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Open Physics

formerly Central European Journal of Physics

Editor-in-Chief: Seidel, Sally

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Volume 15, Issue 1


Volume 13 (2015)

Radiation dose and cancer risk estimates in helical CT for pulmonary tuberculosis infections

Bamise Adeleye
  • School of Chemistry & Physics, University of KwaZulu-Natal, Pietermaritzburg Campus, Private Bag X01, Scottsville 3209, South Africa
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Naven Chetty
  • Corresponding author
  • School of Chemistry & Physics, University of KwaZulu-Natal, Pietermaritzburg Campus, Private Bag X01, Scottsville 3209, South Africa
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2017-12-29 | DOI: https://doi.org/10.1515/phys-2017-0090


The preference for computed tomography (CT) for the clinical assessment of pulmonary tuberculosis (PTB) infections has increased the concern about the potential risk of cancer in exposed patients. In this study, we investigated the correlation between cancer risk and radiation doses from different CT scanners, assuming an equivalent scan protocol. Radiation doses from three 16-slice units were estimated using the CT-Expo dosimetry software version 2.4 and standard CT scan protocol for patients with suspected PTB infections. The lifetime risk of cancer for each scanner was determined using the methodology outlined in the BEIR VII report. Organ doses were significantly different (P < 0.05) between the scanners. The calculated effective dose for scanner H2 is 34% and 37% higher than scanners H3 and H1 respectively. A high and statistically significant correlation was observed between estimated lifetime cancer risk for both male (r2 = 0.943, P < 0.05) and female patients (r2 = 0.989, P < 0.05). The risk variation between the scanners was slightly higher than 2% for all ages but was much smaller for specific ages for male and female patients (0.2% and 0.7%, respectively). These variations provide an indication that the use of a scanner optimizing protocol is imperative.

Keywords: Pulmonary tuberculosis; Computed tomography; Radiation dose; Lifetime attributable risk of cancer

PACS: 87.57.Q; 87.57.uq

1 Introduction

Tuberculosis (TB) is an infection caused by Mycobacterium tuberculosis and is one of the leading causes of mortality and morbidity in the world. The World Health Organization (WHO) global tuberculosis report (2014) estimated that 9.0 million people developed TB in 2013, of which 1.5 million died [1]. Pulmonary tuberculosis (PTB), classified as primary and post-primary (reactivation), is considered to be the most infective form of the disease, and it occurs in more than 80% of TB cases [2, 3]. To date, tuberculosis remains endemic in most of the developing countries and countries with high rates of infection with human immunodeficiency virus (HIV), including South Africa. The estimated incidence of undiagnosed active TB infection in South Africa is 450,000 patients [1, 4]. The KwaZulu-Natal province, where HIV infection rates are high, has been the most affected region, accounting for 22% (99,067) of the patients. The WHO report indicates that this rate represents an increase of approximately 400% over the past 15 years [1] and represents the third highest infection rate of any country worldwide after India and China. This high rate is largely attributed to both late and poor diagnosis and leads to delays in the appropriate treatment of infected patients. To date, the mainstay for the diagnosis of adult chest TB is the identification of acid-fast bacilli (AFB) by sputum smear microscopy. However, previous studies have shown that acid-fast bacilli are found in the sputum of a limited number of patients (20% – 55%) with active pulmonary TB [5]. Moreover, smear microscopy results are available within days, while the culture results of M. tuberculosis from sputum requires (3 – 8) weeks for results, primarily because of the slow growth of the organism [6]. These limitations have increased the importance of medical imaging as a diagnostic procedure for the evaluation of suspected TB and PTB. Despite the increased doses of radiation compared with radiography and the need for the administration of intravenous contrast agent, CT remains the method of choice for the diagnosis of primary and postprimary PTB [3, 7]. CT is more sensitive than chest radiography for making the diagnosis and characterizing the cases of both subtle and disseminated parenchymal disease and mediastinal lymphadenopathy that are predominantly situated in peripheral subregions. CT is also more sensitive for the evaluation of cases of tuberculous effusion, emphysema, and bronchopleural fistula that are not evident on plain radiographs [8, 9, 10, 11, 12]. The increased use of CT, and in particular helical CT, for higher resolution and higher definition of internal structures for the diagnosis of suspected PTB before treatment, has raised concerns about the radiation dose and associated cancer risk for exposed individuals. Although the risk for the general population is small and non-uniform, a previous study has shown that an increase in the exposure to ionizing radiation potentially increases the risk of cancer [13]. Therefore, considering the increase in TB prevalence in the general population, consequent increase in exposure to ionizing radiation from diagnostic testing, and the use of generic protocols by imaging professional, our study aimed to estimate CT radiation doses with the risk of cancer from different 16-slice models, and investigate their correlation, assuming equivalent scan protocol. It is also anticipated that the study will help to understand the benefits of optimizing protocols for imaging technique.

2 Materials and Methods

CT models and protocols

The following 16-detector row scanners based on our survey were included in this study: (i) the Toshiba Aquilion 16 (Toshiba Medical Systems) (ii) the GE LightSpeed 16 (General Electric Medical Systems, Milwaukee, WI) and (iii) the Somatom Sensation 16 (Siemens Healthcare, Germany). Routine scan protocol for patients with suspected PTB infections in an institution in the KwaZulu-Natal province was followed. Patients were scanned at 120 kVp, using an electrical current (mA) setting adapted to the patient’s weight up to a maximum of 200 mA for patients with larger body habitus to ensure proper pathologic findings of structures in the lungs and acceptable diagnostic image quality. Images were reconstructed at a slice thickness of either 3 mm or 5 mm. Although exposure parameters were modified to lower the radiation exposure of patients, the parameters mentioned above represented the standard scanning protocols largely employed. For purposes of privacy protection, the scanners were coded randomly as H1 - H3.

Dose assessment

Organ-specific doses were estimated using the CT-Expo (version 2.4) dosimetry software with adult male phantoms (ADAM; 170-cm height and 70-kg weight) and adult female phantoms (EVA; 160-cm height and 60-kg weight)[14]. CT-Expo is a Microsoft Excel application that allows the computation of age- and sex-specific radiation (organ and effective) doses on the basis of the inputted scanner model, manufacturer, scanning parameters, and scanned area using one of four anthropomorphic mathematical phantoms (ADAM, EVA, CHILD, and BABY) and organ dose data generated by Monte Carlo simulation methods [15, 16]. The mathematical phantoms allowed us to indicate precisely the prescribed anatomical range and obtain more accurate radiation dose estimation for CT examinations as there is no underestimation issue from insufficient voxel images sampling. Simulations were performed in each scanner using the maximum mA and standard scanning parameters settings (Table 1), and anatomic regions (Table 2). We selected the widest X-ray beam width or maximum available detector channels in each scanner, the rotation time of 1 second, slice thickness of 5 mm, and related spiral pitch factor for ease of comparison.

Table 1

Summary of the technical parameters used in three 16- slice computed tomography scanners evaluated in this study.

Table 2

Anatomical extent of computed tomographic examinations using CT-Expo mathematical phantoms

The volume CT dose index (CTDIvol) is a standardized value of the respective radiation output of each scanner measured in a 32-cm diameter acrylic phantom with helical scanning mode. The product of the volume CT dose index (CTDIvol) and the irradiated scan length (L) is the dose-length product (DLP), which represents a measure of the total energy delivered to a patient from a specific CT acquisition. DLPs value for each scanner was averaged over the male and female patient phantoms. The effective dose E was calculated on the basis of tissue weighting factors, as detailed in publication 103 from the International Commission on Radiological Protection (ICRP). CTDIvol, the corresponding value of DLP (in mGycm) and effective dose E were determined using the CT Expo dosimetry software version 2.4[14].

Calculation of the attributable risk of cancer

The lifetime attributable risk (LAR) of cancer incidence, which indicates the risk of developing whole-body or organ-specific cancer for each sex after radiation exposure at a certain age, was estimated using Table 12D-1 of the phase 2 report of the National Academies Committee on the Biological Effects of Ionizing Radiation (BEIR) VII [17]. The LAR was estimated on the basis of protocols employed during the scans and the scanner type. Organ-specific LARs were determined from organ-equivalent doses using a linear no-threshold assumption for the organs specified in the BEIR report. Whole-body LAR was calculated by summation of organ-specific LARs for the various organs and adding a composite equivalent dose for other malignancies not included in the BEIR report. The linear interpolation of the two nearest ages was performed for cases in which organ-specific risk factors for a specific age were not available. The risk estimation method described above has been used in several studies to estimate the cancer risk from CT radiation [18, 19, 20].

Statistical analysis

A one-way analysis of variance (ANOVA) was used to determine significant differences in organ doses between the sexes and scanners. The relationship between the estimated cancer risk for male and female patients in all scanners was analyzed by linear regression. All statistical analyses were performed using Origin software version 6.1 [21] and Microsoft Excel 2013 at a significance level of 0.05.

3 Results

Organ-specific and effective doses

Table 3 shows the estimated equivalent doses in radiosensitive organs with a strong proclivity for carcinogenesis according to the BEIR VII report [17], including directly exposed and adjacent organs for the three 16-slice CT models. Significant differences in radiation doses were observed between the different scanners for male (P = 0.048, F = 2.746) as well as female patients (P = 0.035, F = 2.989). Overall, scanner H2 produced the highest doses compared with the other models, especially in organs such as the heart, lungs, and breast for female patients within the field of view. Variability in organ doses was observed, particularly because of differences in detector collimation and pitch ratio, despite the use of equivalent scanning parameters [22]. Effective dose (De) values (calculated on the basis of tissue weighting factors and averaging between patients for each acquisition and scanner type, as detailed in ICRP 103 [23]), were highest for scanner H2 (11.1mSv), followed by H3 (7.35 mSv), and scanner H1 (7.00 mSv). The CTDIvol, which indicates the radiation output, particularly for scanners operating in helical mode, obtained using the selected acquisition parameters was highest for scanner H2 (16.3 mGy) and lowest for the scanner H1 (12.2 mGy). These observed disparities are likely due to the relationship between CTDIvol and the pitch ratio of different CT models, which affects the X-ray beam width and table feed per gantry rotation in helical scanning [24].

Table 3

Estimated dose (mSv) from a single helical CT scan for diagnosis of pulmonary tuberculosis with three 16-slice scanners

Attributable risk of cancer

The LAR of cancer incidence for each scanner for the ages considered is shown in Figure 1 and Figure 2. The LAR varied slightly according to a patient’s age, sex, and scanner type, and a typically high risk was observed with the scanner H2. For a 20-year-old woman, the LARs of 1 in 106, 1 in 172, and 1 in 170 were associated with scanners H2, H3, and H1 respectively. For a 20-year-old man, the LARs of 1 in 143, 1 in 237, and 1 in 228 were associated with the scanner H2, the H3, and H1, respectively. Pearson correlation and linear regression analysis of estimated risk for the different 16-slice units revealed a high and statistically significant correlation (r2 = 0.943, P < 0.05) and (r2 = 0.989, P < 0.05) between cancer risk for male and female patients, but a negative correlation between cancer risk and age, indicating a lower risk of cancer for older patients. The negative correlation between cancer risk and age is attributed primarily to the BEIR VII risk models [17] and corresponded to a risk reduction of approximately 63% (73% with the scanner H2) for a 50-year-old male patient and 66% for a 50- year-old female patient, relative to a 15 -year-old male and female patient, for all scanners. The relative variations in the estimated risk between the scanners, calculated as the difference between maximum and minimum values, normalized by the mean, were slightly higher than 2% for all ages but were much smaller for specific ages for both male and female patients (up to 0.2% and 0.7%, respectively). This finding indicates that, despite differences in the scanner models and technologies (pitch and collimation), the correlation between age and cancer risk was similar between the scanners. Overall, the estimated risk in female patients was significantly higher than that in male patients of the same age. Accordingly, the LARs for a 35-year old woman were 0.340%, 0.344%, and 0.546% compared with 0.255%, 0.265%, and 0.421%, respectively, for a 35-year-old man, using scanners H3, H1, and H2, respectively. Tables 4 and 5 summarize the contribution of organs exposed to the highest radiation to whole-body risk. The estimated LARs in these organs were lower than 0.1% for individuals aged 25 years or older, who represented the majority of patients undergoing CT evaluation for PTB disease.

Estimated lifetime risk of cancer with respect to age from a single standard computerized tomography dose for diagnosis of pulmonary tuberculosis infections in male patients
Figure 1

Estimated lifetime risk of cancer with respect to age from a single standard computerized tomography dose for diagnosis of pulmonary tuberculosis infections in male patients

Estimated lifetime risk of cancer with respect to age from a single standard computerized tomography dose for diagnosis of pulmonary tuberculosis infections in female patients
Figure 2

Estimated lifetime risk of cancer with respect to age from a single standard computerized tomography dose for diagnosis of pulmonary tuberculosis infections in female patients

Table 4

The Contributions of organs exposed to the highest radiation (Breasts and Lungs) for female patients

Table 5

The Contributions of organs exposed to the highest radiation (Lungs) for male patients

4 Discussion

In this study, we estimated the probability of developing cancer from radiation produced by three 16-slice CT scanners used in PTB diagnosis and assuming equivalent scan protocol. A small increase in cancer risk at low doses could result in a significant increase in the number of cases of cancer in a population in which many individuals are exposed to radiation [25]. As expected, critical organs (breast and lungs) along with the esophagus, thymus, bone surfaces, thyroid, and heart, which are in the direct path of X-ray beams, absorbed the greatest amount of radiation. Overall, the doses absorbed by these organs lied within the 10 – 30 mGy range reported by Mettler et al. [26] for organs in the direct path of X-ray beams from CT scans. The comparison of average effective dose (De) values for all scanners indicated that the scanner H2 delivers higher dose respect to the other two scanners, while scanners H3 and H1 deliver about the same dose. However, these results were expected and might be partly explained by technique parameters, such as tube current – time product (mAs) settings, the contrasting scanner geometry of the CT models as well as the correlation between the table feed per 360° rotation of the x-ray tube, beam collimation and pitch factor in helical scanning. For scanner geometry, the relative positions of the x-ray source (focal spot in the tube) and the center of rotation (isocenter) significantly affect the absorbed dose in a patient. This follows from the inverse square law, radiation intensity varies as the inverse of the squared distance between the radiation source and point of measurement and might explain the slight difference in radiation dose between the scanners H1 and H3 with a focal spot to an isocenter distance of 535 and 541 mm respectively. It is, however, noteworthy that for the scanner H2, despite a longer focal spot to isocenter distance and lowest effective milliampere-second setting in contrast to other CT models, delivered the highest radiation dose. This finding demonstrates the influence of selected scan parameters. While examinations perform at a higher pitch like in the scanner H2 is found to generally reduce radiation exposure [27], the use of effective mAs (mAs/pitch) setting by the scanner means that the effect of high pitch on dose is negated by a proportional increase in tube current to maintain similar image noise thereby increasing radiation dose given the linear relationship between tube current and absorbed dose. A combination of the relatively high electrical current (mA) and tube rotation time (seconds) values used could also explain the high radiation dose observed in some scanners particularly the H2. Patient dose is found to decrease linearly with a reduction in either the tube rotation time (faster gantry rotation) or current [28, 29]. Modification of the tube current-time product (mAs) is essential for reducing radiation dose. If the electrical current is increased the gantry rotation time must be reduced by the same factor to compensate for the increased milliampere value in order not to increase radiation dose. Overranging and Overbeaming or penumbra effect are also possible contributors to the high radiation doses. Overbeaming is the excess radiation exposure beyond the collimated beam in the z-direction. Overranging refers to the increase in the dose-length product beyond the volume imaged in helical CT owing to the additional rotations that are required in spiral interpolation algorithms. Both effects depend strongly on beam collimation (the number of data channels multiplied by the effective detector row thickness) and additionally the pitch and scan length for overranging effect [30]. It is noted that the greater the number of detectors the wider the beam width that can be obtained. This is consistent with the results indicated in Table 3 where the maximum DLP value was for the scanner H2 at 589 mGycm. Choosing a collimation that is unnecessarily narrow will increase overbeaming but reduce the overranging effect. Conversely, a wider collimation, high pitch, and short scan length such as in some scanners for this study increases overranging but decrease the overbeaming effect. Therefore to reduce dose a relative adjustment of beam collimation and helical pitch must be made for the patient size and specific clinical problem. These results highlight the need for caution in transferring scan parameters from one scanner to another and the maintenance of image quality at the lowest radiation dose, depending on scanner characteristics [31]. In general, the effective doses in each scanner were within the range of 4.0–18.0 mSv reported in the literature for a full diagnostic helical chest CT examination [26]. However, it is of note that the same effective dose does not correspond to the same cancer risk [32], and this is evidenced by the significantly higher estimated whole-body risk using the scanner H1 compared with the scanner H3, which produced a higher effective dose. The higher estimated risk in female patients than in male patients is attributed to the additional risk of breast cancer together with the increased risk of lung cancer [18, 25]. The overall decrease in LAR with increasing age at exposure (Figure 1 and Figure 2) is in agreement with the results of other studies [20, 22] where LAR also declined with increasing age. Our cancer risk estimates indicated an elevated risk of breast cancer for women younger than 40 years, followed by lung cancer risk. Similarly, in men, the lungs contributed more to the whole-body cancer risk. The relatively high risk in these organs, particularly breasts in women and lungs in men, of up to 0.1432% and 0.0452%, respectively, for patients aged 15 years, could lead to an increase in these malignancies in the population and constitute a potential public health problem, considering the large number of individuals undergoing CT examinations for PTB diagnosis. Although the magnitude of LAR estimates reported here appeared to be relatively low for all age categories, these small doses are not necessarily risk-free. There is reasonable epidemiological evidence that organ doses in the range of 5 to 125 mSv results in a small but statistically significant increase in cancer risk [33, 34]. Therefore, the risk of cancer from radiation exposure should be balanced and weighed against the anticipated benefits obtained from the diagnostic information [35]. Furthermore, exposure should be as low as reasonably achievable [ALARA principle]. The ALARA principle recommends the optimization of the use of X-rays; therefore, high doses should be avoided because they increase the risk of cancer [33, 36]. Several factors significantly influence the risk of developing cancer following radiation exposure, including genetic effects, age at exposure, sex, fractionated exposure, and protraction of exposure [34]. Therefore, additional studies are required to elucidate the effect of these factors. This study has some limitations. First, although the dose depended on the scanner manufacturer and model, the CT dose and the risk estimates reported here were based on anthropomorphic mathematical phantoms, which represented reference-sized adults with specific locations for each organ. Therefore, these results might not be applicable to real patients (or might influence the accuracy of the estimates), whose size differed from those of the designated phantoms [22]. Second, some CT acquisition settings, such as exposure scan time relative to the volume of injected contrast media, which is often used to provide optimally enhanced images, were not selected in this study, which simply considered the standard scanning parameters used in routine examinations. In addition, it has to be emphasized that the effects of automatic exposure control (AEC) systems, particularly angular tube current modulation and image quality reference parameters were not analysed within this study because the CT Expo dosimetry software does not account for these options. However, the use of AEC systems depending on the patient size and specified image quality is likely to cause a reduction in radiation dose at different CT models.

The magnitude of any such changes has been estimated as being about 11% [22]. Finally, uncertainties are reported to be associated with risk estimation by the BEIR VII report, predicated on the linear no-threshold model. As a result, the emphasis in this study is on the relative differences in estimated absolute risk between CT systems defining the same scan protocol.

5 Conclusions

This study showed significant variations in radiation dose and the lifetime attributable cancer risk between 16-slice scanners used in helical CT scan for pulmonary tuberculosis, using equivalent scan protocol for each model. Although the increase in risk was less than 1% irrespective of the CT scanner producing the highest cancer risk, the related increase in cancer are high enough to warrant reconsideration of means to reduce patient exposure. The need for optimized scanner protocols, that is, exposure protocols that lead to an acceptable image quality for patient-specific indication, based on the individual scanner as opposed to current generic practices with an adverse effect on patient cancer risk are imperative. The aim of this study is not to compare the performance of the different 16-Slice scanners, as this cannot be done based on dosimetric results alone. Each scanner depending on settings such as FOV size, image quality, etc., possesses a wide range of application. Therefore the findings of this work only serve to create awareness for CT practitioners of the consequences of transferring protocols between different scanners.


This work was funded by the authors from research allowance given to academic staff of the University of KwaZulu-Natal. No potential conflict of interest is relevant to this article.


  • [1]

    World Health Organization, Global Tuberculosis Report. 2014., Available at: http://www.who.int/tb/publications/globalreport/, Accessed 12. 05. 16 

  • [2]

    De Backer A.I., Mortelé K.J., De Keulenaer, B.L., Parizel P.M., Tuberculosis: Epidemiology, Manifestations, and the Value of Medical imaging in Diagnosis. JBR–BTR., 2006, 89, 243-250. Google Scholar

  • [3]

    Van Dyck P., Vanhoenacker F.M., Van den Brande P., De Schepper A.M., Imaging of pulmonary tuberculosis. Eur Radiol., 2003, 13, 1771-1785. CrossrefGoogle Scholar

  • [4]

    Churchyard G.J., Mametja L.D., Mvusi L., Ndjeka N., Hesseling A.C., Reid A., Babatunde S. and Pillay Y., Tuberculosis control 40 in South Africa: Successes, challenges and recommendations. South African Medical Journal, 2014, 104(3), 244. CrossrefWeb of ScienceGoogle Scholar

  • [5]

    Lee K.S., Im J.G., CT in adults with tuberculosis of the chest .Characteristic findings and role in Management. AJR, 1995, 164, 1361–1367 CrossrefGoogle Scholar

  • [6]

    Foulds J., O’Brien R., New tools for the diagnosis of tuberculosis: The perspective of developing countries. Int J Tuberc Lung Dis., 1998, 2,778-83 Google Scholar

  • [7]

    Van den Brande P., Vanhoenacker F., Demedts M., Tuberculosis at the beginning of the third millennium: one disease, three epidemics. Eur Radiol., 2003, 13, 1767-1770. CrossrefGoogle Scholar

  • [8]

    Christophe D., Tania M.M, Valerie B., Jacques de Blic, Natacha S., Denis L. and Scheinmann P . Computed tomography with normal chest radiograph in tuberculous infection. Arch Dis Child, 1993, 69,430-432 CrossrefGoogle Scholar

  • [9]

    Woodring J.H, Vandiviere H.M., Fried A.M, Dillon M.L, Williams T.D and Melvin IG, Update: the radiographic features of pulmonary tuberculosis. AJR., 1986,146,497-506 CrossrefGoogle Scholar

  • [10]

    McGuiness G., Naidich D.P., Jagirdar J., Leitman B., McCauley Dl., High resolution CT findings in miliary lung disease. J Comput Assist Tomogr. 1992, 16,384-390 CrossrefGoogle Scholar

  • [11]

    Hulnick D.H., Naidich D.P., McCauley D.I. Pleural tuberculosis evaluated by computed tomography. Radiology, 1983, 149,759-765 CrossrefGoogle Scholar

  • [12]

    Kim W.S., Moon W.K., Kim I.O., Lee H.J., Im JG, Yeon KM., et.al., Pulmonary tuberculosis in children: evaluation with CT. American Journal of Roentgenology., 1997, 168, 1005-1009 CrossrefGoogle Scholar

  • [13]

    Brenner D.J., Hall E.J., Computed tomography—an increasing source of radiation exposure. N Engl. J. Med., 2007, 357, 2277-2284 CrossrefGoogle Scholar

  • [14]

    Stamm G., Nagel H.D., CT-Expo Version 2.4. A novel tool for dose evaluation in Computed tomography, 2015 Google Scholar

  • [15]

    Lopez-Rendon X., Bosmans H., Oyen R., Zanca F., Effective dose and organ doses estimation taking tube current modulation into account with a commercial software package. Eur. Radiol., 2015, 25, 1919-1925 CrossrefWeb of ScienceGoogle Scholar

  • [16]

    Kramer R., Zankl M., Williams G., Drexler G., GSF Report, 1982, S-88 Part I Google Scholar

  • [17]

    Biological Effects of Ionizing Radiation Committee. Health risks from exposure to low levels of ionizing radiation, BEIR. VII phase 2. Bethesda: National Research Council, National Academy of Science, 2006. Google Scholar

  • [18]

    Einstein A.J., Henzlova M.J, Rajagopalan S. Estimating risk of cancer associated with radiation exposure from 64-slice computed tomography coronary angiography. JAMA, 2007, 298,317-323 CrossrefWeb of ScienceGoogle Scholar

  • [19]

    Smith-Bindman R., Lipson J., Marcus R., Kim K.P., 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, 2078-2086 CrossrefWeb of ScienceGoogle Scholar

  • [20]

    Tatum V. T., Geoffrey S., Rajesh S., Estimating the Risk of Cancer Associated With Imaging Related Radiation During Surveillance for Stage I Testicular Cancer Using Computerized Tomography. Journal of Urology, 2009, 181(2), 627-633 Web of ScienceCrossrefGoogle Scholar

  • [21]

    Origin Data Analysis and Graphing Software. Origin Lab Corporation, Northampton, USA. Google Scholar

  • [22]

    Walter H., Kent O.M., Mohammad K. R., Converting Dose-Length Product to Effective Dose at CT. Journal of radiological society of North America, 2008, 248(3), 995-1003 Google Scholar

  • [23]

    ICRP. Recommendations of the International Commission on Radiological Protection ICRP publication 103 Ann ICRP 2007, 37, (2–4) Google Scholar

  • [24]

    Huda W., Mettler F.A., Volume CT Dose Index and Dose-length Displayed during CT: what good are they? Journal of radiological society of North America, 2011, 258 (1) Google Scholar

  • [25]

    Berrington G.A., Mahesh M., Kim K.P., 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, 2071-2077. CrossrefGoogle Scholar

  • [26]

    Mettler F.A., Huda W., Yoshizumi T.T., Mahesh M. Effective doses in radiology and diagnostic nuclear medicine: A catalog. Radiology, 2008, 248(1), 254-263. Web of ScienceCrossrefGoogle Scholar

  • [27]

    Vade A., Demos T. C., Olson M.C., Subbaiah P., Turbin R.C., Vickery K., et.al, Evaluation of image quality using 1: 1 pitch and 1.5: 1 pitch helical CT in children: a comparative study. Pediatr Radiol.1996, 26, 891-893 CrossrefGoogle Scholar

  • [28]

    Smergel E., Benson D., Radiation dose on pediatric CT: Loosing track of time. AJR, 2002, 178(2), 507-508 CrossrefGoogle Scholar

  • [29]

    Leena H. M., James R. T., George H. J., James T. H., Multi–Detector Row CT: Radiation Dose Characteristics. Radiology, 2003, 226, 762-772 CrossrefGoogle Scholar

  • [30]

    Hans Nagel D., Significance of overbeaming and overranging effects of single- and multi-slice CT scanners, In: Proceedings of the International Congress on Medical Physics, Nuremburg. 2005, 50, 395-396. Google Scholar

  • [31]

    Madan R.C., Mannudeep K., McCollough C., Nagel HD., Managing Patient Dose in Multi-Detector Computed Tomography (MDCT) 2006, 32, 219. Google Scholar

  • [32]

    McCollough C.H., Christner J.A., Kofler J.M., How effective is effective dose as a predictor of radiation risk? AJR Am J Roentgenol, 2010, 194,890-896 CrossrefGoogle Scholar

  • [33]

    Zanca F., Demeter M., Oyen R., Bosmans H., Excess radiation and organ dose in chest and abdominal CT due to CT acquisition beyond expected anatomical boundaries. Eur Radiol., 2012, 22,779-788 CrossrefWeb of ScienceGoogle Scholar

  • [34]

    Hricak H., Brenner D.J., Adelstein S.J., Frush D.P., Hall E.J., Howell R.W., et.al., Managing radiation use in medical imaging, a multifaceted challenge Radiology, 2011, 258,889-905 CrossrefWeb of ScienceGoogle Scholar

  • [35]

    Walter Huda. Radiation Doses and Risks in Chest Computed Tomography Examinations. Atsjournals, 2007, 4, 316-320 Google Scholar

  • [36]

    Thomas S.L., The ALARA concept in The ALARA Concept in Paediatric CT: Myth or Reality? Radiology, 2002, 223, 5-6 CrossrefGoogle Scholar

About the article

Received: 2017-08-03

Accepted: 2017-09-14

Published Online: 2017-12-29

Ethical approval: This article does not contain any studies with human participants performed by any of the authors.

Citation Information: Open Physics, Volume 15, Issue 1, Pages 769–776, ISSN (Online) 2391-5471, DOI: https://doi.org/10.1515/phys-2017-0090.

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© 2017 B. Adeleye and N. Chetty. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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