The microdosimetric-kinetic (MK) model for cell killing by ionizing radiation is summarized. An equation based on the MK model is presented which gives the dependence of the relative biological effectiveness in the limit of zero dose (RBE1) on the linear energy transfer (LET). The relationship coincides with the linear relationship of RBE1 and LET observed for low LET, which is characteristic of a Poisson distribution of lethal lesions among the irradiated cells. It incorporates the effect of deviation from the Poisson distribution at higher LET. This causes RBE1 to be less than indicated by extrapolation of the linear relationship to higher LET, and to pass through a maximum in the range of LET of 50 to 200 keV per micrometer. The relationship is compared with several experimental studies from the literature. It is shown to approximately fit their results with a reasonable choice for the value of a cross-sectional area related to the morphology and ultrastructure of the cell nucleus. The model and the experiments examined indicate that the more sensitive cells are to radiation at low LET, the lower will be the maximum in RBE they attain as LET increases. An equation that portrays the ratio of the sensitivity of a pair of cell types as a function of LET is presented. Implications for radiotherapy with high-LET radiation are discussed.

A model of mammalian cell death and survival following exposure to ionizing radiation that combines a kinetic description of repair and injury processes with a microdosimetric description of radiation energy deposition is presented. With reduction of one of the defining kinetic equations from quadratic to linear form, relations are obtained that describe the results of commonly performed variations of the cell survival experiment. These include single-dose survival of linear-quadratic form, survival after split-dose treatment and after post-irradiation change ill culture conditions and survival after exposure to continuously administered irradiation at low constant dose-rate. The effect of the inhomogeneous deposition of radiation energy inherent in exposure to radiation of significantly non-zero LET is included in these relations which apply to radiation of any LET. The values of the kinetic rate and time constants for repair and the processes that lead to cell death postulated in the model, which compose the alpha and beta parameters of the linear-quadratic survival relation, are estimated from cell survival experiments and DNA double-strand break measurements from the literature. A relation for estimating the daily fractional dose equivalent to continuous irradiation as employed in low dose-rate brachytherapy cancer treatment is presented.

A theory is presented that provides an explanation for the observed features of the survival of cultured cells after exposure to densely ionizing high-linear energy transfer (LET) radiation. It starts from a phenomenological postulate based on the linear-quadratic form of cell survival observed for low-LET radiation and uses principles of statistics and fluctuation theory to demonstrate that the effect of varying LET on cell survival can be attributed to random variation of dose to small volumes contained within the nucleus. A simple relation is presented for surviving fraction of cells after exposure to radiation of varying LET that depends on the alpha and beta parameters for the same cells in the limit of low-LET radiation. This relation implies that the value of beta is independent of LET. Agreement of the theory with selected observations of cell survival from the literature is demonstrated. A relation is presented that gives relative biological effectiveness (RBE) as a function of the alpha and beta parameters for low-LET radiation. Measurements from microdosimetry are used to estimate the size of the subnuclear volume to which the fluctuation pertains.

PCV produces tumor regressions in a meaningful proportion of patients with LGO/LGOA. Toxicity, especially myelosuppression, is significant. Loss of 1p and 19q seems limited to patients with pure LGO and is inversely related to p53 alterations.