Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 409
Appendix F Ionizing Radiation Exposure to the U.S. Population, with a Focus on Radiation from Medical Imaging 1 Rebecca Smith-Bindman, M.D. University of California, San Francisco School of Medicine DEFINITION OF IONIZING RADIATION AND UNITS Radiation is energy in the form of high-speed particles and electromag- netic waves. Radiation from electromagnetic waves is characterized by the wavelength and the amount of energy they transfer. In general, the shorter the wavelength, the greater the energy of the radiation, and the greater the potential for biological damage. The types of electromagnetic radiation and examples of sources of this radiation are shown in Figure F-1. Ionizing Radiation Radiation with enough energy to remove tightly bound electrons from their orbits (and enough energy to break chemical bonds) is called ionizing radiation (reflected by wave lengths to the right in Figure F-1, shown for electromagnetic radiation, including ultraviolet waves, X-rays and gamma rays). Wavelengths to the left of Figure F-1 (i.e., microwaves, radio waves, and low-frequency cell phone waves, which are extremely low frequency and energy) do not have this amount of energy and cannot break chemical bonds and are non-ionizing radiation. This does not confirm that they are safe, just that they do not cause biological damage through the mecha- nism of breaking chemical bonds. There are three main kinds of ionizing 1 The responsibility for the content of this article rests with the author and does not neces- sarily represent the views of the Institute of Medicine or its committees and convening bodies. 409
OCR for page 410
410 BREAST CANCER AND THE ENVIRONMENT FIGURE F-1 Energy spectrum of radiation. SOURCE: NASA (http://mynasadata.larc.nasa.gov/images/EM_Spectrum3-new.jpg). Figure F-1 800 px-EM_Spectrum3-new.eps bitmap, landscape radiation: alpha and beta particles (not electromagnetic), gamma rays, and X-rays. There are many different naturally occurring sources of radiation, and radiation is used in many areas of industry and medicine. A few typical doses (exposure levels) and impacts of radiation are shown in Figure F-2. Ionizing Radiation Used in Medical Imaging Ionizing radiation used in medical imaging includes gamma rays and X-rays. Gamma rays are delivered through nuclear medicine examinations, when a small amount of radioactive material is inhaled, injected, or swal- lowed by a patient, and the resulting gamma waves that are emitted by the radio-pharmaceutical from within the patient are detected. A variety of imaging tests use X-ray technology, including radiographs (also known as conventional X-rays, plain films, and sometimes just X-rays for short even though each of these sources use X-rays), fluoroscopy, angiography, and computed tomography (CT). Ultrasound and magnetic resonance imaging utilize ultrasound waves and magnetic waves respectively, and neither deliv- ers ionizing radiation.
OCR for page 411
FIGURE F-2 Sample doses of and exposures to ionizing radiation. 411 Figure F-2.eps bitmap, landscape
OCR for page 412
412 BREAST CANCER AND THE ENVIRONMENT Biological Effect of Ionizing Radiation Ionizing radiation passes through air and will deposit energy into the tissue that absorbs it. Ionizing radiation deposits a relatively large amount of energy into a small area, and damage caused by the radiation varies with the dose. At low doses, cells repair the damage with no lasting effects. At moderate doses, cells can be changed permanently, leading to cancer or other abnormalities such as birth defects. At high doses, such as those delivered through radiation treatment for cancer or following the immedi- ate effect of the atomic bombs dropped on Japan, tissues fail to function, severe burns result, and people who are exposed at these levels may die. Predictability of Response to Ionizing Radiation The severity of responses to high-dose radiation (generally considered a dose above 1 sievert, Sv) increases directly in proportion to the dose. There is generally a threshold for damage from the radiation: below a certain level the damage will not occur, and above the threshold, the higher the dose, the more extensive and severe the injury. These responses tend to be predict- able, and are termed deterministic. Many of the earlier radiology pioneers developed erythema, burns, and radiation sickness from their exposures, as did individuals who lived near the atomic bomb explosions, and these are deterministic effects. At lower doses of radiation, generally below 1 Sv, the effect of the radiation is much less predictable, and no clear threshold exists. There is a chance that a person will experience an adverse outcome if exposed to the radiation, but it is not certain, and while the probability increases with increasing exposure, the severity may not. These effects tend to be all-or-none effects (either a cancer occurs or it does not). These effects are called stochastic effects. The types of effects included in this group are carcinogenesis and birth defects. Mechanism of Carcinogenesis The mechanism through which radiation exposure can lead to cancer is outside the scope of this review. However, carcinogenesis is believed to be multifactorial. Patient-related vulnerabilities are important, and a few patient groups have been identified who are particularly vulnerable to radiation-related carcinogenesis. Ionizing radiation has sufficient energy to break chemical bonds, can cause DNA damage, and therefore can con- tribute to how cancer may occur, but it is thought to act through various mechanisms rather than a single effect. Radiation can initiate gene muta- tions, promote the number of premalignant cells, and alter DNA repair.
OCR for page 413
413 APPENDIX F There are believed to be important differences in cancer risks by age, almost certainly reflecting some of these differences. Radiation Measurements Several commonly used radiation measurements are described below, and the measures used in subsequent discussion are summarized in Table F-1. The roentgen (R) describes the intensity of a beam of X-rays or gamma rays and the ionization of atoms in air as radiation passes through space. The roentgen also is the unit used in the calibration of X-ray generating equipment (CE Essentials, 2011). The radiation absorbed dose (rad) describes radiation in a medium other than air. As ionizing radiation passes through matter (e.g., human tis- sue) it imparts energy into the medium ionizing it. One rad is equivalent to 100 ergs of energy absorbed in a gram of material (tissue). The comparable SI unit (International System of Units, adopted by nearly all countries) is the gray (Gy), which is expressed as joules per kilogram (1 Gy = 100 rad). The measure of rad or Gy describes the absorption of ionizing radiation in matter and is related to the biological damage in tissue; the greater the amount of energy transferred to tissue by ionizing radiation, the higher the rad or gray and the greater the biological damage (CE Essentials, 2011). There are different types of radiation (e.g., X-rays, particle radiation), and these are associated with different amounts of energy and potential to cause biological damage; this variation in effect is attributed to the linear energy transfer (LET), which has to do with the type of radiation and the different biological effect on the tissue. Thus, while rads or grays measure the physical aspects of the energy, they do not reference the biological effect of various types of ionizing radiations and are not generally used as TABLE F-1 Selected Units of Ionizing Radiation (measurements in bold are used in this summary) Measurement Description RAD / Gray (=100 rad) Radiation in tissue REM / Sievert (=100 rem) Radiation in tissue, accounting for biologic sensitivity of tissue Effective dose Full body equivalent dose equal to a partial anatomic area radiation EUS Average effective dose per individual in the U.S. population, whether exposed to the specific exposure or not EExp Average effective dose to an individual in a group exposed to that source of radiation
OCR for page 414
414 BREAST CANCER AND THE ENVIRONMENT measures of exposure. The sievert (Sv) is the SI unit of dose that is used as a measure of exposure, as it attempts to reflect the biological effects of radiation. It is also measured in joules/kilogram (as is the gray), but it incor- porates the biological effectiveness of different types of ionizing radiation in different types of tissues. For a given amount of radiation (measured in grays), the biological effect (measured in sieverts) can vary considerably as a result of the radiation-weighting factor (WR). The roentgen equivalent man (rem) is the older unit of equivalent dose, and 1 Sv = 100 rem. Rem remains the unit most widely used for occupational exposure. Radiation exposures from medical imaging are rarely uniform—usually one area of the body is exposed much more than another (compare the tis- sue exposed to radiation from a mammogram to the tissue exposed for a head CT). This is very different from naturally occurring radiation, which often is more equally distributed across the body. To compare the radiation doses associated with different types of exposures, it would be most accu- rate to compare organ-specific exposures from different types of examina- tions. For example, comparison of the dose to the lungs from a chest X-ray and a chest CT would likely reflect the most accurate information regarding the potential for these two types of tests to cause harm. However, this is extremely impractical, as it would require creating a complex matrix of organ-specific doses for each medical procedure. This would make it dif- ficult to compare different exposures, as some types of exposures involve partial-body irradiation, others full-body irradiation, and it makes it hard to compare overall exposures in this way. In order to compare radiation doses to different body parts on an equivalent basis, it would be helpful to have a single metric that could be used to compare all radiation doses (even though this is imprecise as the mammogram is truly best summarized as a breast dose and a head CT a brain dose). The effective dose (E) is a metric for estimating a full-body dose that would be equivalent to an individual organ dose. It is estimated by calculating a weighted average of the doses (equivalent dose) to different organ systems. Thus, a large dose to a single organ might be similar (with respect to the stochastic cancer risks) to a smaller dose to the entire body. The weighting factors used to make these calculations reflect the different radio sensitivities of the tissues. Because of the ease of comparison, effective dose is an extremely useful measure of radiation exposure and will be the primary metric used in this summary. The measurement of radiation emitted by radioisotopes used in nuclear medicine and positron emission tomography (PET) imaging, is the curie (Ci), which describes a quantity of radioactive material that disintegrates per second (CE Essentials, 2011). Decay or disintegration is a process by which a radioactive nucleus changes to another type of atomic nucleus. The SI unit of radioactivity is the becquerel (Bq). The becquerel is the activity of
OCR for page 415
415 APPENDIX F a quantity of radioactive material in which one nucleus decays per second. The curie is an older, non-SI unit of radioactivity equal to the activity of 1 gram of radium-226. Measurement of Absorbed Dose, Radiation Detriment, and Impact of Individual Factors on Radiation Detriment The amount of radiation absorbed into the body, and the resulting doses to different parts of the body and organs, will depend on the person’s sex and size (including relative amounts of different tissues). Compared with an adult, a child exposed to a particular radiation dose will absorb more per unit of tissue, as there is less organ volume in which the radiation can dissipate. For example, compare a teaspoon of red dye added to a cup of water as compared with a gallon of water—the dye in the gallon of water will become much more dilute. The radiation detriment will relate both to the absorbed dose and to the type of tissue that has been irradiated, as some organs are much more vulnerable to the effects of radiation than other organs. A complete comparison of different sources of radiation exposure would try to estimate exposures to different organ systems and how this varies by age of exposure (as both will influence the detriment), but this level of detail would make it nearly impossible to provide an overview. Thus to keep the summary as simple as possible, I will use primarily the mea- surement of effective dose to describe the U.S. population’s exposures to radiation, variation within and across different imaging tests in the delivery of radiation, and radiation detriment. Metrics of Population Exposure The most useful metric to compare the population’s radiation expo- sure from different sources is the average exposure, measured in effective dose, per individual in the entire population. It is calculated by dividing the cumulative dose to the population by the number of individuals in the population (EUS) and does not consider whether an individual person is exposed or not. As an example, television (TV) exposes individuals to a small amount of ionizing radiation, and the average exposure from TV would be calculated by dividing the total radiation delivered by all hours of TV watched in the United States by the number of individuals in the United States. This will be an estimate (as individuals watch different amounts of TV), but it is useful for comparing average exposure to ionizing radiation from TV and other sources, such as the sun or radon. In contrast, certain types of radiation are received by a much smaller group of individuals, such as occurs with occupational exposures. For these exposures it is more reasonable to calculate the average dose to individuals exposed to that
OCR for page 416
416 BREAST CANCER AND THE ENVIRONMENT source of radiation, rather than compute an overall effective dose for the population. This measurement, effective dose to those exposed (EExp), is calculated by dividing the cumulative dose to the individuals exposed by the number of individuals exposed. Both metrics will be used to describe population exposure. WHAT IS KNOWN ABOUT CARCINOGENICITY OF IONIZING RADIATION Ionizing radiation is widely used in industry and medicine, occurs in many different natural sources, and presents a health hazard. It causes microscopic damage to living tissue, and this results in elevated risks of cancer and birth defects at low exposures, and more substantial biological damage, including burns, radiation sickness and death, at higher exposures. Radiation is one of the most heavily studied carcinogens, and exten- sive epidemiological and biological evidence supports the association of low and moderate doses of ionizing radiation with increased cancer risk. The epidemiological evidence of an increased risk of cancer comes from (1) cancer development among survivors of environmental and accidental exposures to radiation (i.e., survivors of atomic bombs, Chernobyl, and Soviet Union and United States weapons testing) (Pierce and Preston, 1993, 2000; Land, 1995; Ron et al., 1995b; NRC, 1996, 2003, 2006; Charles, 2001; Brenner et al., 2003; Preston et al., 2003, 2007; Preston, 2008); (2) populations medically irradiated for benign conditions such as scoliosis, tinea capitis, and tuberculosis (Ron et al., 1995a; Little, 2001; Modan et al., 2000; Ron, 2003); (3) patients receiving radiotherapy for malignant disease (Little, 2001; Neglia et al., 2001, 2006; Ron, 2003; Sachs and Benner, 2005; Sigurdson et al., 2005; Bassal et al., 2006; Ronckers et al., 2006); and (4) those who have received occupational exposures, including radiologists, radiological technologists, and nuclear power workers (Lewis, 1963; Matanoski et al., 1975; Muirhead et al., 1999, 2009; Berrington et al., 2001; Cardis et al., 2007; Linet et al., 2010). All of these groups received doses in the range of that delivered by current medical imaging and have been shown to be at increased risk of developing cancer. Evidence of radiation-induced cancer is strongest for leukemia, but an increased risk of all solid cancer types (e.g., breast, lung, colon) has been associated with exposure to doses of ionizing radiation in the same range as that delivered by medical imaging. A full discussion of the data on the risks of ionizing radiation is outside the scope of the review; however, a comprehensive review of the published literature can be found in the report of the National Research Council, Biological Effects of Ionizing Radiation (BEIR) Subcommittee (BEIR VII; NRC, 2006). According to the BEIR subcommittee, the most accurate
OCR for page 417
417 APPENDIX F current model of radiation carcinogenesis at low to moderate doses is the linear and nonthreshold model, which predicts that the risk of outcomes (primarily cancer) is directly proportional to the radiation dose received, is additive, and does not respect a minimum-risk threshold. This model assumes there is no safe level of radiation exposure. This theory is the basis for radiation protection recommendations by national and international committees tasked with ensuring radiation protection of workers and the general population (NRC, 1996; Charles, 2001; Gonzalez et al., 2007; NCRP, 2009). While this theory is widely endorsed within the radiation safety and protection communities, it is challenged by some who believe there is a threshold below which there is no cancer risk (Strzelczyk et al., 2007). Its important to emphasize that this theory is far less relevant for understanding the detrimental effects of radiation from many exposures, such as CT, where directly observed evidence shows that radiation doses delivered to patients in the range of CT are carcinogenic. The model is most helpful to understand the carcinogenicity of very low exposures that are below those that have been studied in epidemiological studies. A number of different mathematical models have been developed to estimate the cancer risks associated with exposure to ionizing radiation across a range of doses. The dominant model that has been most widely adopted was used by National Academy of Sciences in the BEIR VII report (NRC, 2006). There are a large number of assumptions in this model, among them that the risk of solid cancer is linear and follows a non- threshold model, and that the patterns of cancer outcomes among Japanese atomic bomb survivors are directly transferable to the U.S. population. The impact of these assumptions is often taken into account with creation of uncertainty limits around estimated risks. SOURCES OF IONIZING RADIATION EXPOSURE TO THE U.S. POPULATION The National Council on Radiation Protection and Measurements (NCRP, 2011) is a nongovernmental, not-for-profit corporation chartered by Congress to collect, analyze, develop, and disseminate to the public information and recommendations about radiation, radiation protection, and radiation measurements. The NCRP published two reports detailing the U.S. population’s exposure to ionizing radiation in two time periods; Report No. 93 was published in 1987 (NCRP, 1987b), and Report No. 160 was published in 2009 as an update to this earlier report and describes exposures through 2006 (NCRP, 2009). These two reports are comprehen- sive, and each reviewed hundreds of different data sources and references. They provide the most accurate overview of the magnitude of the U.S. population’s exposure to radiation and the distribution of exposure among
OCR for page 418
418 BREAST CANCER AND THE ENVIRONMENT the various sources of radiation. Data from these two reports have been summarized to highlight current exposures, sources that deliver high radia- tion exposures, and sources that have changed over time. Radiation from medical imaging is a large and growing source of radiation exposure to the U.S. population. I have led several analyses that describe medical imaging and associated radiation exposure within a large cohort of patients (approximately 2.5 million) enrolled across six integrated health plans in the United States (Burger et al., 2010a,b). These health plans participate in the Health Maintenance Organization (HMO) Research Network, and the National Cancer Institute (NCI)-funded Cancer Research Network (CRN), and as such, they have common data elements to permit assessing medical imaging within the HMO setting. The work was used to supplement the NCRP reports and to further characterize the U.S. population’s exposure to radiation from medical imaging. We had more detailed data on medical imaging at the patient (rather than population) level, allowing more accurate estimates of individual doses and the propor- tion of patients who exceed certain threshold doses. Sources of Radiation Radiation exposure is described within five broad categories: (1) ubiq- uitous background radiation, sometimes described as natural sources of radiation; (2) radiation from medical procedures; (3) radiation from con- sumer products or activities involving radiation sources; (4) radiation from industrial, security, medical, education and research activities; and (5) occu- pational exposure (see Table F-2). Ubiquitous Background Radiation There are four primary sources of radiation exposure that fall in this category: (1) external exposure from the sun and cosmic rays (space radi- ation); (2) external exposure emitted from the earth (terrestrial radia- tion, primarily from potassium, uranium, and thorium in surface soil and rocks); (3) internal exposure from inhaled radon (released from the earth); and (4) internal exposure from radionuclides in the body (particularly potassium). Exposure to radon is the largest contributor to this category, accounting for nearly 75 percent of ubiquitous background radiation. Radon gas comes from the breakdown of uranium in soil, rock, and water, and it is trapped in houses and inhaled.
OCR for page 419
419 APPENDIX F TABLE F-2 Summary of U.S. Population’s Annual Exposure to Ionizing Radiation from Different Sources, 2006–2010 Radiation Source EUS (mSv) EExp (mSv) Ubiquitous background radiation 3.11 — Radon and thoron (inhalation) 2.28 Space 0.33 Ingestion 0.29 Terrestrial 0.21 Medical radiation 3.00 7.8 Computed tomography 1.47 5.1 Nuclear medicine 0.77 0.61 Interventional radiology 0.43 1.14 Conventional X-rays* 0.33 0.68 Consumer 0.13 Industrial, security, research, education 0.003 Occupational 0.005 1.1 Medical 0.8 Aviation 3.1 Nuclear power 1.9 Industry and commerce 0.8 Education and research 0.7 Government, Department of Energy, military 0.6 TOTAL 6.2 NOTE: These numbers have been adapted from NCRP (2009) and from our research of ra- diation exposure across six integrated health care systems that participate in the NCI funded Cancer Research Network (calculations of EExp, medical imaging) (Burger et al., 2010a,b). *Includes mammography. SOURCES: NCRP (2009, p. 242–243; used with permission of the National Council on Ra- diation Protection and Measurements, http://NCRPpublications.org); Burger et al. (2010a,b). Medical Exposure to Radiation Radiation used for medical imaging Most medical imaging tests—including radiography, fluoroscopy, angiography, and CT (all utilize X-rays), and nuclear medicine (utilizes gamma rays)—expose patients to ionizing radia- tion. In any given year, between 30 and 40 percent of the U.S. population will undergo one or more imaging tests that deliver radiation, varying by age and sex, and this has increased only slightly over time (Burger et al., 2010a,b). Numerically, conventional radiographs contribute the great- est number of imaging tests (58 percent), followed by CT (12 percent), and fluoroscopy, angiography, and nuclear medicine (2–5 percent each). However, because the doses are so much higher for CT, it contributes the majority (nearly 70 percent) of patients’ exposure to radiation from medi- cal imaging (NCRP, 2009; Burger et al., 2010a,b). Currently, the average exposure to radiation from medical imaging is around 3 mSv per year
OCR for page 434
434 BREAST CANCER AND THE ENVIRONMENT that have estimated the number of future cancers that would expected to result from ionizing radiation associated with current levels of medical imaging. These analyses have estimated future cancers that would result from exposure to conventional radiographs (Berrington de Gonzalez and Darby, 2004), CT (Berrington de Gonzalez et al., 2009), and myocardial perfu- sion scanning (the most common type of nuclear medicine examination) (Berrington de Gonzalez et al., 2010). Combined, these exposures would account for approximately 80 percent of the U.S. population’s cumulative annual exposure to radiation from medical imaging. These previously published results have been updated by Dr. Berrington de Gonzalez for this report to focus specifically on future breast cancers, taking into account the increase in imaging rates since these papers were published, and including cancer risks associated with the additional imag- ing examinations not covered in these prior reports. These calculations were based on estimates of the number of imaging tests conducted annually, the age distribution of patients undergoing those tests, radiation delivered by those tests, organ-specific doses, and models of carcinogenesis, including the biological effectiveness of the radiation, underlying cancer risks of the population, lag time between exposure and cancer induction, and mortality in the population undergoing imaging. The major sources of information used in each of these analyses are clearly outlined in the primary manu- scripts. For CT, which is the largest contributor to radiation dose, each of the major assumptions used to generate the estimates was varied in the model to generate an estimate of the uncertainty limits. Each of the papers is summarized below. Cancers Associated with Radiography (Berrington de Gonzalez and Darby, 2004) Dr. Berrington de Gonzalez’s original analysis estimated the risk of cancer from conventional X-rays in the United Kingdom and 13 other developed countries. The authors combined data on the frequency of X-rays (including mammography), estimated organ-specific radiation doses from each type of X-ray, and used cancer risk models for each organ system that were based on the Japanese atomic bomb survivor data, and combined these with population-based cancer incidence rates. The authors estimate that in the United Kingdom about 0.6 percent of the cumulative risk of cancer to age 75 years could be attributable to diagnostic X-rays. This percentage is equivalent to about 700 cases of cancer per year. In the 13 other countries, estimates of the attributable risk ranged from 0.6 percent to 1.8 percent; whereas in Japan, which had the highest estimated annual exposure level in the world, it was more than 3 percent.
OCR for page 435
435 APPENDIX F The model developed for the 2004 paper was updated for this Insti- tute of Medicine summary to estimate breast cancers that would result from conventional radiographs conducted in the United States in 2006. This involved updating assumptions regarding the number of conventional radiographs conducted in the United States in 2006 (Mettler et al., 2009) (overall increase from 960 to 1,080 tests /1,000 patients/year), and adapting the results for the 14 countries included in the original publication to cancer incidence rates in the United States. Based on these analyses, Dr. Berrington de Gonzales has estimated that 250 breast cancers would result from conventional X-ray use in the United States in 2006, and that the number would be likely to increase to 280 with imaging rates observed in 2010. Cancers Associated with CT (Berrington de Gonzalez et al., 2009) Berrington de Gonzalez et al. (2009) estimated the frequency of dif- ferent types of CT scans performed in the United States in 2007 using a combination of data sources, primarily Medicare claims data and the IMV Medical Information Division survey of CT scan use in 2,451 U.S. facilities in 2007. Radiation-related cancer risks depend on sex and age at exposure, and the authors estimated the age and sex distribution for each CT scan type using a large national commercial insurance database. These estimates were scaled to be applicable to the age–sex distribution of the U.S. popula- tion and combined with the national frequency estimates. The authors used risk models based on the National Research Council’s BEIR VII report (NRC, 2006) with minor modifications, and they developed additional models for anatomic sites that were not covered in the BEIR VII report. An important assumption in the estimation of lifetime radiation-related cancer risk is the life expectancy of persons receiving CT scans. There is a lag between radiation exposure and cancer diagnosis (which can be as short as 2 years for leukemia and 10 years for brain cancer [Preston et al., 2007]), and patients who are unlikely to survive that long are unlikely to develop imaging-related cancer. To address the problem of survival, the authors used the commercial insurance data set to estimate the proportion of scans performed in patients who were unlikely to survive long enough to develop cancer. Scans performed in cancer patients were also omitted, as consideration of second cancers was outside the scope of their analysis. The estimated mean number of radiation-related incident cancers, with 95 percent uncertainty limits (UL), were calculated using Monte Carlo simulation. Uncertainty intervals were estimated to account for statistical uncertainties in the risk parameters, uncertainties in the dose rate reduction effectiveness factor, and differences in application of risks from the Japanese to the U.S. population. Overall, the authors estimated that approximately 29,000 future can-
OCR for page 436
436 BREAST CANCER AND THE ENVIRONMENT cers (95% UL, 15,000–45,000) could be related to CT scans performed in the United States in 2007. The largest contributions were from scans of the abdomen and pelvis (n = 14,000) (95% UL, 6,900–25,000), chest (n = 4,100) (95% UL, 1,900–8,100), and head (n = 4,000) (95% UL, 1,100–8,700), as well as from chest CT angiography (n = 2,700) (95% UL, 1,300–5,000). Approximately one-third of the projected cancers were from scans performed on patients between the ages of 35 and 54 years, whereas only 15 percent were from scans performed on patients under the age of 18 years. This is important, as it is widely believed that cancer risks are only of concern in children; however, because imaging with CT increases so much with increasing age, cancers that result from radiation from the more frequent medical imaging that occurs in middle age are actually more numerous. Further, Berrrington de Gonzalez’s models assumed that the risks of cancer per exposure decline with advancing age. However, several recent analyses have suggested that risks might even increase with exposures at older ages (Preston et al., 2007; Shuryak et al., 2010), making the estimates presented here highly conservative (i.e., the true risks may be higher than these analyses suggest). The breakdown by cancer site showed that lung cancer was the most common projected radiation-related cancer (n = 6,200) (95% UL, 2,300– 13,000), followed by colon cancer (n = 3,500) (95% UL, 1,000–6,800) and leukemia (n = 2,800) (95% UL, 800–4,800) (Figure F-6). The cancer sites with the highest risks were common cancers with a high frequency of exposure to that organ (e.g., colon from CT of the abdomen and pelvis and lung from CT of the chest) or higher radiosensitivity (e.g., red bone marrow and leukemia). The projected radiation-related cancers would be spread out over many decades. However, if CT scan use remains at the current level or increases further, then the results of the Berrington de Gonzalez analyses suggest that eventually 29,000 (95% UL, 15,000–45,000) cancers every year could be related to past CT scan use. This is equivalent to approxi- mately 2 percent (1–3 percent) of the 1.4 million cancers that are diagnosed annually in the United States being attributable to the prior use of CT. Using very slight modification of these methods, Dr. Berrington de Gonzalez estimates that 1,800 future breast cancers could result from CT utilization in 2007. Cancers Associated with Cardiac Nuclear Medicine Imaging (Berrington de Gonzalez et al., 2010) Nuclear cardiac perfusion tests are used in the assessment of coronary artery disease, and they represent the second largest source of medical radiation exposure in the United States. It is estimated that 85 percent of radiation exposure from nuclear medicine procedures is accounted for from
OCR for page 437
437 APPENDIX F Number of future cancers FIGURE F-6 Projected number of future cancers (mean and 95% uncertainty lim- its) that could be related to CT scan use in the United States in 2007, according to cancer type. SOURCE: Berrington de Gonzalez et al. (2009, p. E1). Reprinted with permis- sion from Berrington de Gonzalez, A., M. Mahesh, K. P. Kim, M. Bhargavan, R. Lewis, F. Mettler, and C. Land. 2009. Projected cancer risks from computed tomographic scans performed in the United States in 2007. Arch Intern Med 169(22):2071–2077. Figure F-6 Future cancers.eps bitmap, type so small, suggest redraw these types of examinations. As described above, Berrington de Gonzalez and colleagues (2010) estimated future cancer risks that would result from the cardiac perfusion scans conducted in 2007. Combination of cancer risk estimates with data on frequency of use suggested that the 9.1 mil- lion annual cardiac perfusion tests in the United States could result in 8,100 (3,700–15,200) additional future cancers, assuming use of median radionuclide activity. If the tests were performed at the lowest or highest recommended activity levels, risks would be reduced or increased by about 20 percent. If the levels of use remain similar in the future, the estimates suggest that, eventually, approximately 0.6 percent (0.3–1.1 percent) of the 1.4 million cancers diagnosed annually in the United States could be related to these studies.
OCR for page 438
438 BREAST CANCER AND THE ENVIRONMENT TABLE F-5 Estimated Number of Future Breast Cancers That Might Occur Related to a Single Year of Medical Radiation Exposure Source of Medical Radiation Estimated Number of Cancers CT scans 1,800 Conventional radiography 280 Nuclear medicine 150 Other 560 All sources 2,800 (UL, 2,000–3,500) Using very slight modification of these methods, Dr. Berrington de Gonzalez estimates that 150 future breast cancers could result from nuclear medicine utilization in 2007. Summary of Future Breast Cancers from Medical Imaging Berrington de Gonzalez estimates that 2,230 future breast cancers would result from radiation from conventional radiography (280), cardiac perfusion imaging (150), and CT (1,800), as described above. These cancers would occur over women’s lifetimes, but result from these medical imaging exposures from a single year. These estimates account for about 80 percent of collective medical radiation dose to the U.S. population as interventional radiology is not included (16 percent of collective U.S. dose) and the other 15 percent of nuclear medicine (4 percent of collective U.S. dose). Thus she estimates an additional 560 breast cancers would result from the remain- ing radiation exposure from angiography and interventional radiology procedures, and from the nuclear medicine procedures not counted in this estimate. This yields a total estimated cancer burden of approximately 2,800 future breast cancers (95% UL, 2,000–3,500) that would result from 1 year of medical radiation exposure among the entire U.S. female popula- tion (Table F-5). REFERENCES ACR (American College of Radiology). 2011. ACR launches Dose Index Registry. Press release, May 12. http://www.acr.org/SecondaryMainMenuCategories/NewsPublications/ FeaturedCategories/CurrentACRNews/ACR-Launches-Dose-Index-Registry.aspx (ac- cessed September 15, 2011). Alliance for Radiation Safety in Pediatric Imaging. 2011. Image gently: CT resources. http:// www.pedrad.org/associations/5364/ig/index.cfm?page=369 (accessed February 13, 2009). Amis, E. S., Jr., P. F. Butler, K. E. Applegate, S. B. Birnbaum, L. F. Brateman, J. M. Hevezi, F. A. Mettler, R. L. Morin, et al. 2007. American College of Radiology white paper on radiation dose in medicine. J Am Coll Radiol 4(5):272–284.
OCR for page 439
439 APPENDIX F Baker, L. C., S. W. Atlas, and C. C. Afendulis. 2008. Expanded use of imaging technology and the challenge of measuring value. Health Aff (Millwood) 27(6):1467–1478. Bassal, M., A. C. Mertens, L. Taylor, J. P. Neglia, B. S. Greffe, S. Hammond, C. M. Ronckers, D. L. Friedman, et al. 2006. Risk of selected subsequent carcinomas in survivors of childhood cancer: A report from the Childhood Cancer Survivor Study. J Clin Oncol 24(3):476–483. Berrington, A., S. C. Darby, H. A. Weiss, and R. Doll. 2001. 100 years of observation on British radiologists: Mortality from cancer and other causes 1897–1997. Br J Radiol 74(882):507–519. Berrington de Gonzalez, A., and S. Darby. 2004. Risk of cancer from diagnostic X-rays: Esti- mates for the UK and 14 other countries. Lancet 363(9406):345–351. Berrington de Gonzalez, A., M. Mahesh, K. P. Kim, M. Bhargavan, R. Lewis, F. Mettler, and C. Land. 2009. Projected cancer risks from computed tomographic scans performed in the United States in 2007. Arch Intern Med 169(22):2071–2077. Berrington de Gonzalez, A., K. P. Kim, R. Smith-Bindman, and D. McAreavey. 2010. Myo- cardial perfusion scans: Projected population cancer risks from current levels of use in the United States. Circulation 122(23):2403–2410. Bhargavan, M., and J. H. Sunshine. 2005. Utilization of radiology services in the United States: Levels and trends in modalities, regions, and populations. Radiology 234(3):824–832. Brenner D. J., R. Doll, and D. T. Goodhead. 2003. Cancer risks attributable to low doses of ionizing radiation: Assessing what we really know. Proc Natl Acad Sci U S A 100(24): 13761–13766. Burger, I., D. Miglioretti, E. Johnson, N. Vanneman, and R. Smith-Bindman. 2010a. Radia- tion exposure increased dramatically in a large health plan, particularly among cancer patients. Paper presented at RSNA meeting, December 1, Chicago, IL. Burger, I., D. Miglioretti, E. Johnson, H. Feigelson, M. Flynn, R. Smith-Bindman, D. Roblin, S. Weinmann, A. Williams, and R. Greenlee. 2010b. Rise in radiation exposure from diagnostic imaging in patients across several different HMO populations. Paper presented at RSNA meeting, December 2, Chicago, IL. Calicchia, A., F. Mazzei, F. Dobici, M. Paganini Fioratti, and P. L. Indovina. 1991. Patient exposure during radiodiagnosis. The Nationwide Evaluation of X-ray Trends (NEXT) program in Italy. Radiol Med 81(6):910–917. Cardis, E., M. Vrijheid, M. Blettner, E. Gilbert, M. Hakama, C. Hill, G. Howe, J. Kaldor, et al. 2007. The 15-country collaborative study of cancer risk among radiation workers in the nuclear industry: Estimates of radiation-related cancer risks. Radiat Res 167(4):396–416. CE Essentials. 2011. Online radiography continuing education for radiologic X ray technolo- gists. http://www.ceessentials.net/article.php (accessed August 1, 2011). Charles, M. 2001. UNSCEAR report 2000: Sources and effects of ionizing radiation. United Nations Scientific Committee on the Effects of Atomic Radiation. J Radiol Prot 21(1):83–86. Chen, J., A. J. Einstein, R. Fazel, H. M. Krumholz, Y. Wang, J. S. Ross, H. H. Ting, N. D. Shah, et al. 2010. Cumulative exposure to ionizing radiation from diagnostic and thera- peutic cardiac imaging procedures: A population-based analysis. J Am Coll Cardiol 56(9):702–711. Conference of Radiation Control Program Directors. 1992. Nationwide Evaluation of X-ray Trends (NEXT): Summary of 1990 computed tomography survey and 1991 fluoroscopy survey. Publication No. 94-2, Frankfurt, KY. Conference of Radiation Control Program Directors. 2007. Nationwide evaluation of X-ray trends (NEXT): Tabulation and graphical summary of 2000 survey of computed tomog- raphy. Frankfurt, KY.
OCR for page 440
440 BREAST CANCER AND THE ENVIRONMENT Dinan, M. A., L. H. Curtis, B. G. Hammill, E. F. Patz, Jr., A. P. Abernethy, A. M. Shea, and K. A. Schulman. 2010. Changes in the use and costs of diagnostic imaging among Medi- care beneficiaries with cancer, 1999–2006. JAMA 303(16):1625–1631. Dorfman, A. L., R. Fazel, A. J. Einstein, K. E. Applegate, H. M. Krumholz, Y. Wang, E. Christodoulou, J. Chen, et al. 2011. Use of medical imaging procedures with ionizing radiation in children: A population-based study. Arch Pediatr Adolesc Med 165(5): 458–464. Einstein, A. J., M. J. Henzlova, and S. Rajagopalan. 2007a. Estimating risk of cancer associ- ated with radiation exposure from 64-slice computed tomography coronary angiography. JAMA 298(3):317–323. Einstein, A. J., K. W. Moser, R. C. Thompson, M. D. Cerqueira, and M. J. Henzlova. 2007b. Radiation dose to patients from cardiac diagnostic imaging. Circulation 116(11): 1290–1305. Einstein, A. J., J. Sanz, S. Dellegrottaglie, M. Milite, M. Sirol, M. Henzlova, and S. Rajagopalan. 2008. Radiation dose and cancer risk estimates in 16-slice computed tomography coro- nary angiography. J Nucl Cardiol 15(2):232–240. Einstein, A. J., C. D. Elliston, A. E. Arai, M. Y. Chen, R. Mather, G. D. Pearson, R. L. Delapaz, E. Nickoloff, et al. 2010. Radiation dose from single-heartbeat coronary CT angiography performed with a 320-detector row volume scanner. Radiology 254(3):698–706. Fazel, R., H. M. Krumholz, Y. Wang, J. S. Ross, J. Chen, H. H. Ting, N. D. Shah, K. Nasir, et al. 2009. Exposure to low-dose ionizing radiation from medical imaging procedures. N Engl J Med 361(9):849–857. FDA (U.S. Food and Drug Administration). 2009. Safety investigation of CT brain perfusion scans: Initial notification. http://www.fda.gov/MedicalDevices/Safety/AlertsandNotices/ ucm193293.htm (accessed August 15, 2011). FDA. 2010. FDA white paper: Initiative to reduce unnecessary radiation exposure from medi- cal imaging. http://www.fda.gov/Radiation-EmittingProducts/RadiationSafety/Radiation DoseReduction/ucm199994.htm (accessed June 30, 2010). Foley, W. D., T. A. Mallisee, M. D. Hohenwalter, C. R. Wilson, F. A. Quiroz, and A. J. Taylor. 2000. Multiphase hepatic CT with a multirow detector CT scanner. AJR Am J Roent- genol 175(3):679–685. Gonzalez, A. J., G. C. Mason, R. H. Clarke, A. D. Wrixon, J. Cooper, L. E. Holm, J. D. Boice, Jr., C. Cousins, et al. 2007. Scope of radiological protection control measures. Ann ICRP 37(5):1–105. Hackbarth, G. M. 2007. Options to improve Medicare’s payments to physicians. Testimony before the Subcommittee on Health of the House Committee on Ways and Means, May 10. http://www.medpac.gov/documents/051007_Testimony_MedPAC_physician_ payment.pdf (accessed August 15, 2010). Hausleiter, J., T. Meyer, F. Hermann, M. Hadamitzky, M. Krebs, T. C. Gerber, C. McCollough, S. Martinoff, et al. 2009. Estimated radiation dose associated with cardiac CT angiog- raphy. JAMA 301(5):500–507. Hendrick, R. E., E. D. Pisano, A. Averbukh, C. Moran, E. A. Berns, M. J. Yaffe, B. Herman, S. Acharyya, et al. 2010. Comparison of acquisition parameters and breast dose in digital mammography and screen-film mammography in the American College of Radiology Imaging Network digital mammographic imaging screening trial. AJR Am J Roentgenol 194(2):362–369. Hoeffner, E. G., I. Case, R. Jain, S. K. Gujar, G. V. Shah, J. P. Deveikis, R. C. Carlos, B. G. Thompson, et al. 2004. Cerebral perfusion CT: Technique and clinical applications. Radiology 231(3):632–644.
OCR for page 441
441 APPENDIX F Hricak, H., D. J. Brenner, S. J. Adelstein, D. P. Frush, E. J. Hall, R. W. Howell, C. H. McCollough, F. A. Mettler, et al. 2011. Managing radiation use in medical imaging: A multifaceted challenge. Radiology 258(3):889–905. Hurwitz, L. M., T. T. Yoshizumi, R. E. Reiman, E. K. Paulson, D. P. Frush, G. T. Nguyen, G. I. Toncheva, and P. C. Goodman. 2006. Radiation dose to the female breast from 16-MDCT body protocols. AJR Am J Roentgenol 186(6):1718–1722. Hurwitz, L. M., R. E. Reiman, T. T. Yoshizumi, P. C. Goodman, G. Toncheva, G. Nguyen, and C. Lowry. 2007. Radiation dose from contemporary cardiothoracic multidetector CT protocols with an anthropomorphic female phantom: Implications for cancer induction. Radiology 245(3):742–750. IAEA (International Atomic Energy Agency). 1996. International basic safety standards for protection against ionizing radiation and for the safety of radiation sources. ISSN 0074- 1892; 115. Safety standards. Vienna, Austria: IAEA. ICRP (International Commission on Radiological Protection). 1991. 1990 recommendations of the International Commission on Radiological Protection. ICRP Pub. No. 60. Oxford, UK: Pergamom. Kuhn, H. 2006. Payment for imaging services under the Medicare physician fee schedule. Testimony before the House Subcommittee on Health of the Committee on Energy And Commerce, July 18. http://www.cms.hhs.gov/apps/media/press/release.asp?Counter=1903 (accessed August 15, 2011). Land, C. E. 1995. Studies of cancer and radiation dose among atomic bomb survivors. The example of breast cancer. JAMA 274(5):402–407. Lewis, E. B. 1963. Leukemia, multiple myeloma, and aplastic anemia in American radiologists. Science 142:1492–1494. Linet, M. S., K. P. Kim, D. L. Miller, R. A. Kleinerman, S. L. Simon, and A. Berrington de Gonzalez. 2010. Historical review of occupational exposures and cancer risks in medical radiation workers. Radiat Res 174(6):793–808. Little, M. P. 2001. Cancer after exposure to radiation in the course of treatment for benign and malignant disease. Lancet Oncol 2(4):212–220. Matanoski, G. M., R. Seltser, P. E. Sartwell, E. L. Diamond, and E. A. Elliott. 1975. The current mortality rates of radiologists and other physician specialists: specific causes of death. Am J Epidemiol 101(3):199–210. Mettler, F. A., Jr., W. Huda, T. T. Yoshizumi, and M. Mahesh. 2008. Effective doses in radiol- ogy and diagnostic nuclear medicine: A catalog. Radiology 248(1):254–263. Mettler, F. A., Jr., M. Bhargavan, K. Faulkner, D. B. Gilley, J. E. Gray, G. S. Ibbott, J. A. Lipoti, M. Mahesh, et al. 2009. Radiologic and nuclear medicine studies in the United States and worldwide: Frequency, radiation dose, and comparison with other radiation sources—1950–2007. Radiology 253(2):520–531. Modan, B., L. Keinan, T. Blumstein, and S. Sadetzki. 2000. Cancer following cardiac catheter- ization in childhood. Int J Epidemiol 29(3):424–428. Muirhead, C. R., A. A. Goodill, R. G. Haylock, J. Vokes, M. P. Little, D. A. Jackson, J. A. O’Hagan, J. M. Thomas, et al. 1999. Occupational radiation exposure and mortal- ity: Second analysis of the National Registry for Radiation Workers. J Radiol Prot 19(1):3–26. Muirhead, C. R., J. A. O’Hagan, R. G. Haylock, M. A. Phillipson, T. Willcock, G. L. Berridge, and W. Zhang. 2009. Mortality and cancer incidence following occupational radiation exposure: Third analysis of the National Registry for Radiation Workers. Br J Cancer 100(1):206–212. NCRP (National Council on Radiation Protection and Measurements). 1987a. NCRP Report No. 91: Recommendations on limits for exposure to ionizing radiation. Bethesda, MD: NCRP.
OCR for page 442
442 BREAST CANCER AND THE ENVIRONMENT NCRP. 1987b. NCRP Report No. 93: Ionizing radiation exposure of the population of the United States. Bethesda, MD: NCRP. NCRP. 1989. NCRP Report No. 105: Radiation protection for medical and allied health personnel. Bethesda, MD: NCRP. NCRP. 1993. NCRP Report No. 116: Limitations on exposure to ionizing radiation. Bethesda, MD: NCRP. NCRP. 2009. NCRP Report No. 160: Ionizing radiation exposure of the population of the United States. Bethesda, MD: NCRP. NCRP. 2011. National Council on Radiation Protection and Measurements. http://www. ncrponline.org/ (accessed August 1, 2011). Neglia, J. P., D. L. Friedman, Y. Yasui, A. C. Mertens, S. Hammond, M. Stovall, S. S. Donaldson, A. T. Meadows, et al. 2001. Second malignant neoplasms in five-year survivors of childhood cancer: Childhood Cancer Survivor Study. J Natl Cancer Inst 93(8):618–629. Neglia, J. P., L. L. Robison, M. Stovall, Y. Liu, R. J. Packer, S. Hammond, Y. Yasui, C. E. Kasper, et al. 2006. New primary neoplasms of the central nervous system in survivors of childhood cancer: A report from the Childhood Cancer Survivor Study. J Natl Cancer Inst 98(21):1528–1537. NRC (National Research Council). 1996. Health effects of exposure to low levels of ionizing radiation: BEIR V. Washington, DC: National Academy Press. NRC. 2003. Exposure of the American population to radioactive fallout from nuclear weap- ons tests: A review of the CDC–NCI draft report on a feasibility study of the health consequences to the American population from nuclear weapons tests conducted by the United States and other nations. Washington, DC: The National Academies Press. NRC. 2006. Health risks from exposure to low levels of ionizing radiation: BEIR VII Phase 2. Washington, DC: The National Academies Press. Pierce, D. A., and D. L. Preston. 1993. Joint analysis of site-specific cancer risks for the atomic bomb survivors. Radiat Res 134(2):134–142. Pierce, D. A., and D. L. Preston. 2000. Radiation-related cancer risks at low doses among atomic bomb survivors. Radiat Res 154(2):178–186. Preston, R. J. 2008. Update on linear non-threshold dose-response model and implications for diagnostic radiology procedures. Health Phys 95(5):541–546. Preston, D. L., D. A. Pierce, Y. Shimizu, E. Ron, and K. Mabuchi. 2003. Dose response and temporal patterns of radiation-associated solid cancer risks. Health Phys 85(1):43–46. Preston, D. L., E. Ron, S. Tokuoka, S. Funamoto, N. Nishi, M. Soda, K. Mabuchi, and K. Kodama. 2007. Solid cancer incidence in atomic bomb survivors: 1958–1998. Radiat Res 168(1):1–64. Ron, E. 2003. Cancer risks from medical radiation. Health Phys 85(1):47–59. Ron, E., J. H. Lubin, R. E. Shore, K. Mabuchi, B. Modan, L. M. Pottern, A. B. Schneider, M. A. Tucker, et al. 1995a. Thyroid cancer after exposure to external radiation: A pooled analysis of seven studies. Radiat Res 141(3):259–277. Ron, E., D. L. Preston, and K. Mabuchi. 1995b. More about cancer incidence in atomic bomb survivors: Solid tumors, 1958–1987. Radiat Res 141(1):126–127. Ronckers, C. M., A. J. Sigurdson, M. Stovall, S. A. Smith, A. C. Mertens, Y. Liu, S. Hammond, C. E. Land, et al. 2006. Thyroid cancer in childhood cancer survivors: A detailed evalua- tion of radiation dose response and its modifiers. Radiat Res 166(4):618–628. Rydberg, J., K. A. Buckwalter, K. S. Caldemeyer, M. D. Phillips, D. J. Conces, Jr., A. M. Aisen, S. A. Persohn, and K. K. Kopecky. 2000. Multisection CT: Scanning techniques and clini- cal applications. Radiographics 20(6):1787–1806. Sachs, R. K., and D. J. Brenner. 2005. Solid tumor risks after high doses of ionizing radiation. Proc Natl Acad Sci U S A 102(37):13040–13045.
OCR for page 443
443 APPENDIX F Shuryak, I., R. K. Sachs, and D. J. Brenner. 2010. Cancer risks after radiation exposure in middle age. J Natl Cancer Inst 102(21):1628–1636. Sigurdson, A. J., C. M. Ronckers, A. C. Mertens, M. Stovall, S. A. Smith, Y. Liu, R. L. Berkow, S. Hammond, et al. 2005. Primary thyroid cancer after a first tumour in childhood (the Childhood Cancer Survivor Study): A nested case–control study. Lancet 365(9476):2014–2023. Smith-Bindman, R., D. L. Miglioretti, and E. B. Larson. 2008. Rising use of diagnostic medical imaging in a large integrated health system. Health Aff (Millwood) 27(6):1491–1502. Smith-Bindman, R., J. Lipson, R. Marcus, K. P. Kim, M. Mahesh, R. Gould, A. Berrington de Gonzalez, and D. L. Miglioretti. 2009. Radiation dose associated with common com- puted tomography examinations and the associated lifetime attributable risk of cancer. Arch Intern Med 169(22):2078–2086. Spelic, D. 2007. Nationwide evaluation of X-ray trends: NEXT 2005–2006. Paper read at Conference of Radiation Control Program Directors annual meeting, Spokane, WA, May 21–24. Spelic, D. C., R. V. Kaczmarek, and O. H. Suleiman. 2004. Nationwide evaluation of X-ray trends survey of abdomen and lumbosacral spine radiography. Radiology 232(1):115–125. State of California. 2010. Senate bill 1237: Radiation Safety Bill. Strzelczyk, J., W. Potter, and Z. Zdrojewicz. 2007. Rad-by-rad (bit-by-bit): Triumph of evi- dence over activities fostering fear of radiogenic cancers at low doses. Dose Response 5(4):275–283. U.S. House of Representatives: Subcommittee on Health. 2010. Medical radiation: An over- view of the issues. http://democrats.energycommerce.house.gov/index.php?q=hearing/ medical-radiation-an-overview-of-the-issues (accessed August 15, 2010).
OCR for page 444