On the choice of methodology for evaluating dose-rate effects on radiation-related cancer risks

Recently, several compilations of individual radiation epidemiology study results have aimed to obtain direct evidence on the magnitudes of dose-rate effects on radiation-related cancer risks. These compilations have relied on meta-analyses of ratios of risks from low dose-rate studies and matched risks from the solid cancer Excess Relative Risk models fitted to the acutely exposed Japanese A-bomb cohort. The purpose here is to demonstrate how choices of methodology for evaluating dose-rate effects on radiation-related cancer risks may influence the results reported for dose-rate effects. The current analysis is intended to address methodological issues and does not imply that the authors recommend a particular value for the dose and dose-rate effectiveness factor. A set of 22 results from one recent published study has been adopted here as a test set of data for applying the many different methods described here, that nearly all produced highly consistent results. Some recently voiced concerns, involving the recalling of the well-known theoretical point—the ratio of two normal random variables has a theoretically unbounded variance—that could potentially cause issues, are shown to be unfounded when aimed at the published work cited and examined in detail here. In the calculation of dose-rate effects for radiation protection purposes, it is recommended that meta-estimators should retain the full epidemiological and dosimetric matching information between the risks from the individual low dose-rate studies and the acutely exposed A-bomb cohort and that a regression approach can be considered as a useful alternative to current approaches

First steps towards a fast-neutron therapy planning program

<p>Abstract</p> <p>Background</p> <p>The Monte Carlo code GEANT4 was used to implement first steps towards a treatment planning program for fast-neutron therapy at the FRM II research reactor in Garching, Germany. Depth dose curves were calculated inside a water phantom using measured primary neutron and simulated primary photon spectra and compared with depth dose curves measured earlier. The calculations were performed with GEANT4 in two different ways, simulating a simple box geometry and splitting this box into millions of small voxels (this was done to validate the voxelisation procedure that was also used to voxelise the human body).</p> <p>Results</p> <p>In both cases, the dose distributions were very similar to those measured in the water phantom, up to a depth of 30 cm. In order to model the situation of patients treated at the FRM II MEDAPP therapy beamline for salivary gland tumors, a human voxel phantom was implemented in GEANT4 and irradiated with the implemented MEDAPP neutron and photon spectra. The 3D dose distribution calculated inside the head of the phantom was similar to the depth dose curves in the water phantom, with some differences that are explained by differences in elementary composition. The lateral dose distribution was studied at various depths. The calculated cumulative dose volume histograms for the voxel phantom show the exposure of organs at risk surrounding the tumor.</p> <p>Conclusions</p> <p>In order to minimize the dose to healthy tissue, a conformal treatment is necessary. This can only be accomplished with the help of an advanced treatment planning system like the one developed here. Although all calculations were done for absorbed dose only, any biological dose weighting can be implemented easily, to take into account the increased radiobiological effectiveness of neutrons compared to photons.</p

Time-integrated radiation risk metrics and interpopulation variability of survival

Task Group 115 of the International Commission on Radiological Protection is focusing on mission-related exposures to space radiation and concomitant health risks for space crew members including, among others, risk of cancer development. Uncertainties in cumulative radiation risk estimates come from the stochastic nature of the considered health outcome (i.e., cancer), uncertainties of statistical inference and model parameters, unknown secular trends used for projections of population statistics and unknown variability of survival properties between individuals or population groups. The variability of survival is usually ignored when dealing with large groups, which can be assumed well represented by the statistical data for the contemporary general population, either in a specific country or world averaged. Space crew members differ in many aspects from individuals represented by the general population, including, for example, their lifestyle and health status, nutrition, medical care, training and education. The individuality of response to radiation and lifespan is explored in this modelling study. Task Group 115 is currently evaluating applicability and robustness of various risk metrics for quantification of radiation-attributed risks of cancer for space crew members. This paper demonstrates the impact of interpopulation variability of survival curves on values and uncertainty of the estimates of the time-integrated radiation risk of cancer