Whether it is astronauts exposed to space radiation or patients receiving radiotherapy, there is a benefit to knowing how radiation effects at a sub-cellular level correspond to whole-body effects over a lifetime. The basis for predicting cell death and radiation effects has a foothold in DNA damage and cell survival curve models.
These current models for mammalian cell survival follow experimental observations of in- vitro irradiation, but do not predict radiation effects on the whole-body scale. The concept of DNA as the primary target for negative radiation outcomes can be attributed to in-vitro studies of non-mammalian cells indicating that DNA was the more radiosensitive structure in the cell. As a result, subsequent studies have irradiated DNA strands and observed repair mechanisms and aberrations.
Using numerical methods, the research will look at how damage from heavy ion radiation exposure at the sub-microscopic level evolves to whole-body effects, and then work to increase the accuracy. The ions chosen are those commonly found in clinical settings and are of major concern with space exploration. By numerically modeling what is occurring at the smaller, sub-microscopic scale, we will be able to follow the result of the damage to explain and predict whole-body effects.
The research done will not make the assumption that DNA is the primary target of interest for assessing both the short- and long- term effects of exposure to ionizing radiation. We will look into how damage to each organelle corresponds to the overall function of the cell and scale this damage up to evaluate the magnitude of influence that damaged cell structures have on the whole body. Most of the data for whole-body noncancer effects, such as cardiovascular or neural side effects, were obtained after acute high dose radiation exposure events. Thus, there is a lack of data for whole-body absorbed dose over a prolonged period of time.
The parameters of current models use dose rate, dose equivalent, LET, and RBE to explain cell survival from radiation exposure. These models, coupled with experimental observations, attempt to find the probability of stochastic radiation outcomes. So, cancerous effects can be better predicted, but there is a lack of substantial evidence following radiation side effects, like non-malignant disease. With concepts like equivalent dose that are based in late stochastic effects, the parameters that make up the basis for cell survival curves may not be appropriate for use in predicting early and late noncancerous radiation effect risks.
In conclusion, sub-microscopic damage is currently predicted from a macroscopic level and this data, in the realm of radiotherapy, is used to describe how cell death corresponds to necrosis and how much a tumor is eradicated from the healthy tissue.
