Skip to main content
Download PDF

CT Scans and Cancer Risks: A Systematic Review and Dose-response Meta-analysis

BMC Cancer volume 22, Article number: 1238 (2022) Cite this article

Abstract

Background

There is still uncertainty on whether ionizing radiation from CT scans can increase the risks of cancer. This study aimed to identify the association of cumulative ionizing radiation from CT scans with pertaining cancer risks in adults.

Methods

Five databases were searched from their inception to November 15, 2020. Observational studies reporting cancer risks from CT scans in adults were included. The main outcome included quantified cancer risks as cancer case numbers in exposed/unexposed adult participants with unified converted measures to odds ratio (OR) for relative risk, hazard ratio. Global background radiation (2.4 mSv per year) was used as control for lifetime attribution risk (LAR), with the same period from incubation after exposure until survival to 100 years.

Results

25 studies were included with a sum of 111,649,943 participants (mean age: 45.37 years, 83.4% women), comprising 2,049,943 actual participants from 6 studies with an average follow-up period as 30.1 years (range, 5 to 80 years); 109,600,000 participants from 19 studies using LAR. The cancer risks for adults following CT scans were inordinately increased (LAR adults, OR, 10.00 [95% CI, 5.87 to 17.05]; actual adults, OR, 1.17 [95%CI, 0.89 to 1.55]; combined, OR, 5.89 [95%CI, 3.46 to 10.35]). Moreover, cancer risks elevated with increase of radiation dose (OR, 33.31 [95% CI, 21.33 to 52.02]), and multiple CT scan sites (OR, 14.08 [95% CI, 6.60 to 30.05]). The risk of solid malignancy was higher than leukemia. Notably, there were no significant differences for age, gender, country, continent, study quality and studying time phrases.

Conclusions

Based on 111.6 million adult participants from 3 continents (Asia, Europe and America), this meta-analysis identifies an inordinately increase in cancer risks from CT scans for adults. Moreover, the cancer risks were positively correlated with radiation dose and CT sites. The meta-analysis highlights the awareness of potential cancer risks of CT scans as well as more reasonable methodology to quantify cancer risks in terms of life expectancy as 100 years for LAR.

Prospero trial registration number

CRD42019133487.

Peer Review reports

Background

As an auxiliary diagnostic imaging modality, CT scans play an important role in the diagnosis of various complicated diseases [1]. As new clinical indications continue to be discovered, the use of CT scan has increased rapidly over the past decade worldwidely [2,3,4,5]. Although CT scans are of great diagnostic benefits to individual patients, relatively higher radiation doses are delivered compared with other conventional imaging modalities [1, 6, 7]..

Substantial follow-up works are now underway to determine whether patients experiencing ionizing radiation from CT scans can significantly increase the risk of cancer. Indeed, many lines of evidence have shown that ionizing radiation from CT scans is associated with cancer/tumor risks [8,9,10,11,12]. Whereas recently epidemiological studies have examined potential disease risks from pediatric CT scanning, studies of cancer risk from CT scans during adulthood are also of critical important for public health. Adults receive over 10 times more CT scans than children [13,14,15] and most radiation induced cancers occur during middle or older age.

However, researchers questioned the validity of the earlier indirect estimates based on uncertain risk projections for radiation [16], whereas others declared that the findings of recent CT scan studies need to be interpreted with caution, due to the possibility of reverse causation [17]. Therefore, we cannot necessarily attribute all excess cases of cancer to ionizing radiation during the period of follow-up after patients undergoing CT scans, since the decision of performing CT scans is not allocated randomly but based on medical indications. For example, patients with precancerous symptoms or early symptoms that might prompt their physician to perform a CT scan, which may lead to the possibility of reverse causation. Until now, there is still uncertainty on whether ionizing radiation from CT scans can increase the risks of cancer. It can be hard for the medical community to design and conduct studies to validate previous reports. Prior studies have presented the evidence on cancer and mortality risks of young scoliosis patients from cumulative radiographic radiation (spinal radiographs) [18] and tentatively proposed low radiation X-ray methodology [19], focusing on the issue dynamically with the medical community [20,21,22,23,24] with the aims for benefiting global patients and the public. Consequently, this work aims to evaluate whether adult CT scan exposure can increase the risks of cancer during the follow-up observation, based on systematic review and meta-analysis of global observational studies.

Methods

Protocol

This systematic review and meta-analysis was successfully registered in the International Prospective Register of Systematic reviews (PROSPERO) on 28 April 2019, with the Registration number CRD42019133487. The initial enrollment was to study the relationship between CT screening and cancer risk in children and adolescents. We revised the registry for adult CT scans and cancer risks due to a published study by another group during our studying process [25]..

Study types

Observational studies, cohort studies, and case-control studies were included in this systematic review and meta-analysis, while studies assessed review articles, proceedings, case series and case reports were excluded. No restrictions to the language of publication were applied to select primary studies. We added extra studies by additional hand search of the reference lists of related articles.

Population

Patients meeting the following requirements were included in this study: 1) Patients were older than 18 years for their first CT scan, 2) Patients did not have any malignant diseases (such as precancerous symptoms or early symptoms of the cancer) prior to their first CT scan, 3) Patients with follow-up of more than 1 year after their first scan. 4) Patients underwent at least one CT scan. Those with the following conditions were excluded: 1) Patients with incomplete demographic data or data errors, 2) Patients lost follow-up for a variety of factors.

Interventions

Included patients received one or more electronically archived CT scans. The absorbed dose from a CT scan mainly depends on factors including age, sex, examination site, year of scan (2007 as a milestone for CT scans in terms of dose reduction in Annals of the ICRP [26]), and machine parameters.

Outcome measures

The study included two outcome measures.

  1. 1)

    Cancer risks, including each part of the human body with at least 1 year lag period after first exposure.

  2. 2)

    The potential associations between adult CT scan exposure radiation doses and cancer risks, including lifetime attribute risk (LAR).

Search methods for identification of studies

A thorough search was conducted in the following global databases, PubMed, Medline, EMBASE, Web of Science, Springer Link, Cochrane Library, from inception through Nov 15th 2020 with terms including “Adult”, “computerized tomography, X ray”, and “Cancer”. Search strategies were designed by an experienced librarian and revised by another librarian according to the PRESS (Peer Review of Electronic Search Strategies) checklist [27]. Three reviewers performed the selection process independently, and disagreements were discussed and resolved by a fourth reviewer.

Assessment of risk of bias (ROBs) in included studies

The ROBs of each study were assessed independently by two authors according to Newcastle-Ottawa Scale [28]..

Dealing with missing data

When missing data were encountered in included articles, we contacted the corresponding authors of relevant studies for these data by sending electronic mails twice with time interval of 1 month. When the study did not provide the number of cancer cases in the case/exposed group or control/unexposed group, the numbers were calculated by the formula defined as Re/Ru for RR (Relative Risk), Re (1- Ru)/[Ru (1- Re)] for OR (the rate in exposed persons, denoted Re; the rate in unexposed persons, denoted Ru), and (Or/Oe)/(Cr/Ce) for HR (experimental group, denoted O; control group, denoted C; actual persons, denoted r; theoretical persons, denoted e) [29].

Assessment of publication bias

Publication bias were explored by a funnel plot (i.e., plots of study results against precision), Egger’s tests [30]..

Subgroup analysis

In studies using LAR to estimate cancer risks, control group was defined according to the global incidence of cancer at 2.4 mSv of background radiation dose, i.e., lifetime baseline risk (LBR) [31]. We used the radiation risk models for sex- and organ-specific cancer incidence developed by the National Research Council’s BEIR VII committee [32]. LAR calculates the risk of cancer from an incubation period after radiation exposure (5 years for solid cancer and 2 years for leukemia) to survival to 100 years. LAR and LBR were calculated with the same method. For an age with a mantissa of 5: 45 years, divide by 2 the sum of the LAR values for 40 years and 50 years. For example, the LAR at the age of 45 years is (141 + 70)/2 = 105.5 at full 100 mSv (141 cases per 100,000 at 40-year-old and 70 cases per 100,000 at 50-year-old by BEIR VII). If less than 100 mSv, if it was 2.4 mSv, the LAR at the age of 40 years, 45 years, and 50 years are 41(2.4/100), 105.5(2.4/100), and 70(2.4/100), respectively.

Sensitivity analysis

Sensitivity analysis was performed by removing relevant studies to observe whether the homogeneity and the results change significantly. If the heterogeneity was too large to be analyzed, descriptive analyses were presented.

Assessment of heterogeneity

All analyses were performed using Stata V.16.0 software (Stata Corp LP, College Station, Texas, USA). Heterogeneity among primary studies were analyzed using standard Chi-squared tests (P value) and the Ι2 statistic as recommended by the Cochrane Handbook for Systematic Reviews of Interventions [33]. We interpreted Ι2 values according to Deeks [34]. Meta-regression was used to explore prior factors that may be important sources of heterogeneity. P < 0.05 was considered as a statistically significant.

Results

Hallmarks of included studies

The literature-retrieving strategy and pertaining results were shown in Fig. 1 and Table S1. A total of 44,657 relevant studies were preliminarily reviewed. In total, 125 studies satisfied the eligibility criteria for full-text screening and 25 were eventually included for this meta-analysis [2, 8,9,10,11, 35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54]. Of these 25 studies, 5 reported actual cancer cases [8, 10, 11, 35, 36], 19 estimated cancer cases by calculating LAR [2, 9, 37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53], 1 reported expected cancer cases in control group [54], and all were published since 2007. Four studies were excluded due to incomplete data [12, 55,56,57]. Additional data were requested by contacting the authors of 4 studies via repeated electronic mails with a time interval of 1 month (Table S2). However, no replies and requested data were received.

Fig. 1
figure 1

Flowchart of literature screening process

Full size image

Participant hallmarks

Studies were predominantly from the US (n = 11), followed by China (n = 4), Sweden (n = 3), Greece (n = 2), and Canada, Italy, Thailand, Croatia, and Denmark (n = 1 each); One study [42] included populations from China (Hong Kong) and the US. Based on the LAR base number of 100,000 persons, 25 studies were included with a sum of 111,649,943 participants, comprising 2,049,943 actual participants (111,449 cases VS 1938494 controls) from 6 studies; 109,600,000 estimated participants (54,912,051 participants received at least one CT radiation) from 19 studies. The average age was 51.3 years in CT scan exposed group (range, 20.0 to 94.0 years) and 40.5 years in control group (range, 25 to 84 years). The gender was reported in 19 studies of CT scan exposed group and 5 studies of unexposed group. The proportion of women was even higher (53.0%, 140,305 participants in CT group; 85.6%, 1,914,381 participants in unexposed group). The average follow-up time was 12.1 years in actual group (range, 5.9 to 22.5 years), 48.0 years (range, 5 to 80 years) in LAR group. The radiation dose per capita was 66.7 mSv (range:5.15 mSv to 122 mSv). A detailed list of study hallmarks was shown in Table 1 and Table 2.

Table 1 Detailed information and characteristics of participants
Full size table
Table 2 Detailed information and characteristics of included studies
Full size table

ROBs of included studies

The quality scores of 5 studies with actual participants and cancer cases ranged from 7 to 9 (Table S3A). Twenty of the studies were estimated cancer incidence and not case-control or cohort studies, the quality scores ranged from 2 to 6 (Table S3B).

Cancer risk from CT scans

The cancer risks for adults following CT scans were inordinately increased (LAR adults, OR, 10.00 [95% CI, 5.87 to 17.05], Ι2 = 99.14; actual adults, OR, 1.17 [95%CI, 0.89 to 1.55], Ι2 = 94.18; combined, OR, 5.89 [95%CI, 3.46 to 10.35], Ι2 = 99.61%; Fig. 2). Notably, cancer incidence for actual studies was significantly different due to the inclusion (OR, 1.17 [95% CI, 0.89 to 1.55]) or exclusion (OR, 1.32 [95% CI, 1.11 to 1.56]) of Bruton’s study [35] with pregnant women participants (Table 3). Subgroup analysis indicated that cancer risks from LAR studies were significantly higher than actual studies (P = 0.00; Table 3), due to a longer life expectancy (to 100 years) used for calculation.

Fig. 2
figure 2

Forest plot of cancer risk from CT scans versus unexposed group

Full size image
Table 3 Subgroup analyses of CT exposure radiation and the risks of cancer incidence
Full size table

There was no evidence of publication bias (egger, P = 0.58). Cancer risks of exposed men and women were not significantly different (P = 0.71, men, OR, 4.89 [95% CI, 2.40 to 9.96]; Ι2 = 99.43%; women, OR, 5.88 [95% CI, 2.96 to 11.68], Ι2 = 99.52%; Table 3). There were no significantly different cancer risks (P = 0.93) for adults in terms of age (Table 3, less than 45 years, OR, 5.79 [95% CI, 2.08 to 16.14], Ι2 = 99.64%; 45 to 65 years, OR, 5.04 [95% CI, 2.02 to 12.57], Ι2 = 99.47%; older than 65 years, OR, 6.66 [95% CI, 2.07 to 21.38], Ι2 = 98.00%).

The LAR estimation included the 2006 National Academy of Sciences BEIR VII. We extracted data in terms of scanning year (before and after 2007, 26] and countries (US or not) to explore the impact of scanning year and countries on cancer risks. Scanning year, countries, and continents of studies did not alter cancer risks (Ι2 = 99.61%, P = 0.88; Ι2 = 99.61%, P = 0.19; Ι2 = 99.61%, P = 0.58, Table 3). There was no significant difference in study quality scores (Ι2 = 99.61%, P = 0.25; Table 3).

Dose-response analysis showed that the cancer risks significantly increased linearly with radiation dose of CT scans (Coefficient = 0.03, P = 0.00) (Fig. S1). In details, the cancer risks were lowest for radiation dose of less than 15 mSv (OR, 2.51 [95% CI, 1.55 to 4.06], Ι2 = 94.46%), highest for dose greater than 55 mSv (OR, 33.31 [95% CI, 21.33 to 52.02], Ι2 = 97.09%), intermediate for dose of 15 to 55 mSv (OR, 5.48 [95% CI, 2.74 to 10.97]), with significant differences between triple groups (P < 0.001, dose grouping according to the overall radiation dose distribution included in the studies) (Fig. S2). Moreover, the relationship between cancer risk and radiation dose was more significant in the < 45 years group (P = 0.00), while there was no significant difference in 45–65 years groups (P = 0.08, Fig. S3).

For cancer types, a significantly higher risk of non-leukemic cancer was noted (P = 0.01; Table 3), in comparison with leukemic cancer. Cancer risks were significantly increased when more than 3 sites were scanned (P = 0.00; Table 3).

Heterogeneity and sensitivity analyses

Sensitivity analyses did not alter the results, by excluding 1 study at a time from each meta-analysis (Table S4). Heterogeneity was present in all analyses (> 99% for all pooled estimates). Meta-regression (Table S5) identified data type, CT sites, and radiation dose contributing to heterogeneity for cancer risk, with no factors substantially reducing heterogeneity between studies.

Discussion

Main findings and the significance of using LBR for LAR studies

The meta-analysis presents novel and complete evidence for the common and important issue concerned by clinicians, patients and the public, i.e., exposed CT scans and pertinent cancer risks for adults in their remaining lives. Based on 2,049,943 actual and 109,600,000 LAR/LBR participants from 9 countries, cancer risks for adults undergoing CT scans were successfully identified. Importantly, studies using LAR have been neglected in previous synthesized reports; partly due to the paucity of an appropriate control/unexposed population in quantify OR for these studies.

Indeed, selecting a control group (LBR) for LAR studies was challenging for such meta-analysis with global included studies. Participants unexposed to CT scans receive cosmic radiation (background radiation) in the earth, with various radiation dose range in different regions [31]. When background radiation was greater than 20 mSv per year, the area is designated as high natural background radiation (HNBR) region [58]. An ideal LBR should estimate cancer incidence based on various background radiation doses in different regions. Since HNBR areas were not covered in LAR studies for our meta-analysis, it is appropriate to use the global mean of 2.4 mSv per year as control group to estimate cancer risks. Our data showed that the incidence of cancer in the LBR group (42.7/100000 for men and 65.7/100000 for women) was lower than that in the CT exposed group (68.8/100000 for men and 91.9/100000 for women) and the updated annual global incidence of cancer [59]..

Sample size strengths and profound analysis for cancer risks from CT scans

So far, no studies have quantified the cancer risk of low-dose radiation. One of the most important reasons is insufficient sample size. According to the evaluation of a total of 1000 mSv for a sample of 1000 people, the sample size needed to evaluate 100 mSv would be 100,000, 10 mSv would be 10 million [60]. In this meta-analysis, the sample size was sufficient with strengths, including 24,000,538 participants for CT radiation exposure < 15 mSv, 1,056,402,315 for 15 to 55 mSv, and 76,600,000 for dose > 55 mSv. Cancer risks increased with cumulative radiation dose from CT scans, consistent with previous evidence [61]. Meanwhile, the results showed that cancer risks increased slowly during radiation dose below 55 mSv, and rapidly for those above 55 mSv.

Ample evidence from Japanese atomic bomb survivors indicates that children are more susceptible than adults to the deleterious effects of ionizing radiation [62]. Children have longer life expectancy since exposure to ionizing radiation, providing more time for a cancer to manifest. This point supports our results with higher cancer risks for LAR than actual studies, since life expectancy used for LAR was 100 years [63]. Notably, there was no significant difference of age on cancer incidence when we divided adults into young, middle-aged and older (age groups according to the 2010 WHO Recommendations on physical activity for health) [64]. Similarly, age did not significantly alter cancer risks for children and adolescents exposed for CT scans in Huang’s study [25] (0 to 5 years (relative risk [RR], 1.35), 6 to 15 years (RR, 1.14), and > 15 years (RR, 1.24) [25]. Mavragani et al. found that DNA damage from low radiation doses was not severe enough to cause cell death, but could trigger a red flag [65, 66]. One of those red flags is the body’s immune system. Increasing evidence suggests that radiation exposure of low dose may not only have immunosuppressive effects, but likely to be associated with a radiation-induced enhancement in the immune system [67,68,69]. However, immune systems of older adults are not as well functioning as those of younger people. This factor may underlie the results that the risk of cancer from CT radiation does not continue to decrease with age. This may also explain why cancer risks in the 45–65 years group are less sensitive to radiation exposure than those in the < 45 years group. Despite the age differences were insignificant, there was a significant increase in cancer risks for exposed adults compared with the background radiation group.

In 2007, the International Commission on Radiological Protection (ICPR) published a guide to the basic principles of appropriate radiation Protection based on radiation exposure. Since then, almost all international standards and national regulations dealing with radiation protection have been based on the recommendations of the Committee. Consequently, 2007 should be a milestone for CT scan in terms of dose reduction. Even in this study, no significant difference was found between radiation and cancer risk compared with studies published before or after 2007. What is clear is that researchers will adjust their protective strategies to a higher level in the plethora of exposure situations, as ICRP itself states.

Limitations

Firstly, There are various confounders for cancer incidence [70], including genetics [71], hormone levels, [72, 73] tobacco, alcohol, overweight, physical activity [74, 75], socio-economic status, [76] and infectious agents [77, 78]. These confounders were not included in this meta-analysis, due to the unavailability of information from original studies. Secondly, the numbers of participants in this study are mostly derived from estimated group and tend to be theoretical cancer risks from CT scan. Nevertheless, evidence from these LAR studies should not be ignored for meta-analysis (have been ignored in previous systematic review). Thirdly, over 80% participants in this study were women, with the risk of cancer in women undergoing CT scans during pregnancy remains unclear. Fourthly, the actual and estimated participants were combined. The difference in age at the end of follow-up between the two groups may amplify the actual cancer incidence. Nevertheless, current follow-up time period from actual studies was relatively limited, with incomplete reflected cancer risks from CT scans. Fifth, it is apparent that CT scans were correlated with increased risk of solid cancers, i.e., cancer risk increased with radiation dose and sites scanned. However, the relative increased quantification of scans may be biased due to different weight factors of various organs/tissues of the body. Finally, heart disease was the most common reason for CT scans in included studies, with variation in terms of the severity of patients, the treatment plan, and the duration of follow-up, thus contributing to the inconsistency of included studies.

Conclusion

Based on 111.6 million adult participants from 3 continents (Asia, Europe and America), this meta-analysis identifies an inordinately increase in cancer risks from CT scans for adults (Additional Video). Moreover, the cancer risks were positively correlated with radiation dose and CT sites. The meta-analysis highlights the awareness of potential cancer risks of CT scans as well as more reasonable methodology to quantify cancer risks in terms of life expectancy as 100 years for LAR.

Abbreviations

LAR:

Lifetime attribution risk

OR:

Odds ratio

CI:

Confidence interval

BEIR:

Biological Effects of Ionizing Radiation

Lbr:

Lifetime baseline risk

RR:

Relative risk

HBV:

Hepatitis B virus

HPV:

Human papilloma virus

HCV:

Hepatitis C virus

LNT:

Linear non-threshold

HDI:

Human development index

References

  1. Mettler FA Jr, Huda W, Yoshizumi TT, Mahesh M. Effective doses in radiology and diagnostic nuclear medicine: a catalog. Radiology. 2008;248(1):254–63.

    Article  PubMed  Google Scholar 

  2. Smith-Bindman R, Lipson J, Marcus R, Kim KP, Mahesh M, Gould R, et al. Radiation dose associated with common computed tomography examinations and the associated lifetime attributable risk of cancer. Arch Intern Med. 2009;169(22):2078–86.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Hricak H, Brenner DJ, Adelstein SJ, Frush DP, Hall EJ, Howell RW, et al. Managing radiation use in medical imaging: a multifaceted challenge. Radiology. 2011;258(3):889–905.

    Article  PubMed  Google Scholar 

  4. Smith-Bindman R, Miglioretti DL, Johnson E, Lee C, Feigelson HS, Flynn M, et al. Use of diagnostic imaging studies and associated radiation exposure for patients enrolled in large integrated health care systems, 1996-2010. JAMA. 2012;307(22):2400–9.

    Article  CAS  PubMed  Google Scholar 

  5. Pola A, Corbella D, Righini A, Torresin A, Colombo PE, Vismara L, et al. Computed tomography use in a large Italian region: trend analysis 2004-2014 of emergency and outpatient CT examinations in children and adults. Eur Radiol. 2018;28(6):2308–18.

    Article  PubMed  Google Scholar 

  6. Schauer DA, Linton OW. NCRP Report No. 160, Ionizing Radiation Exposure of the Population of the United States, medical exposure--are we doing less with more, and is there a role for health physicists? Health Phys. 2009;97(1):1–5.

    Article  CAS  PubMed  Google Scholar 

  7. Rehani MM, Berry M. Radiation doses in computed tomography. The increasing doses of radiation need to be controlled. BMJ. 2000;320(7235):593–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Shao YH, Tsai K, Kim S, Wu YJ, Demissie K. Exposure to Tomographic Scans and Cancer Risks. JNCI Cancer Spectr. 2020;4(1):pkz072.

    Article  PubMed  Google Scholar 

  9. Rampinelli C, De Marco P, Origgi D, Maisonneuve P, Casiraghi M, Veronesi G, et al. Exposure to low dose computed tomography for lung cancer screening and risk of cancer: secondary analysis of trial data and risk-benefit analysis. BMJ. 2017;356:j347.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Nordenskjold AC, Bujila R, Aspelin P, Flodmark O, Kaijser M. Risk of Meningioma after CT of the Head. Radiology. 2017;285(2):568–75.

    Article  PubMed  Google Scholar 

  11. Davis F, Il'yasova D, Rankin K, McCarthy B, Bigner DD. Medical diagnostic radiation exposures and risk of gliomas. Radiat Res. 2011;175(6):790–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Cohen S, Liu A, Gurvitz M, Guo L, Therrien J, Laprise C, et al. Exposure to Low-Dose Ionizing Radiation From Cardiac Procedures and Malignancy Risk in Adults With Congenital Heart Disease. Circulation. 2018;137(13):1334–45.

    Article  PubMed  Google Scholar 

  13. Hansen J, Jurik AG. Analysis of Current Practice of CT examinations. Acta Oncol. 2009;48(2):295–301.

    Article  PubMed  Google Scholar 

  14. Berrington de Gonzalez A, Mahesh M, Kim KP, Bhargavan M, Lewis R, Mettler F, et al. Projected cancer risks from computed tomographic scans performed in the United States in 2007. Arch Intern Med. 2009;169(22):2071–7.

    Article  PubMed  Google Scholar 

  15. Mettler FA Jr. Medical Radiation Exposure in the United States: 2006-2016 Trends. Health Phys. 2019;116(2):126–8.

    Article  CAS  PubMed  Google Scholar 

  16. Cucinotta FA, Schimmerling W, Wilson JW, Peterson LE, Saganti PB, Dicello JF. Uncertainties in estimates of the risks of late effects from space radiation. Adv Space Res. 2004;34(6):1383–9.

    Article  CAS  PubMed  Google Scholar 

  17. Hendee WR, O'Connor MK. Radiation risks of medical imaging: separating fact from fantasy. Radiology. 2012;264(2):312–21.

    Article  PubMed  Google Scholar 

  18. Luan FJ, Wan Y, Mak KC, Ma CJ, Wang HQ. Cancer and mortality risks of patients with scoliosis from radiation exposure: a systematic review and meta-analysis. Eur Spine J. 2020;29(12):3123–34.

    Article  PubMed  Google Scholar 

  19. Luan F-J, Zhang J, Mak K-C, Liu Z-H, Wang H-Q. Low Radiation X - rays: Benefiting People Globally by Reducing Cancer Risks. Int J Med Sci. 2021;18(1):73–80.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Liu TF, Shan H, Wang HQ, Luan FJ. Ionizing Radiation Exposure and Cancer Risks: Matter or not Matter? Spine (Phila Pa 1976). 2021;46(4):E286.

    Article  PubMed  Google Scholar 

  21. Luan FJ, Zhang J, Wang HQ. Epidemiological study of adolescent idiopathic scoliosis using low/non-radiation screening methodology. J Rehabil Med. 2018;50(8):765–6.

    Article  PubMed  Google Scholar 

  22. Wang HQ, Zhang J, Ma CJ. Triple Issues Underlying Lung Injury for Adolescent Idiopathic Scoliosis Surgery. Lung. 2018;196(4):381–2.

    Article  PubMed  Google Scholar 

  23. Zhang J, Ma CJ, Liu ZH, Wang HQ. Defining the Pros and Cons of AIS Surgery: Bringing Truth to the Neurosurgery Community and the Public. World Neurosurg. 2018;113:393–4.

    Article  PubMed  Google Scholar 

  24. Zhang J, Ma CJ, Xin XF, Wang HQ. Critical issues underlying expenditures for adolescent idiopathic scoliosis surgery: questioning the surgical treatment motivation. J Pediatr. 2018;198:326–7.

    Article  PubMed  Google Scholar 

  25. Huang R, Liu X, He L, Zhou PK. Radiation Exposure Associated With Computed Tomography in Childhood and the Subsequent Risk of Cancer: A Meta-Analysis of Cohort Studies. Dose Response. 2020;18(2):1559325820923828.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Wrixon AD. New ICRP recommendations. J Radiol Prot. 2008;28(2):161–8.

    Article  CAS  PubMed  Google Scholar 

  27. McGowan J, Sampson M, Salzwedel DM, Cogo E, Foerster V, Lefebvre C. PRESS Peer Review of Electronic Search Strategies: 2015 Guideline Statement. J Clin Epidemiol. 2016;75:40–6.

    Article  PubMed  Google Scholar 

  28. Wells GA, Shea B, O’Connell D, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomized studies in meta-analyses. Secondary The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomized studies in meta-analyses. 2011.

  29. Parmar MK, Torri V, Stewart L. Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. Stat Med. 1998;17(24):2815–34.

    Article  CAS  PubMed  Google Scholar 

  30. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Mc Laughlin JP. Some characteristics and effects of natural radiation. Radiat Prot Dosim. 2015;167(1–3):2–7.

    Article  CAS  Google Scholar 

  32. Committee to Assess Health Risks from Exposure to Low Levels of Ionizing Radiation, Board on Radiation Effects, Research Division on Earth and Life Studies, National Research Council of the National Academies. Health risks from exposure to low levels of ionizing radiation: BEIR VII phase 2. Washington, DC: National Academy of Sciences; 2006.

  33. Higgins JP, Altman DG, Gotzsche PC, Juni P, Moher D, Oxman AD, et al. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. BMJ. 2011;343:d5928.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Deeks JJ, Higgins JPT, Altman DG. Analysing Data and Undertaking Meta-Analyses. In: Higgins JPT, editor. Cochrane Handbook for Systematic Review of Interventions. Hoboken (NJ): Wiley-Blackwell; 2011. p. 243–96.

    Google Scholar 

  35. Burton KR, Park AL, Fralick M, Ray JG. Risk of early-onset breast cancer among women exposed to thoracic computed tomography in pregnancy or early postpartum. J Thromb Haemost. 2018;16(5):876–85.

    Article  CAS  PubMed  Google Scholar 

  36. Hung MC, Hwang JJ. Cancer risk from medical radiation procedures for coronary artery disease: a nationwide population-based cohort study. Asian Pac J Cancer Prev. 2013;14(5):2783–7.

    Article  PubMed  Google Scholar 

  37. Kritsaneepaiboon S, Jutiyon A, Krisanachinda A. Cumulative radiation exposure and estimated lifetime cancer risk in multiple-injury adult patients undergoing repeated or multiple CTs. Eur J Trauma Emerg Surg. 2018;44(1):19–27.

    Article  CAS  PubMed  Google Scholar 

  38. Griffey RT, Sodickson A. Cumulative radiation exposure and cancer risk estimates in emergency department patients undergoing repeat or multiple CT. AJR Am J Roentgenol. 2009;192(4):887–92.

    Article  PubMed  Google Scholar 

  39. Einstein AJ, Sanz J, Dellegrottaglie S, Milite M, Sirol M, Henzlova M, et al. Radiation dose and cancer risk estimates in 16-slice computed tomography coronary angiography. J Nucl Cardiol. 2008;15(2):232–40.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Faletra FF, D'Angeli I, Klersy C, Averaimo M, Klimusina J, Pasotti E, et al. Estimates of lifetime attributable risk of cancer after a single radiation exposure from 64-slice computed tomographic coronary angiography. Heart. 2010;96(12):927–32.

    Article  CAS  PubMed  Google Scholar 

  41. Niemann T, Zbinden I, Roser HW, Bremerich J, Remy-Jardin M, Bongartz G. Computed tomography for pulmonary embolism: assessment of a 1-year cohort and estimated cancer risk associated with diagnostic irradiation. Acta Radiol. 2013;54(7):778–84.

    Article  CAS  PubMed  Google Scholar 

  42. Huang B, Law MW, Khong PL. Whole-body PET/CT scanning: estimation of radiation dose and cancer risk. Radiology. 2009;251(1):166–74.

    Article  PubMed  Google Scholar 

  43. Perisinakis K, Seimenis I, Tzedakis A, Papadakis AE, Damilakis J. Individualized assessment of radiation dose in patients undergoing coronary computed tomographic angiography with 256-slice scanning. Circulation. 2010;122(23):2394–402.

    Article  PubMed  Google Scholar 

  44. Sodickson A, Baeyens PF, Andriole KP, Prevedello LM, Nawfel RD, Hanson R, et al. Recurrent CT, cumulative radiation exposure, and associated radiation-induced cancer risks from CT of adults. Radiology. 2009;251(1):175–84.

    Article  PubMed  Google Scholar 

  45. Huang B, Li J, Law MW, Zhang J, Shen Y, Khong PL. Radiation dose and cancer risk in retrospectively and prospectively ECG-gated coronary angiography using 64-slice multidetector CT. Br J Radiol. 2010;83(986):152–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Huda W, Schoepf UJ, Abro JA, Mah E, Costello P. Radiation-related cancer risks in a clinical patient population undergoing cardiac CT. AJR Am J Roentgenol. 2011;196(2):W159–65.

    Article  PubMed  Google Scholar 

  47. Perisinakis K, Seimenis I, Tzedakis A, Papadakis AE, Damilakis J. Triple-rule-out computed tomography angiography with 256-slice computed tomography scanners: patient-specific assessment of radiation burden and associated cancer risk. Investig Radiol. 2012;47(2):109–15.

    Article  Google Scholar 

  48. Einstein AJ, Henzlova MJ, Rajagopalan S. Estimating risk of cancer associated with radiation exposure from 64-slice computed tomography coronary angiography. JAMA. 2007;298(3):317–23.

    Article  CAS  PubMed  Google Scholar 

  49. Kim KP, Einstein AJ, Berrington de Gonzalez A. Coronary artery calcification screening: estimated radiation dose and cancer risk. Arch Intern Med. 2009;169(13):1188–94.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Majer M, Knezevic Z, Popic J, Hrsak H, Miljanic S. Organ doses and associated cancer risks for computed tomography examinations of the thoracic region. Nuclear Technol Rad Protect. 2018;33(1):100–5.

    Article  CAS  Google Scholar 

  51. Salibi PN, Agarwal V, Panczykowski DM, Puccio AM, Sheetz MA, Okonkwo DO. Lifetime attributable risk of cancer from CT among patients surviving severe traumatic brain injury. AJR Am J Roentgenol. 2014;202(2):397–400.

    Article  PubMed  Google Scholar 

  52. Shah KH, Slovis BH, Runde D, Godbout B, Newman DH, Lee J. Radiation exposure among patients with the highest CT scan utilization in the emergency department. Emerg Radiol. 2013;20(6):485–91.

    Article  PubMed  Google Scholar 

  53. Wylie JD, Jenkins PA, Beckmann JT, Peters CL, Aoki SK, Maak TG. Computed Tomography Scans in Patients With Young Adult Hip Pain Carry a Lifetime Risk of Malignancy. Arthroscopy: The Journal of Arthroscopic & Related Surgery. 2018;34(1):155–163.e153.

    Article  Google Scholar 

  54. Olsen M, Garne E, Svaerke C, Sondergaard L, Nissen H, Andersen HO, et al. Cancer risk among patients with congenital heart defects: a nationwide follow-up study. Cardiol Young. 2014;24(1):40–6.

    Article  PubMed  Google Scholar 

  55. Meulepas JM, Hauptmann M, Lubin JH, Shuryak I, Brenner DJ. Is there Unmeasured Indication Bias in Radiation-Related Cancer Risk Estimates from Studies of Computed Tomography? Radiat Res. 2018;189(2):128–35.

    Article  CAS  PubMed  Google Scholar 

  56. Wu TH, Lin WC, Chen WK, Chang YC, Hwang JJ. Predicting cancer risks from dental computed tomography. J Dent Res. 2015;94(1):27–35.

    Article  PubMed  Google Scholar 

  57. Bosch de Basea M, Morina D, Figuerola J, Barber I, Muchart J, Lee C, et al. Subtle excess in lifetime cancer risk related to CT scanning in Spanish young people. Environ Int. 2018;120:1–10.

    Article  PubMed  Google Scholar 

  58. Hendry JH, Simon SL, Wojcik A, Sohrabi M, Burkart W, Cardis E, et al. Human exposure to high natural background radiation: what can it teach us about radiation risks? J Radiol Prot. 2009;29(2A):A29–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021.

  60. Brenner DJ, Doll R, Goodhead DT, Hall EJ, Land CE, Little JB, et al. Cancer risks attributable to low doses of ionizing radiation: assessing what we really know. Proc Natl Acad Sci U S A. 2003;100(24):13761–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Hauptmann M, Daniels RD, Cardis E, Cullings HM, Kendall G, Laurier D, et al. Epidemiological Studies of Low-Dose Ionizing Radiation and Cancer: Summary Bias Assessment and Meta-Analysis. J Natl Cancer Inst Monogr. 2020;2020(56):188–200.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Pierce DA, Shimizu Y, Preston DL, Vaeth M, Mabuchi K. Studies of the mortality of atomic bomb survivors. Report 12, Part I. Cancer: 1950-1990. Radiat Res. 1996;146(1):1–27.

    Article  CAS  PubMed  Google Scholar 

  63. Siegel JA, Greenspan BS, Maurer AH, Taylor AT, Phillips WT, Van Nostrand D, et al. The BEIR VII Estimates of Low-Dose Radiation Health Risks Are Based on Faulty Assumptions and Data Analyses: A Call for Reassessment. J Nucl Med. 2018;59(7):1017–9.

    Article  CAS  PubMed  Google Scholar 

  64. In: Global Recommendations on Physical Activity for Health. edn. Geneva; 2010.

  65. Mavragani IV, Laskaratou DA, Frey B, Candeias SM, Gaipl US, Lumniczky K, et al. Key mechanisms involved in ionizing radiation-induced systemic effects. A current review. Toxicol Res (Camb). 2016;5(1):12–33.

    Article  PubMed  Google Scholar 

  66. Mavragani IV, Nikitaki Z, Souli MP, Aziz A, Nowsheen S, Aziz K, et al. Complex DNA Damage: A Route to Radiation-Induced Genomic Instability and Carcinogenesis. Cancers (Basel). 2017;9(7).

  67. Hellweg CE. The Nuclear Factor kappaB pathway: A link to the immune system in the radiation response. Cancer Lett. 2015;368(2):275–89.

    Article  CAS  PubMed  Google Scholar 

  68. Cui J, Yang G, Pan Z, Zhao Y, Liang X, Li W, et al. Hormetic Response to Low-Dose Radiation: Focus on the Immune System and Its Clinical Implications. Int J Mol Sci. 2017;18(2).

  69. Alexakhin RM. Radiation, United Nations Scientific Committee on the Effects of Atomic 2008. Radiats Biol Radioecol. 2015;55(5):548–9.

    CAS  PubMed  Google Scholar 

  70. Arem H, Loftfield E. Cancer Epidemiology: A Survey of Modifiable Risk Factors for Prevention and Survivorship. Am J Lifestyle Med. 2018;12(3):200–10.

    Article  PubMed  Google Scholar 

  71. Metcalfe KA, Poll A, Royer R, Llacuachaqui M, Tulman A, Sun P, et al. Screening for founder mutations in BRCA1 and BRCA2 in unselected Jewish women. J Clin Oncol. 2010;28(3):387–91.

    Article  CAS  PubMed  Google Scholar 

  72. Hunter DJ, Colditz GA, Hankinson SE, Malspeis S, Spiegelman D, Chen W, et al. Oral contraceptive use and breast cancer: a prospective study of young women. Cancer Epidemiol Biomark Prev. 2010;19(10):2496–502.

    Article  Google Scholar 

  73. La Vecchia C, Tavani A. Female hormones and benign liver tumours. Dig Liver Dis. 2006;38(8):535–6.

    Article  PubMed  Google Scholar 

  74. Katzke VA, Kaaks R, Kuhn T. Lifestyle and cancer risk. Cancer J. 2015;21(2):104–10.

    Article  PubMed  Google Scholar 

  75. Song M, Giovannucci E. Preventable Incidence and Mortality of Carcinoma Associated With Lifestyle Factors Among White Adults in the United States. JAMA Oncol. 2016;2(9):1154–61.

    Article  PubMed  PubMed Central  Google Scholar 

  76. Pearce MS, Salotti JA, McHugh K, Kim KP, Craft AW, Lubin J, et al. Socio-economic variation in CT scanning in Northern England, 1990-2002. BMC Health Serv Res. 2012;12:24.

    Article  PubMed  PubMed Central  Google Scholar 

  77. White MK, Pagano JS, Khalili K. Viruses and human cancers: a long road of discovery of molecular paradigms. Clin Microbiol Rev. 2014;27(3):463–81.

    Article  PubMed  PubMed Central  Google Scholar 

  78. Munoz N, Castellsague X, de Gonzalez AB, Gissmann L. Chapter 1: HPV in the etiology of human cancer. Vaccine. 2006;24(Suppl 3):S3/1–10.

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Not application.

Availability of data and material

All data generated or analyzed during this study are included in this published article and its supplementary information files.

Funding

This work was supported by the National Natural Science Foundation of China (Grant number: 81572182 to HQW) and Shaanxi provincial key research and development program (Grant number: 2021SF-353 to JZ). The funding bodies played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

Author information

Authors and Affiliations

  1. Department of Orthopedics, Yongchuan Hospital of Chongqing Medical University, Hua Road, No. 439, Yongchuan, 402160, Chongqing, People’s Republic of China

    Chun-Feng Cao & Kun-Long Ma

  2. Institute of Integrative Medicine, Shaanxi University of Chinese Medicine, Xixian Avenue, Xixian District, Xi’an, 712046, Shaanxi Province, People’s Republic of China

    Hua Shan, Tang-Fen Liu & Hai-Qiang Wang

  3. Department of Orthopedics, No.1 Hospital of Xi’an City, Northwestern University, Xi’an, 710002, Shaanxi Province, People’s Republic of China

    Si-Qiao Zhao

  4. Department of Health Services, Fourth Military Medical University, Xi’an, 710032, No.169 West Changle Road, Shaanxi Province, People’s Republic of China

    Yi Wan

  5. Baoji Central Hospital, 8 Jiangtan Road, Baoji, 721008, Shaanxi Province, People’s Republic of China

    Jun-Zhang

  6. School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an, 710061, Shaanxi Province, People’s Republic of China

    Jun-Zhang

Authors
  1. Chun-Feng Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kun-Long Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hua Shan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tang-Fen Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Si-Qiao Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yi Wan
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jun-Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Hai-Qiang Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

HQW had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: CFC and HQW. Acquisition of data: CFC, HS, SQZ, and TFL. Analysis and interpretation of data: CFC, YW, and HQW. Drafting of the manuscript: CFC, KLM, and JZ. Critical revision of the manuscript for important intellectual content: HQW. Administrative, technical, or material support: HQW. All authors have read and approved the manuscript.

Corresponding author

Correspondence to Hai-Qiang Wang.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1 Table S1.

Search strategy and results

Additional file 2 Table S2.

Contacting authors for additional information

Additional file 3 Table S3A.

Newcastle-Ottawa Quality Assessment Scale – Case–control studies. (.docx). Table S3B. Newcastle-Ottawa Quality Assessment Scale – Cohort studies

Additional file 4 Table S4.

Ionizing radiation and cancer risks sensitivity analysis

Additional file 5 Table S5.

Meta regression analysis

Additional file 6 Fig. S1.

Bubble plot depicting the relationship between “dose” as radiation to CT scans and “response” as cancer risks

Additional file 7 Fig. S2.

Forest plot of cancer risk at different doses from CT scans

Additional file 8 Fig. S3.

Forest plot of cancer risks at radiation doses from CT radiation exposure in age groups (A: <45 years; B: 45 to 65 years)

Additional file 9 Video. The association of cumulative ionizing radiation from CT scans with pertinent cancer risks in adults. (.mp4) (The source of the images included in the video are original.)

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cao, CF., Ma, KL., Shan, H. et al. CT Scans and Cancer Risks: A Systematic Review and Dose-response Meta-analysis. BMC Cancer 22, 1238 (2022). https://doi.org/10.1186/s12885-022-10310-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12885-022-10310-2

Keywords

  • Computed tomography
  • Adult
  • Cancer risk
  • Radiation exposure
  • Meta-analysis

BMC Cancer

ISSN: 1471-2407

Contact us