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Research article
First published online March 30, 2015

Does Imaging Technology Cause Cancer? Debunking the Linear No-Threshold Model of Radiation Carcinogenesis


In the past several years, there has been a great deal of attention from the popular media focusing on the alleged carcinogenicity of low-dose radiation exposures received by patients undergoing medical imaging studies such as X-rays, computed tomography scans, and nuclear medicine scintigraphy. The media has based its reporting on the plethora of articles published in the scientific literature that claim that there is “no safe dose” of ionizing radiation, while essentially ignoring all the literature demonstrating the opposite point of view. But this reported “scientific” literature in turn bases its estimates of cancer induction on the linear no-threshold hypothesis of radiation carcinogenesis. The use of the linear no-threshold model has yielded hundreds of articles, all of which predict a definite carcinogenic effect of any dose of radiation, regardless of how small. Therefore, hospitals and professional societies have begun campaigns and policies aiming to reduce the use of certain medical imaging studies based on perceived risk:benefit ratio assumptions. However, as they are essentially all based on the linear no-threshold model of radiation carcinogenesis, the risk:benefit ratio models used to calculate the hazards of radiological imaging studies may be grossly inaccurate if the linear no-threshold hypothesis is wrong. Here, we review the myriad inadequacies of the linear no-threshold model and cast doubt on the various studies based on this overly simplistic model.


Intensive media attention aimed at the general public regarding the alleged cancer-inducing potential of the low-dose radiation exposure associated with medical imaging can provoke anxiety and even unnecessarily scare patients. In a vicious circle, the recent increased media hype may have caused individual physicians, hospitals, and even professional medical societies to create policies that unnecessarily limit radiological imaging studies. Additionally, because of a perceived need to reduce radiation dose, suboptimal imaging that does not yield a definitive diagnosis might result in the need for additional or repeat imaging studies, ironically increasing the overall radiation dose required to establish a diagnosis.
Although radiation is known to cause cancer at high doses and high-dose rates, no data have ever unequivocally demonstrated the induction of cancer following exposure to low doses and dose rates (<100-200 mSv acute or chronic exposures). A hypothetical model must be therefore applied to high-dose data to estimate what the presumed carcinogenic effects of low-dose radiation might be. The most commonly employed model is the linear no-threshold (LNT) model wherein dose-effect data at high doses are simply extrapolated linearly downward to zero dose with no threshold. The LNT model, although being heavily promoted by scientific advisory bodies around the world and serving as the established paradigm used by radiation regulators, is of questionable validity, utility, and applicability for estimation of cancer risks resulting from low-dose radiation exposures.13 We will provide compelling evidence that the dose–effect relationship at low doses is not linear and there is an obvious threshold demonstrating the existence of the body’s adaptive protective responses.

The LNT Model of Radiation Carcinogenesis is Likely Incorrect

Figure 1 illustrates the dose–response relationship for solid cancer incidence using data from 1958 to 1998 in the Life Span Study (LSS) atomic bomb (A-bomb) survivor population as presented in the Radiation Effects Research Foundation (RERF) Website ( and as reported by Preston et al.4 The LSS data have been considered by many to be the most important data for estimating radiation effects in humans and have traditionally been used to justify the existence of adverse health effects due to low-dose radiation exposure.
Figure 1. Dose–response relationship for solid cancer incidence using data from the Life Span Study (LSS) A-bomb survivor population.4 As stated on the Radiation Effects Research Foundation (RERF) Web site, the thick solid line is the fitted linear sex-averaged excess relative risk (ERR) dose response at age 70 after exposure at age 30. The thick dashed line is a nonparametric smoothed estimate of the dose category-specific risks and the thin dashed lines are 1 standard error above and below this smoothed estimate.
According to the RERF, the dose–response relationship in Figure 1 “appears to be linear, without any apparent threshold below which effects may not occur.” It is also noted, however, that there has been no statistically significant increase in the observed cancer frequency in survivors who were exposed to radiation doses of 150 mSv or less. Based mainly on these LSS data, the National Academy of Sciences Biological Effects of Ionizing Radiation (BEIR) VII Committee5 concluded that the “current scientific evidence is consistent with the hypothesis that there is a linear, no-threshold dose–response relationship between exposure to ionizing radiation and the development of radiation-induced solid cancers in humans.” However, this report does not conclude that the LNT theory is correct and it does not rule out the possibility of a threshold. In contrast to BEIR VII, the French Academy of Sciences report6 came to very different conclusions regarding the LNT model. The French report raised doubts about the validity of using the LNT model to estimate carcinogenic risks at doses less than 100 mSv, recognizing the abundant evidence for radiation adaptive response in terms of protection and lack of evidence for harm below this dose level.
An independent analysis of these LSS A-bomb survivor population data (using all data except the last 2 data points) based on linear regression (ie, a linear dose–response model) indicated an excellent correlation coefficient (r = .98), but with an apparent threshold at approximately 45 mGy.1 The 95% confidence interval for this threshold was determined to be 37 to 55 mGy, consistent with a linear threshold (LT) model, under the assumption that the dose–response is linear. Consistent with this result, others have determined that a threshold as high as 60 mSv may be present for cancer from these Japanese data.7,8 It appears then that the data in Figure 1 are not consistent with the LNT model; the only way the data fit would be linear and not exhibit a threshold is to constrain the fit through the origin, but there is no scientific basis for such an action. Thus, even using this paragon of A-bomb survivor data, the LNT model still does not correctly represent the data, particularly at low doses.
Figure 2 is a graph of excess risk versus dose using the LSS data from Figure 1, but only showing, for the first time, the portion of the curve in the low-dose region that consists of the 8 data points for doses ranging from 0 to ≤ 0.2 Gy (illustrated by the solid rectangles). For illustrative purposes, this portion of the curve below 0.2 Gy will be referred to as “the box.” It is apparent from the graph that at these low doses the dose–response is not linear.
Figure 2. Graph of excess risk versus dose using only low-dose data (≤0.2 Gy) as presented in Figure 1.
Three curve fits are presented and characterized in Figure 2 illustrating the analyses, based only on a linear dose–response model, reflecting thinking both “inside” and “outside” the box:
Using only risk versus dose data for doses ranging from 0 to ≤ 0.2 Gy, also known as thinking inside the box. The solid line is a linear fit to these 8 data points (solid rectangles), constrained to go through the origin, and as can be seen, the dose–response relationship is very poor (r2 = .25), indicating a linear fit is inadequate. If the fit is unconstrained, there is an obvious threshold, but the data fit is still poor. So, excess risk data at low doses does not conform to the LNT model; in fact, any adequate dose–response model would have to exhibit a threshold to describe these data.
Using all data in Figure 1 except the last 2 data points, that is, a wider dose range from 0 to approximately 2.2 Gy. The dotted line is an unconstrained linear fit to these data and this fit exhibits a threshold of approximately 0.045 Gy (45 mGy) as discussed previously. Therefore, an LT model is more appropriate than use of an LNT model. The correlation coefficient is better but this is because of use of data “outside the box.” Note that the linear fit to the data points ≤0.2 Gy is still very poor, again indicating the lack of a linear relationship at low doses, even though the correlation coefficient for the wider dose range is good (r = .98). The slopes of these 2 linear fits are significantly different (0.52 vs 0.34, respectively) illustrating that an extrapolation of what to expect at low doses (dotted line) rather than what has been observed (solid line) yield significantly different results.
Using all data in Figure 1 except the last 2 data points, but this time constraining the linear fit to pass through origin. The dashed line is the constrained linear fit and has essentially the same slope and correlation coefficient as the unconstrained fit. Note again that the use of the LNT model to characterize what happens at low doses using only low-dose data (solid line) or to predict what might happen at low doses based on an extrapolation (dotted and dashed lines) both yield poor results in the low-dose region. So the actual low-dose data are not adequately characterized by applying the LNT model to only these low-dose data, ranging from 0 to ≤0.2 Gy, nor are they adequately predicted based on extrapolated results from higher doses.
Thus, based on data from 1958 to 1998 in the LSS A-bomb survivor population, analyses performed either “inside the box” or “outside the box” demonstrate that there is not a linear, no-threshold relationship between excess risk and radiation dose at low doses (≤0.2 Gy or 200 mSv), so other dose–response models need to be utilized. Linearity at low doses does not exist; rather, it is forced by the high-dose extrapolation of the LNT model. If high-dose data did not exist and only the low-dose data were known and analyzed, it is obvious and inescapable that the LNT model is inadequate to describe the reported low-dose LSS data. Furthermore, a threshold is rendered invisible by the preconceived assumption that none exists—a self-fulfilling prophecy. If no such assumption is made to begin with and an unconstrained fit is then used, the data force the acceptance of a threshold.

Recent Evidence Further Contradicting the LNT Model—A Hormetic Model Perhaps?

A recent update to the LSS data reported by Ozasa et al9 indicated that the new dose–response data for cancer mortality at low doses are more consistent with a linear-quadratic dose–response model because a significant upward curvature is exhibited. Further, according to a 2013 revision of this update (explanatory material available at, “The linear dose–response relationship provided the best fit for the ERR data across the entire dose range, but a concave curve was the best fit for data restricted to dose <2 Gy. This resulted because risk estimates for exposure to around 0.5 Gy were lower than those in the linear model.” It is important to note that zero dose was reported to be the best estimate of the threshold, but this may be unjustified as the model used for their formal dose-threshold analysis restricted excess relative risk (ERR) values from extending into negative values. Use of a more generalized model employing multiple linear regression indicated the presence of a nonzero dose threshold and in addition, when a correction was applied to these data for a likely bias in the baseline cancer rate,10 it provided possible evidence of radiation hormesis, that is, ERR values were negative for all doses below approximately 0.6 Gy. This is indicative of a beneficial or cancer preventative effect such that low-dose radiation would reduce rather than increase cancer risk. Finally, another recent reanalysis of the LSS cohort of A-bomb survivors using a nonparametric statistical procedure has exhibited a threshold at low dose (<0.2 Sv or 200 mSv) which is manifested as negative ERR, again consistent with a radiation hormesis model.11
Such conclusions are consistent with the existence of an adaptive response, which serves to protect organisms following low-dose radiation exposure. These findings are in agreement with the experimental evidence of, for example, DNA double-strand break repair as has been reported after patient low-dose radiation exposure from computed tomography (CT) scans.12 Thus, overall, these data are more consistent with a radiation hormesis model than the LNT model, paradoxically indicating that low-dose radiation is beneficial, not harmful, from both mechanistic and epidemiological considerations.8
Based on the above-mentioned revisions to, and analyses of, the LSS data since the BEIR VII report, the atomic bomb survivor data no longer support the LNT model, but rather a hormetic model exhibiting a negative ERR at low doses (<200 mSv). This hormetic concept is further supported by a large body of evidence indicating that low-dose radiation has the opposite effect of high-dose radiation exposure.13 Although any damage that may occur after exposure to low-dose radiation exposure may occur in a linear fashion (ie, the dose-damage response may be linear), the dose–response at this dose level is not linear because of the body’s demonstrated response to mitigate/eliminate this damage.

The LNT Hypothesis is Not Biologically Plausible

When viewing radiation carcinogenesis from an exclusively molecular biological perspective or when only considering in vitro cellular experiments, it is easy to get lulled into an LNT mindset. It is true that any dose of ionizing radiation is capable of inducing a mutation and there is a finite probability that such mutations could be deleterious or transform normal cells into a malignant phenotype. However, when considering a broader, organismal-level perspective, the pitfalls of the LNT hypothesis of radiation carcinogenesis become apparent. For example, the average human body has a spontaneous background mutation rate that has been estimated to be 2 × 105 mutations per cell per day thanks to thermal insults and oxidative metabolism.14 This spontaneous rate of DNA alterations absolutely dwarfs the DNA alteration rate due to background radiation (10-100 DNA alterations per cell per cGy per year). To put things in perspective, the natural background radiation mutation rate, assuming an average background exposure rate of 3 mSv per year in the United States, would be 3 to 30 DNA alterations per cell per year, which is almost 2.5 million times lower than the spontaneous mutation rate. The point is that the normal body effectively deals with these numerous spontaneous mutations through a set of mechanisms collectively called the adaptive response; the small excess conferred by a low dose of radiation, even if LNT were true, is unlikely to overwhelm the system.
The observed threshold and negative ERRs are in agreement with experimental evidence for the induction of adaptive protection against cancer, such as antioxidant production, apoptosis, immune system-mediated effects, and repair of DNA double-strand breaks that have been shown to occur even after patient exposure to the low-dose radiation from CT scans.12 DNA damage response mechanisms defend against exogenous and endogenous DNA damage and enhance both survival and maintenance of genomic stability (which is critical for cancer avoidance).
The vast majority of human cancers are not simply the end products of a single (or even multiple) driver mutations. Such mutations may be necessary, but they are not sufficient to produce cancer. Modern understanding of the role of the immune system in the development of clinically overt cancers has led to a replacement of the outdated “one mutation = one cancer” model. In fact, evasion from immune system detection and escape from destruction have emerged as one of the newer “hallmarks of cancer.”15 Supporting this concept is the observation that in immunocompromised patients (eg, patients with HIV/AIDS and organ transplant recipients), vastly increased cancer rates have been reported.16 Thus, there is far more than the simple accumulation of mutations in the creation of a clinically overt cancer.
Additionally, the LNT hypothesis is illogical from the perspective of evolutionary biology.17 The early Earth was far richer in natural background radionuclides than it is today.18 Much of our planet’s primordial radionuclide endowment such as 40K has decayed and in fact the “neptunium series” or 4n + 1 series has long been extinct in nature due to the relatively short half-lives of the radioactive isotopes involved. The bottom line is that life emerged and evolved in an environment several-fold higher in background radiation than the levels of today. It is likely that powerful adaptive responses developed thanks to this high radiation background and it would be overly simplistic to assume that organisms have “forgotten” how to cope with low-level radiation damage.
Mechanisms of action are unique for low-dose radiation exposure. Processes activated by low doses are related to protective responses, whereas high-dose responses are associated with extensive damage, such as cell killing, tissue disruption, and inflammatory diseases.19 Furthermore, low-dose radiation exposure is known to boost the immune system causing a reduction in cancers.20 Intriguingly, low-dose radiation exposure might paradoxically be invaluable in radiation therapy of cancer thanks to recently uncovered immunomodulatory effects on tumor-infiltrating macrophages and on regulatory T-cells (Tregs).2123
Thus, there are different mechanisms of action at high and low doses indicating that the LNT-based assumption of, or “belief” in, an excess cancer risk at low doses is erroneous. High-dose effects cannot be extrapolated down to accurately predict effects at low doses, that is, “what happens at high doses, stays at high doses.” Paracelsus, a 16th century Renaissance physician, took an anti-LNT stance before it was even known or fashionable to do so when he said, “Poison is in everything, and no thing is without poison. The dosage makes it either a poison or a remedy” (

Recent Epidemiological Studies Do Not Provide Evidence of Radiation Carcinogenesis at Low Doses

There are 2 recently published epidemiological studies suggesting increased cancer risks at low radiation doses associated with pediatric CT scans24,25 and a third large record-based case–control study indicating an excess risk of childhood leukemia associated with natural background radiation exposure.26 However, significant concerns have been raised in a 2013 United Nations Scientific Committee on the Effect of Atomic Radiation (UNSCEAR) report that serve to invalidate these risk estimates.27 The putative CT-caused cancers may have been caused by the medical conditions prompting the CT scans and may have nothing to do with the radiation exposure involved (reverse causation—CT scans aren’t causing cancers and cancers are causing CT scans). Further, there is a huge uncertainty associated with the assigned radiation doses as individual dosimetry was not performed. Since the 2 pediatric CT studies do not provide evidence that low doses are causally associated with cancers in children, direct estimation of the health impact of CT radiation exposure remains imprecise. Further large-scale epidemiological studies with more accurate dosimetry and assessment of potential biases and uncertainties are needed. The “Epidemiological study to quantify risks for pediatric computerized tomography and to optimize doses” (EPI-CT) was set up to enroll approximately 1 million patients in 18 centers located in 11 countries to investigate these issues (; results are expected in 2015.
According to the UNSCEAR report, the study indicating natural background-associated cancers “should be interpreted with caution because of the large uncertainties associated with using an ecological measure of dose.” Radiation doses in this study were based on estimated mean exposure levels for the county district in which the mother resided at the child’s birth; thus, there is a huge uncertainty associated with these assigned radiation doses as individual dosimetry was not performed. Further, although the authors conclude that substantial bias is unlikely, the study provides no information on potential confounding factors other than measures of socioeconomic status.

Background Radiation and Definitions of a “Low Dose” of Radiation

There are perhaps 2 realistic definitions of a low dose of radiation. One is a dose below which it is not possible to detect adverse health effects (<100 mSv, according to the International Commission on Radiological Protection and the Health Physics Society). The second is the level of radiation that we are exposed to annually from natural background radiation, a dose range spanning 2 orders of magnitude depending on where in the world you live, from a few mSv to as high as 260 mSv in Ramsar, Iran.28
The high end of the range, corresponding to high natural background levels in regions including Ramsar, Iran, Yangjiang County of the Guangdong Province in China, and Kerala, India, are fascinating because of the very high background radiation but no apparent increased incidence of cancer. In fact, 1 in vitro study demonstrated a significantly reduced frequency of chromosome aberrations in lymphocytes following a challenge dose of 1.5 Gy of γ rays from people living in high background versus those living in normal background areas in and near Ramsar.28 These data are consistent with an adaptive response to low-dose chronic radiation exposure.
Irrespective of the level of background exposure to a given population, to date no associated health effects have been documented anywhere in the world. In fact, people in the United States are living longer today than ever before, likely due to always improving levels of medical care, including even more radiation exposure from diagnostic medical radiation (eg, life-saving X-ray and CT imaging examinations) which are well within the background dose range across the globe. Therefore, a low dose of radiation can be considered to be a dose less than 100 to 200 mSv.

Overestimating Radiation Risks—The Fukushima and Chernobyl Accidents

Use of the LNT model to illegitimately and unjustifiably predict low-dose effects (risk assessment) is not only wrong, it is not even conservative. Conservative is an ambiguous word and we wish to clarify its meaning here since it can mean conserving either life or resources; concepts that may be in opposition. In the case of Fukushima, for example, as discussed subsequently, the use of the LNT model and its derived policies was intended to be conservative with respect to protecting lives (ie, minimizing loss of life, a good thing), but despite the intentions, the outcome was quite different due to the actions taken (eg, forced evacuations), resources used, and number of actual lives lost. More thought should be given to policy decisions (risk management) based on the LNT model. Current regulatory dose limits should certainly be raised as they are somewhat arbitrary and well below the level at which adverse health effects have been demonstrated in humans.1 Overestimating radiation risks using the LNT model may be more detrimental than underestimating them, as this approach has resulted in unnecessary loss of life due to traumatic forced evacuations, suicides, and unneeded abortions after the Fukushima nuclear accident. Fear of radiation in this case may have been more harmful than the radiation itself as official figures indicate that well over 1000 deaths ( have been reported due to the forced evacuations. These avoidable and unnecessary “disaster-related deaths” were caused by fear of radiation resulting from LNT-derived policies that are directly attributable to ICRP recommendations. According to the UNSCEAR (, “Radiation exposure following the nuclear accident at Fukushima-Daiichi did not cause any immediate health effects. It is unlikely to be able to attribute any health effects in the future among the general public and the vast majority of workers.”
Following the Fukushima accident, the ICRP convened Task Group 84 to collate lessons learned in a memorandum29; for the record, the ICRP has noted that the material contained in this memorandum does not reflect their official view. Nevertheless, it is instructive to note some of the conclusions of this memorandum, such as “Following exposure to low radiation doses below about 100 mSv an increase of cancer has not been convincingly or consistently observed in epidemiological or experimental studies and will probably never be observed because of overwhelming statistical and biasing factors. In sum, theoretical cancer deaths after low-dose radiation exposure situations are obtained by inappropriate calculations based on the LNT model and misuse of the collective dose concept. Any effects—if they occur at all—will be so small that they would fall within the ‘ noise’ (scatter) of the ‘spontaneous’ cancer of unexposed people.” It should therefore be patently obvious that the ICRP needs to immediately raise its recommended dose limits, as adherence to the LNT model will cause more real deaths than the imaginary ones the model purports to save.
With respect to Chernobyl, 1 study examined cancer incidence (1986-2008) and mortality (1986-2011) among the Estonian cleanup workers in comparison with the Estonian male population.30 The cohort of 4810 men worked in the contaminated area for a median duration of 92 days and were exposed to an average radiation dose of approximately 10 cGy (certainly a low radiation dose). The conclusion of the article states, “…our study suggests that after a quarter century of follow-up of the Estonian cohort of Chernobyl cleanup workers, there is an increase risk of alcohol-related cancers, and of suicide. No definite indication of health effects directly attributable to radiation exposure was found.”

Medical Imaging and Low-Dose Health Effects

First and foremost, any discussion of risks related to radiation dose from medical imaging procedures must be accompanied by acknowledgment of the benefits of the procedures. Radiation exposure is considered by many to be the only risk involved in medical imaging applications. The more significant and actual risks associated with not undergoing an imaging procedure or undergoing a more invasive exploratory surgery are generally being ignored in both the scientific literature and the popular media.31 The LNT model and the philosophy behind it are more concerned with the extremely small number of very long term and only theoretically predicted cancer deaths attributed to radiation exposure rather than the much larger numbers of actual deaths that are certain to occur without imaging.
One group has even gone so far as to predict that CT scans will cause at least 29 000 cases of cancer and 14 500 deaths in the United States each year.32 This prediction was based on the LNT model, that is, by a simple multiplication of the unproven and theoretical cancer risk associated with the small radiation dose involved by the estimated number of CT scans performed in 2007 (the authors referred to this simple and trivial prediction as a “detailed” calculation). This type of calculation and result appears to be condoned by Brenner and Hall33 who have stated that, “although CT risks are small, a small risk multiplied by many millions of scans may translate into a public health concern some years in the future…” These types of inappropriate calculations based on the LNT model are at the very least misleading; they are in fact absolutely wrong and should be firmly criticized as being alarmist and not founded in scientific reality. According to ICRP Publication34 103 and others,29,35 the LNT hypothesis should not be used to calculate the hypothetical number of cancers that might be associated with small radiation doses received by large numbers of people.
Radiation is a weak carcinogen. In considering a strategy of risk reduction (for radiological imaging as well in the aftermath of a radiological event), it is critical for the general public and public health officials to understand that lifetime risk of developing cancer for an individual is not exclusively related to unnecessary or accidental exposure to radiation but is dependent on several factors including age at the time of radiation exposure and other variables such as genetics, and voluntary and involuntary exposures to carcinogens, such as cigarette smoke.36 For example, in the United States, the lifetime risk of developing cancer in the absence of radiation exposure is already quite high, that is, ∼41% of the population is likely to develop cancer during their lifetimes from factors other than radiation exposure.37 This high baseline rate of developing cancer in the absence of radiation exposure poses a challenge in the determination of probability of causation of cancer in an individual.
There is no question that risk:benefit analysis and risk communication are keys to how the public will respond. A reasonable summary risk (for high radiation doses) for an exposed general population has been reported to be 6% per Sv,36 based on the increased excess lifetime cancer risk as reported by the ICRP.34 Given that a single CT examination is associated with a radiation dose of approximately 10 mSv, this corresponds to a 0.06% fatal cancer risk based on the LNT model. A fatal cancer risk of 0.06% means that 99.94% of patients so exposed are not expected to get cancer due to this low radiation dose exposure. The average lifetime risk of dying from cancer in the United States is approximately 21%.37 A CT examination would theoretically add only another 0.06% to the lifetime risk of cancer death, bringing the LNT-based calculated risk to 21.06%. Put this way, the LNT-based risk of cancer due to a CT scan can be seen as miniscule. Importantly, as minute as this purported risk is, since it is an LNT-derived hypothetical estimate, it is in actuality likely much lower, probably nonexistent and most likely inversely correlated. The 10-mSv CT dose is a factor of 10 lower than the average radiation dose of 10 cGy received by the Chernobyl cleanup workers, a dose that caused no observable health effects, as noted previously.
If it turns out that the responses to low radiation doses are more consistent with the hormetic model than the LNT model, there may be no risk at all, and instead there may be a benefit. In this case, the risk:benefit idea would give way to the benefit:benefit paradigm for radiological imaging and adherence to firmly entrenched “as low as is reasonably achievable” regulatory policies would no longer have any validity.
It is of course important to minimize radiological imaging studies that are not clinically warranted, as should be the case for any medical procedure.35 Nevertheless, according to the American Association of Physicists in Medicine, “Risks of medical imaging at effective doses below 50 mSv for single procedures or 100 mSv for multiple procedures over short time periods are too low to be detectable and may be nonexistent.38 Predictions of hypothetical cancer incidence and deaths in patient populations exposed to such low doses are highly speculative and should be discouraged. These predictions are harmful because they lead to sensationalistic articles in the public media that cause some patients and parents to refuse medical imaging procedures, placing them at substantial risk by not receiving the clinical benefits of the prescribed procedures.”

The LNT Model Contradicted by Environmental Protection Agency Policies

Apparently, the carcinogenic risk associated with radiological imaging, as discussed previously, has not been given much weight by the US Environmental Protection Agency (EPA) as provided in their Protection Action Guides (PAG) manual.39 For example, according to the EPA PAG Manual, the decision to shelter-in-place or evacuate should begin at 10 mSv, that is, a dose level corresponding to a single CT scan and an associated hypothetical risk of no more than 0.06%. Given this negligible risk, it is likely that real deaths may occur—not due to radiation exposure but rather due to forced unnecessary evacuations.
It is important to note that although the EPA strongly asserts that LNT is the most suitable basis for assessing radiation risks at low doses, LNT was not used in the setting of its radon mitigation requirements.40 The EPA has set 0.15 Bq L−1 as the action level above, which it recommends that a homeowner take corrective measures to mitigate radon exposure and below which no action is needed. This action level represents a de facto “acceptable” level, as well as a de facto threshold, that presents the same lung cancer risk as having 200 chest X-rays per year (equivalent to an annual dose of 20 mSv). In the EPA’s response to a critique of this policy by Stabin and Siegel,41 EPA noted this action level was not chosen on a health-risk basis, but it was rather driven by technical feasibility, thereby admitting LNT played no role. It would thus be contradictory of EPA policy and therefore need to be so noted, each and every time LNT is applied for any lesser exposures (such as may result from a medical radiological imaging procedure, such as a CT scan); such doses should just be associated with “acceptable risk” or represent a risk that is so low as to be of no concern.


Low-dose radiation exposure (<100-200 mSv) is likely beneficial, not harmful. The LNT model does not account for the body’s response (ie, repair) of any radiation-induced damage and assumes that all outcomes are linear across the range of high- and low-dose exposures; an assumption that is likely false. The use of the LNT model is not conservative and therefore should be abandoned; otherwise, more people may be inadequately diagnosed and treated and perhaps even die unjustifiably should they refuse a needed imaging study. The cause of death would not be radiation, but rather “radiophobia,” due to misguided LNT-driven policies at a cost to tax payers amounting to billions of dollars of wasteful spending. It may be time for radiation protection policies to adopt a different paradigm that would also not compromise public health and safety or the environment. There is a need for national policy discussions. In light of limited health care resources, it is increasingly important that policies serve not only to protect society from real hazards but also be based on realistic projections of the severity and likelihood of risks, as well as on consideration of the actual financial and other costs to patients, radiation workers, and society.


biological effects of ionizing radiation; CT, computed tomography
Environmental Protection Agency
excess relative risk
linear no-threshold
linear threshold
Life Span Study
Protection Action Guides
Radiation Effects Research Foundation
United Nations Scientific Committee on the Effect of Atomic Radiation.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.


The author(s) received no financial support for the research, authorship, and/or publication of this article.


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Published In

Article first published online: March 30, 2015
Issue published: April 2016


  1. radiation carcinogenesis
  2. linear no-threshold model
  3. low-dose radiation exposure risk
  4. CT scans
  5. cancer

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Manuscript received: December 17, 2014
Revision received: February 3, 2015
Manuscript accepted: February 22, 2015
Published online: March 30, 2015
Issue published: April 2016
PubMed: 25824269



Jeffry A. Siegel, PhD
Nuclear Physics Enterprises, Marlton, NJ, USA
James S. Welsh, MS, MD, FACRO
Department of Radiation Oncology, Stritch School of Medicine Loyola University-Chicago, Maywood, IL, USA


James S. Welsh, MS, MD, FACRO, Department of Radiation Oncology, Stritch School of Medicine Loyola University-Chicago, 2160 S 1st Ave, Maguire Center, Rm 2932, Maywood, IL 60153, USA. Email: [email protected]

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