When internal doses are calculated for the purpose of epidemiology studies, it is important that an assessment of the uncertainty in these doses is performed. This assessment should include both uncertainties in measured quantities and those in the various parameter values used in the calculation. In the Mayak Worker dosimetry system this is achieved by assigning a probability distribution to each parameter value. Multiple realisations of the dose for each worker can then be produced by randomly sampling from each distribution during each realisation of the dose. This process is repeated for each worker. It is important to distinguish between parameter values which are shared between workers and those which are unshared. Monte Carlo techniques are used to implement this scheme. When running such a scheme in reverse, from measured data to intake and dose, it is necessary to take account of the varying goodness of fit to the data for different selections of parameter values. This requires the use of Bayesian statistics. A novel method called WelMoS was developed to apply the Bayesian method to these calculations.

Epidemiological studies have shown that the main risk arising from exposure to plutonium aerosols is lung cancer, with other detrimental effects in the bone and liver. A realistic assessment of these risks, in turn, depends on the accuracy of the dosimetric models used to calculate doses in such studies. A state-of-the-art biokinetic model for plutonium, based on the current International Commission on Radiological Protection biokinetic model, has been developed for this purpose in an epidemiological study involving the plutonium exposure of Mayak workers in Ozersk, Russia. One important consequence of this model is that the lung dose is extremely sensitive to the fraction (fb) of plutonium, which becomes bound to lung tissue after it dissolves. It has been shown that if just 1% of the material becomes bound in the bronchial region, this will double the lung dose. Furthermore, fb is very difficult to quantify from experimental measurements. This paper summarizes the work carried out thus far to quantify fb. Bayesian techniques have been used to analyze data from different sources, including both humans and dogs, and the results suggest a small, but nonzero, fraction of < 1%. A Bayesian analysis of 20 Mayak workers exposed to plutonium nitrate suggests an fb between 0 and 0.3%. Based on this work, the International Commission on Radiological Protection is currently considering the adoption of a value of 0.2% for the default bound fraction for all actinides in its forthcoming recommendations on internal dosimetry. In an attempt to corroborate these findings, further experimental work has been carried out by the US Transuranium and Uranium Registries. This work has involved direct measurements of plutonium in the respiratory tract tissues of workers who have been exposed to soluble plutonium nitrate. Without binding, one would not expect to see any activity remaining in the lungs at long times after exposure since it would have been cleared by the natural process of mucociliary clearance. Further supportive study of workers exposed to plutonium oxide is planned. This paper ascertains the extent to which these results corroborate previous inferences concerning the bound fraction.

In epidemiological studies, exposures of interest are often measured with uncertainties, which may be independent or correlated. Independent errors can often be characterized relatively easily while correlated measurement errors have shared and hierarchical components that complicate the description of their structure. For some important studies, Monte Carlo dosimetry systems that provide multiple realizations of exposure estimates have been used to represent such complex error structures. While the effects of independent measurement errors on parameter estimation and methods to correct these effects have been studied comprehensively in the epidemiological literature, the literature on the effects of correlated errors, and associated correction methods is much more sparse. In this paper, we implement a novel method that calculates corrected confidence intervals based on the approximate asymptotic distribution of parameter estimates in linear excess relative risk (ERR) models. These models are widely used in survival analysis, particularly in radiation epidemiology. Specifically, for the dose effect estimate of interest (increase in relative risk per unit dose), a mixture distribution consisting of a normal and a lognormal component is applied. This choice of asymptotic approximation guarantees that corrected confidence intervals will always be bounded, a result which does not hold under a normal approximation. A simulation study was conducted to evaluate the proposed method in survival analysis using a realistic ERR model. We used both simulated Monte Carlo dosimetry systems (MCDS) and actual dose histories from the Mayak Worker Dosimetry System 2013, a MCDS for plutonium exposures in the Mayak Worker Cohort. Results show our proposed methods provide much improved coverage probabilities for the dose effect parameter, and noticeable improvements for other model parameters.

Previous Mayak worker epidemiological studies designed to quantify the risk of cancer following exposure to airborne plutonium have calculated organ doses by dividing the organ-absorbed energy by the individual's estimated organ mass. For living workers, this was done by using a relationship between organ mass and total mass and height. For autopsy cases, this was measured directly. In the Mayak Worker Dosimetry System-2013 study, organ doses are calculated by dividing this energy by a population average organ mass. The reasons for departing from previous methodologies are described in this note. The average organ masses that were used in the final analysis are tabulated for males and females.

The calculation of reliable and realistic doses for use in epidemiological studies for the quantification of risk from internal exposure to radioactive material is fundamental to the development of advice, guidance and regulations for the control and use of radioactive material. Thus, any programme of work carried out which requires the calculation of doses for use by epidemiologists ideally should contain a rigorous program of quality assurance (QA). This paper describes the initial QA (Phase I) implemented by Public Health England (PHE) and the Southern Urals Biophysics Institute (SUBI) as part of the work programme on internal dosimetry in the Joint Coordinating Committee for Radiation Effects Research Project 2.4 for the 2013 Mayak Worker Dosimetry System. SUBI designed and implemented new software (PANDORA) to include the latest Mayak Worker Dosimetry System and to calculate organ burdens, urinary excretion rates, intakes and absorbed doses, while PHE modified their commercially available IMBA Professional Plus software package. Comparisons of output from the two codes for the Mayak Worker Dosimetry System 2013 showed calculated values of absorbed doses, intakes, organ burdens and urinary excretion agreed to within 1%. The 1% discrepancy can be explained by the approximation used in IMBA to speed up dose calculations.

Background: Carcinogenic risks of internal exposures to alphaemitters (except radon) are poorly understood. Since exposure to alpha particles-particularly through inhalation-occurs in a range of settings, understanding consequent risks is a public health priority. We aimed to quantify dose-response relationships between lung dose from alpha-emitters and lung cancer in nuclear workers.Methods: We conducted a case-control study, nested within Belgian, French, and UK cohorts of uranium and plutonium workers. Cases were workers who died from lung cancer; one to three controls were matched to each. Lung doses from alpha-emitters were assessed using bioassay data. We estimated excess odds ratio (OR) of lung cancer per gray (Gy) of lung dose.Results: The study comprised 553 cases and 1,333 controls. Median positive total alpha lung dose was 2.42 mGy (mean: 8.13 mGy; maximum: 316 mGy); for plutonium the median was 1.27 mGy and for uranium 2.17 mGy. Excess OR/Gy (90% confidence interval)adjusted for external radiation, socioeconomic status, and smokingwas 11 (2.6, 24) for total alpha dose, 50 (17, 106) for -plutonium, and 5.3 (-1.9, 18) for uranium.Conclusions: We found strong evidence for associations between low doses from alpha-emitters and lung cancer risk. The excess OR/Gy was greater for plutonium than uranium, though confidence intervals overlap. Risk estimates were similar to those estimated previously in plutonium workers, and in uranium miners exposed to radon and its progeny. Expressed as risk/equivalent dose in sieverts (Sv), our estimates are somewhat larger than but consistent with those for atomic bomb survivors.

In the Mayak Worker Dosimetry System (MWDS-2013), intakes of plutonium and organ doses are assessed on the basis of measurements made on the plutonium content of 56 400 urine samples. Altogether, there were urine bioassays for 7591 (29%) of the 25 757 cohort members who were employed any time at Mayak between 1948 and 1982. These measurements are subject to uncertainty due to many factors (e.g. whether or not creatinine is measured, the volume of the sample, whether diethylenetriaminepentaacetic acid was administered, etc.) and this uncertainty will affect not only the uncertainty in the estimated doses, but also the values of the doses themselves. Therefore, it is important for the estimated uncertainty to be as accurate as possible. The input to the dose calculation requires an estimate of the plutonium activity in a true 24-hour sample. The uncertainty in this activity is approximated by a lognormal distribution. The aim of this paper is to describe and justify how the parameters of this lognormal distribution are derived from the raw data. Histograms of the distribution of sample volumes are given for both sexes. The method of calculation of the decision threshold and relative standard uncertainty (RSU) of a measurement result for Pu activity in a worker's urine sample is shown. Diagrams of correlation between Pu activity in collected urine and its RSU are given.

The Alpha-Risk study required the reconstruction of doses to lung and red bone marrow for lung cancer and leukaemia cases and their matched controls from cohorts of nuclear workers in the UK, France and Belgium. The dosimetrists and epidemiologists agreed requirements regarding the bioassay data, biokinetic and dosimetric models and dose assessment software to be used and doses to be reported. The best values to use for uncertainties on the monitoring data, setting of exposure regimes and characteristics of the exposure material, including lung solubility, were the responsibility of the dosimetrist responsible for each cohort. Among 1721 subjects, the median absorbed dose to the lung from alpha radiations was 2.1 mGy, with a maximum dose of 316 mGy. The lung doses calculated reflect the higher levels of exposure seen among workers in the early years of the nuclear industry compared to today.

In the Mayak Worker Dosimetry System-2013, lung dose is calculated as an average of the three absorbed doses to the bronchial, the bronchiolar and the alveolar regions. Previous epidemiological studies involving Mayak Workers have used a lung dose calculated as the total energy deposited in the lungs divided by the mass. These two definitions lead to very different estimates of lung dose, especially for radon dosimetry. This paper uses the results of recent epidemiological studies to justify the use of a regionally weighted lung dose (wi = 1/3, I = 1, 3) over the use of an 'average lung' dose.

The Mayak Worker Dosimetry System (MWDS-2013) is a system for interpreting measurement data from Mayak workers from both internal and external sources. This paper is concerned with the calculation of annual organ doses for Mayak workers exposed to plutonium aerosols, where the measurement data consists mainly of activity of plutonium in urine samples. The system utilises the latest biokinetic and dosimetric models, and unlike its predecessors, takes explicit account of uncertainties in both the measurement data and model parameters. The aim of this paper is to describe the complete MWDS-2013 system (including model parameter values and their uncertainties) and the methodology used (including all the relevant equations) and the assumptions made. Where necessary, Supplementary papers which justify specific assumptions are cited.

The Mayak Worker Dosimetry System-2013 (MWDS-2013) uses a model developed by Leggett and colleagues to represent the biokinetic behaviour of plutonium after uptake to blood. Of particular importance, with regard to estimating intakes (and doses), is the distribution of activity between urine and body organs (particularly liver and skeleton). In this study, measurement data (urine and autopsy) from around 500 Mayak workers have been used to validate use of this model. A robust method has been developed and used to estimate intakes from both urine and autopsy data separately, and the ratio of these estimates has been calculated for each worker. The geometric mean ratio has been shown to lie within a range of 0.92-1.14, depending on assumptions made. Since this range includes 1, the hypothesis that the model is unbiased with regard to estimating intakes either with urine or autopsy data cannot be rejected on the basis of these data. This lends weight to the argument for increasing the MWDS-2013 cohort to include an additional 500 workers for whom only autopsy data are available, and who have previously been excluded from the cohort. Future directions in which this work could be extended are also suggested.

In order to check developed software tools, it was necessary to compare estimates of statistical characteristics of annual absorbed plutonium internal doses obtained by PANDORA and IMBA software with the same original data. The results were compared from dose calculations of five cases with different initial data on plutonium inhalation intake, lifetime measurements of plutonium activity in daily urine and post-mortem measurements in lungs, lung lymph nodes, liver and skeleton. Estimates of geometric mean and geometric standard deviation of annual regionally weighted lung dose and bone surface dose were compared. Satisfactory agreements of the estimates of statistical characteristics of annual doses to two critical organs for the selected cases were shown. One hundred individual hyper-realizations (forward model evaluations) are sufficient to calculate MWDS-2013 if only measurements of plutonium activity in daily urine are used, and 2000 individual hyper-realizations if both urine and autopsy measurement results are used.

Two important aspects in which the MWDS-2013 output (absorbed dose to organs calculated in each calendar year) differs from previous data bases (MWDS-2008 and DOSES-2005) are that they have been designed to (a) deal explicitly with uncertainties in model parameters, and (b) differentiate parameters that are considered to be shared (unknown, but having the same value for all workers) and unshared (unknown, but having different values between workers). A multiple-realisation approach is used to preserve information on the effects of shared and unshared parameters both for internal and external doses. Previously, a single realisation (a set of organ doses: one for each worker in the cohort) was calculated using the best estimates of parameter values only. In MWDS-2013, a set of 1000 realisations is produced, to reflect the uncertainty in assumed model parameters: each realisation using a different set of parameter values. Within each realisation, shared parameter values are fixed throughout the cohort, while unshared parameters are allowed to vary between workers. One problem is that because the calculation of organ dose is Bayesian, the estimate for each organ dose is not just a single value, but is itself a distribution (hyper-dose). Technically, it is the probability density of dose given the sampled set of parameter values and given the data for that worker. Thus, in our case, the realisations consist not of single doses, but distributions of doses. The term hyper-realisation is used to differentiate this from the more conventional realisation. Although the multiple hyper-realisation in principle contains all of the necessary information on parameter uncertainty, including shared and unshared parameters, in order to make preliminary epidemiological analyses tractable, and also for consistency with the external doses, it was required to convert the hyper-realisations to realisations. The aim of this paper is to discuss the different approaches that were considered to do this, and to define the method that was eventually chosen. Single spot (point) estimates of dose (for each worker) were also calculated to support the epidemiological analysis. The different methods for obtaining these and the implications are also discussed.

Estimates of plutonium lung doses from urine bioassay are highly dependent on the rate of absorption from the lungs to blood assumed for the inhaled aerosol. Absorption occurs by dissolution of particles in lung fluid followed by uptake to blood. The latter may occur either rapidly or dissolved ions may first become temporarily bound within airway tissue. The presence of long-term binding can greatly increase lung doses, particularly if it occurs in the bronchial and bronchiolar regions. Analyses of autopsy data from Beagle dogs and USTUR Case 0269, obtained following exposure to plutonium nitrate, suggest that a small fraction of 0.2-1.1 and 0.4-0.7%, respectively, of plutonium becomes permanently bound within the lungs. The present work performs a further analysis using autopsy data of former plutonium workers of the Mayak Production Association to determine values of the bound fraction that are supported by these data. The results suggest a bound fraction value of 0-0.3%. The results also indicate that the Mayak worker population median values of the particle transport clearance parameters from the alveolar-interstitial region are largely consistent with expected values, but suggest the rate from the alveolar region to the interstitium may be lower than initially thought.

The calculation of internal doses for the Mayak Worker Dosimetry System (MWDS-2013) involved extensive computational resources due to the complexity and sheer number of calculations required. The required output consisted of a set of 1000 hyper-realizations: each hyper-realization consists of a set (1 for each worker) of probability distributions of organ doses. This report describes the hardware components and computational approaches required to make the calculation tractable. Together with the software, this system is referred to here as the 'PANDORA system'. It is based on a commercial SQL server database in a series of six work stations. A complete run of the entire Mayak worker cohort entailed a huge amount of calculations in PANDORA and due to the relatively slow speed of writing the data into the SQL server, each run took about 47 days. Quality control was monitored by comparing doses calculated in PANDORA with those in a specially modified version of the commercial software 'IMBA Professional Plus'. Suggestions are also made for increasing calculation and storage efficiency for future dosimetry calculations using PANDORA.

In order to estimate doses of workers exposed to plutonium, it is necessary to make assumptions about both the route and the time course of intake. The objective of this study was to determine a time course for the inhalation rate for plutonium (intake regime) useful for biokinetic modeling. Records from workplace air sampling, personnel biophysical examinations and autopsy data from former Mayak Production Association (MPA) workers were used. Plutonium accumulation strongly correlated with the volumetric activity of plutonium in workplace air. Using data from activity in air at MPA workplaces over time, a three-step function of intake was adopted. The adequacy of this three-step function was tested by comparing predicted doses using more complicated intake regimes. Uncertainties on the three-step function were also characterized based on air sampling data. The three-step function was assumed to be common to all workers, but an individual intake regime for each worker was calculated by convoluting it with the worker's actual employment history.

Radionuclides in ionic form can become chemically bound in the airways of the lungs following dissolution of inhaled particulates in lung fluid. The presence of long-term binding can greatly increase lung doses from inhaled plutonium, particularly if it occurs in the bronchial and bronchiolar regions. However, the only published evidence that plutonium binding occurs in humans comes from an analysis of the autopsy and bioassay data of United States Transuranium and Uranium Registries Case 0269, a plutonium worker who experienced a very high (58 kBq) acute inhalation of plutonium nitrate. This analysis suggested a bound fraction of around 8 %, inferred from an unexpectedly low ratio of estimated total thoracic lymph node activity:total lung activity, at the time of death. However, there are some limitations with this study, the most significant being that measurements of the regional distribution of plutonium activity in the lungs, which provide more direct evidence of binding, were not available when the analysis was performed. The present work describes the analysis of new data, which includes measurements of plutonium activity in the alveolar-interstitial (AI) region, bronchial (BB) and bronchiolar (bb) regions, and extra-thoracic (ET) regions, at the time of death. A Bayesian approach is used that accounts for uncertainties in model parameter values, including particle transport clearance, which were not considered in the original analysis. The results indicate that a long-term bound fraction between 0.4 and 0.7 % is required to explain this data, largely because plutonium activity is present in the extra-thoracic (ET2), bronchial and bronchiolar airways at the time of death.

Different dose estimates have been produced for the Mayak PA workforce over recent years (DOSES-2000, DOSES-2005, MWDS-2008). The dosimetry system MWDS-2013 described here differs from previous analyses, in that it deals directly with uncertainty in the assumed model parameters. This paper details the way in which uncertainty is dealt with within MWDS-2013 to produce the final output represented by a multiple hyper-realisation of organ doses. More specifically, the paper describes: Application of the WeLMoS method to calculate Bayesian posterior probability distributions of organ doses.Extension of the WeLMoS method for dealing with multiple intake regimes.How shared and unshared parameters are dealt with using a multiple realisation method.A practical algorithm for the generation of multiple hyper-realisations.How to deal with uncertainty in the intake and the intake regime.The resulting multiple hyper-realisation contains all of the information required to take account of model parameter uncertainty and the effects of shared and unshared parameters in any epidemiological analysis, which uses this information, although it is acknowledged that in practice, certain data simplifications may be required to make such analyses tractable, and comparable to previous analyses. Such simplifications are outside the scope of this paper.

The distribution of calculated internal doses has been determined for 8043 Mayak Production Associate (Mayak PA) workers. This is a subset of the entire cohort of 25 757 workers, for whom monitoring data are available. Statistical characteristics of point estimates of accumulated doses to 17 different tissues and organs and the uncertainty ranges were calculated. Under the MWDS-2013 dosimetry system, the mean accumulated lung dose was 185 ± 594 mGy (geometric mean = 28 mGy; geometric standard deviation = 9.32; median value = 31 mGy; maximum value = 8980 mGy). The ranges of relative standard uncertainty were from 40 to 2200% for accumulated lung dose, from 25-90% to 2600-3000% for accumulated dose to different regions of respiratory tract, from 13-22% to 2300-2500% for systemic organs and tissues. The Mayak PA workers accumulated internal plutonium lung dose is shown to be close to log normal. The accumulated internal plutonium dose to systemic organs was close to a log triangle. The dependency of uncertainty of accumulated absorbed lung and liver doses on the dose estimates itself is also shown. The accumulated absorbed doses to lung, alveolar-interstitial region, liver, bone surface cells and red bone marrow calculated both with MWDS-2013 and MWDS-2008 have been compared. In general, the accumulated lung doses increased by a factor of 1.8 in median value, while the accumulated doses to systemic organs decreased by factor of 1.3-1.4 in median value. For the cases with identical initial data, accumulated lung doses increased by a factor of 2.1 in median value, while accumulated doses to systemic organs decreased by 8-13% in median value. For the cases with both identical initial data and all of plutonium activity in urine measurements above the decision threshold, accumulated lung doses increased by a factor of 2.7 in median value, while accumulated doses to systemic organs increased by 6-12% in median value.

For the first time, plutonium retention in human upper airways was investigated based on the dosimetric structure of the human respiratory tract proposed by the International Commission on Radiological Protection (ICRP). This paper describes analytical work methodology, case selection criteria, and summarizes findings on soluble (ICRP 68 Type M material) plutonium distribution in the lungs of a former nuclear worker occupationally exposed to plutonium nitrate [239Pu(NO3)4]. Thirty-eight years post-intake, plutonium was found to be uniformly distributed between bronchial (BB), bronchiolar (bb) and alveolar-interstitial (AI) dosimetric compartments as well as between the left and right lungs. 239+240Pu and 238Pu total body activity was estimated to be 2333 ± 23 and 42.1 ± 0.7 Bq, respectively. The results of this work provide key information on the extent of plutonium binding in the upper airways of the human respiratory tract.