Changes induced in the human respiratory tract by chronic cigarette smoking can reduce the dose to the lungs from exposure to radon progeny.

Chronic cigarette smoking leads to changes in the respiratory tract that might affect the dose received from exposure to radon progeny. In this study, changes induced by cigarette smoking in the respiratory tract were collected from the literature and used for calculation of the dose received by the lungs and organs outside the respiratory tract. Morphological and physiological parameters affected by chronic smoking were implemented in the human respiratory tract model (HRTM) used by the International Commission of Radiological Protection (ICRP). Smokers were found to receive lung doses 3% smaller than the ICRP reference worker (non-smoking reference adult male) in mines and 14% smaller in indoor workplaces and tourist caves. A similar dose reduction was found for the extrathoracic region of the HRTM. Conversely, kidneys, brain, and bone marrow of smokers were found to receive from 2.3- up to 3-fold of the dose received by the respective organ in the ICRP reference worker, although they remained at least two orders of magnitude smaller than the lung dose. These results indicate that the differences in the lung dose from radon progeny exposure in cigarette smokers and non-smokers are smaller than 15%.

Patient-specific biokinetics and hybrid 2D/3D approach integration in OEDIPE software: Application to radioiodine therapy.

BACKGROUND: The progression of targeted radionuclide therapy requires the development of dosimetry software accounting for patient-specific biokinetics. New functionalities were thus developed in the OEDIPE software, to deal with multiple 3D images or multiple planar images and a SPECT image. MATERIEL & METHOD: Methods were implemented to recover patient biokinetics in volumes of interest. If several 3D SPECT images are available, they are registered to a reference CT scan. When several planar images and a single SPECT are available, the planar images are registered to the SPECT and counts of the planar images converted to activity. To validate these developments, six SPECT/CT and planar images of a Jaszczak phantom containing I-131 were acquired at different dates. Cumulated activity was estimated in each sphere using the SPECT/CT images only or the planar series associated to one SPECT/CT. Biokinetics and doses in lesions and in the lungs of a patient treated with I-131 for differentiated thyroid cancer were then estimated using four planar images and a SPECT/CT scan. Whole-body retention data were used to compare the biokinetics obtained from the planar and SPECT data. RESULTS: Activities and cumulated activities estimated using OEDIPE in the phantom spheres agreed well with the reference values for both approaches. Results obtained for the patient compared well with those derived from whole-body retention data. CONCLUSION: The implemented features allow automatic evaluation of patient-specific biokinetics from different series of patient images, enabling patient-specific dosimetry without the need for external software to estimate the cumulated activities in different VOIs.

Optimisation of internal contamination monitoring programme by integration of uncertainties.

Potential internal contamination of workers is monitored by periodic bioassay measurements interpreted in terms of intake and committed effective dose by the use of biokinetic and dosimetric models. After a prospective evaluation of exposure at a workplace, a suitable monitoring programme can be defined by choosing adequate measurement techniques and frequency. In this study, the sensitivity of a programme is evaluated by the minimum intake and dose, which may be detected with a given level of confidence by taking into account uncertainties on exposure conditions and measurements. This is made for programme optimisation, which is performed by comparing the sensitivities of different alternative programmes. These methods were applied at the AREVA NC reprocessing plant and support the current monitoring programme as the best compromise between the cost of the measurements and the sensitivity of the programme.

Integration of uncertainties into internal contamination monitoring.

Potential internal contaminations of workers are monitored by periodic bioassays interpreted in terms of intake and committed effective dose through biokinetic and dosimetric models. After a prospective evaluation of exposure at a workplace, a suitable monitoring program can be defined by the choice of measurement techniques and frequency of measurements. However, the actual conditions of exposure are usually not well defined and the measurements are subject to errors. In this study we took into consideration the uncertainties associated with a routine monitoring program in order to evaluate the minimum intake and dose detectable for a given level of confidence. Major sources of uncertainty are the contamination time, the size distribution and absorption into blood of the incorporated particles, and the measurement errors. Different assumptions may be applied to model uncertain knowledge, which lead to different statistical approaches. The available information is modeled here by classical or Bayesian probability distributions. These techniques are implemented in the OPSCI software under development. This methodology was applied to the monitoring program of workers in charge of plutonium purification at the AREVA NC reprocessing facility (La Hague, France). A sensitivity analysis was carried out to determine the important parameters for the minimum detectable dose. The methods presented here may be used for assessment of any other routine monitoring program through the comparison of the minimum detectable dose for a given confidence level with dose constraints.

Absorption of plutonium compounds in the respiratory tract.

In order to optimise the monitoring of potentially exposed workers, it is desirable to determine specific values of absorption for the compounds handled. This study derives specific values of absorption rates for different chemical forms of plutonium from in vitro and animal (monkeys, dogs, mice, rats) experiments, and from human contamination cases. Different published experimental data have been reinterpreted here to derive values for the absorption parameters, f(r), s(r) and s(s), used in the human respiratory tract model currently adopted by the International Commission on Radiological Protection (ICRP). The consequences of the use of these values were investigated by calculating related committed effective doses per unit intake. Average and median estimates were calculated for f(r), s(r), and s(s) for each plutonium compound, that can be used as default values for specific chemical forms instead of the current reference types. Nevertheless, it was shown that the use of the current ICRP reference absorption types provides reasonable approximations. Moreover, this work provides estimates of the variability in pulmonary absorption and, therefore, facilitates analyses of the uncertainties associated with assessments, either from bioassay measurements or from prospective calculations, of intake and dose.

Modeling the imprecision in prospective dosimetry of internal exposure to uranium.

The dosimetry of internal exposure to radionuclides is performed on the basis of biokinetic and dosimetric models. For prospective purpose, the organ or effective dose resulting from potential conditions of exposure can be calculated by applying these models with dedicated software. However, it is acknowledged that a significant uncertainty is associated with such calculation due to the variability of individual cases and to the possible lack of knowledge about some factors influencing the dosimetry. This uncertainty has been studied in a range of situations by modeling the uncertainty on the model parameters by probability distributions and propagating this uncertainty onto the dose result by Monte Carlo calculation. However, while probability distributions are well adapted to model the known variability of a parameter, they may lead to an unrealistically low estimate of the uncertainty due to a lack of knowledge about some input parameters. Here we present a mathematical method, based on the Dempster-Shafer theory, to deal with such imprecise knowledge. We apply this method to the prospective dosimetry of inhaled uranium dust in the nuclear fuel cycle when its physico-chemical properties are not precisely known. The results show an increased estimation of the range of uncertainty as compared to the application of a probabilistic method. This Dempster-Shafer method may valuably be applied in future prospective dosimetry of internal exposure in order to more realistically estimate the uncertainty resulting from an imprecise knowledge of the parameters of the dose calculation.