Radiation Adverse Outcome pathways (AOPs): examining priority questions from an international horizon-style exercise.

PURPOSE: The Organisation for Economic Co-operation and Development (OECD) Adverse Outcome Pathway (AOP) Development Programme is being explored in the radiation field, as an overarching framework to identify and prioritize research needs that best support strengthening of radiation risk assessment and risk management strategies. To advance the use of AOPs, an international horizon-style exercise (HSE) was initiated through the Radiation/Chemical AOP Joint Topical Group (JTG) formed by the OECD Nuclear Energy Agency (NEA) High-Level Group on Low Dose Research (HLG-LDR) under the auspices of the Committee on Radiological Protection and Public Health (CRPPH). The intent of the HSE was to identify key research questions for consideration in AOP development that would help to reduce uncertainties in estimating the health risks following exposures to low dose and low dose-rate ionizing radiation. The HSE was conducted in several phases involving the solicitation of relevant questions, a collaborative review of open-ended candidate questions and an elimination exercise that led to the selection of 25 highest priority questions for the stated purpose. These questions were further ranked by over 100 respondents through an international survey. This final set of questions was judged to provide insights into how the OECD's AOP approach can be put into practice to meet the needs of hazard and risk assessors, regulators, and researchers. This paper examines the 25 priority questions in the context of hazard/risk assessment framework for ionizing radiation. CONCLUSION: By addressing the 25 priority questions, it is anticipated that constructed AOPs will have a high level of specificity, making them valuable tools for simplifying and prioritizing complex biological processes for use in developing revised radiation hazard and risk assessment strategies.

Revisiting an Inverse Dose-Fractionation Effect of Ionizing Radiation Exposure for Ischemic Heart Disease: Insights from Recent Studies.

Over the last two decades, there has been emerging evidence suggesting that ionizing radiation exposures could be associated with elevated risks of cardiovascular disease (CVD), particularly ischemic heart disease (IHD). Excess CVD risks have been observed in a number of exposed groups, with generally similar risk estimates at both at low and high radiation doses and dose rates. In 2014, in this journal we reported for the first time significantly higher risks of IHD mortality when radiation doses were delivered over a protracted period of time (an inverse dose-fractionation effect) in the Canadian Fluoroscopy Cohort Study. Here we review the current evidence on the dose-fractionation effect of radiation exposure, discuss potential implication for radiation protection policies and suggest further directions for research in this area.

AOP report: Development of an adverse outcome pathway for deposition of energy leading to cataracts.

Cataracts are one of the leading causes of blindness, with an estimated 95 million people affected worldwide. A hallmark of cataract development is lens opacification, typically associated not only with aging but also radiation exposure as encountered by interventional radiologists and astronauts during the long-term space mission. To better understand radiation-induced cataracts, the adverse outcome pathway (AOP) framework was used to structure and evaluate knowledge across biological levels of organization (e.g., macromolecular, cell, tissue, organ, organism and population). AOPs identify a sequence of key events (KEs) causally connected by key event relationships (KERs) beginning with a molecular initiating event to an adverse outcome (AO) of relevance to regulatory decision-making. To construct the cataract AO and retrieve evidence to support it, a scoping review methodology was used to filter, screen, and review studies based on the modified Bradford Hill criteria. Eight KEs were identified that were moderately supported by empirical evidence (e.g., dose-, time-, incidence-concordance) across the adjacent (directly linked) relationships using well-established endpoints. Over half of the evidence to justify the KER linkages was derived from the evidence stream of biological plausibility. Early KEs of oxidative stress and protein modifications had strong linkages to downstream KEs and could be the focus of countermeasure development. Several identified knowledge gaps and inconsistencies related to the quantitative understanding of KERs which could be the basis of future research, most notably directed to experiments in the range of low or moderate doses and dose-rates, relevant to radiation workers and other occupational exposures.

Cancer and Non-Cancer Effects Following Ionizing Irradiation.

On the one hand, ionizing radiation has been used to treat not only cancer, but also non-cancer diseases. On the other hand, associations with radiation exposure have increasingly been reported not only for cancer, but also non-cancer diseases, both at doses or dose rates much lower than previously suggested or considered. This underscores the need for considering both cancer and non-cancer effects of medical (diagnostic or therapeutic), occupational or environmental exposure to radiation. As such, this Special Issue aims to serve as a forum to gather the latest developments and discuss future prospects in the field of normal tissue responses to radiation exposure. The Special Issue is composed of 18 articles outlining the radiation effects arising in various tissues (e.g., those in the circulatory, sensory, nervous, respiratory, and reproductive systems).

A generalisation of the method of regression calibration and comparison with Bayesian and frequentist model averaging methods.

For many cancer sites low-dose risks are not known and must be extrapolated from those observed in groups exposed at much higher levels of dose. Measurement error can substantially alter the dose-response shape and hence the extrapolated risk. Even in studies with direct measurement of low-dose exposures measurement error could be substantial in relation to the size of the dose estimates and thereby distort population risk estimates. Recently, there has been considerable attention paid to methods of dealing with shared errors, which are common in many datasets, and particularly important in occupational and environmental settings. In this paper we test Bayesian model averaging (BMA) and frequentist model averaging (FMA) methods, the first of these similar to the so-called Bayesian two-dimensional Monte Carlo (2DMC) method, and both fairly recently proposed, against a very newly proposed modification of the regression calibration method, the extended regression calibration (ERC) method, which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. The quasi-2DMC with BMA method performs well when a linear model is assumed, but very poorly when a linear-quadratic model is assumed, with coverage probabilities both for the linear and quadratic dose coefficients that are under 5% when the magnitude of shared Berkson error is large (50%). For the linear model the bias is generally under 10%. However, using a linear-quadratic model it produces substantially biased (by a factor of 10) estimates of both the linear and quadratic coefficients, with the linear coefficient overestimated and the quadratic coefficient underestimated. FMA performs as well as quasi-2DMC with BMA when a linear model is assumed, and generally much better with a linear-quadratic model, although the coverage probability for the quadratic coefficient is uniformly too high. However both linear and quadratic coefficients have pronounced upward bias, particularly when Berkson error is large. By comparison ERC yields coverage probabilities that are too low when shared and unshared Berkson errors are both large (50%), although otherwise it performs well, and coverage is generally better than the quasi-2DMC with BMA or FMA methods, particularly for the linear-quadratic model. The bias of the predicted relative risk at a variety of doses is generally smallest for ERC, and largest for the quasi-2DMC with BMA and FMA methods (apart from unadjusted regression), with standard regression calibration and Monte Carlo maximum likelihood exhibiting bias in predicted relative risk generally somewhat intermediate between ERC and the other two methods. In general ERC performs best in the scenarios presented, and should be the method of choice in situations where there may be substantial shared error, or suspected curvature in the dose response.

Radiotherapy for non-cancer diseases: benefits and long-term risks.

PURPOSE: The discovery of X-rays was followed by a variety of attempts to treat infectious diseases and various other non-cancer diseases with ionizing radiation, in addition to cancer. There has been a recent resurgence of interest in the use of such radiotherapy for non-cancer diseases. Non-cancer diseases for which use of radiotherapy has currently been proposed include refractory ventricular tachycardia, neurodegenerative diseases (e.g. Alzheimer's disease and dementia), and Coronavirus Disease 2019 (COVID-19) pneumonia, all with ongoing clinical studies that deliver radiation doses of 0.5-25 Gy in a single fraction or in multiple daily fractions. In addition to such non-cancer effects, historical indications predominantly used in some countries (e.g. Germany) include osteoarthritis and degenerative diseases of the bones and joints. This narrative review gives an overview of the biological rationale and ongoing preclinical and clinical studies for radiotherapy proposed for various non-cancer diseases, discusses the plausibility of the proposed biological rationale, and considers the long-term radiation risks of cancer and non-cancer diseases. CONCLUSIONS: A growing body of evidence has suggested that radiation represents a double-edged sword, not only for cancer, but also for non-cancer diseases. At present, clinical evidence has shown some beneficial effects of radiotherapy for ventricular tachycardia, but there is little or no such evidence of radiotherapy for other newly proposed non-cancer diseases (e.g. Alzheimer's disease, COVID-19 pneumonia). Patients with ventricular tachycardia and COVID-19 pneumonia have thus far been treated with radiotherapy when they are an urgent life threat with no efficient alternative treatment, but some survivors may encounter a paradoxical situation where patients were rescued by radiotherapy but then get harmed by radiotherapy. Further studies are needed to justify the clinical use of radiotherapy for non-cancer diseases, and optimize dose to diseased tissue while minimizing dose to healthy tissue.

A generalisation of the method of regression calibration and comparison with Bayesian and frequentist model averaging methods.

For many cancer sites low-dose risks are not known and must be extrapolated from those observed in groups exposed at much higher levels of dose. Measurement error can substantially alter the dose-response shape and hence the extrapolated risk. Even in studies with direct measurement of low-dose exposures measurement error could be substantial in relation to the size of the dose estimates and thereby distort population risk estimates. Recently, there has been considerable attention paid to methods of dealing with shared errors, which are common in many datasets, and particularly important in occupational and environmental settings. In this paper we test Bayesian model averaging (BMA) and frequentist model averaging (FMA) methods, the first of these similar to the so-called Bayesian two-dimensional Monte Carlo (2DMC) method, and both fairly recently proposed, against a very newly proposed modification of the regression calibration method, the extended regression calibration (ERC) method, which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. The quasi-2DMC with BMA method performs well when a linear model is assumed, but very poorly when a linear-quadratic model is assumed, with coverage probabilities both for the linear and quadratic dose coefficients that are under 5% when the magnitude of shared Berkson error is large (50%). For the linear model the bias is generally under 10%. However, using a linear-quadratic model it produces substantially biased (by a factor of 10) estimates of both the linear and quadratic coefficients, with the linear coefficient overestimated and the quadratic coefficient underestimated. FMA performs as well as quasi-2DMC with BMA when a linear model is assumed, and generally much better with a linear-quadratic model, although the coverage probability for the quadratic coefficient is uniformly too high. However both linear and quadratic coefficients have pronounced upward bias, particularly when Berkson error is large. By comparison ERC yields coverage probabilities that are too low when shared and unshared Berkson errors are both large (50%), although otherwise it performs well, and coverage is generally better than the quasi-2DMC with BMA or FMA methods, particularly for the linear-quadratic model. The bias of the predicted relative risk at a variety of doses is generally smallest for ERC, and largest for the quasi-2DMC with BMA and FMA methods (apart from unadjusted regression), with standard regression calibration and Monte Carlo maximum likelihood exhibiting bias in predicted relative risk generally somewhat intermediate between ERC and the other two methods. In general ERC performs best in the scenarios presented, and should be the method of choice in situations where there may be substantial shared error, or suspected curvature in the dose response.

Sparing and enhancing dose protraction effects for radiation damage to the aorta of wild-type mice.

PURPOSE: Our previous work indicated the greater magnitude of damage to the thoracic aorta at 6 months after starting 5 Gy irradiation in descending order of exposure to X-rays in 25 fractions > acute X-rays > acute γ-rays > X-rays in 100 fractions ≫ chronic γ-rays, in which the limitations of the study included a lack of data for fractionated γ-ray exposure. To better understand effects of dose protraction and radiation quality, the present study examined changes after exposure to γ-rays in 25 fractions, and compared its biological effectiveness with five other irradiation regimens. MATERIALS AND METHODS: Male C57BL/6J mice received 5 Gy of 137Cs γ-rays delivered in 25 fractions spread over six weeks. At 6 months after starting irradiation, mice were subjected to echocardiography, followed by tissue sampling. The descending thoracic aorta underwent scanning electron microscopy, immunofluorescence staining and histochemical staining. The integrative analysis of multiple aortic endpoints was conducted for inter-regimen comparisons. RESULTS: Exposure to γ-rays in 25 fractions induced vascular damage (evidenced by increases in endothelial detachment and vascular endothelial cell death, decreases in endothelial waviness, CD31, endothelial nitric oxide synthase and vascular endothelial cadherin), inflammation (evidenced by increases in tumor necrosis factor α, CD68 and F4/80) and fibrosis (evidenced by increases in transforming growth factor ß1, alanine blue stain and intima-media thickness). The integrative analysis revealed biological effectiveness in descending order of exposure to X-rays in 25 fractions > acute X-rays > γ-rays in 25 fractions > acute γ-rays > X-rays in 100 fractions ≫ chronic γ-rays. CONCLUSIONS: The results suggest that dose protraction effects on aortic damage depend on radiation quality, and are not a simple function of dose rate and the number of fractions.

A generalisation of the method of regression calibration and comparison with the Bayesian 2-dimensional Monte Carlo method.

For many cancer sites it is necessary to assess risks from low-dose exposures via extrapolation from groups exposed at moderate and high levels of dose. Measurement error can substantially alter the shape of this relationship and hence the derived population risk estimates. Even in studies with direct measurement of low-dose exposures measurement error could be substantial in relation to the size of the dose estimates and thereby distort population risk estimates. Recently, much attention has been devoted to the issue of shared errors, common in many datasets, and particularly important in occupational settings. In this paper we test a Bayesian model averaging method, the so-called Bayesian two-dimensional Monte Carlo (2DMC) method, that has been fairly recently proposed against a very newly proposed modification of the regression calibration method, which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. We also compared both methods against standard regression calibration and Monte Carlo maximum likelihood. The Bayesian 2DMC method performs poorly, with coverage probabilities both for the linear and quadratic dose coefficients that are under 5%, particularly when the magnitudes of classical and Berkson error are both moderate to large (20%-50%). The method also produces substantially biased (by a factor of 10) estimates of both the linear and quadratic coefficients, with the linear coefficient overestimated and the quadratic coefficient underestimated. By comparison the extended regression calibration method yields coverage probabilities that are too low when shared and unshared Berkson errors are both large (50%), although otherwise it performs well, and coverage is generally better than the Bayesian 2DMC and all other methods. The bias of the predicted relative risk at a variety of doses is generally smallest for extended regression calibration, and largest for the Bayesian 2DMC method (apart from unadjusted regression), with standard regression calibration and Monte Carlo maximum likelihood exhibiting bias in predicted relative risk generally somewhat intermediate between the other two methods.

A generalisation of the method of regression calibration.

There is direct evidence of risks at moderate and high levels of radiation dose for highly radiogenic cancers such as leukaemia and thyroid cancer. For many cancer sites, however, it is necessary to assess risks via extrapolation from groups exposed at moderate and high levels of dose, about which there are substantial uncertainties. Crucial to the resolution of this area of uncertainty is the modelling of the dose-response relationship and the importance of both systematic and random dosimetric errors for analyses in the various exposed groups. It is well recognised that measurement error can alter substantially the shape of this relationship and hence the derived population risk estimates. Particular attention has been devoted to the issue of shared errors, common in many datasets, and particularly important in occupational settings. We propose a modification of the regression calibration method which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. This method can be used in settings where there is a mixture of Berkson and classical error. In fits to synthetic datasets in which there is substantial upward curvature in the true dose response, and varying (and sometimes substantial) amounts of classical and Berkson error, we show that the coverage probabilities of all methods for the linear coefficient [Formula: see text] are near the desired level, irrespective of the magnitudes of assumed Berkson and classical error, whether shared or unshared. However, the coverage probabilities for the quadratic coefficient [Formula: see text] are generally too low for the unadjusted and regression calibration methods, particularly for larger magnitudes of the Berkson error, whether this is shared or unshared. In contrast Monte Carlo maximum likelihood yields coverage probabilities for [Formula: see text] that are uniformly too high. The extended regression calibration method yields coverage probabilities that are too low when shared and unshared Berkson errors are both large, although otherwise it performs well, and coverage is generally better than these other three methods. A notable feature is that for all methods apart from extended regression calibration the estimates of the quadratic coefficient [Formula: see text] are substantially upwardly biased.

A generalisation of the method of regression calibration.

There is direct evidence of risks at moderate and high levels of radiation dose for highly radiogenic cancers such as leukaemia and thyroid cancer. For many cancer sites, however, it is necessary to assess risks via extrapolation from groups exposed at moderate and high levels of dose, about which there are substantial uncertainties. Crucial to the resolution of this area of uncertainty is the modelling of the dose-response relationship and the importance of both systematic and random dosimetric errors for analyses in the various exposed groups. It is well recognised that measurement error can alter substantially the shape of this relationship and hence the derived population risk estimates. Particular attention has been devoted to the issue of shared errors, common in many datasets, and particularly important in occupational settings. We propose a modification of the regression calibration method which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. This method can be used in settings where there is a mixture of Berkson and classical error. In fits to synthetic datasets in which there is substantial upward curvature in the true dose response, and varying (and sometimes substantial) amounts of classical and Berkson error, we show that the coverage probabilities of all methods for the linear coefficient \(\alpha\) are near the desired level, irrespective of the magnitudes of assumed Berkson and classical error, whether shared or unshared. However, the coverage probabilities for the quadratic coefficient \(\beta\) are generally too low for the unadjusted and regression calibration methods, particularly for larger magnitudes of the Berkson error, whether this is shared or unshared. In contrast Monte Carlo maximum likelihood yields coverage probabilities for \(\beta\) that are uniformly too high. The extended regression calibration method yields coverage probabilities that are too low when shared and unshared Berkson errors are both large, although otherwise it performs well, and coverage is generally better than these other three methods. A notable feature is that for all methods apart from extended regression calibration the estimates of the quadratic coefficient \(\beta\) are substantially upwardly biased.

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.

Immunohistochemical Analysis of Lung Adenocarcinoma in Russian Mayak Nuclear Workers.

Specimens of lung adenocarcinoma (AdCa) from Russian nuclear workers (n = 54) exposed to alpha particles and gamma rays and from individuals non-exposed to radiation (n = 21) were examined using immunohistochemistry. Estimated significant associations with alpha dose were negative for Ki-67 and collagen IV in AdCa. Associations with gamma-ray dose were negative for tissue inhibitor of matrix metalloproteinase 2 and caspase 3 and positive for matrix metalloproteinase 2 and leukemia inhibiting factor in AdCa. The findings provide some evidence supporting alterations in apoptosis, cell proliferation and extracellular matrix in lung tissues affected by chronic radiation exposure that can contribute to radiogenic cancerogenesis.

Ionising radiation and cardiovascular disease: systematic review and meta-analysis.

OBJECTIVE: To systematically review and perform a meta-analysis of radiation associated risks of cardiovascular disease in all groups exposed to radiation with individual radiation dose estimates. DESIGN: Systematic review and meta-analysis. MAIN OUTCOME MEASURES: Excess relative risk per unit dose (Gy), estimated by restricted maximum likelihood methods. DATA SOURCES: PubMed and Medline, Embase, Scopus, Web of Science Core collection databases. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Databases were searched on 6 October 2022, with no limits on date of publication or language. Animal studies and studies without an abstract were excluded. RESULTS: The meta-analysis yielded 93 relevant studies. Relative risk per Gy increased for all cardiovascular disease (excess relative risk per Gy of 0.11 (95% confidence interval 0.08 to 0.14)) and for the four major subtypes of cardiovascular disease (ischaemic heart disease, other heart disease, cerebrovascular disease, all other cardiovascular disease). However, interstudy heterogeneity was noted (P<0.05 for all endpoints except for other heart disease), possibly resulting from interstudy variation in unmeasured confounders or effect modifiers, which is markedly reduced if attention is restricted to higher quality studies or those at moderate doses (<0.5 Gy) or low dose rates (<5 mGy/h). For ischaemic heart disease and all cardiovascular disease, risks were larger per unit dose for lower dose (inverse dose effect) and for fractionated exposures (inverse dose fractionation effect). Population based excess absolute risks are estimated for a number of national populations (Canada, England and Wales, France, Germany, Japan, USA) and range from 2.33% per Gy (95% confidence interval 1.69% to 2.98%) for England and Wales to 3.66% per Gy (2.65% to 4.68%) for Germany, largely reflecting the underlying rates of cardiovascular disease mortality in these populations. Estimated risk of mortality from cardiovascular disease are generally dominated by cerebrovascular disease (around 0.94-1.26% per Gy), with the next largest contribution from ischaemic heart disease (around 0.30-1.20% per Gy). CONCLUSIONS: Results provide evidence supporting a causal association between radiation exposure and cardiovascular disease at high dose, and to a lesser extent at low dose, with some indications of differences in risk between acute and chronic exposures, which require further investigation. The observed heterogeneity complicates a causal interpretation of these findings, although this heterogeneity is much reduced if only higher quality studies or those at moderate doses or low dose rates are considered. Studies are needed to assess in more detail modifications of radiation effect by lifestyle and medical risk factors. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020202036.

Dose rate effect on mortality from ischemic heart disease in the cohort of Russian Mayak Production Association workers.

For improvement of the radiation protection system it is crucial to know the factors that modify the radiation dose-response relationship. One of such key factors is the ionizing radiation dose rate. There are, however, very few studies that examine the impact of the dose rate on radiogenic risks observed in human cohorts exposed to radiation at various dose rates. Here we investigated the impact of the dose rate (in terms of the recorded annual dose) on ischemic heart disease (IHD) mortality among Russian nuclear workers chronically exposed to radiation. We observed significantly increased excess relative risks (ERR) of IHD mortality per unit of external gamma-ray absorbed dose accumulated at higher dose rates (0.005-0.050 Gy/year). The present findings provide evidence for the association between radiation dose rate and ERRs of IHD mortality in occupationally chronically exposed workers per unit total dose. IHD mortality risk estimates considerably increased with increasing duration of uninterrupted radiation exposure at high rates. The present findings are consistent with other studies and can contribute to the scientific basis for recommendations on the radiation protection system.

Incidence risks for subtypes of heart diseases in a Russian cohort of Mayak Production Association nuclear workers.

Heart diseases are one of the main causes of death. The incidence risks were assessed for various types of heart diseases (HDs) in a cohort of Russian nuclear workers of the Mayak Production Association (PA) who had been chronically occupationally exposed to external gamma and/ or internal alpha radiation. The study cohort included all workers (22,377 individuals) who had been hired at the Mayak PA during 1948-1982 and followed up until 31 December 2018. The mean gamma-absorbed dose to the liver (standard deviation) was 0.43 (0.63) Gy, and the mean alpha-absorbed dose to the liver was 0.25 (1.19) Gy. Excess relative risk (ERR) per unit liver-absorbed dose (Gy) was calculated based on maximum likelihood. At the end of the follow-up, 559 chronic rheumatic heart disease (CRHD), 7722 ischemic heart disease (IHD) [including 2185 acute myocardial infarction (AMI) and 3976 angina pectoris (AP)], 4939 heart failure (HF), and 3689 cardiac arrhythmia and conduction disorder (CACD) cases were verified in the study cohort. Linear model fits of the gamma dose response for HDs were best once adjustments for non-radiation factors (sex, attained age, calendar period, smoking status and alcohol consumption) and alpha dose were included. ERR/Gy in males and females was 0.17 (95% confidence intervals: 0.10, 0.26) and 0.23 (0.09, 0.38) for IHD; 0.18 (0.09, 0.29) and 0.26 (0.08, 0.49) for AP; - 0.01 (n/a, 0.1) and - 0.01 (n/a, 0.27) for AMI; 0.27 (0.16, 0.40) and 0.27 (0.10, 0.49) for HF; 0.32 (0.19, 0.46) and 0.05 (- 0.09, 0.22) for CACD; 0.73 (- 0.02, 2.40) and - 0.12 (- 0.50, 0.69) for CRHD, respectively. Sensitivity analyses demonstrated the persistence of a significant dose-response regardless of exclusion/inclusion of adjustments for known potential non-radiation confounders (smoking, alcohol consumption, body mass index, hypertension, diabetes mellitus), and it was only the magnitude of the risk estimate that varied. The risks of HD incidence were not modified with sex (except for the CACD risk). This study provides evidence for a significant association of certain types of HDs with cumulative dose of occupational chronic external exposure to gamma radiation.

Individual response of the ocular lens to ionizing radiation.

PURPOSE: Cataract (opacification of the ocular lens) is a typical tissue reaction (deterministic effect) following ionizing radiation exposure, for which prevention dose limits have been recommended in the radiation protection system. Manifestations of radiation cataracts can vary among individuals, but such potential individual responses remain uncharacterized. Here we review relevant literature and discuss implications for radiation protection. This review assesses evidence for significant modification of radiation-induced cataractogenesis by age at exposure, sex and genetic factors based on current scientific literature. CONCLUSIONS: In addition to obvious physical factors (e.g. dose, dose rate, radiation quality, irradiation volume), potential factors modifying individual responses for radiation cataracts include sex, age and genetics, with comorbidity and coexposures also having important roles. There are indications and preliminary data identifying such potential modifiers of radiation cataract incidence or risk, although no firm conclusions can yet be drawn. Further studies and a consensus on the evidence are needed to gain deeper insights into factors determining individual responses regarding radiation cataracts and the implications for radiation protection.

Low-dose radiotherapy for COVID-19 pneumonia and cancer: summary of a recent symposium and future perspectives.

The lessons learned from the Coronavirus Disease 2019 (COVID-19) pandemic are numerous. Low dose radiotherapy (LDRT) was used in the pre-antibiotic era as treatment for bacterially/virally associated pneumonia. Motivated in part by these historic clinical and radiobiological data, LDRT for treatment of COVID-19-associated pneumonia was proposed in early 2020. Although there is a large body of epidemiological and experimental data pointing to effects such as cancer at low doses, there is some evidence of beneficial health effects at low doses. It has been hypothesized that low dose radiation could be combined with immune checkpoint therapy to treat cancer. We shall review here some of these old radiobiological and epidemiological data, as well as the newer data on low dose radiation and stimulated immune response and other relevant emerging data. The paper includes a summary of several oral presentations given in a Symposium on "Low dose RT for COVID and other inflammatory diseases" as part of the 67th Annual Meeting of the Radiation Research Society, held virtually 3-6 October 2021.

Regulatory implementation of the occupational equivalent dose limit for the lens of the eye and underlying relevant efforts in Japan.

In April 2011, the International Commission on Radiological Protection recommended reducing the occupational equivalent dose limit for the lens. Such a new occupational lens dose limit has thus far been implemented in many countries, and there are extensive discussions toward its regulatory implementation in other countries. In Japan, discussions in the Japan Health Physics Society (JHPS) began in April 2013 and in Radiation Council in July 2017, and the new occupational lens dose limit was implemented into regulation in April 2021. To share our experience, we have published a series of papers summarizing situations in Japan: the first paper based on information available by early 2017, and the second paper by early 2019. This paper (our third paper of this series) aims to review updated information available by mid-2022, such as regarding regulatory implementation of the new occupational lens dose limit, recent discussions by relevant ministries based on the opinion from the council, establishment process of safety and health management systems, the JHPS guidelines on lens dose monitoring and radiation safety, voluntary countermeasures of the licensees, development of lens dose calibration method, and recent studies on exposure of the lens in nuclear workers and biological effect on the lens.