Brian Moroz

NCICT: a computational solution to estimate organ doses for pediatric and adult patients undergoing CT scans

We developed computational methods and tools to assess organ doses for pediatric and adult patients undergoing computed tomography (CT) examinations. We used the International Commission on Radiological Protection (ICRP) reference pediatric and adult phantoms combined with the Monte Carlo simulation of a reference CT scanner to establish comprehensive organ dose coefficients (DC), organ absorbed dose per unit volumetric CT Dose Index (CTDIvol) (mGy/mGy). We also developed methods to estimate organ doses with tube current modulation techniques and size specific dose estimates. A graphical user interface was designed to obtain user input of patient- and scan-specific parameters, and to calculate and display organ doses. A batch calculation routine was also integrated into the program to automatically calculate organ doses for a large number of patients. We entitled the computer program, National Cancer Institute dosimetry system for CT(NCICT). We compared our dose coefficients with those from CT-Expo, and evaluated the performance of our program using CT patient data. Our pediatric DCs show good agreements of organ dose estimation with those from CT-Expo except for thyroid. Our results support that the adult phantom in CT-Expo seems to represent a pediatric individual between 10 and 15 years rather than an adult. The comparison of CTDIvol values between NCICT and dose pages from 10 selected CT scans shows good agreements less than 12% except for two cases (up to 20%). The organ dose comparison between mean and modulated mAs shows that mean mAs-based calculation significantly overestimates dose (up to 2.4-fold) to the organs in close proximity to lungs in chest and chest-abdomen-pelvis scans. Our program provides more realistic anatomy based on the ICRP reference phantoms, higher age resolution, the most up-to-date bone marrow dosimetry, and several convenient features compared to previous tools. The NCICT will be available for research purpose in the near future.

Fallout Deposition in the Marshall Islands from Bikini and Enewetak Nuclear Weapons Tests

Deposition densities (Bq m−2) of all important dose-contributing radionuclides occurring in nuclear weapons testing fallout from tests conducted at Bikini and Enewetak Atolls (1946–1958) have been estimated on a test-specific basis for 32 atolls and separate reef islands of the Marshall Islands. A complete review of various historical and contemporary data, as well as meteorological analysis, was used to make judgments regarding which tests deposited fallout in the Marshall Islands and to estimate fallout deposition density. Our analysis suggested that only 20 of the 66 nuclear tests conducted in or near the Marshall Islands resulted in substantial fallout deposition on any of the 23 inhabited atolls. This analysis was confirmed by the fact that the sum of our estimates of 137Cs deposition from these 20 tests at each atoll is in good agreement with the total 137Cs deposited as estimated from contemporary soil sample analyses. The monitoring data and meteorological analyses were used to quantitatively estimate the deposition density of 63 activation and fission products for each nuclear test, plus the cumulative deposition of 239+240Pu at each atoll. Estimates of the degree of fractionation of fallout from each test at each atoll, as well as of the fallout transit times from the test sites to the atolls were used in this analysis. The estimates of radionuclide deposition density, fractionation, and transit times reported here are the most complete available anywhere and are suitable for estimations of both external and internal dose to representative persons as described in companion papers.

Accounting for Shared and Unshared Dosimetric Uncertainties in the Dose Response for Ultrasound-Detected Thyroid Nodules after Exposure to Radioactive Fallout

Dosimetic uncertainties, particularly those that are shared among subgroups of a study population, can bias, distort or reduce the slope or significance of a dose response. Exposure estimates in studies of health risks from environmental radiation exposures are generally highly uncertain and thus, susceptible to these methodological limitations. An analysis was published in 2008 concerning radiation-related thyroid nodule prevalence in a study population of 2,994 villagers under the age of 21 years old between August 1949 and September 1962 and who lived downwind from the Semipalatinsk Nuclear Test Site in Kazakhstan. This dose-response analysis identified a statistically significant association between thyroid nodule prevalence and reconstructed doses of fallout-related internal and external radiation to the thyroid gland; however, the effects of dosimetric uncertainty were not evaluated since the doses were simple point “best estimates”. In this work, we revised the 2008 study by a comprehensive treatment of dosimetric uncertainties. Our present analysis improves upon the previous study, specifically by accounting for shared and unshared uncertainties in dose estimation and risk analysis, and differs from the 2008 analysis in the following ways: 1. The study population size was reduced from 2,994 to 2,376 subjects, removing 618 persons with uncertain residence histories; 2. Simulation of multiple population dose sets (vectors) was performed using a two-dimensional Monte Carlo dose estimation method; and 3. A Bayesian model averaging approach was employed for evaluating the dose response, explicitly accounting for large and complex uncertainty in dose estimation. The results were compared against conventional regression techniques. The Bayesian approach utilizes 5,000 independent realizations of population dose vectors, each of which corresponds to a set of conditional individual median internal and external doses for the 2,376 subjects. These 5,000 population dose vectors reflect uncertainties in dosimetric parameters, partly shared and partly independent, among individual members of the study population. Risk estimates for thyroid nodules from internal irradiation were higher than those published in 2008, which results, to the best of our knowledge, from explicitly accounting for dose uncertainty. In contrast to earlier findings, the use of Bayesian methods led to the conclusion that the biological effectiveness for internal and external dose was similar. Estimates of excess relative risk per unit dose (ERR/Gy) for males (177 thyroid nodule cases) were almost 30 times those for females (571 cases) and were similar to those reported for thyroid cancers related to childhood exposures to external and internal sources in other studies. For confirmed cases of papillary thyroid cancers (3 in males, 18 in females), the ERR/Gy was also comparable to risk estimates from other studies, but not significantly different from zero. These findings represent the first reported dose response for a radiation epidemiologic study considering all known sources of shared and unshared errors in dose estimation and using a Bayesian model averaging (BMA) method for analysis of the dose response.

PREDICTIONS OF DISPERSION AND DEPOSITION OF FALLOUT FROM NUCLEAR TESTING USING THE NOAA-HYSPLIT METEOROLOGICAL MODEL

The NOAA Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) was evaluated as a research tool to simulate the dispersion and deposition of radioactive fallout from nuclear tests. Model-based estimates of fallout can be valuable for use in the reconstruction of past exposures from nuclear testing, particularly where little historical fallout monitoring data are available. The ability to make reliable predictions about fallout deposition could also have significant importance for nuclear events in the future. We evaluated the accuracy of the HYSPLIT-predicted geographic patterns of deposition by comparing those predictions against known deposition patterns following specific nuclear tests with an emphasis on nuclear weapons tests conducted in the Marshall Islands. We evaluated the ability of the computer code to quantitatively predict the proportion of fallout particles of specific sizes deposited at specific locations as well as their time of transport. In our simulations of fallout from past nuclear tests, historical meteorological data were used from a reanalysis conducted jointly by the National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR). We used a systematic approach in testing the HYSPLIT model by simulating the release of a range of particle sizes from a range of altitudes and evaluating the number and location of particles deposited. Our findings suggest that the quantity and quality of meteorological data are the most important factors for accurate fallout predictions and that, when satisfactory meteorological input data are used, HYSPLIT can produce relatively accurate deposition patterns and fallout arrival times. Furthermore, when no other measurement data are available, HYSPLIT can be used to indicate whether or not fallout might have occurred at a given location and provide, at minimum, crude quantitative estimates of the magnitude of the deposited activity. A variety of simulations of the deposition of fallout from atmospheric nuclear tests conducted in the Marshall Islands (mid-Pacific), at the Nevada Test Site (U.S.), and at the Semipalatinsk Nuclear Test Site (Kazakhstan) were performed. The results of the Marshall Islands simulations were used in a limited fashion to support the dose reconstruction described in companion papers within this volume.

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.

Computational lymphatic node models in pediatric and adult hybrid phantoms for radiation dosimetry

We developed models of lymphatic nodes for six pediatric and two adult hybrid computational phantoms to calculate the lymphatic node dose estimates from external and internal radiation exposures. We derived the number of lymphatic nodes from the recommendations in International Commission on Radiological Protection (ICRP) Publications 23 and 89 at 16 cluster locations for the lymphatic nodes: extrathoracic, cervical, thoracic (upper and lower), breast (left and right), mesentery (left and right), axillary (left and right), cubital (left and right), inguinal (left and right) and popliteal (left and right), for different ages (newborn, 1-, 5-, 10-, 15-year-old and adult). We modeled each lymphatic node within the voxel format of the hybrid phantoms by assuming that all nodes have identical size derived from published data except narrow cluster sites. The lymph nodes were generated by the following algorithm: (1) selection of the lymph node site among the 16 cluster sites; (2) random sampling of the location of the lymph node within a spherical space centered at the chosen cluster site; (3) creation of the sphere or ovoid of tissue representing the node based on lymphatic node characteristics defined in ICRP Publications 23 and 89. We created lymph nodes until the pre-defined number of lymphatic nodes at the selected cluster site was reached. This algorithm was applied to pediatric (newborn, 1-, 5-and 10-year-old male, and 15-year-old males) and adult male and female ICRP-compliant hybrid phantoms after voxelization. To assess the performance of our models for internal dosimetry, we calculated dose conversion coefficients, called S values, for selected organs and tissues with Iodine-131 distributed in six lymphatic node cluster sites using MCNPX2.6, a well validated Monte Carlo radiation transport code. Our analysis of the calculations indicates that the S values were significantly affected by the location of the lymph node clusters and that the values increased for smaller phantoms due to the shorter inter-organ distances compared to the bigger phantoms. By testing sensitivity of S values to random sampling and voxel resolution, we confirmed that the lymph node model is reasonably stable and consistent for different random samplings and voxel resolutions.

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.

Organ Doses From Diagnostic Medical Radiography-Trends Over Eight Decades (1930 to 2010).

AbstractThis study provides a retrospective assessment of doses to 13 organs for the most common radiographic examinations conducted between the 1930s and 2010, taking into account typical technical parameters used for radiography during those years. This study is intended to be a resource on changes in medical diagnostic radiation exposure over time with a specific purpose of supporting retrospective epidemiological studies of radiation health risks. The authors derived organ doses to the brain, esophagus, thyroid, red bone marrow, lungs, breast, heart, stomach, liver, colon, urinary bladder, ovaries, and testes based on 14 common radiographic procedures and compared, when possible, with doses reported in the literature. These dose estimates were based on radiographic exposure parameters described in textbooks widely used by radiologic technologists in training from 1939 to 2010. The derived estimated doses presented here are believed to be representative of typical organs for an average-size adult who might be considered to be similar to the reference person. There were large variations in organ doses noted among the different types of radiographic examinations. Doses were highest in organs within the area imaged and next highest in organs in close proximity to the area imaged. Estimated organ doses have declined substantially [overall 22‐fold (±38)] over time as a consequence of changes in technology, imaging protocols and protective measures. For some examinations, only slight differences were observed in doses for the decades of the 1960s, 1970s, and 1980s due to minor changes in technical parameters. Substantial dose reductions were observed in the 1990s and 2000s.

Organ Dose Estimates for Hyperthyroid Patients Treated with 131I: An Update of the Thyrotoxicosis Follow-Up Study

The Thyrotoxicosis Therapy Follow-up Study (TTFUS) is comprised of 35,593 hyperthyroid patients treated from the mid-1940s through the mid-1960s. One objective of the TTFUS was to evaluate the long-term effects of high-dose iodine-131 (131I) treatment (1–4). In the TTFUS cohort, 23,020 patients were treated with 131I, including 21,536 patients with Graves disease (GD), 1,203 patients with toxic nodular goiter (TNG) and 281 patients with unknown disease. The study population constituted the largest group of hyperthyroid patients ever examined in a single health risk study. The average number (±1 standard deviation) of 131I treatments per patient was 1.7 ± 1.4 for the GD patients and 2.1 ± 2.1 for the TNG patients. The average total 131I administered activity was 380 ± 360 MBq for GD patients and 640 ± 550 MBq for TNG patients. In this work, a biokinetic model for iodine was developed to derive organ residence times and to reconstruct the radiation-absorbed doses to the thyroid gland and to other organs resulting from administration of 131I to hyperthyroid patients. Based on 131I data for a small, kinetically well-characterized sub-cohort of patients, multivariate regression equations were developed to relate the numbers of disintegrations of 131I in more than 50 organs and tissues to anatomical (thyroid mass) and clinical (percentage thyroid uptake and pulse rate) parameters. These equations were then applied to estimate the numbers of 131I disintegrations in the organs and tissues of all other hyperthyroid patients in the TTFUS who were treated with 131I. The reference voxel phantoms adopted by the International Commission on Radiological Protection (ICRP) were then used to calculate the absorbed doses in more than 20 organs and tissues of the body. As expected, the absorbed doses were found to be highest in the thyroid (arithmetic means of 120 and 140 Gy for GD and TNG patients, respectively). Absorbed doses in organs other than the thyroid were much smaller, with arithmetic means of 1.6 Gy, 1.5 Gy and 0.65 Gy for esophagus, thymus and salivary glands, respectively. The arithmetic mean doses to all other organs and tissues were more than 100 times less than those to the thyroid gland. To our knowledge, this work represents the most comprehensive study to date of the doses received by persons treated with 131I for hyperthyroidism.

EVALUATION OF THE USE OF SURROGATE TISSUES FOR CALCULATING RADIATION DOSE TO LYMPHATIC NODES FROM EXTERNAL PHOTON BEAMS

Lymphatic node chains of the human body are particularly difficult to realistically model in computational human phantoms. In the absence of a lymphatic node model, researchers have used the following surrogate tissues to calculate the radiation dose to the lymphatic nodes: blood vessels, muscle and the combination of the muscle and adipose tissues. In the present work, the authors investigated whether and in which extent the use of different surrogate tissues is appropriate to assess the lymph node dose, using a realistic model of lymphatic nodes that the authors recently reported. Using a Monte Carlo radiation transport method coupled with the adult male hybrid phantom that included the lymph node model, the air kerma-to-absorbed dose conversion coefficients (Gy Gy(-1)) to the lymph nodes and other tissues used as surrogates for external photon beams of 15 discrete energies (0.015-10 MeV) were computed using the following six idealised geometries: anterior-posterior (AP), posterior-anterior (PA), right lateral, left lateral, rotational and isotropic. To validate the results of this study, the lymph node dose calculated here was compared with the dose published by the International Commission on Radiological Protection for the adult male reference phantom. The lymph node dose conversion coefficients with the values calculated for the blood vessels, muscle, adipose tissue and the combination of muscle and adipose tissues were then compared. It was found that muscle was the best estimator for the lymph nodes, with a dose difference averaged across energies >0.08 MeV of <8 % in all irradiation geometries excluding the AP and PA geometries for which the blood vessels were found to be the best estimator. In conclusion, muscle and blood vessels may preferably be used as surrogate tissues in the absence of lymphatic nodes in a given voxel phantom. For energies <0.08 MeV, for which the authors observed a difference of up to 30-fold, an explicit lymph node model may be required to prevent increasing differences with the lymph node dose as the photon energy decreases, though the absolute values of the dose conversion coefficients are smaller than at higher energy.