Frequentist model averaging for analysis of dose-response in epidemiologic studies with complex exposure uncertainty.

In epidemiologic studies, association estimates of an exposure with disease outcomes are often biased when the uncertainties of exposure are ignored. Consequently, corresponding confidence intervals (CIs) will not have correct coverage. This issue is particularly problematic when exposures must be reconstructed from physical measurements, for example, for environmental or occupational radiation doses that were received by a study population for which radiation doses cannot be measured directly. To incorporate complex uncertainties in reconstructed exposures, the two-dimensional Monte Carlo (2DMC) dose estimation method has been proposed and used in various dose reconstruction efforts. The 2DMC method generates multiple exposure realizations from dosimetry models that incorporate various sources of errors to reflect the uncertainty of the dose distribution as well as the uncertainties in individual doses in the exposed population. Traditional measurement-error model approaches, typically based on using mean doses in the dose-exposure analysis, do not fully account exposure uncertainties. A recently developed statistical approach that overcomes many of these limitations by analyzing multiple exposure realizations in relation to disease risk is Bayesian model averaging (BMA). The analytic advantage of the BMA is its ability to better accommodate complex exposure uncertainty in the risk estimation, but a practical. Drawback is its significant computational complexity. In this present paper, we propose a novel frequentist model averaging (FMA) approach which has all the analytical advantages of the BMA method but is much simpler to implement and computationally faster. We show in simulations that, like BMA, FMA yields 95% confidence intervals for association parameters that close to 95% coverage rate. In simulations, the FMA has shorter length of CIs than those of another frequentist approach, the corrected information matrix (CIM) method. We illustrate the similarities in performance of BMA and FMA from a study of exposures from radioactive fallout in Kazakhstan.

Fluoroscopy X-Ray Organ-Specific Dosimetry System (FLUXOR) for Estimation of Organ Doses and Their Uncertainties in the Canadian Fluoroscopy Cohort Study.

As part of ongoing efforts to assess lifespan disease mortality and incidence in 63,715 patients from the Canadian Fluoroscopy Cohort Study (CFCS) who were treated for tuberculosis between 1930 and 1969, we developed a new FLUoroscopy X-ray ORgan-specific dosimetry system (FLUXOR) to estimate radiation doses to various organs and tissues. Approximately 45% of patients received medical procedures accompanied by fluoroscopy, including artificial pneumothorax (air in pleural cavity to collapse of lungs), pneumoperitoneum (air in peritoneal cavity), aspiration of fluid from pleural cavity and gastrointestinal series. In addition, patients received chest radiographs for purposes of diagnosis and monitoring of disease status. FLUXOR utilizes age-, sex- and body size-dependent dose coefficients for fluoroscopy and radiography exams, estimated using radiation transport simulations in up-to-date computational hybrid anthropomorphic phantoms. The phantoms include an updated heart model, and were adjusted to match the estimated mean height and body mass of tuberculosis patients in Canada during the relevant time period. Patient-specific data (machine settings, exposure duration, patient orientation) used during individual fluoroscopy or radiography exams were not recorded. Doses to patients were based on parameter values inferred from interviews with 91 physicians practicing at the time, historical literature, and estimated number of procedures from patient records. FLUXOR uses probability distributions to represent the uncertainty in the unknown true, average value of each dosimetry parameter. Uncertainties were shared across all patients within specific subgroups of the cohort, defined by age at treatment, sex, type of procedure, time period of exams and region (Nova Scotia or other provinces). Monte Carlo techniques were used to propagate uncertainties, by sampling alternative average values for each parameter. Alternative average doses per exam were estimated for patients in each subgroup, with the total average dose per individual determined by the number of exams received. This process was repeated to produce alternative cohort vectors of average organ doses per patient. This article presents estimates of doses to lungs, female breast, active bone marrow and heart wall. Means and 95% confidence intervals (CI) of average organ doses across all 63,715 patients were 320 (160, 560) mGy to lungs, 250 (120, 450) mGy to female breast, 190 (100, 340) mGy to heart wall and 92 (47, 160) mGy to active bone marrow. Approximately 60% of all patients had average doses to the four studied organs of less than 10 mGy, 10% received between 10 and 100 mGy, 25% between 100 and 1,000 mGy, and 5% above 1,000 mGy. Pneumothorax was the medical procedure that accounted for the largest contribution to cohort average doses. The major contributors to uncertainty in estimated doses per procedure for the four organs of interest are the uncertainties in exposure duration, tube voltage, tube output, and patient orientation relative to the X-ray tube, with the uncertainty in exposure duration being most often the dominant source. Uncertainty in patient orientation was important for doses to female breast, and, to a lesser degree, for doses to heart wall. The uncertainty in number of exams was an important contributor to uncertainty for ∼30% of patients. The estimated organ doses and their uncertainties will be used for analyses of incidence and mortality of cancer and non-cancer diseases. The CFCS cohort is an important addition to existing radio-epidemiological cohorts, given the moderate-to-high doses received fractionated over several years, the type of irradiation (external irradiation only), radiation type (X rays only), a balanced combination of both genders and inclusion of people of all ages.

Organ-specific dose coefficients derived from Monte Carlo simulations for historical (1930s to 1960s) fluoroscopic and radiographic examinations of tuberculosis patients.

This work provides dose coefficients necessary to reconstruct doses used in epidemiological studies of tuberculosis patients treated from the 1930s through the 1960s, who were exposed to diagnostic imaging while undergoing treatment. We made use of averaged imaging parameters from measurement data, physician interviews, and available literature of the Canadian Fluoroscopy Cohort Study and, on occasion, from a similar study of tuberculosis patients from Massachusetts, United States, treated between 1925 and 1954. We used computational phantoms of the human anatomy and Monte Carlo radiation transport methods to compute dose coefficients that relate dose in air, at a point 20 cm away from the source, to absorbed dose in 58 organs. We selected five male and five female phantoms, based on the mean height and weight of Canadian tuberculosis patients in that era, for the 1-, 5-, 10-, 15-year old and adult ages. Using high-performance computers at the National Institutes of Health, we simulated 2,400 unique fluoroscopic and radiographic exposures by varying x-ray beam quality, field size, field shuttering, imaged anatomy, phantom orientation, and computational phantom. Compared with previous dose coefficients reported for this population, our dosimetry system uses improved anatomical phantoms constructed from computed tomography imaging datasets. The new set of dose coefficients includes tissues that were not previously assessed, in particular, for tissues outside the x-ray field or for pediatric patients. In addition, we provide dose coefficients for radiography and for fluoroscopic procedures not previously assessed in the dosimetry of this cohort (i.e. pneumoperitoneum and chest aspirations). These new dose coefficients would allow a comprehensive assessment of exposures in the cohort. In addition to providing newly derived dose coefficients, we believe the automation and methods developed to complete these dosimetry calculations are generalizable and can be applied to other epidemiological studies interested in an exposure assessment from medical x-ray imaging. These epidemiological studies provide important data for assessing health risks of radiation exposure to help inform the current system of radiological protection and efforts to optimize the use of radiation in medical studies.

Association of Radioactive Iodine Treatment With Cancer Mortality in Patients With Hyperthyroidism.

IMPORTANCE: Radioactive iodine (RAI) has been used extensively to treat hyperthyroidism since the 1940s. Although widely considered a safe and effective therapy, RAI has been associated with elevated risks of total and site-specific cancer death among patients with hyperthyroidism. OBJECTIVE: To determine whether greater organ- or tissue-absorbed doses from RAI treatment are associated with overall and site-specific cancer mortality in patients with hyperthyroidism. DESIGN, SETTING, AND PARTICIPANTS: This cohort study is a 24-year extension of the multicenter Cooperative Thyrotoxicosis Therapy Follow-up Study, which has followed up US and UK patients diagnosed and treated for hyperthyroidism for nearly 7 decades, beginning in 1946. Patients were traced using records from the National Death Index, Social Security Administration, and other resources. After exclusions, 18 805 patients who were treated with RAI and had no history of cancer at the time of the first treatment were eligible for the current analysis. Excess relative risks (ERRs) per 100-mGy dose to the organ or tissue were calculated using multivariable-adjusted linear dose-response models and were converted to relative risks (RR = 1 + ERR). The current analyses were conducted from April 28, 2017, to January 30, 2019. EXPOSURES: Mean total administered activity of sodium iodide I 131 was 375 MBq for patients with Graves disease and 653 MBq for patients with toxic nodular goiter. Mean organ or tissue dose estimates ranged from 20 to 99 mGy (colon or rectum, ovary, uterus, prostate, bladder, and brain/central nervous system), to 100 to 400 mGy (pancreas, kidney, liver, stomach, female breast, lung, oral mucosa, and marrow), to 1.6 Gy (esophagus), and to 130 Gy (thyroid gland). MAIN OUTCOMES AND MEASURES: Site-specific and all solid-cancer mortality. RESULTS: A total of 18 805 patients were included in the study cohort, and the mean (SD) entry age was 49 (14) years. Most patients were women (14 671 [78.0%]), and most had a Graves disease diagnosis (17 615 [93.7%]). Statistically significant positive associations were observed for all solid cancer mortality (n = 1984; RR at 100-mGy dose to the stomach = 1.06; 95% CI, 1.02-1.10; P = .002), including female breast cancer (n = 291; RR at 100-mGy dose to the breast = 1.12; 95% CI, 1.003-1.32; P = .04) and all other solid cancers combined (n = 1693; RR at 100-mGy dose to the stomach = 1.05; 95% CI, 1.01-1.10; P = .01). The 100-mGy dose to the stomach and breast corresponded to a mean (SD) administered activity of 243 (35) MBq and 266 (58) MBq in patients with Graves disease. For every 1000 patients with hyperthyroidism receiving typical doses to the stomach (150 to 250 mGy), an estimated lifetime excess of 19 (95% CI, 3-40) to 32 (95% CI, 5-66) solid cancer deaths could occur. CONCLUSIONS AND RELEVANCE: In RAI-treated patients with hyperthyroidism, greater organ-absorbed doses appeared to be modestly positively associated with risk of death from solid cancer, including breast cancer. Additional studies are needed of the risks and advantages of all major treatment options available to patients with hyperthyroidism.

Assessment of thyroid cancer risk associated with radiation dose from personal diagnostic examinations in a cohort study of US radiologic technologists, followed 1983-2014.

OBJECTIVE: To assess whether personal medical diagnostic procedures over life, but particularly those associated with exposure in adulthood, were associated with increased thyroid cancer risk. DESIGN: Participants from the US Radiologic Technologists Study, a large, prospective cohort, were followed from the date of first mailed questionnaire survey completed during 1983-1989 to the earliest date of self-reported diagnosis of thyroid cancer or of any other cancer than non-melanoma skin cancer (NMSC) in any of three subsequent questionnaires up to the last in 2012-2014. SETTING: US nationwide, occupational cohort. PARTICIPANTS: US radiologic technologists with exclusion of: those who reported a previous cancer apart from NMSC on the first questionnaire; those who reported a cancer with an unknown date of diagnosis on any of the questionnaires; and those who did not respond to both the first questionnaire and at least one subsequent questionnaire. PRIMARY OUTCOME MEASURE: We used Cox proportional hazards models with age as timescale to compute HRs and 95% CI for thyroid cancer in relation to cumulative 5-year lagged diagnostic thyroid dose. RESULTS: There were 414 self-reported thyroid cancers (n=275 papillary) in a cohort of 76 415 persons. Cumulative thyroid dose was non-significantly positively associated with total (excess relative risk/Gy=2.29 (95% CI -0.91 to 7.01, p=0.19)) and papillary thyroid cancer (excess relative risk/Gy=4.15 (95% CI -0.39, 11.27, p=0.08)) risk. These associations were not modified by age at, or time since, exposure and were independent of occupational exposure. CONCLUSION: Our study provides weak evidence that thyroid dose from diagnostic radiation procedures over the whole of life, in particular associated with exposure in adulthood, influences adult thyroid cancer risk.

BODY SIZE-SPECIFIC EFFECTIVE DOSE CONVERSION COEFFICIENTS FOR CT SCANS.

Effective dose from computed tomography (CT) examinations is usually estimated using the scanner-provided dose-length product and using conversion factors, also known as k-factors, which correspond to scan regions and differ by age according to five categories: 0, 1, 5, 10 y and adult. However, patients often deviate from the standard body size on which the conversion factor is based. In this study, a method for deriving body size-specific k-factors is presented, which can be determined from a simple regression curve based on patient diameter at the centre of the scan range. Using the International Commission on Radiological Protection reference paediatric and adult computational phantoms paired with Monte Carlo simulation of CT X-ray beams, the authors derived a regression-based k-factor model for the following CT scan types: head-neck, head, neck, chest, abdomen, pelvis, abdomen-pelvis (AP) and chest-abdomen-pelvis (CAP). The resulting regression functions were applied to a total of 105 paediatric and 279 adult CT scans randomly sampled from patients who underwent chest, AP and CAP scans at the National Institutes of Health Clinical Center. The authors have calculated and compared the effective doses derived from the conventional age-specific k-factors with the values computed using their body size-specific k-factor. They found that by using the age-specific k-factor, paediatric patients tend to have underestimates (up to 3-fold) of effective dose, while underweight and overweight adult patients tend to have underestimates (up to 2.6-fold) and overestimates (up to 4.6-fold) of effective dose, respectively, compared with the effective dose determined from their body size-dependent factors. The authors present these size-specific k-factors as an alternative to the existing age-specific factors. The body size-specific k-factor will assess effective dose more precisely and on a more individual level than the conventional age-specific k-factors and, hence, improve awareness of the true exposure, which is important for the clinical community to understand.

Bayesian dose-response analysis for epidemiological studies with complex uncertainty in dose estimation.

Most conventional risk analysis methods rely on a single best estimate of exposure per person, which does not allow for adjustment for exposure-related uncertainty. Here, we propose a Bayesian model averaging method to properly quantify the relationship between radiation dose and disease outcomes by accounting for shared and unshared uncertainty in estimated dose. Our Bayesian risk analysis method utilizes multiple realizations of sets (vectors) of doses generated by a two-dimensional Monte Carlo simulation method that properly separates shared and unshared errors in dose estimation. The exposure model used in this work is taken from a study of the risk of thyroid nodules among a cohort of 2376 subjects who were exposed to fallout from nuclear testing in Kazakhstan. We assessed the performance of our method through an extensive series of simulations and comparisons against conventional regression risk analysis methods. When the estimated doses contain relatively small amounts of uncertainty, the Bayesian method using multiple a priori plausible draws of dose vectors gave similar results to the conventional regression-based methods of dose-response analysis. However, when large and complex mixtures of shared and unshared uncertainties are present, the Bayesian method using multiple dose vectors had significantly lower relative bias than conventional regression-based risk analysis methods and better coverage, that is, a markedly increased capability to include the true risk coefficient within the 95% credible interval of the Bayesian-based risk estimate. An evaluation of the dose-response using our method is presented for an epidemiological study of thyroid disease following radiation exposure.

S values for 131I based on the ICRP adult voxel phantoms.

To improve the estimates of organ doses from nuclear medicine procedures using (131)I, the authors calculated a comprehensive set of (131)I S values, defined as absorbed doses in target tissues per unit of nuclear transition in source regions, for different source and target combinations. The authors used the latest reference adult male and female voxel phantoms published by the International Commission on Radiological Protection (ICRP Publication 110) and the (131)I photon and electron spectra from the ICRP Publication 107 to perform Monte Carlo radiation transport calculations using MCNPX2.7 to compute the S values. For each phantom, the authors simulated 55 source regions with an assumed uniform distribution of (131)I. They computed the S values for 42 target tissues directly, without calculating specific absorbed fractions. From these calculations, the authors derived a comprehensive set of S values for (131)I for 55 source regions and 42 target tissues in the ICRP male and female voxel phantoms. Compared with the stylised phantoms from Oak Ridge National Laboratory (ORNL) that consist of 22 source regions and 24 target regions, the new data set includes 1662 additional S values corresponding to additional combinations of source-target tissues that are not available in the stylised phantoms. In a comparison of S values derived from the ICRP and ORNL phantoms, the authors found that the S values to the radiosensitive tissues in the ICRP phantoms were 1.1 (median, female) and 1.3 (median, male) times greater than the values based on the ORNL phantoms. However, for several source-target pairs, the difference was up to 10-fold. The new set of S values can be applied prospectively or retrospectively to the calculation of radiation doses in adults internally exposed to (131)I, including nuclear medicine patients treated for thyroid cancer or hyperthyroidism.

Thyroid Dose Estimates for a Cohort of Belarusian Children Exposed to (131)I from the Chernobyl Accident: Assessment of Uncertainties.

Deterministic thyroid radiation doses due to iodine-131 ((131)I) intake were reconstructed in a previous article for 11,732 participants of the Belarusian-American cohort study of thyroid cancer and other thyroid diseases in individuals exposed during childhood or adolescence to fallout from the Chernobyl accident. The current article describes an assessment of uncertainties in reconstructed thyroid doses that accounts for the shared and unshared errors. Using a Monte Carlo simulation procedure, 1,000 sets of cohort thyroid doses due to (131)I intake were calculated. The arithmetic mean of the stochastic thyroid doses for the entire cohort was 0.68 Gy. For two-thirds of the cohort the arithmetic mean of individual stochastic thyroid doses was less than 0.5 Gy. The geometric standard deviation of stochastic doses varied among cohort members from 1.33 to 5.12 with an arithmetic mean of 1.76 and a geometric mean of 1.73. The uncertainties in thyroid dose were driven by the unshared errors associated with the estimates of values of thyroid mass and of the (131)I activity in the thyroid of the subject; the contribution of shared errors to the overall uncertainty was small. These multiple sets of cohort thyroid doses will be used to evaluate the radiation risks of thyroid cancer and noncancer thyroid diseases, taking into account the structure of the errors in the dose estimates.

The two-dimensional Monte Carlo: a new methodologic paradigm for dose reconstruction for epidemiological studies.

Retrospective dose estimation, particularly dose reconstruction that supports epidemiological investigations of health risk, relies on various strategies that include models of physical processes and exposure conditions with detail ranging from simple to complex. Quantification of dose uncertainty is an essential component of assessments for health risk studies since, as is well understood, it is impossible to retrospectively determine the true dose for each person. To address uncertainty in dose estimation, numerical simulation tools have become commonplace and there is now an increased understanding about the needs and what is required for models used to estimate cohort doses (in the absence of direct measurement) to evaluate dose response. It now appears that for dose-response algorithms to derive the best, unbiased estimate of health risk, we need to understand the type, magnitude and interrelationships of the uncertainties of model assumptions, parameters and input data used in the associated dose estimation models. Heretofore, uncertainty analysis of dose estimates did not always properly distinguish between categories of errors, e.g., uncertainty that is specific to each subject (i.e., unshared error), and uncertainty of doses from a lack of understanding and knowledge about parameter values that are shared to varying degrees by numbers of subsets of the cohort. While mathematical propagation of errors by Monte Carlo simulation methods has been used for years to estimate the uncertainty of an individual subject's dose, it was almost always conducted without consideration of dependencies between subjects. In retrospect, these types of simple analyses are not suitable for studies with complex dose models, particularly when important input data are missing or otherwise not available. The dose estimation strategy presented here is a simulation method that corrects the previous deficiencies of analytical or simple Monte Carlo error propagation methods and is termed, due to its capability to maintain separation between shared and unshared errors, the two-dimensional Monte Carlo (2DMC) procedure. Simply put, the 2DMC method simulates alternative, possibly true, sets (or vectors) of doses for an entire cohort rather than a single set that emerges when each individual's dose is estimated independently from other subjects. Moreover, estimated doses within each simulated vector maintain proper inter-relationships such that the estimated doses for members of a cohort subgroup that share common lifestyle attributes and sources of uncertainty are properly correlated. The 2DMC procedure simulates inter-individual variability of possibly true doses within each dose vector and captures the influence of uncertainty in the values of dosimetric parameters across multiple realizations of possibly true vectors of cohort doses. The primary characteristic of the 2DMC approach, as well as its strength, are defined by the proper separation between uncertainties shared by members of the entire cohort or members of defined cohort subsets, and uncertainties that are individual-specific and therefore unshared.

Nuclear medicine practices in the 1950s through the mid-1970s and occupational radiation doses to technologists from diagnostic radioisotope procedures.

Data on occupational radiation exposure from nuclear medicine procedures for the time period of the 1950s through the 1970s is important for retrospective health risk studies of medical personnel who conducted those activities. However, limited information is available on occupational exposure received by physicians and technologists who performed nuclear medicine procedures during those years. To better understand and characterize historical radiation exposures to technologists, the authors collected information on nuclear medicine practices in the 1950s, 1960s, and 1970s. To collect historical data needed to reconstruct doses to technologists, a focus group interview was held with experts who began using radioisotopes in medicine in the 1950s and the 1960s. Typical protocols and descriptions of clinical practices of diagnostic radioisotope procedures were defined by the focus group and were used to estimate occupational doses received by personnel, per nuclear medicine procedure, conducted in the 1950s to 1960s using radiopharmaceuticals available at that time. The radionuclide activities in the organs of the reference patient were calculated using the biokinetic models described in ICRP Publication 53. Air kerma rates as a function of distance from a reference patient were calculated by Monte Carlo radiation transport calculations using a hybrid computational phantom. Estimates of occupational doses to nuclear medicine technologists per procedure were found to vary from less than 0.01 µSv (thyroid scan with 1.85 MBq of administered I-iodide) to 0.4 µSv (brain scan with 26 MBq of Hg-chlormerodin). Occupational doses for the same diagnostic procedures starting in the mid-1960s but using Tc were also estimated. The doses estimated in this study show that the introduction of Tc resulted in an increase in occupational doses per procedure.

Association of chromosome translocation rate with low dose occupational radiation exposures in U.S. radiologic technologists.

Chromosome translocations are a well-recognized biological marker of radiation exposure and cancer risk. However, there is uncertainty about the lowest dose at which excess translocations can be detected, and whether there is temporal decay of induced translocations in radiation-exposed populations. Dosimetric uncertainties can substantially alter the shape of dose-response relationships; although regression-calibration methods have been used in some datasets, these have not been applied in radio-occupational studies, where there are also complex patterns of shared and unshared errors that these methods do not account for. In this article we evaluated the relationship between estimated occupational ionizing radiation doses and chromosome translocation rates using fluorescent in situ hybridization in 238 U.S. radiologic technologists selected from a large cohort. Estimated cumulative red bone marrow doses (mean 29.3 mGy, range 0-135.7 mGy) were based on available badge-dose measurement data and on questionnaire-reported work history factors. Dosimetric assessment uncertainties were evaluated using regression calibration, Bayesian and Monte Carlo maximum likelihood methods, taking account of shared and unshared error and adjusted for overdispersion. There was a significant dose response for estimated occupational radiation exposure, adjusted for questionnaire-based personal diagnostic radiation, age, sex and study group (5.7 translocations per 100 whole genome cell equivalents per Gy, 95% CI 0.2, 11.3, P = 0.0440). A significant increasing trend with dose continued to be observed for individuals with estimated doses <100 mGy. For combined estimated occupational and personal-diagnostic-medical radiation exposures, there was a borderline-significant modifying effect of age (P = 0.0704), but little evidence (P > 0.5) of temporal decay of induced translocations. The three methods of analysis to adjust for dose uncertainty gave similar results. In summary, chromosome translocation dose-response slopes were detectable down to <100 mGy and were compatible with those observed in other radiation-exposed populations. However, there are substantial uncertainties in both occupational and other (personal-diagnostic-medical) doses that may be imperfectly taken into account in our analysis.

Impact of uncertainties in exposure assessment on estimates of thyroid cancer risk among Ukrainian children and adolescents exposed from the Chernobyl accident.

The 1986 accident at the Chernobyl nuclear power plant remains the most serious nuclear accident in history, and excess thyroid cancers, particularly among those exposed to releases of iodine-131 remain the best-documented sequelae. Failure to take dose-measurement error into account can lead to bias in assessments of dose-response slope. Although risks in the Ukrainian-US thyroid screening study have been previously evaluated, errors in dose assessments have not been addressed hitherto. Dose-response patterns were examined in a thyroid screening prevalence cohort of 13,127 persons aged <18 at the time of the accident who were resident in the most radioactively contaminated regions of Ukraine. We extended earlier analyses in this cohort by adjusting for dose error in the recently developed TD-10 dosimetry. Three methods of statistical correction, via two types of regression calibration, and Monte Carlo maximum-likelihood, were applied to the doses that can be derived from the ratio of thyroid activity to thyroid mass. The two components that make up this ratio have different types of error, Berkson error for thyroid mass and classical error for thyroid activity. The first regression-calibration method yielded estimates of excess odds ratio of 5.78 Gy(-1) (95% CI 1.92, 27.04), about 7% higher than estimates unadjusted for dose error. The second regression-calibration method gave an excess odds ratio of 4.78 Gy(-1) (95% CI 1.64, 19.69), about 11% lower than unadjusted analysis. The Monte Carlo maximum-likelihood method produced an excess odds ratio of 4.93 Gy(-1) (95% CI 1.67, 19.90), about 8% lower than unadjusted analysis. There are borderline-significant (p = 0.101-0.112) indications of downward curvature in the dose response, allowing for which nearly doubled the low-dose linear coefficient. In conclusion, dose-error adjustment has comparatively modest effects on regression parameters, a consequence of the relatively small errors, of a mixture of Berkson and classical form, associated with thyroid dose assessment.

Guidelines for exposure assessment in health risk studies following a nuclear reactor accident.

BACKGROUND: Worldwide concerns regarding health effects after the Chernobyl and Fukushima nuclear power plant accidents indicate a clear need to identify short- and long-term health impacts that might result from accidents in the future. Fundamental to addressing this problem are reliable and accurate radiation dose estimates for the affected populations. The available guidance for activities following nuclear accidents is limited with regard to strategies for dose assessment in health risk studies. OBJECTIVES: Here we propose a comprehensive systematic approach to estimating radiation doses for the evaluation of health risks resulting from a nuclear power plant accident, reflected in a set of seven guidelines. DISCUSSION: Four major nuclear reactor accidents have occurred during the history of nuclear power production. The circumstances leading to these accidents were varied, as were the magnitude of the releases of radioactive materials, the pathways by which persons were exposed, the data collected afterward, and the lifestyle factors and dietary consumption that played an important role in the associated radiation exposure of the affected populations. Accidents involving nuclear reactors may occur in the future under a variety of conditions. The guidelines we recommend here are intended to facilitate obtaining reliable dose estimations for a range of different exposure conditions. We recognize that full implementation of the proposed approach may not always be feasible because of other priorities during the nuclear accident emergency and because of limited resources in manpower and equipment. CONCLUSIONS: The proposed approach can serve as a basis to optimize the value of radiation dose reconstruction following a nuclear reactor accident.

Assessing organ doses from paediatric CT scans--a novel approach for an epidemiology study (the EPI-CT study).

The increasing worldwide use of paediatric computed tomography (CT) has led to increasing concerns regarding the subsequent effects of exposure to radiation. In response to this concern, the international EPI-CT project was developed to study the risk of cancer in a large multi-country cohort. In radiation epidemiology, accurate estimates of organ-specific doses are essential. In EPI-CT, data collection is split into two time periods--before and after introduction of the Picture Archiving Communication System (PACS) introduced in the 1990s. Prior to PACS, only sparse information about scanner settings is available from radiology departments. Hence, a multi-level approach was developed to retrieve information from a questionnaire, surveys, scientific publications, and expert interviews. For the years after PACS was introduced, scanner settings will be extracted from Digital Imaging and Communications in Medicine (DICOM) headers, a protocol for storing medical imaging data. Radiation fields and X-ray interactions within the body will be simulated using phantoms of various ages and Monte-Carlo-based radiation transport calculations. Individual organ doses will be estimated for each child using an accepted calculation strategy, scanner settings, and the radiation transport calculations. Comprehensive analyses of missing and uncertain dosimetry data will be conducted to provide uncertainty distributions of doses.

Recovery and resilience after a nuclear power plant disaster: a medical decision model for managing an effective, timely, and balanced response.

Resilience after a nuclear power plant or other radiation emergency requires response and recovery activities that are appropriately safe, timely, effective, and well organized. Timely informed decisions must be made, and the logic behind them communicated during the evolution of the incident before the final outcome is known. Based on our experiences in Tokyo responding to the Fukushima Daiichi nuclear power plant crisis, we propose a real-time, medical decision model by which to make key health-related decisions that are central drivers to the overall incident management. Using this approach, on-site decision makers empowered to make interim decisions can act without undue delay using readily available and high-level scientific, medical, communication, and policy expertise. Ongoing assessment, consultation, and adaption to the changing conditions and additional information are additional key features. Given the central role of health and medical issues in all disasters, we propose that this medical decision model, which is compatible with the existing US National Response Framework structure, be considered for effective management of complex, large-scale, and large-consequence incidents.

Organ doses for reference adult male and female undergoing computed tomography estimated by Monte Carlo simulations.

PURPOSE: To develop a computed tomography (CT) organ dose estimation method designed to readily provide organ doses in a reference adult male and female for different scan ranges to investigate the degree to which existing commercial programs can reasonably match organ doses defined in these more anatomically realistic adult hybrid phantoms METHODS: The x-ray fan beam in the SOMATOM Sensation 16 multidetector CT scanner was simulated within the Monte Carlo radiation transport code MCNPX2.6. The simulated CT scanner model was validated through comparison with experimentally measured lateral free-in-air dose profiles and computed tomography dose index (CTDI) values. The reference adult male and female hybrid phantoms were coupled with the established CT scanner model following arm removal to simulate clinical head and other body region scans. A set of organ dose matrices were calculated for a series of consecutive axial scans ranging from the top of the head to the bottom of the phantoms with a beam thickness of 10 mm and the tube potentials of 80, 100, and 120 kVp. The organ doses for head, chest, and abdomen/pelvis examinations were calculated based on the organ dose matrices and compared to those obtained from two commercial programs, CT-EXPO and CTDOSIMETRY. Organ dose calculations were repeated for an adult stylized phantom by using the same simulation method used for the adult hybrid phantom. RESULTS: Comparisons of both lateral free-in-air dose profiles and CTDI values through experimental measurement with the Monte Carlo simulations showed good agreement to within 9%. Organ doses for head, chest, and abdomen/pelvis scans reported in the commercial programs exceeded those from the Monte Carlo calculations in both the hybrid and stylized phantoms in this study, sometimes by orders of magnitude. CONCLUSIONS: The organ dose estimation method and dose matrices established in this study readily provides organ doses for a reference adult male and female for different CT scan ranges and technical parameters. Organ doses from existing commercial programs do not reasonably match organ doses calculated for the hybrid phantoms due to differences in phantom anatomy, as well as differences in organ dose scaling parameters. The organ dose matrices developed in this study will be extended to cover different technical parameters, CT scanner models, and various age groups.

Current use and future needs of biodosimetry in studies of long-term health risk following radiation exposure.

Biodosimetry measurements can potentially be an important and integral part of the dosimetric methods used in long-term studies of health risk following radiation exposure. Such studies rely on accurate estimation of doses to the whole body or to specific organs of individuals in order to derive reliable estimates of cancer risk. However, dose estimates based on analytical dose reconstruction (i.e., models) or personnel monitoring measurements (i.e., film badges) can have substantial uncertainty. Biodosimetry can potentially reduce uncertainty in health risk studies by corroboration of model-based dose estimates or by using them to assess bias in dose models. While biodosimetry has begun to play a more significant role in long-term health risk studies, its use is still generally limited in that context due to one or more factors including inadequate limits of detection, large inter-individual variability of the signal measured, high per-sample cost, and invasiveness. Presently, the most suitable biodosimetry methods for epidemiologic studies are chromosome aberration frequencies from fluorescence in situ hybridization (FISH) of peripheral blood lymphocytes and electron paramagnetic resonance (EPR) measurements made on tooth enamel. Both types of measurements, however, are usually invasive and require biological samples that can be difficult to obtain. Moreover, doses derived from these methods are not always directly relevant to the tissues of interest. To increase the value of biodosimetry to epidemiologic studies, a number of issues need to be considered, including limits of detection, effects of inhomogenous exposure of the body, how to extrapolate from the tissue sampled to the tissues of interest, and how to adjust dosimetry models applied to large populations based on sparse biodosimetry measurements. The requirements of health risk studies suggest a set of characteristics that, if satisfied by new biodosimetry methods, would increase the overall usefulness of biodosimetry in determining radiation health risks.

Retrospective dose assessment for the population living in areas of local fallout from the Semipalatinsk nuclear test site Part I: External exposure.

A short analysis of all 111 atmospheric events conducted at the Semipalatinsk Test Site (STS) in 1949-1962 with regard to significant off-site exposure (more than 5 mSv of the effective dose during the first year after the explosion) has been made. The analytical method used to assess external exposure to the residents living in settlements near the STS is described. This method makes use of the archival data on the radiological conditions, including the measurements of exposure rate. Special attention was given to the residents of Dolon and Kanonerka villages exposed mainly as a result of the first test, detonated on August 29, 1949. For the residents of those settlements born in 1935, the dose estimates calculated according to the analytical method, are compared to those derived from the thermoluminescence measurements in bricks and electron paramagnetic resonance measurements in teeth. The methods described in this paper were used for external dose assessment for the cohort members at an initial stage of an ongoing epidemiological study conducted by the U.S. National Cancer Institute in the Republic of Kazakhstan. Recently revised methods and estimates of external exposure for that cohort are given in another paper (Simon et al.) in this conference.

Retrospective dose assessment for the population living in areas of local fallout from the Semipalatinsk Nuclear Test Site Part II: Internal exposure to thyroid.

A methodology to assess internal exposure to thyroid from radioiodines for the residents living in settlements located in the vicinity of the Semipalatinsk Nuclear Test Site is described that is the result of many years of research, primarily at the Moscow Institute of Biophysics. This methodology introduces two important concepts. First, the biologically active fraction, is defined as the fraction of the total activity on fallout particles with diameter less than 50 microns. That fraction is retained by vegetation and will ultimately result in contamination of dairy products. Second, the relative distance is derived as a dimensionless quantity from information on test yield, maximum height of cloud, and average wind velocity and describes how the biologically active fraction is distributed with distance from the site of the explosion. The parameter is derived in such a way that at locations with equal values of relative distance, the biologically active fraction will be the same for any test. The estimates of internal exposure to thyroid for the residents of Dolon and Kanonerka villages, for which the external exposure were assessed and given in a companion paper (Gordeev et al. 2006) in this conference, are presented. The main sources of uncertainty in the estimates are identified.