The current system of radiological protection (SRP) is based on the linear no-threshold (LNT) hypothesis for radiation-caused cancer and other forms of health detriment. Now there is overwhelming evidence of a dose-rate-dependent population threshold (abbreviated t) absorbed dose for cancer induction. Thus, the SRP needs to be updated to account for the threshold, and tools for doing so are provided in this article. These tools include the organ/tissue-T-related, threshold{t}-based, equivalent dose H{t}T (e.g., in sieverts), which is evaluated using the threshold-based radiation weighting factor wR,t. A second tool is the population equivalent dose threshold HT,t. When used in radiation exposure limitation, its value is assigned for a reference group, reference organ/tissue characteristics, and reference exposure scenario (high dose rate), so that the equivalent dose limit H{t}T,lim is expressed as H{t}T < H{t}T,lim ≤ HT,t (high dose rate). A third tool is the organ/tissue-specific exceedance equivalent dose "ΔH{t}T= H{t}T- HT,t≥ 0 Sv," which is summed to get the total-body exceedance (TBEX). For many different radiation exposure scenarios, TBEX will be zero (Sv), unlike for the effective dose E. With an updated SRP based on a modern-science-related population threshold dose for radiation-caused health detriment, use of the LNT-based effective dose E and the as low as reasonably achievable principle would no longer be credible.

Background: We are exposed to natural ionizing radiation and other genomic stressors throughout life and radiophobia has caused much harm to society. The main basis for radiophobia is the invalid linear no-threshold (LNT) hypothesis for cancer induction, which the System of Radiological Protection (SRP) is linked to. Largely unknown to the public, evolution-associated genomic stress adaptation (gensadaptation) over many previous generations now provides protection to all lifeforms from low radiation doses. Objective: To help bring about an improved SRP not linked to the invalid LNT hypothesis for radiation-caused health detriment and to promote low-dose radiation therapy for different diseases. Methods: All-solid-cancer mortality risk dose-response relationships for A-bomb survivors were generated based on published LNT-modeling-related results. Dose-response relationships for lung cancer prevention by low-dose radiation were generated by linear interpolation based on published data from a study using > 15,000 mice. Uncertainty characterization was based on Monte Carlo calculations for binomial and Poisson distributions. New dose characterization tools were used for threshold dose-response relationships for radiation-caused cancer mortality. Results: The all-solid-cancer mortality risk for A-bomb survivors transitioned from LNT to threshold-linear when adjusted for key missing uncertainty at low doses. The prevention of lung cancer in mice by low radiation doses depends on the radiation absorbed dose and type. Conclusions: The SRP should be linked to population dose thresholds rather than the invalid LNT hypothesis and small likely harmless radiation doses could possibly be used in treating different diseases.

Background:Previously the author was unable to develop a formal mathematical characterization of his probability-based hormetic relative risk (HRR) model for cancer prevention/elimination by absorbed doses (D) of ionizing radiation in the hormetic zone where D < D t (population absorbed dose threshold for cancer induction). Objective:To develop a formal mathematical characterization of the HRR model's disease prevention function DPF(D), which is the cancer prevention/elimination probability. Approach:Use distributed (over a population) individual-specific, natural-defenses-enhancing (E) and suppressing (S) dose thresholds. Results:DPF(D) is now mathematically characterized based on Weibull-type E and S thresholds distributions. The E thresholds predominate at very low radiation doses and the S thresholds predominate at higher doses just below D t. This leads to a hormetic dose-response relationship for cancer relative risk RR(D) (= 1 - DPF(D)) for doses from zero (representing natural background radiation exposure) to dose D t. The greatly improved HRR model is quite flexible and was applied to lung cancer and reticulum cell sarcoma prevention/elimination data from a study involving more than 15 000 gamma-ray exposed mice. Conclusion:The System of Radiological Protection needs to be updated to account for health benefits rather than invalid LNT-hypothesis-based phantom radiation-caused cancers from radiation doses < D t.

ABSTRACT:The system of radiological protection has been based on linear no-threshold theory and related dose-response models for health detriment (in part related to cancer induction) by ionizing radiation exposure for almost 70 y. The indicated system unintentionally promotes radiation phobia, which has harmed many in relationship to the Fukushima nuclear accident evacuations and led to some abortions following the Chernobyl nuclear accident. Linear no-threshold model users (mainly epidemiologists) imply that they can reliably assess the cancer excess relative risk (likely none) associated with tens or hundreds of nanogray (nGy) radiation doses to an organ (e.g., bone marrow); for 1,000 nGy, the excess relative risk is 1,000 times larger than that for 1 nGy. They are currently permitted this unscientific view (ignoring evolution-related natural defenses) because of the misinforming procedures used in data analyses of which many radiation experts are not aware. One such procedure is the intentional and unscientific vanishing of the excess relative risk uncertainty as radiation dose decreases toward assigned dose zero (for natural background radiation exposure). The main focus of this forum article is on correcting the serious error of discarding risk uncertainty and the impact of the correction. The result is that the last defense of the current system of radiological protection relying on linear no-threshold theory (i.e., epidemiologic studies implied findings of harm from very low doses) goes away. A revised system is therefore needed.

Assigned cancer risks (related to real or phantom risks) for low radiation doses derived from epidemiologic studies depend on the radiation-exposure scenario, study-population character-istics, and risk-analysis methods employed. Some researchers use an assumed dose-response model (e.g., Ref [1]) while others do not (e.g., Ref [2]). The risk-analysis methods used are based on presumed (but not demonstrated) reliability for low radiation doses; thus, reliability assessments for the different methods need to be performed so that unreliable methods for low radiation doses can be revealed and their use discontinued. An ethods-r e l iability (RAMRL) assessment for epidemiologic studies of cancer risk after low radiation doses is discussed. RAMRL assessment can be conducted using simulated study data generated based on cancer occurrence (spontaneous or induced speci fi c type) being evaluated as a dose-response-model – related B ernoulli r andom v ariable (BRV) for each member of the study population of interest. The BRV is discrete and would stochastically take on a value of 1 (with probability p ) indicating a simulated cancer victim (for any cause) or a value of 0 (with probability 1 - p ) indicating a simulated cancer-free individual. The cancer probability p would be assigned using a plausible multivariate (due to multiple cancer causes) cancer-risk model for a speci fi c set of risk factors including radiation dose (individual-speci c).

The seriously damaged Chernobyl nuclear power plant is located in the Ukrainian war zone. Intentional or accidental release via detonation of radionuclides from the plant site could pose serious health risks to the nearby population. Cancers in different organs are the main risk of concern for low radiation doses; however, the manner of assessing cancer risks is now controversial in that the linear-nothreshold (LNT) model used by epidemiologists (e.g., ) contradicts current knowledge of the chemico-biological interactions that occur in the body after low radiation doses and also promotes radiation phobia. Which other model to use is unclear. The previous Low Dose Radiation Research Program in the United States that partly focused on radiobiological research that was linked to improving health-risk-assessment approaches was unfortunately canceled about 10 years ago. In establishing an approach to use in addressing health risks for low radiation doses to humans, researchers need to take into consideration that unlike animal-studies data, epidemiologic-studies data for humans are very noisy (wider stochastic error distributions) 5 so that any risk estimates generated using such data likely involve large errors. Animal-studies data with smaller errors (for radiation doses and biological effects) than epidemiologic-studies data could be used in improving modeling methods employed in epidemiologic studies and in testing reliability of cancer risk predictions for low radiation doses. Regarding the risks of specific life-threatening deterministic effects of large radiation doses (unlikely to occur for most individuals in the Ukrainian war zone), the acute lethality and morbidity risks can be approximated using endpoint-specific, nonlinear, hazard-function (HF) models. These models feature dose and dose-rate-related thresholds and allow for external exposure to gamma radiation in combination with internal exposure via alphaparticle-, beta-particle-, and gamma-ray-emitting radionuclides. The HF models also address the complex doserate patterns that are associated with internal radionuclides and can be implemented using existing computer code systems developed in the United States and in Europe for assessing expected health consequences of nuclear power plant accidents for given populations; however, parameters for the endpoint-specific HF models were estimated using deficient data that were available at the time the models were developed (i.e., prior to 1995). Thus, parameters for endpoint-specific HF models need to be updated using now-available data and the updated parameter estimates (and related uncertainties) need to be incorporated into computer codes used in assessing risks (and related uncertainties) of radiation deterministic health effects that include specific morbidity types and lethality modes.

The main basis for cancer risk quantification for humans exposed to low radiation doses is epidemiologic studies. Findings from such studies have influenced the development of the current system of radiological protection along with the related radiation-dose-reducing concept “As Low As Reasonably Achievable (ALARA).” Cancer risk quantification for low radiation doses is mainly based on the controversial linear-no-threshold (LNT) model which is unsupported by modern radiation biology. There are uncertainties with any cancer risk assessment related to radiation exposure. With use of the LNT model to estimate relative risk (or excess relative risk) for low radiation doses, the uncertainty in the risk estimate is strangely modeled as progressively vanishing as radiation dose decreases to assigned dose zero (e.g., “0 mGy”); an oddity of contemporary epidemiologic studies such as conducted by Leuraud et al. This is problematic because there is no actual zero-radiation exposure since everyone is continuously exposed to natural background radiation and cancer absolute risk in the absence of any radiation exposure throughout life is uncertain. Thus, epidemiologist when employing the LNT model to radiationdose-response data for cancer-relative-risk estimation can predict the absolute risk (estimated as “A{U}” with uncertainty U) for the type of cancer of interest for a radiationfree world. The estimated absolute risk A{U} can then be used in generating the relative risk estimate and related uncertainty for a given dose-group studied. In this case, the zero-radiation relative risk estimate “A{U}/A{U},” with central estimate “1,” also has nonvanishing uncertainty because of uncertainty propagation. The indicated approach would help in preventing the inappropriate vanishing by design of risk uncertainty for decreasing low radiation doses. Uncertainty about the correct risk model (other models are possible, including threshold and hormetic) also needs careful consideration and there are reliable ways to address this. The indicted uncertainty becomes quite important when predicting relative risk (or excess relative risk) for cancer at below normal natural background radiation levels because LNT and hormetic models lead to very different risk predictions. Below-natural-background-radiation radiobiological studies deep underground that used various organisms have produced results that do not support the LNT model as applied to radiation-induced stochastic effects (e.g., mutations). Additionally, neoplastic transformation in cultured cells was reduced rather than increased by above-naturalbackground-radiation, gamma-ray doses of 1 to 100 mGy. Given the information provided in this publication, vanishing by design of cancer risk uncertainty for decreasing low radiation doses is misleading and unscientific.

The core of the current system of radiological protection (SRP) consists of 3 fundamental principles: justification, optimization, and applying ionizing radiation dose limits: the principle of justification specifies that any activity (or intervention) that changes the exposure scenario should be overall beneficial to individuals and/or society; the principle of optimization specifies that radiation doses should be as low as reasonably achievable, considering both economic and societal factors; the principle of dose limitation applies to planned radiation exposures (other than medical and environmental) and dictates that doses should not exceed established limits. The dose limits are linked to the linear-no-threshold (LNT) risk model for ionizing radiation harm. Ethics and societal values form one of the 3 pillars supporting the current SRP of humans, augmenting the science (considered flawed by some) related to the system. The International Commission on Radiological Protection (ICRP) has highlighted the ethical foundations of the SRP for humans via its Publication 138; the earlier Publication 91 outlined ethical principles that apply to environmental radiation protection of non-human species. Now there is interest in addressing the ethics associated with intentional diagnostic or therapeutic (e.g., for pets) or other exposures of animals to ionizing radiation (such as in animal research). The already cited new publication on this topic is entitled Ethics and Values Surrounding the Radiation Protection of Animals. The following important question is raised in this letter to the editor: are ethical values used in the current SRP based on sufficient knowledge about low-dose-radiation health effects in humans and in animals? This question relates to current reliance on the LNT model for low-dose-radiation health risk assessment. What if the LNT model is invalid? This would be the case if there are actual dose thresholds for the different health effects of interest or if low radiation doses are not harmful and often beneficial to our health (i.e., hormetic) depending on the circumstances. Now there is overwhelming evidence that low radiation doses stimulate rather than suppress the body’s natural defenses. In fact, the use of low-dose radiation to stimulate the body’s natural defenses is now being considered for treating life-threatening COVID-19-related pneumonia and greatly-debilitating Alzheimer’s disease. Should convincing success with low-dose-radiation therapy be demonstrated for such diseases, physicians not using the therapy due to concern for harm to patients from low radiation doses because of the current SRP-projected health risks should be considered unethical in my opinion.

The linear-no-threshold (LNT) model is currently used in low-dose-radiation cancer risk assessment and this practice is supported by organizations that include the Environmental Protection Agency and the Nuclear Regulatory Commission. Lagging low radiation doses has been used in epidemiologic studies and this helps to justify reliance on an LNT function for excess relative risk (ERR) for cancer incidence. Some of the low dose is discarded (lagging of dose) with the remaining even smaller dose then treated as relevant for cancer induction. This presumed-relevant smaller dose can be expressed mathematically as D-L where D is the assigned total absorbed dose and L (<D) is the discarded amount. Excess relative risk (evaluated as the product k[D-L], with the lagged dose D-L treated as the independent variable) is then the positive-slope (k used here) LNT function to be generated in the epidemiologic study for a given cancer type. The predetermined conclusion of such studies is that any amount of radiation no matter how small is carcinogenic. Interestingly, for a future group exposed to a low dose D of the same type of radiation under similar circumstances, ERR (evaluated as the product kD with slope k based on lagged dose) is then used in predicting cancer risk. This leads to inflation of LNT-based ERR by a factor 1/(1-f) where f is the fraction of D that was discarded when previously estimating k. The ERR inflation promotes radiation phobia and this can lead to detrimental outcomes including the loss of many lives as occurred among evacuees after the Fukushima nuclear accident in March 2011. The phobia can also lead to refusals by millions of individuals worldwide of potentially lifesaving and health-enhancing, low-dose-radiation therapy for health problems that may include cancer, Alzheimer’s disease, and COVID-19-related pneumonia. Because a low dose (eg, 10 mGy) is highly unlikely to cause cancer but may with high probability stimulate the body’s natural anticancer defenses, there is no well-founded scientific justification for radiation dose lagging in epidemiologic studies of cancer risk after exposure to low-dose radiation or for use of an LNT risk model. Lagging low doses and using other misinforming procedures (MisPros) in epidemiologic studies to make the LNT model appear acceptable is misleading. For low radiation doses and an appropriate null hypothesis of no radiation-induced cancers, blaming all observed cancers on very small doses (a dose-lagging consequence) rather than other risk factors is unscientific.

US homeland security concerns related to potential misuse of γ-ray-emitting radiation sources employed in radiobiological research (eg, shielded cesium-137 irradiators) led to recommendations by the National Research Council to conduct studies into possibly replacing γ-ray irradiators used in research involving small rodent and other models with X-ray instruments. A limiting factor is suitability of the X-ray photon energy spectra. The objective of our research was to demonstrate the suitability of the radiation energy spectrum of 320-kV X rays after filtration (HVL = 4 mm Cu) for in-vivo cytotoxicity studies in immunodeficient C.B-17 SCID mice. By using a previously-published Hazard Function (HF) model to characterize dose-response relationships for in vivo bone marrow and spleen cell survival fractions and also to characterize the acute lethality risk (hematopoietic syndrome mode) we demonstrate that the filtered 320-kV X-ray beam appears suitable for such studies. A key finding for C.B-17 SCID mice when compared to results previously obtained for immunocompetent C.B-17 mice is that the immunodeficient mice appear to be more radioresistant, implicating a possible role of the immune system capacity in radiosensitivity of mammals.

Well-designed epidemiologic studies, e.g. some COVID-19 pandemic applications, provide reliable information for society. Poorly-designed epidemiologic studies, as with some that relate to cancer risks for low-dose radiation, employ misinforming procedures (MisPros; singular MisPro; new abbreviations) that can lead to unintended harmful actions related to radiation phobia. This phobia led to enormous societal losses following the Fukushima and Chernobyl nuclear accidents. The phobia is linked to the linear-no-threshold (LNT) cancer risk model used in many epidemiologic studies. LNT is based on the conjecture that any amount of radiation can cause cancer and cancer risk increases linearly as radiation dose increases; however, extensive radiobiological data related to chemico-biological interactions and their consequences do not support LNT. This letter focuses on elucidating how some epidemiologic studies of radiation-induced cancer that supposedly support the LNT model were designed to lead to an LNT outcome via using clever MisPros. The studies generally focus on the relative risk estimate (RRE; usually misleadingly abbreviated RR) for a specific type of cancer. For the supposedly un-irradiated group (unexposed), RRE 1⁄4 1, with no uncertainty (MisPro #1; vanishing uncertainty). Some studies also discard some of the radiation dose (called lagging; MisPro #2) allowing epidemiologists to treat radiation doses as being smaller than they were. Another MisPro (#3) is to treat the unexposed group as having never been irradiated (via natural background or other radiation sources). Acknowledging that dose > 0 (eg, in mGy or mSv) for this group forces (as should be the case) LNT advocates to predict radiation risk at absolute zero radiation dose where no measurements can be performed because of unavoidable natural background radiation. This would also force the RRE for the unexposed group (actually irradiated) to be assigned uncertainty > 0 (as should be the case). High-dose data are usually included (MisPro #4) and guarantees a positive slope to the fitted LNT line. Dose groups with a range (sometimes wide) of doses in each group are used (MisPro #5) which hides nonlinearity. In addition, the null hypothesis is usually misassigned to LNT (MisPro #6) rather than to no radiation effect. With the LNT model, preventing all radiation exposures throughout life would be predicted to minimize the overall cancer absolute risk; however, all life forms initially evolved in the presence of higher natural background radiation than now and a slightly elevated radiation level is known to stimulate the body’s natural defenses (hormetic benefits) against cancer. Thus, residing in a radiationfree world would likely significantly increases the overall cancer absolute risk, which essentially renders LNT highly implausible.

The current system of radiological protection (SRP) is founded on principles linked to the hypothetical linear-no-threshold (LNT) risk model for health detriment from low-dose radiation exposure. This letter relates to needed improvements in the SRP due to scientific deficiencies (eg, missing thresholds, nonlinear dose responses) and to major challenges in achieving the improvements. There now is extensive radiobiological evidence that the LNT model is invalid for cancer induction (main contribution to health detriment), as chemico-biological interactions and their systemic consequences after low radiation doses (e.g., < 100 mGy) are consistently showing no adverse health effects and possible health benefits. The health benefits (eg, cancer prevention) occur above an adaptive response threshold but below a second dose threshold for harm. Radiation-stimulated, hierarchical-natural-defenses models (with deterministic or stochastic thresholds) have been researched (but insufficiently) and are more credible than LNT for low radiation doses. Related to the deficient LNT-based SRP, it has been stated “Preconceived concepts impede progress; in the case of the LNT model, they have resulted in substantial medical, economic, and other societal harm.” Indeed, the SRPbased, very stressful population evacuation following the 2011 Fukushima nuclear incident led to many lives lost unnecessarily. Developing a more scientifically credible SRP based on nonlinear dose-response (NDR) relationships (eg, single-thresholdsigmoidal; hormetic-two-thresholds; other) for harm or benefit/ harm to health is however much more challenging. A largely trusted organization [eg, the International Commission on Radiological Protection (ICRP)] will be needed to achieve the goal of an improved and widely accepted SRP based on NDR relationships. Questions that need to be addressed in a timely manner via research in order to develop an improved SRP include the following: a, what dose-response models will be best to use for the NDR curves; b, how will mixed radiations (e.g., alphaþ betaþ gamma) be addressed given that the current LNT-based, fixed radiation weighting factors (and linked equivalent doses) are unlikely to be reliably applicable to NDR relationships; c, if new radiation weighting factors (for NDRs) are to be developed and justifiably used, won’t they need to vary as absorbed dose increases or will some form of averaging over dose ranges be credible (validation likely needed); d, how will repeated exposures and dose-ratehistory (when dose rate changes over time) effects be accounted for; e, won’t LNT-related, whole-body effective dose need to be abandoned and if so will tissue-specific, weighted (eg, via RBE) doses be adequate. Whether some organization (eg, ICRP) or organizations will be willing to take on such challenging questions via research is unclear. Hopefully, such questions will be timely addressed for the benefit of future generations.

US homeland security concerns regarding the potential misuse of some radiation sources used in radiobiological research, for example, cesium-137 (137Cs), have resulted in recommendations by the National Research Council to conduct studies into replacing these sources with suitable X-ray instruments. The objective of this research is to compare the effectiveness of an X-RAD 320 irradiator (PXINC 2010) with a 137Cs irradiator (Gammacell-1000 Unit) using an established bone marrow chimeric model. Using measured radiation doses for each instrument, we characterized the dose–response relationships for bone marrow and splenocyte ablation, using a cytotoxicity-hazard model. Our results show that the X-RAD 320 photon energy spectrum was suitable for ablating bone marrow at the 3 exposure levels used, similar to that of 137Cs photons. However, the 320-kV X-rays were not as effective as the much higher energy γ rays at depleting mouse splenocytes. Furthermore, the 3 X-ray levels used were less effective than the higher energy γ rays in allowing the successful engraftment of donor bone marrow, potentially as a result of the incomplete depletion of the spleen cells. More defined studies are warranted for determining whether bone marrow transplantation in mice can be successfully achieved using 320-kV X-rays. A higher X-ray dose then used is likely needed for transplantation success.