Skip to main content
banner image
No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.
1. R. Cierniak, X-Ray Computed Tomography in Biomedical Engineering (Springer, New York, NY, 2011).
2. American Association of Physicists in Medicine, “The measurement, reporting, and management of radiation dose in CT,” AAPM Report No. 96, 2008.
3. O. W. Linton and F. A. Mettler, “National conference on dose reduction in CT, with an emphasis on pediatric patients,” Am. J. Roentgenol. 181, 321329 (2003).
4. C. Lee, K. P. Kim, D. Long, R. Fisher, C. Tien, S. L. Simon, A. Bouville, and W. E. Bolch, “Organ doses for reference adult male and female undergoing computed tomography estimated by Monte Carlo simulations,” Med. Phys. 38, 11961206 (2011).
5. D. A. Schauer and O. W. Linton, “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. 97, 15 (2009).
6. D. J. Brenner, C. D. Elliston, E. J. Hall, and W. E. Berdon, “Estimated risks of radiation-induced fatal cancer from pediatric CT,” Am. J. Roentgenol. 176, 289296 (2001).
7. L. F. Donnelly, K. H. Emery, A. S. Brody, T. Laor, V. M. Gylys-Morin, C. G. Anton, S. R. Thomas, and D. P. Frush, “Minimizing radiation dose for pediatric body applications of single-detector helical CT strategies at a large children's hospital,” Am. J. Roentgenol. 176, 303306 (2001).
8. A. J. Einstein, M. J. Henzlova, and S. Rajagopalan, “Estimating risk of cancer associated with radiation exposure from 64-slice computed tomography coronary angiography,” JAMA, J. Am. Med. Assoc. 298, 317323 (2007).
9. A. Ding, M. M. Mille, T. Liu, P. F. Caracappa, and X. G. Xu, “Extension of RPI-adult male and female computational phantoms to obese patients and a Monte Carlo study of the effect on CT imaging dose,” Phys. Med. Biol. 57, 24412459 (2012).
10. A. C. Turner, D. Zhang, M. Khatonabadi, M. Zankl, J. J. DeMarco, C. H. Cagnon, D. D. Cody, D. M. Stevens, C. H. McCollough, and M. F. McNitt-Gray, “The feasibility of patient size-corrected, scanner-independent organ dose estimates for abdominal CT exams,” Med. Phys. 38, 820829 (2011).
11. X. Li, E. Samei, W. P. Segars, G. M. Sturgeon, J. G. Colsher, and D. P. Frush, “Patient-specific radiation dose and cancer risk for pediatric chest CT,” Radiology 259, 862874 (2011).
12. X. Li, E. Samei, C. H. Williams, W. P. Segars, D. J. Tward, M. I. Miller, J. T. Ratnanather, E. K. Paulson, and D. P. Frush, “Effects of protocol and obesity on dose conversion factors in adult body CT,” Med. Phys. 39, 65506571 (2012).
13. American Association of Physicists in Medicine, “Size-specific dose estimates (SSDE) in pediatric and adult body CT examinations,” AAPM Report No. 204, 2011.
14. J. M. Boone, W. R. Hendee, M. F. McNitt-Gray, and S. E. Seltzer, “Radiation exposure from CT scans: how to close our knowledge gaps, monitor and safeguard exposure—proceedings and recommendations of the Radiation Dose Summit, Sponsored by NIBIB, February 24–25, 2011,” Radiology 265, 544554 (2012).
15. E. Angel, C. V. Wellnitz, M. M. Goodsitt, N. Yaghmai, J. J. DeMarco, C. H. Cagnon, J. W. Sayre, D. D. Cody, D. M. Stevens, and A. N. Primak, “Radiation dose to the fetus for pregnant patients undergoing multidetector CT imaging: Monte Carlo simulations estimating fetal dose for a range of gestational age and patient size1,” Radiology 249, 220227 (2008).
16. J. DeMarco, C. Cagnon, D. Cody, D. Stevens, C. McCollough, J. O’Daniel, and M. McNitt-Gray, “A Monte Carlo based method to estimate radiation dose from multidetector CT (MDCT): cylindrical and anthropomorphic phantoms,” Phys. Med. Biol. 50, 39894004 (2005).
17. C. Lee, C. Lee, R. J. Staton, D. E. Hintenlang, M. M. Arreola, J. L. Williams, and W. E. Bolch, “Organ and effective doses in pediatric patients undergoing helical multislice computed tomography examination,” Med. Phys. 34, 18581873 (2007).
18. D. Jones, P. C. Shrimpton, and G. Britain, Survey of CT Practice in the UK. Part 3: Normalised Organ Doses Calculated Using Monte Carlo Techniques (National Radiological Protection Board, UK, 1991).
19. R. Kramer, M. Zankl, G. Williams, and G. Drexler, The Calculation of Dose from External Photon Exposures using Reference Human Phantoms and Monte Carlo Methods (Gesellschaft fur Strahlen-und Umweltforschung, Neuherberg (Germany), 1991).
20.“ImPACT's CT Dosimetry Tool: CT dosimetry version 1.0.4” (available URL: Last accessed January 2014.
21. G. Jarry, J. DeMarco, U. Beifuss, C. Cagnon, and M. McNitt-Gray, “A Monte Carlo-based method to estimate radiation dose from spiral CT: from phantom testing to patient-specific models,” Phys. Med. Biol. 48, 26452663 (2003).
22. W. Segars, J. Bond, J. Frush, S. Hon, C. Eckersley, C. H. Williams, J. Feng, D. J. Tward, J. Ratnanather, and M. Miller, “Population of anatomically variable 4D XCAT adult phantoms for imaging research and optimization,” Med. Phys. 40, 043701 (11pp.) (2013).
23. W. Segars, G. Sturgeon, S. Mendonca, J. Grimes, and B. Tsui, “4D XCAT phantom for multimodality imaging research,” Med. Phys. 37, 49024915 (2010).
24. D. J. Tward, C. Ceritoglu, A. Kolasny, G. M. Sturgeon, W. P. Segars, M. I. Miller, and J. T. Ratnanather, “Patient specific dosimetry phantoms using multichannel LDDMM of the whole body,” J. Biomed. Imaging 2011, 3.
25. W. Segars, G. Sturgeon, X. Li, L. Cheng, C. Ceritoglu, J. Ratnanather, M. Miller, B. Tsui, D. Frush, and E. Samei, “Patient specific computerized phantoms to estimate dose in pediatric CT,” SPIE Med. Imaging 7258, 72580H (2009).
26. G. L. de la Grandmaison, I. Clairand, and M. Durigon, “Organ weight in 684 adult autopsies: new tables for a Caucasoid population,” Forensic Sci. Int. 119, 149154 (2001).
27.CIRS User Manual” (available URL: Last accessed April, 2014.
28. J. Baro, J. Sempau, J. Fernandez-Varea, and F. Salvat, “PENELOPE: an algorithm for Monte Carlo simulation of the penetration and energy loss of electrons and positrons in matter,” Nucl. Instrum. Methods Phys. Res., Sect. B 100, 3146 (1995).
29. X. Li, E. Samei, W. P. Segars, G. M. Sturgeon, J. G. Colsher, G. Toncheva, T. T. Yoshizumi, and D. P. Frush, “Patient-specific radiation dose and cancer risk estimation in CT: Part I. Development and validation of a Monte Carlo program,” Med. Phys. 38, 397407 (2011).
30. X. Li, E. Samei, W. P. Segars, G. M. Sturgeon, J. G. Colsher, G. Toncheva, T. T. Yoshizumi, and D. P. Frush, “Patient-specific radiation dose and cancer risk estimation in CT: Part II. Application to patients,” Med. Phys. 38, 408419 (2011).
31. J. F. WilliamsonMonte Carlo evaluation of kerma at a point for photon transport problems,” Med. Phys. 14(4), 567576 (1987).
32. M. Cristy and K. F. Eckerman, Specific Absorbed Fractions of Energy at Various Ages from Internal Photon Sources: 1, Methods (Atomic Energy Research Establishment, Oak Ridge, TN: Oak Ridge National Laboratory, 1987).
33. G. D. Kerr, and K. F. Eckerman, “Neutron and photon fluence-to-dose conversion factors for active marrow of the skeleton,” Report No. CONF-8409161-2, Oak Ridge National Lab., TN (USA), 1984.
34. ICRP, “Basic anatomical and physiological data for use in radiological protection: Reference values,” ICRP Publication 89, Ann. ICRP 32 (2002).
35. ICRP. “The 2007 recommendations of the International Commission on Radiological Protection,” ICRP Publication 103, Ann. ICRP 32 (2007).
36. A. C. Turner, M. Zankl, J. J. DeMarco, C. H. Cagnon, D. Zhang, E. Angel, D. D. Cody, D. M. Stevens, C. H. McCollough, and M. F. McNitt-Gray, “The feasibility of a scanner-independent technique to estimate organ dose from MDCT scans: Using CTDI to account for differences between scanners,” Med. Phys. 37, 18161825 (2010).
37. P. Shrimpton, Assessment of Patient Dose in CT (National Radiological Protection Board (NRPB), Chilton, England, 2004).
38. W. Huda, K. M. Ogden, and M. R. Khorasani, “Converting dose-length product to effective dose at CT1,” Radiology 248, 9951003 (2008).
39. M. van Straten, P. Deak, P. C. Shrimpton, and W. A. Kalender, “The effect of angular and longitudinal tube current modulations on the estimation of organ and effective doses in x-ray computed tomography,” Med. Phys. 36, 48814889 (2009).
40. X. Tian, X. Li, W. P. Segars, D. P. Frush, E. K. Paulson, and E. Samei, “Dose coefficients in pediatric and adult abdominopelvic CT based on 100 patient models,” Phys. Med. Biol. 58(24), 87558768 (2013).
41. R. L. Dixon and J. M. Boone, “Dose equations for tube current modulation in CT scanning and the interpretation of the associated CTDIvol,” Med. Phys. 40, 111920 (42pp.) (2013).
42. E. L. Nickoloff, A. K. Dutta, and Z. F. Lu, “Influence of phantom diameter, kVp and scan mode upon computed tomography dose index,” Med. Phys. 30, 395402 (2003).
43. W. Huda, J. V. Atherton, D. E. Ware, and W. A. Cumming, “An approach for the estimation of effective radiation dose at CT in pediatric patients,” Radiology 203, 417422 (1997).
44. O. Christianson, X. Li, D. Frush, and E. Samei, “Automated size-specific CT dose monitoring program: Assessing variability in CT dose,” Med. Phys. 39, 71317139 (2012).
45. K. E. Thomas and B. Wang, “Age-specific effective doses for pediatric MSCT examinations at a large children's hospital using DLP conversion coefficients: a simple estimation method,” Pediatr. Radiol. 38, 645656 (2008).
46. P. D. Deak, Y. Smal, and W. A. Kalender, “Multisection CT protocols: Sex-and age-specific conversion factors used to determine effective dose from dose-length product 1,” Radiology 257, 158166 (2010).
47.See supplementary material at for Table II. Fitting parameters (α, β), root-mean-square from the residual, and the mean value for h factor for each protocol-organ combination. [Supplementary Material]

Data & Media loading...


Article metrics loading...



This study aimed to provide a comprehensive patient-specific organ dose estimation across a multiplicity of computed tomography (CT) examination protocols.

A validated Monte Carlo program was employed to model a common CT system (LightSpeed VCT, GE Healthcare). The organ and effective doses were estimated from 13 commonly used body and neurological CT examination. The dose estimation was performed on 58 adult computational extended cardiac-torso phantoms (35 male, 23 female, mean age 51.5 years, mean weight 80.2 kg). The organ dose normalized by CTDI ( factor) and effective dose normalized by the dose length product (DLP) ( factor) were calculated from the results. A mathematical model was derived for the correlation between the and factors with the patient size across the protocols. Based on this mathematical model, a dose estimation iPhone operating system application was designed and developed to be used as a tool to estimate dose to the patients for a variety of routinely used CT examinations.

The organ dose results across all the protocols showed an exponential decrease with patient body size. The correlation was generally strong for the organs which were fully or partially located inside the scan coverage (Pearson sample correlation coefficient () of 0.49). The correlation was weaker for organs outside the scan coverage for which distance between the organ and the irradiation area was a stronger predictor of dose to the organ. For body protocols, the effective dose before and after normalization by DLP decreased exponentially with increasing patient's body diameter ( > 0.85). The exponential relationship between effective dose and patient's body diameter was significantly weaker for neurological protocols ( < 0.41), where the trunk length was a slightly stronger predictor of effective dose (0.15 < < 0.46).

While the most accurate estimation of a patient dose requires specific modeling of the patient anatomy, a first order approximation of organ and effective doses from routine CT scan protocols can be reasonably estimated using size specific factors. Estimation accuracy is generally poor for organ outside the scan range and for neurological protocols. The dose calculator designed in this study can be used to conveniently estimate and report the dose values for a patient across a multiplicity of CT scan protocols.


Full text loading...


Access Key

  • FFree Content
  • OAOpen Access Content
  • SSubscribed Content
  • TFree Trial Content
752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd