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JACC: CARDIOVASCULAR IMAGING
VOL. 3, NO. 5, 2010
© 2010 BY THE AMERICAN COLLEGE OF CARDIOLOGY FOUNDATION
PUBLISHED BY ELSEVIER INC.
ISSN 1936-878X/$36.00
DOI:10.1016/j.jcmg.2009.11.017
STATE-OF-THE-ART PAPER
Low-Level Ionizing Radiation From Noninvasive
Cardiac Imaging: Can We Extrapolate Estimated
Risks From Epidemiologic Data to the
Clinical Setting?
Warren K. Laskey, MD,* Ludwig E. Feinendegen, MD,†‡ Ronald D. Neumann, MD,§
Vasken Dilsizian, MD储
Albuquerque, New Mexico; Düsselfdorf, Germany; Upton, New York; and Bethesda
and Baltimore, Maryland
Clinical decision-making regarding the use of low-level ionizing radiation for diagnostic and/or therapeutic purposes in patients with cardiovascular disease must, as in all other clinical scenarios, encompass the
broad range of the risk– benefit ratio. Concerns regarding the late carcinogenic effects of exposure to low
levels, i.e., ⬍100 mSv, of ionizing radiation stem from extrapolation of exposure-outcome data in survivors
of World War II atomic bomb explosions. However, ongoing debate regarding the true incremental risk to
subjects exposed to doses currently administered in cardiovascular procedures fails to take into account
the uncertainty of the dose-response relationship in this lower range, as well as tissue-specific reparative
responses, also manifest at lower levels of exposure. The present discussion draws attention to both of
these aspects as they relate to clinical decision-making. (J Am Coll Cardiol Img 2010;3:517–24) © 2010 by
the American College of Cardiology Foundation
Epidemiology, Clinical Decision-Making, and
the Risk–Benefit Ratio
Clinicians are constantly weighing the risk of a
procedure, or treatment, against the benefit. In
deciding on the appropriate recommendation(s), the clinician resorts to the available
“evidence”: that body of information derived
from carefully obtained observations and measurements that themselves have been tested for
their validity and predictive value. When such
evidence is obtained from population-based
observational or rigorous epidemiologic studies,
the conclusions and predictions made on the basis
of such observations will generally apply to an
“average” member of a similar population. The
problem arises when such population-derived
data are then applied to an individual patient.
This classic dilemma of clinical decisionmaking is mitigated, but not obviated, when
*From the Department of Medicine, University of New Mexico School of Medicine, Albuquerque, New Mexico;
†Heinrich-Heine-University Düsseldorf, Düsselfdorf, Germany; ‡Brookhaven National Laboratory, Upton, New York;
§Department of Medical Imaging, Clinical Center, the National Institutes of Health, Bethesda, Maryland; and the
储Department of Diagnostic Radiology and Nuclear Medicine. University of Maryland School of Medicine, Baltimore,
Maryland. This paper represents the opinions of the authors. It does not represent the position of the NIH, DHHS, or
the U.S. Government.
Manuscript received August 11, 2009; revised manuscript received November 3, 2009, accepted November 6, 2009.
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Low-Level Ionizing Radiation
most of the patient’s characteristics match those of
the studied population. However, even under ideal
conditions of complete matching of such characteristics, the predictive probability of an event (outcome) in a given individual will always be characterized by greater uncertainty when compared to
the probability of an event in a large sample (Fig. 1).
Uncertainty in the estimate of risk must be
expressed in conditional probabilistic terms. Distributions for the parameter of interest, e.g., effective
dose (ED), should be explicitly presented as probability density functions. Point estimates and their
associated credible intervals should be reported.
Perhaps the best example of this uncertainty is
demonstrated in the distinction between an “average” subject and a subject with specific characteristics exposed to ionizing radiation. This distinction
is at the heart of the application, or its failure, of
ED at the level of the individual patient, or test.
The ED is, by definition, a calculated (as opposed
to measured) quantity that reflects the “average”
age, “average” gender (realizing there cannot be
such an entity), and “average” relative tissue radiosensitivities (tissue weighting factors) in a
ABBREVIATIONS
given population exposed to a given
AND ACRONYMS
amount of ionizing radiation.
Table 1 summarizes the influence of age
CT ⴝ computed tomography
and gender on the uncertainty in the risk
ED ⴝ effective dose
of cancer-related mortality, as presented in
LNT ⴝ linear no-threshold
the Biologic Effects of Ionizing Radiation
(BEIR) VII report (1). The 2% increase in
risk (relative risk [RR]: 1.02) associated with a dose
of 0.1 Gy differs significantly from the longstanding International Commission for Radiation
Protection– developed overall risk of 5% per Sievert
(2). However, an order of magnitude of error in the
estimation of risk may not be unexpected when
both exposure and risk are “low” and each is
characterized by considerable uncertainty. For the
clinician, the ED (and the associated risk of fatal
cancer) must be viewed in broader terms and should
not be used to assess the risk of any 1 test involving
ionizing radiation or the risk to any 1 patient. The
population-based data discussed earlier must be
interpreted in that light, i.e., as population-based.
Uncertainty in the “true” relationship between absorbed dose and risk at low doses further removes
the concept of ED from a predictable single exposure–single patient context.
If, then, the risk to the individual patient is
uncertain at low levels of ionizing radiation, the
potential benefit of the radiation-based procedure
or treatment must be clear-cut in order to effect
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sound decision-making. Unfortunately, too few
ionizing radiation-based diagnostic or therapeutic
modalities have been subjected to the rigor of
randomized clinical trials. Although few would
argue with a favorable risk– benefit ratio for cardiac
catheterization in the setting of acute ST-segment
elevation myocardial infarction, where the lifesaving benefit of the procedure is immediate, clearcut, and overwhelmingly in favor of the procedure.
At the other end of the clinical spectrum is the
widespread use of computed tomography (CT)
scanning as a screening tool in low- to medium-risk
subjects in the general population. In this instance,
where virtually no data are available pointing to the
benefit of the procedure— either at the individual or
population level—the lack of objective benefit likely
equals (at best) or is less than (at worst) the
population attributable risk of cancer induction. In
“real-world” clinical medicine, where the majority
of risk– benefit decision-making resides in a gray
area, the lack of relevant data, clinical equipoise,
and the level of clinical exigency characterize this
process. The difficulty in predicting risk for fatal
cancer 40 or 50 years following nonsurgical
catheter-based correction of a life-altering congenital heart defect in a child might more properly be
considered in terms of years per life lost, or
disability-adjusted life years. Such approaches are
needed for these gray areas where cancer-related
mortality is, practically speaking, a nonissue, but
morbidity and quality of life are very real, and
immediate, issues for the individual patient. Considering this background, a re-examination of the
basic concepts of the interaction of ionizing radiation with tissue is in order.
The Concept(s) of Dose
Absorbed dose is defined as the amount of energy
associated with ionizing radiation that is deposited
per unit mass (of matter, tissue, etc.). The biological
hazard of ionizing radiation is expressed as the ED
and reflects not only the absorbed dose, but age at
exposure, gender, cellular radiosensitivity, the specific type of radiation and its “biological effectiveness,” the population in which the biological sequelae were ascertained, and the mathematical
relationship between absorbed dose and biological
response. The terms absorbed dose and ED are,
unfortunately, often used interchangeably in the lay
press as well as in the scientific literature. Although
absorbed dose is the appropriate quantity to use for
experimental and epidemiologic analyses of dose-
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response relationships, ED is the appropriate quantity to use for the comparison of an exposure to
ionizing radiation with regulatory dose limits based
on the risks of whole-body exposure (3). The risks,
however, are based on mathematical modeling of
the rates of incident cancers mainly in the survivors
of the atomic bomb explosions as a function of
(inferred) absorbed dose (4,5) and have been the
subject of considerable discussion, if not frank
controversy, at absorbed doses ⬍100 mGy. The
absorbed dose of ionizing radiation for diagnostic
testing in cardiovascular medicine resides at the
lower end of this range and presents the greatest
challenge for meaningful interpretation of the previously noted epidemiologic relationship between
dose and outcome. Thus, careful consideration of
the sources of uncertainty in the assessment of ED
as well as a more critical understanding of the
distinction between absorbed dose and ED is imperative for an informed discussion of the risks
associated with ionizing radiation for diagnostic
purposes (Table 2).
Table 3 summarizes approximate EDs for the
most commonly performed diagnostic and therapeutic studies in cardiovascular medicine. However,
ongoing modifications in acquisition protocols for
multidetector CT coronary angiography will result
in somewhat lower EDs than those reported (6).
Additionally, with current advances in both singlephoton emission tomography and positron emission
tomography instrumentation, diagnostic quality
images can be acquired using nearly 50% of the
doses listed in Table 3.
Comparison of High- Versus Low-Dose Ionizing
Radiation Exposure
All would agree that high values for absorbed doses
of ionizing radiation are harmful and result in acute
illness as well as late consequences, e.g., an elevated
risk of cancer decades after irradiation (7,8). In
contrast, the situation is quite different for short- or
long-term exposures to absorbed doses below about
100 mGy. Not only are acute illnesses absent at this
dose level, but late effects (such as cancer) have not
been observed in populations such as in Japan
following the atom bomb explosions (3,4,9), in
cohorts of nuclear workers (10), or in populations
living in geographic regions with high backgroundlevel radiation exposures (11).
The difficulty in attributing an increased risk of
cancer to low-dose exposure is due, in part, to the
relatively high incidence of nonradiogenic cancer in
Posterior Probability Density
Predictive Probability Density
Figure 1. Probability Density Distributions
The upper panel demonstrates a hypothetical normal (beta) distribution for
the posterior probability of a specific parameter, e.g., the risk of death from
fatal cancer due to exposure to ionizing radiation. Such distributions are
generated from the product of prior probabilities and a Bayes factor, or likelihood ratio, reflecting observed data, e.g., the Life Span Study cohort data.
The lower panel demonstrates the hypothetical distribution for the predictive probability for the next observation. Notice the imprecision (magnitude
of standard deviation) in this quantity, reflecting uncertainty in the mean for
the parameter coupled with uncertainty inherent in a single observation.
industrialized countries as well as to the fact that
ionizing radiation is a weak carcinogen, compared
to many other toxins to which humans are exposed.
Despite the widespread belief that the majority of
cancer-related deaths following the atom bomb
explosions in Hiroshima and Nagasaki were caused
by radiation, only 10% of the 3,350 identified
cancer-related deaths have been attributed to radiation exposure (7). What was a good intention to
protect workers from exposure to ionizing radiation
is beginning to cause widespread radiation phobia.
Even with no increase in cancer recognizable at
Table 1. Estimated Lifetime Attributable Risk of Solid
Cancer-Related Mortality (With 95% Probability Interval)
Mortality (per 100,000 Exposed)
Exposure
Men
Women
0.1 Gy to “general
population”
410 (200, 830)
610 (300, 1,230)
0.1 Gy at age 10 yrs
640 (300, 1,390)
0.1 Gy at age 30 yrs
320 (150, 650)
490 (250, 950)
0.1 Gy at age 50 yrs
290 (140, 600)
420 (210, 810)
1,050 (470, 2,330)
519
520
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Table 2. Nomenclature
Exposure (kerma, k; coulombs/kg): sum energies of charged particles (ions) created by
photons interacting with a defined unit of matter (e.g., air)
Absorbed dose (gray, Gy; joule/kg): amount of energy deposited in unit mass of tissue
Biologic effects of absorbed dose (Sievert, Sv)
Dose equivalent (DE, Sv): (absorbed dose) ⫻ (radiation weighting factor specific for
type of radiation)
Effective dose (ED, Sv): ⌺ (dose equivalent) ⫻ (tissue weighting factor) summed over
whole body
doses below about 100 mSv, many patients seeking
medical help question the rationale of, and risk
from, exposure to doses far below 100 mSv in the
course of diagnostic work-up. They fear cancer may
result from being exposed. Such fears are reenforced by publications such as a recent appraisal
of medical radiation exposure that concluded that
1.5% to 2% of all solid cancers in the U.S. might be
caused by the use of CT for diagnostic testing on a
widespread basis (12).
Only by way of modeling using certain assumptions, such as the linear no-threshold (LNT) hypothesis, can epidemiological data be made to fit
the notion that any amount of radiation absorbed by
the body potentially causes a malignant disease. The
LNT hypothesis is widely accepted, and is the basis
for current radiation protection regulations and
guidelines, as suggested by the International Commission for Radiation Protection (ICRP) for the
purpose of making sure that nobody suffers harm from
exposure to ionizing radiation (13). However, more
recent discoveries on low-dose effects in biological
systems challenge the validity of the model based on
this hypothesis.
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“up-grading” of defenses, called adaptive protection, or radiation hormesis, functions under genetic
guidance against the abundant endogenous (mainly
metabolic) sources of DNA damage. A malignant
process occurs only when cells with unrepaired or
misrepaired DNA damage suffer malignant transformation and exceed the cellular and tissue functions of protection. Therefore, the risk of clinical
cancer induction after low-dose irradiation appears
as the difference between the risk of induced cancer
calculated on the basis of the LNT hypothesis and
prevented cancer from the aforementioned protective mechanisms.
Damage to DNA and Its Repair
The immediate DNA damage and cellular responses to that damage include molecular crosslinks of various kinds, base changes, sugar modifications, single-strand breaks, and the more serious
double-strand breaks (8). It needs be stressed that
the radiation-induced physicochemical damage to
DNA increases linearly with dose. The reason for
this is the particular impact of ionizing radiation in
microdose events in biological tissue. The spectrum
of these microdoses is characteristic for a given type
of radiation. As the radiation energy transfer increases, the number of microdose events increases,
and with them, the number of individual damage
sites caused by each one of the events. A dose effect
curve for chemical DNA damage in tissue actually
conforms to a linear “Impact-Number-Effectiveness
Table 3. Estimated ED (mSv) for Frequently Performed
Diagnostic and Therapeutic Cardiovascular Procedures
LNT Hypothesis Versus Radiation Hormesis
Ionizing radiation primarily perturbs the molecules
in cells in a manner proportional to dose, with
potential damage amplification at higher levels.
Cellular defenses operate at each level, aimed at
scavenging of toxins, repair of damage (especially
that of DNA), and removal of damaged components with replacement of lost elements essential for
maintaining structural and functional integrity of
the organism. Whereas cancer was generally understood to develop from primary and/or secondary
DNA damage through cell transformation and
subsequent stages to clinical malignancy in the face
of rather constant function of defense mechanisms
at the various levels, newer research indicates that
low doses of ionizing radiation can upgrade these
protective mechanisms to operate also against nonradiogenic, i.e., “spontaneous” cancer (14,15). This
Procedure/Radionuclide
201
Thallium (stress–rest)
Dose
(mCi)
ED
(mSv)
3.5
16.9
99m
27.5/10.0
10.7
99m
27.5/10.0
8.6
82
50/50
12.8
13
15/15
2.3
18
10.0
6.4
22.5
5.7
Tc-Sestamibi (stress–rest)
Tc-Tetrofosmin (stress–rest)
Rubidium (stress–rest)
N-ammonia (stress–rest)
F-FDG
99m
Tc-labeled erythrocytes
CXR
MDCT–CA
Invasive–CA
0.1
15.0
7.0
PCI
15.0
RF arrhythmia ablation
15.0
Estimations take into consideration tissue weighting factors from the most
recent International Commission on Radiological Protection publication (Publication 103) for radiopharmaceuticals (28).
CA ⫽ coronary angiogram; CXR ⫽ chest roentgenogram; ED ⫽ effective
dose; FDG ⫽ fluorodeoxyglucose; MDCT ⫽ multidetector computed tomography; PCI ⫽ percutaneous coronary intervention; RF ⫽ radiofrequency; Tc ⫽
technetium.
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Function” without threshold (16). This linear function, however, is not identical in all cell types due to
differing genomic activity. Moreover, secondary
DNA damage may arise in bystander cells and add
to the deviation from linearity.
Within minutes after irradiation, there is a
plethora of DNA and chromatin modification.
Within 24 h after low-dose exposure, doublestrand breaks decrease in number, approaching
that of the background “spontaneous” doublestrand breaks (17). At typical background radiation levels, the probability of a radiation-induced
double-strand break per day per cell is, on average, about 1 in 10,000 (18). The capacity of
normal cells to repair damage to DNA and other
cellular components is genetically determined
and may vary individually. More than 150 genes
have been described in DNA repair at high and
low doses (19,20). Some genes are active only in
low-dose stress responses; others again are modulated only after high doses (20,21). These data
contradict a fundamental assumption of the LNT
hypothesis for assessing long-term health detri-
ment solely as function of dose. Moreover, lowdose irradiated confluent cells in vitro appear to
stall DNA repair until cell proliferation begins
again (17). Indeed, an immediate induction of
DNA repair has been detected in proliferating
cells at low doses of about 1 mGy of X- and
gamma radiation (21,22). In general, then, initial
nonlethal radiation damage is answered in normal
individuals by immediate attempts at structural
reconstitution with regained functional homeostasis. Radiation effects involving DNA are
ultimately determined by the final extent of DNA
damage with sequence mutations and the protective response by the organism. Multiple malfunctioning genes or gene cassettes are required for
cancer induction, invasion, and metastases to
occur.
Figure 2 shows, as a function of dose, the 2
opposing effects: the risk of developing cancer and
the degree of adaptive protection against cancer,
with the baseline showing the level of lifetime
nonradiation-induced cancer that is observed in
industrialized countries. Whereas the degree of
Dual Responses After Single Low-Doses
Up-Regulation of Defenses
Cancer at Constant Defenses
Risk of Cancer Induction
Adaptive Protection
Summary of Data
Papf (D; tp1)
Pind
0
Pspo
0
0.05
0.1
0.15
0.2
0.25
0.3
Single Dose (Gy)
Figure 2. Schematic Representation of the Dual Response to Single Low Doses
Low doses of ionizing radiation can up-regulate physiological defenses with delay with some lasting beyond a year. The up-regulated
defenses are also called adaptive protections and depend on dose D and on the time tp of their action: the probability of protection
ranges from 0 to 1 and is Pap f (D; tp). The risk of radiation-induced cancer assumes constant defenses in the body at every dose D
according to the linear no-threshold hypothesis and is expressed here by the value of Pind D. Both probabilities have uncertainties at
low-dose levels shown by light dotted lines: for cancer induction due to bystander effects, genomic instability, induction of repair; for
adaptive protections due to individual degrees of cellular responses. The risk of cancer following a single low-dose exposure, therefore,
would at every dose level be the difference between radiogenic cancer risk and the prevented cancer risk, with the latter being the
product of the degree of protection and the value of the spontaneous cancer risk. Pind D ⫽ radiation induced lethal cancer with
constant defenses in the system, from a single dose D, Pap f (D; tp) ⫽ adaptive protection (0 to 1) in the system as function of D
and time of effectiveness tp, Pspo ⫽ “spontaneous” life time cancer risk of the exposed individual, in the industrialized world.
Adapted from data in Tubiana et al. (21).
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Table 4. Lifetime Attributable Risk for Exposure-Related Mortality From
Solid Cancers
Excess deaths from
exposure to 0.1 Gy
Number of deaths in the
absence of exposure
Men, per 100,000
Exposed (95%
Credible Interval)
Women, per 100,00
Exposed (95%
Credible Interval)
410 (200, 830)
610 (300, 1200)
22,100
17,500
protection according to experimental observations
rises with increasing doses to a maximum at about
100 mGy and then falls toward 0 (23), the cancer
risk is given to rise linearly with dose if one assumes
that existing protections against cancer are also
constant at low doses in the exposed system. The
latter approach conforms to the LNT hypothesis.
The figure also includes detrimental bystander effects and consequences for cancer risk in the lowdose range and also acknowledges immediate repair
induction, as discussed earlier.
Calculations presented elsewhere show that a
very small degree of increased protection, in the
region of 2% of lifetime cancer risk, might be
sufficient to fully balance the assumed cancer risk at
100 mGy, based on the LNT hypothesis. Ongoing,
and unresolved, controversy in the literature regarding the differential risk of high- and low-dose
ionizing radiation (24,25) has given rise to the
hypothesis that long-term, low doses of ionizing
radiation may actually be beneficial and may amplify or stimulate repair mechanisms that protect
against disease (21,23,26).
Uncertainty in the Measurements Themselves
Starting from classic epidemiologic studies and
progressing through extensive experimental data,
it is clear that the probability of harm, expressed
as ED, is related in a complex fashion to the type
of radiation, the value of absorbed dose (and dose
rate), and tissue radiosensitivity. Confining the
clinician’s concerns to the absorbed dose encountered in medical diagnostic imaging simplifies
things somewhat but does not avoid dependence
on many assumptions. Although exposure (in
Roentgen or air kerma) is directly translatable to
dose (Gy) for X-rays and gamma rays, the measure of the overall probability of harm is a
function of (organ) dose conversion coefficients as
well as tissue weighting factors. The former
speaks to geometrical considerations and the
spatial relationship of the exposed tissue and the
primary radiation field, whereas the latter speaks
to the radiosensitivity of the irradiated tissue
itself. Thus, it is not surprising to see uncertainties in the estimation of individual organ EDs
ranging from 20% to 50% and that for a “representative” subject approaching 40%. An in-depth
discussion of the assumptions and sources of error
in the estimation of ED is available elsewhere
(27–29). However, several clinically relevant caveats must be emphasized. Among these are the
issues of single exposure versus multiple exposures (with a corollary being the influence of
exposure rate), uniform exposure versus more
localized (heterogeneous) exposure, and the application of atomic bomb survivor– derived risk
data to the individual patient undergoing diagnostic testing.
Coupled with these uncertainties in dose is the
relationship of dose to risk. Ignoring for a moment the true shape of the population probability
distribution for survival, the LNT relationship
posits: 1) no “safe” dose; and 2) a finite, lifelong
risk for “low” doses, i.e., ⬍100 mSv. It must be
pointed out, however, that the BEIR VII conclusions in this regard may only be meaningful when
a normal individual, belonging to a population of
100,000 individuals with an age distribution similar to the U.S. population, is exposed to a single
100 mGy dose. Once again, because risk is a
probabilistic concept, it must be expressed by a
distribution, or density, with a mean value and an
expression of uncertainty: the standard deviation.
The uncertainty in the estimate of risk when
added to the uncertainty inherent in fitting (stochastic) data even to an assumed linear relationship properly lends itself to a Bayesian approach.
For the clinician, the outcome of such a process is
itself uncertain. Thus, it comes as no surprise that
the credibility intervals for lifetime attributable
cancer risk, as presented in the BEIR VII report,
are wide (Table 4). Finally, although the LNT
relationship posits a linear relationship between
Table 5. Selected Relevant Exposures Found in Daily Living
Exposure
Trans-Atlantic airline flight
Average Individual
Effective Dose (mSv)
0.1
Screening mammogram
3
Background “natural” radiation
3/yr
Dose over 70 yrs in Chernobyl
14
Radiation worker exposure limit
20/yr
Exposure on international space station
170/yr
Atom bomb survivors
200
Nuclear workers
20
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risk and dose at low exposure, i.e., ⬍100 mSv, the
“true” nature of this relationship in this lower
ranges of radiation that are common for medical
uses of ionizing radiation (Table 3, diagnostic or
diagnostic/therapeutic exposure) is unknown, and
it may well display nonlinearities due to the
damage-limiting protective mechanisms discussed earlier.
Conclusions
The clinician must understand that the prediction
of risk of a subsequent malignancy for an individual
undergoing a medical diagnostic test, or procedure,
employing ionizing radiation is a complex, uncertain exercise. As with any risk calculation, “average”
risks obtained from population-based studies are of
little value for the individual. Population-based data
must be weighted, or adjusted, for important clinical variables known to be associated with the risk of
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Key Words: radiation y imaging
y risk.