Radiation exposure, models used estimating risks from

Radiation-induced genomic instability and bystander effects are now well-established consequences of exposure of living cells to ionizing radiation. Cells not directly traversed by radiation may still exhibit radiation effects. This phenomenon, known as bystander effect, has become a major activity in radiation biology and in some cases has challenged the conventional wisdom. An example is the currently accepted models used for low-dose extrapolation of radiation risks. The currently used models assume that cells in an irradiated population respond individually rather than collectively. If bystander effects have implications for health risks estimates from exposure to ionizing radiation, then the question of whether this is a general phenomenon or solely a characteristic of a particular type of cell and the radiation under test becomes an important issue. 

UCL takes into account measurement uncertainty in the study used to estimate the dose-response relationship, such as the statistical uncertainty in the number of tumors at each administered dose, but it does not take into account other uncertainties, such as the relevance of animal data to humans. It is important to emphasize that UCL gives an indication of how well the model fits the data at the high doses where data are available, but it does not indicate how well the model reflects the true response at low doses. The reason for this is that the bounding procedure used is highly conservative. Use of UCL has become a routine practice in dose-response assessments for chemicals that cause stochastic effects even though a best estimate (MLE) also is available (Crump, 1996 Crump et al., 1976). Occasionally, EPA will use MLE of the dose-response relationship obtained from the model if human epidemiologic data, rather than animal data, are used to estimate risks at low doses. MLEs have been used nearly universally in estimating stochastic responses due to radiation exposure. 

Models of radiation damage have been explored and are well developed. For many years, accidental releases of ionizing radiation have been universally feared. Alternatively, radiation has been used in controlled, defined amoimts as a therapy for certain tumors in both companion animals and humans. Taken together, all studies provide a cohesive and comprehensive picture of radiation toxicity. There are sufficient details of radiation effects to make credible estimates of risk resulting from radiation exposure (Harley 2001, 2008). 

The methodology leading to the presented risk estimates has serious hmitations. Firstly, the risk models are based on extrapolated data of the consequences of radiation exposure, and secondly, the appHed Monte Carlo methods use standardized geometrical phantoms not corresponding to different types of patient morphology. However, as Einstein states, ...this study provides a simplified approach, albeit one that we beheve is the best available from current data. ... 

Dogs exposed to radium to establish coefficients for plutonium produced data that showed the best way to translate data to humans was to use a two-mutation model to calculate radiation risks to supplement published risk estimates (Bijwaard, 2006 Bijwaard and Dekkers, 2007). The total exposure resulting from a 5 mGi administration of 18F fluoroethyl cyanophenoxy methyl piperidine 18F SFE as a tracer show it to be safe in human positron emission tomography (PET) imaging studies (Waterhouse et al, 2006). 

---