Probability Distribution of Dose and Dose-Rate Effectiveness Factor for use in Estimating Risks of Solid Cancers From Exposure to Low-Let Radiation

Noncancer Effects of Ionizing Radiation Exposure on the Eye, the Circulatory System and beyond: Developments made since the 2011 ICRP Statement on Tissue Reactions

For radiation protection purposes, noncancer effects with a threshold-type dose-response relationship have been classified as tissue reactions (formerly called nonstochastic or deterministic effects), and equivalent dose limits aim to prevent occurrence of such tissue reactions. Accumulating evidence demonstrates increased risks for several late occurring noncancer effects at doses and dose rates much lower than previously considered. In 2011, the International Commission on Radiological Protection (ICRP) issued a statement on tissue reactions to recommend a threshold of 0.5 Gy to the lens of the eye for cataracts and to the heart and brain for diseases of the circulatory system (DCS), independent of dose rate. Literature published thereafter continues to provide updated knowledge. Increased risks for cataracts below 0.5 Gy have been reported in several cohorts (e.g., including in those receiving protracted or chronic exposures). A dose threshold for cataracts is less evident with longer follow-up, with limited evidence available for risk of cataract removal surgery. There is emerging evidence for risk of normal-tension glaucoma and diabetic retinopathy, but the long-held tenet that the lens represents among the most radiosensitive tissues in the eye and in the body seems to remain unchanged. For DCS, increased risks have been reported in various cohorts, but the existence or otherwise of a dose threshold is unclear. The level of risk is less uncertain at lower dose and lower dose rate, with the possibility that risk per unit dose is greater at lower doses and dose rates. Target organs and tissues for DCS are also unknown, but may include heart, large blood vessels and kidneys. Identification of potential factors (e.g., sex, age, lifestyle factors, coexposures, comorbidities, genetics and epigenetics) that may modify radiation risk of cataracts and DCS would be important. Other noncancer effects on the radar include neurological effects (e.g., Parkinson's disease, Alzheimer's disease and dementia) of which elevated risk has increasingly been reported. These late occurring noncancer effects tend to deviate from the definition of tissue reactions, necessitating more scientific developments to reconsider the radiation effect classification system and risk management. This paper gives an overview of historical developments made in ICRP prior to the 2011 statement and an update on relevant developments made since the 2011 ICRP statement.

Pediatric Brain Tumor Risk Associated with Head Computed Tomography: Systematic Literature Review

Computed tomography (CT) of the brain has changed diagnostic neuroradiology significantly over the past 50 years since it was firstly used back in 1971 to visualize suspected frontal lobe tumour. The safety of head CT is determined by the small amount of radiation and the low sensibility of brain tissue to cytotoxic damage due to ionizing radiation compared to other organs. However, some population groups may be at increased risk. Thus, children are more susceptible to radiation cancer than adults and lifelong attributive risk (LAR) can be more than 10 times higher for an infant than for a middle-aged adult. The authors have reviewed published studies that examined the prevalence and mortality of intracranial tumors in children undergoing head CT in comparison to unaffected individuals. Electronic search of publications in the PubMed database from 1966 to date was carried out. We have carried out intersectoral search for documents containing keywords or medical subject headings (MeSH) related to three wide categories: 1) computed tomography, 2) radiation-induced tumors, 3) risk, morbidity or epidemiology. Further search was performed in manual mode. Available epidemiological data generally confirmed correlation between head CT and tumor growth induction. Thus, current epidemiological data accept the opinion that the risk of tumor induction associated with head CT in children is very small (one tumor per 3,000–10,000 studies). The minimal estimated risk of tumor induction due to head CT in children is mostly offset by its diagnostic imaging benefits considering the clinical indications to minimize radiation dose. Understanding and quantitative risk assessment of carcinogenesis associated with CT imaging led to dose reduction in pediatric CT protocols. This trend should continue and should be implemented in all age groups. Although the decision to perform head CT is often undeniable (injury or hemorrhage), careful assessment of studies frequency is required, especially in patients who need disease monitoring. Cumulative effect in such cases may increase the minimal risk of carcinogenesis. Larger and advanced epidemiological studies are required to better understand these risks.

Low-Dose Extrapolation Factors Implied by Mortality and Incidence Data from the Japanese Atomic Bomb Survivor Life Span Study Data

Assessment of the effect of low dose and low-dose-rate exposure depends critically on extrapolation from groups exposed at high dose and high-dose rates such as the Japanese atomic bomb survivor data, and has often been achieved via application of a dose and dose-rate effectiveness factor (DDREF). An important component of DDREF is the factor determining the effect of extrapolation of dose, the so-called low-dose extrapolation factor (LDEF). To assess LDEF models linear (or linear quadratic) in dose are often fitted. In this report LDEF is assessed via fitting relative rate models that are linear or linear quadratic in dose to the latest Japanese atomic bomb survivor data on solid cancer, leukemia and circulatory disease mortality (followed from 1950 through 2003) and to data on solid cancer, lung cancer and urinary tract cancer incidence. The uncertainties in LDEF are assessed using parametric bootstrap techniques. Analysis is restricted to survivors with <3 Gy dose. There is modest evidence for upward curvature in dose response in the mortality data. For leukemia and for all solid cancer excluding lung, stomach and breast cancer there is significant curvature (P < 0.05). There is no evidence of curvature for circulatory disease (P > 0.5). The estimate of LDEF for all solid cancer mortality is 1.273 [95% confidence intervals (CI) 0.913, 2.182], for all solid cancer mortality excluding lung cancer, stomach cancer and breast cancer is 2.183 (95% CI 1.090, >100) and for leukemia mortality is 11.447 (95% CI 2.390, >100). For stomach cancer mortality LDEF is modestly raised, 1.077 (95% CI 0.526, >100), while for lung cancer, female breast cancer and circulatory disease mortality the LDEF does not much exceed 1. LDEF for solid cancer incidence is 1.186 (95% CI 0.942, 1.626) and for urinary tract cancer is 1.298 (95% CI <0, 7.723), although for lung cancer LDEF is not elevated, 0.842 (95% CI 0.344, >100).

Radiation dose rate effects: what is new and what is needed?

Despite decades of research to understand the biological effects of ionising radiation, there is still much uncertainty over the role of dose rate. Motivated by a virtual workshop on the "Effects of spatial and temporal variation in dose delivery" organised in November 2020 by the Multidisciplinary Low Dose Initiative (MELODI), here, we review studies to date exploring dose rate effects, highlighting significant findings, recent advances and to provide perspective and recommendations for requirements and direction of future work. A comprehensive range of studies is considered, including molecular, cellular, animal, and human studies, with a focus on low linear-energy-transfer radiation exposure. Limits and advantages of each type of study are discussed, and a focus is made on future research needs.

Review of the risk of cancer following low and moderate doses of sparsely ionising radiation received in early life in groups with individually estimated doses

BACKGROUND

The detrimental health effects associated with the receipt of moderate (0.1-1 Gy) and high (>1 Gy) acute doses of sparsely ionising radiation are well established from human epidemiological studies. There is accumulating direct evidence of excess risk of cancer in a number of populations exposed at lower acute doses or doses received over a protracted period. There is evidence that relative risks are generally higher after radiation exposures in utero or in childhood.

METHODS AND FINDINGS

We reviewed and summarised evidence from 60 studies of cancer or benign neoplasms following low- or moderate-level exposure in utero or in childhood from medical and environmental sources. In most of the populations studied the exposure was predominantly to sparsely ionising radiation, such as X-rays and gamma-rays. There were significant (p < 0.001) excess risks for all cancers, and particularly large excess relative risks were observed for brain/CNS tumours, thyroid cancer (including nodules) and leukaemia.

CONCLUSIONS

Overall, the totality of this large body of data relating to in utero and childhood exposure provides support for the existence of excess cancer and benign neoplasm risk associated with radiation doses < 0.1 Gy, and for certain groups exposed to natural background radiation, to fallout and medical X-rays in utero, at about 0.02 Gy.

Parameter Values for Estimation of Internal Doses from Ingestion of Radioactive Fallout from Nuclear Detonations

ABSTRACT

This paper suggests values or probability distributions for a variety of parameters used in estimating internal doses from radioactive fallout due to ingestion of food. Parameters include those needed to assess the interception and initial retention of radionuclides by vegetation, translocation of deposited radionuclides to edible plant parts, root uptake by plants, transfer of radionuclides from vegetation into milk and meat, transfer of radionuclides into non-agricultural plants and wildlife, and transfer from food and drinking water to mother's milk (human breast milk). The paper includes discussions of the weathering half-life for contamination on plant surfaces, biological half-lives of organisms, food processing (culinary factors), and contamination of drinking water. As appropriate, and as information exists, parameter values or distributions are specific for elements, chemical forms, plant types, or other relevant characteristics. Information has been obtained from the open literature and from publications of the International Atomic Energy Agency. These values and probability distributions are intended to be generic; they should be reviewed for applicability to a given location, time period, or season of the year, as appropriate. In particular, agricultural practices and dietary habits may vary considerably both with geography and over time in a given location.

Valid versus invalid radiation cancer risk assessment methods illustrated using Swiss population data

After the nuclear accident in Fukushima, the public interest in radiation related cancer-risk assessment increased. However, interpretations of results from epidemiological studies and comprehension of cancer risk assessment methods can be unclear and involve questions about correctness and validity of the approaches. To shed some light on this potential lack of clarity, valid versus invalid radiation cancer risk assessments methods are illustrated here using Swiss population data. This involves a comparison of the cancer risk assessment method based on collective dose and the cumulative risk assessment method, where the latter is recommended with regard to uncertainties and risk of misinterpretation. Further, risk assessment in different dose ranges is discussed and it is concluded that below 100 mSv it cannot be appropriately stated that an adequate strength of evidence of a causal relationship between cancer and radiation is provided, because of the large uncertainties in this dose range. However, the linear non-threshold (LNT) model can be used to model the dose response, because it represents a prudent and parsimonious model, that fits the data well and lies within the given uncertainties. Additionally, treatments of uncertainties in the risk models are illustrated. The EU-project CONFIDENCE software is applied here to obtain example radiation related lifetime cancer risks for exposures of 20 mSv and 5 mSv. Furthermore, the impact of different dosimetry errors on the uncertainties in the cancer lifetime risk calculation is analysed, by including different standard deviations (SD) and by comparing the sampling of the doses from a normal and a lognormal distribution. Using the normal distribution, for females exposed to 20 mSv, the 95% confidence interval (CI) on the cancer lifetime risk increases, when compared to using a SD of 4 mSv, by a factor of 1.5 using a SD of 8 mSv and by a factor of 1.7 using a SD of 10 mSv. The corresponding factors for males for the same exposure are 1.3 and 1.5 respectively. For exposure to 5 mSv, the 95% CIs on the risk increase by a factor of 1.2 for females and 1.4 for men for a SD of 2 mSv using the normal distribution compared to the lognormal distribution and by a factor of 1.5 and 1.8 for a SD of 3 mSv compared to a SD of 1 mSv respectively. Furthermore, differences in the resulting 95% CI on the risk, using different distributions for the dose sampling are visible.

Improving astronaut cancer risk assessment from space radiation with an ensemble model framework

A new approach to NASA space radiation risk modeling has successfully extended the current NASA probabilistic cancer risk model to an ensemble framework able to consider sub-model parameter uncertainty as well as model-form uncertainty associated with differing theoretical or empirical formalisms. Ensemble methodologies are already widely used in weather prediction, modeling of infectious disease outbreaks, and certain terrestrial radiation protection applications to better understand how uncertainty may influence risk decision-making. Applying ensemble methodologies to space radiation risk projections offers the potential to efficiently incorporate emerging research results, allow for the incorporation of future models, improve uncertainty quantification, and reduce the impact of subjective bias. Moreover, risk forecasting across an ensemble of multiple predictive models can provide stakeholders additional information on risk acceptance if current health/medical standards cannot be met for future space exploration missions, such as human missions to Mars. In this work, ensemble risk projections implementing multiple sub-models of radiation quality, dose and dose-rate effectiveness factors, excess risk, and latency are presented. Initial consensus methods for ensemble model weights and correlations to account for individual model bias are discussed. In these analyses, the ensemble forecast compares well to results from NASA's current operational cancer risk projection model used to assess permissible mission durations for astronauts. However, a large range of projected risk values are obtained at the upper 95th confidence level where models must extrapolate beyond available biological data sets. Closer agreement is seen at the median ± one sigma due to the inherent similarities in available models. Identification of potential new models, epidemiological data, and methods for statistical correlation between predictive ensemble members are discussed. Alternate ways of communicating risk and acceptable uncertainty with respect to NASA's current permissible exposure limits are explored.

Methodological improvements to meta-analysis of low dose rate studies and derivation of dose and dose-rate effectiveness factors

Epidemiological studies of cancer rates associated with external and internal exposure to ionizing radiation have been subject to extensive reviews by various scientific bodies. It has long been assumed that radiation-induced cancer risks at low doses or low-dose rates are lower (per unit dose) than those at higher doses and dose rates. Based on a mixture of experimental and epidemiologic evidence the International Commission on Radiological Protection recommended the use of a dose and dose-rate effectiveness factor for purposes of radiological protection to reduce solid cancer risks obtained from moderate-to-high acute dose studies (e.g. those derived from the Japanese atomic bomb survivors) when applied to low dose or low-dose rate exposures. In the last few years there have been a number of attempts at assessing the effect of extrapolation of dose rate via direct comparison of observed risks in low-dose rate occupational studies and appropriately age/sex-adjusted analyses of the Japanese atomic bomb survivors. The usual approach is to consider the ratio of the excess relative risks in the two studies, a measure of the inverse of the dose rate effectiveness factor. This can be estimated using standard meta-analysis with inverse weighting of ratios of relative risks using variances derived via the delta method. In this paper certain potential statistical problems in the ratio of estimated excess relative risks for low-dose rate studies to the excess relative risk in the Japanese atomic bomb survivors are discussed, specifically the absence of a well-defined mean and the theoretically unbounded variance of this ratio. A slightly different method of meta-analysis for estimating uncertainties of these ratios is proposed, motivated by Fieller's theorem, which leads to slightly different central estimates and confidence intervals for the dose rate effectiveness factor. However, given the uncertainties in the data, the differences in mean values and uncertainties from the dose rate effectiveness factor estimated using delta-method-based meta-analysis are not substantial, generally less than 70%.

Risk of cancer associated with low-dose radiation exposure: comparison of results between the INWORKS nuclear workers study and the A-bomb survivors study

The Life Span Study (LSS) of Japanese atomic bomb survivors has served as the primary basis for estimates of radiation-related disease risks that inform radiation protection standards. The long-term follow-up of radiation-monitored nuclear workers provides estimates of radiation-cancer associations that complement findings from the LSS. Here, a comparison of radiation-cancer mortality risk estimates derived from the LSS and INWORKS, a large international nuclear worker study, is presented. Restrictions were made, so that the two study populations were similar with respect to ages and periods of exposure, leading to selection of 45,625 A-bomb survivors and 259,350 nuclear workers. For solid cancer, excess relative rates (ERR) per gray (Gy) were 0.28 (90% CI 0.18; 0.38) in the LSS, and 0.29 (90% CI 0.07; 0.53) in INWORKS. A joint analysis of the data allowed for a formal assessment of heterogeneity of the ERR per Gy across the two studies (P = 0.909), with minimal evidence of curvature or of a modifying effect of attained age, age at exposure, or sex in either study. There was evidence in both cohorts of modification of the excess absolute risk (EAR) of solid cancer by attained age, with a trend of increasing EAR per Gy with attained age. For leukemia, under a simple linear model, the ERR per Gy was 2.75 (90% CI 1.73; 4.21) in the LSS and 3.15 (90% CI 1.12; 5.72) in INWORKS, with evidence of curvature in the association across the range of dose observed in the LSS but not in INWORKS; the EAR per Gy was 3.54 (90% CI 2.30; 5.05) in the LSS and 2.03 (90% CI 0.36; 4.07) in INWORKS. These findings from different study populations may help understanding of radiation risks, with INWORKS contributing information derived from cohorts of workers with protracted low dose-rate exposures.

Cancer incidence risks above and below 1 Gy for radiation protection in space

The risk assessment quantities called lifetime attributable risk (LAR) and risk of exposure-induced cancer (REIC) are used to calculate the cumulative cancer incidence risks for astronauts, attributable to radiation exposure accumulated during long term lunar and Mars missions. These risk quantities are based on the most recently published epidemiological data on the Life Span Study (LSS) of Japanese A-bomb survivors, who were exposed to γ-rays and neutrons. In order to analyze the impact of a different neutron RBE on the risk quantities, a model for the neutron relative biological effectiveness (RBE) relative to gammas in the LSS is developed based on an older dataset with less follow-up time. Since both risk quantities are based on uncertain quantities, such as survival curves, and REIC includes deterministic radiation induced non-cancer mortality risks, modelled with data based on the general population, the risks for astronauts may not be optimally estimated. The suitability of these risk assessment measures for the use of cancer risk calculation for astronauts is discussed. The work presented here shows that the use of a higher neutron RBE than the value of 10, traditionally used in the LSS risk models, can reduce the risks up to almost 50%. Additionally, including an excess absolute risk (EAR) baseline scaling also increases the risks by between 0.4% and 8.1% for the space missions considered in this study. Using just an EAR model instead of an equally weighted EAR and excess relative risk (ERR) model can decrease the cumulative risks for the considered missions by between 0.4% and 4.1% if no EAR baseline scaling is applied. If EAR baseline scaling is included, the calculated risks with the EAR- and the mixed model, as well as the risks calculated with just the ERR model are almost identical and only small differences in the uncertainties are visible.

Adverse outcome pathways, key events, and radiation risk assessment

The overall aim of this contribution to the 'Second Bill Morgan Memorial Special Issue' is to provide a high-level review of a recent report developed by a Committee for the National Council on Radiation Protection and Measurements (NCRP) titled 'Approaches for Integrating Information from Radiation Biology and Epidemiology to Enhance Low-Dose Health Risk Assessment'. It derives from previous NCRP Reports and Commentaries that provide the case for integrating data from radiation biology studies (available and proposed) with epidemiological studies (also available and proposed) to develop Biologically-Based Dose-Response (BBDR) models. In this review, it is proposed for such models to leverage the adverse outcome pathways (AOP) and key events (KE) approach for better characterizing radiation-induced cancers and circulatory disease (as the example for a noncancer outcome). The review discusses the current state of knowledge of mechanisms of carcinogenesis, with an emphasis on radiation-induced cancers, and a similar discussion for circulatory disease. The types of the various informative BBDR models are presented along with a proposed generalized BBDR model for cancer and a more speculative one for circulatory disease. The way forward is presented in a comprehensive discussion of the research needs to address the goal of enhancing health risk assessment of exposures to low doses of radiation. The use of an AOP/KE approach for developing a mechanistic framework for BBDR models of radiation-induced cancer and circulatory disease is considered to be a viable one based upon current knowledge of the mechanisms of formation of these adverse health outcomes and the available technical capabilities and computational advances. The way forward for enhancing low-dose radiation risk estimates will require there to be a tight integration of epidemiology data and radiation biology information to meet the goals of relevance and sensitivity of the adverse health outcomes required for overall health risk assessment at low doses and dose rates.

ProZES: the methodology and software tool for assessment of assigned share of radiation in probability of cancer occurrence

ProZES is a software tool for estimating the probability that a given cancer was caused by preceding exposure to ionising radiation. ProZES calculates this probability, the assigned share, for solid cancers and hematopoietic malignant diseases, in cases of exposures to low-LET radiation, and for lung cancer in cases of exposure to radon. User-specified inputs include birth year, sex, type of diagnosed cancer, age at diagnosis, radiation exposure history and characteristics, and smoking behaviour for lung cancer. Cancer risk models are an essential part of ProZES. Linking disease and exposure to radiation involves several methodological aspects, and assessment of uncertainties received particular attention. ProZES systematically uses the principle of multi-model inference. Models of radiation risk were either newly developed or critically re-evaluated for ProZES, including dedicated models for frequent types of cancer and, for less common diseases, models for groups of functionally similar cancer sites. The low-LET models originate mostly from the study of atomic bomb survivors in Hiroshima and Nagasaki. Risks predicted by these models are adjusted to be applicable to the population of Germany and to different time periods. Adjustment factors for low dose rates and for a reduced risk during the minimum latency time between exposure and cancer are also applied. The development of the methodology and software was initiated and supported by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) taking up advice by the German Commission on Radiological Protection (SSK, Strahlenschutzkommission). These provide the scientific basis to support decision making on compensation claims regarding malignancies following occupational exposure to radiation in Germany.

Dose limits for occupational exposure to ionising radiation and genotoxic carcinogens: a German perspective

This paper summarises the view of the German Commission on Radiological Protection ("Strahlenschutzkommission", SSK) on the rationale behind the currently valid dose limits and dose constraints for workers recommended by the International Commission on Radiological Protection (ICRP). The paper includes a discussion of the reasoning behind current dose limits followed by a discussion of the detriment used by ICRP as a measure for stochastic health effects. Studies on radiation-induced cancer are reviewed because this endpoint represents the most important contribution to detriment. Recent findings on radiation-induced circulatory disease that are currently not included in detriment calculation are also reviewed. It appeared that for detriment calculations the contribution of circulatory diseases plays only a secondary role, although the uncertainties involved in their risk estimates are considerable. These discussions are complemented by a review of the procedures currently in use in Germany, or in discussion elsewhere, to define limits for genotoxic carcinogens. To put these concepts in perspective, actual occupational radiation exposures are exemplified with data from Germany, for the year 2012, and regulations in Germany are compared to the recommendations issued by ICRP. Conclusions include, among others, considerations on radiation protection concepts currently in use and recommendations of the SSK on the limitation of annual effective dose and effective dose cumulated over a whole working life.

Sensitivity analysis of parameters and methodological choices used in calculation of radiation detriment for solid cancer

Purpose: Radiation detriment is a concept used by the International Commission on Radiological Protection (ICRP) to quantify the harmful health effects of radiation exposure in humans. The current approach of radiation detriment calculation has been defined in ICRP Publication 103 in 2007. It is determined from lifetime risk of cancer and heritable effects for a composite reference population, taking into account the severity of the disease in terms of lethality, quality of life and years of life lost. Many parameters are used in the calculations and the variation of these parameters can have effects on the cancer detriment, which needs to be investigated.Materials and methods: In this paper, we conducted a sensitivity analysis for examining the impact of 12 different parameters or methodological choices on the calculation of solid cancer detriment, such as the lifetime risk calculation method, survival curve, dose and dose-rate effectiveness factor (DDREF), age-at-exposure, sex, reference population, risk transfer model, latency, attained age, lethality, minimum quality of life factor and relative cancer-free life lost. Sensitivity calculations have been performed systematically for each of 10 solid cancer sites, by changing each one of the parameters in turn.Results: This sensitivity analysis demonstrated a large impact on estimated detriment from DDREF, age-at-exposure, sex and lethality, a noticeable impact of risk transfer model associated to variation of baseline rates, and a limited impact of risk calculation method, survival curve, latency, attained age, quality of life and relative years of life lost.Conclusion: These results could have implications for radiation protection standards, and they should help define priorities for future research in the field of low radiation dose and dose rate research. The present sensitivity analysis is part of a global effort of ICRP to review the bases of radiation detriment calculation and assess potential evolutions to improve the radiation protection system.