured for a variety of end points in in vitro experiments that include human and animal cell lines, as well as in vivo experiments with animals. Such studies have shown that the magnitude of a biological effect depends not only on dose and the type and energy of the radiation delivering the dose, but also on the rate at which the dose is delivered and, most importantly, the endpoint under study. The need to apply this knowledge to radiation protection of humans has led to an aggregation and analysis of RBE data to develop such constructs as “radiation weighting factors”. In recent years, radiation protection has taken on a broader meaning, and is now evolving to include protection of the environment from ionising radiation. However, the application of radiation weighting factors in the context of assessing biologically significant doses to animals and plants is not without some controversy. Protection of biota from the effects of ionising radiation has largely focused on endpoints which are relevant at the population level, such as reduced reproductive fitness. This means that use of radiation weighting factors derived from evaluations of stochastic effects, as in the system of protection for humans, appears inappropriate. This presentation discusses efforts to develop a logical, transparent, and defensible approach to establishing radiation weighting factors for use in assessing impacts to non-human biota. It also considers the challenges in differentiating stochastic from deterministic impacts.

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تاریخ انتشار 2015