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Pediatric head computed tomography with advanced modeled iterative reconstruction: focus on image quality and reduction of radiation dose

  • Hyun-Hae ChoEmail author
  • So Mi Lee
  • Sun Kyoung You
Original Article

Abstract

Background

Iterative reconstruction has become the standard method for reconstructing computed tomography (CT) scans and needs to be verified for adaptation.

Objective

To assess the image quality after adapting advanced modeled iterative reconstruction (ADMIRE) for pediatric head CT.

Materials and methods

We included image sets with filtered back projection reconstruction (the cFBP group, n=105) and both filtered back projection and ADMIRE reconstruction (the lower-dose group, n=109) after dose reduction. All five strength levels of ADMIRE and filtered back projection were adapted for the lower-dose group and compared with the cFBP group. Quantitative parameters including noise, signal-to-noise ratio and contrast-to-noise ratio and qualitative parameters including noise, white matter and gray matter differentiation of the supra- and infratentorial levels, sharpness, artifact, and diagnostic accuracy were also evaluated and compared with interobserver agreement.

Results

There was a mean dose reduction of 30.6% in CT dose index volume, 32.1% in dose length product, and 32.1% in effective dose after tube current reduction. There was gradual reduction of noise in air, cerebrospinal fluid and white matter with strength levels of ADMIRE from 1 to 5 (P<0.001). Signal-to-noise ratio and contrast-to-noise ratio in all age groups increased among strength levels of ADMIRE, in sequence from 1 to 5, with statistical significance (P<0.001). Gradual reduction of qualitative parameters was noted among strength levels of ADMIRE in sequence from 1 to 5 (P<0.001).

Conclusion

Use of ADMIRE for pediatric head CT can reduce radiation dose without degrading image quality.

Keywords

Brain Children Computed tomography Image quality Iterative reconstruction Radiation dose 

Notes

Compliance with ethical standards

Conflicts of interest

None

References

  1. 1.
    McKnight CD, Watcharotone K, Ibrahim M et al (2014) Adaptive statistical iterative reconstruction: reducing dose while preserving image quality in the pediatric head CT examination. Pediatr Radiol 44:997–1003CrossRefGoogle Scholar
  2. 2.
    Brenner DJ, Hall EJ (2007) Computed tomography--an increasing source of radiation exposure. N Engl J Med 357:2277–2284CrossRefGoogle Scholar
  3. 3.
    Solomon J, Mileto A, Ramirez-Giraldo JC, Samei E (2015) Diagnostic performance of an advanced modeled iterative reconstruction algorithm for low-contrast detectability with a third-generation dual-source multidetector CT scanner: potential for radiation dose reduction in a multireader study. Radiology 275:735–745CrossRefGoogle Scholar
  4. 4.
    Beister M, Kolditz D, Kalender WA (2012) Iterative reconstruction methods in X-ray CT. Phys Med 28:94–108CrossRefGoogle Scholar
  5. 5.
    Ramirez-Giraldo J, Grant K, Schmidt B, Fuld MK (2014) Radiation dose optimization technologies in multidetector computed tomography: a review. Medical Physics 2:420–430Google Scholar
  6. 6.
    The 2007 recommendations of the International 456 Commission on Radiological Protection. ICRP publication 103. 457 Ann ICRP 37:1–332Google Scholar
  7. 7.
    Deak PD, Smal Y, Kalender WA (2010) Multisection CT protocols: sex- and age-specific conversion factors used to determine effective dose from dose-length product. Radiology 257:158–166CrossRefGoogle Scholar
  8. 8.
    Kilic K, Erbas G, Guryildirim M et al (2013) Quantitative and qualitative comparison of standard-dose and low-dose pediatric head computed tomography: a retrospective study assessing the effect of adaptive statistical iterative reconstruction. J Comput Assist Tomogr 37:377–381CrossRefGoogle Scholar
  9. 9.
    Mullins ME, Lev MH, Bove P et al (2004) Comparison of image quality between conventional and low-dose nonenhanced head CT. AJNR Am J Neuroradiol 25:533–538PubMedGoogle Scholar
  10. 10.
    Kilic K, Erbas G, Guryildirim M et al (2011) Lowering the dose in head CT using adaptive statistical iterative reconstruction. AJNR Am J Neuroradiol 32:1578–1582CrossRefGoogle Scholar
  11. 11.
    Korn A, Fenchel M, Bender B et al (2012) Iterative reconstruction in head CT: image quality of routine and low-dose protocols in comparison with standard filtered back-projection. AJNR Am J Neuroradiol 33:218–224CrossRefGoogle Scholar
  12. 12.
    Rivers-Bowerman MD, Shankar JJ (2014) Iterative reconstruction for head CT: effects on radiation dose and image quality. Can J Neurol Sci 41:620–625CrossRefGoogle Scholar
  13. 13.
    Ono S, Niwa T, Yanagimachi N et al (2016) Improved image quality of helical computed tomography of the head in children by iterative reconstruction. J Neuroradiol 43:31–36CrossRefGoogle Scholar
  14. 14.
    Simon B, Letourneau P, Vitorino E, McCall J (2001) Pediatric minor head trauma: indications for computed tomographic scanning revisited. J Trauma 51:231–237CrossRefGoogle Scholar
  15. 15.
    Rompel O, Glockler M, Janka R et al (2016) Third-generation dual-source 70-kVp chest CT angiography with advanced iterative reconstruction in young children: image quality and radiation dose reduction. Pediatr Radiol 46:462–472CrossRefGoogle Scholar
  16. 16.
    Linet MS, Kim KP, Rajaraman P (2009) Children’s exposure to diagnostic medical radiation and cancer risk: epidemiologic and dosimetric considerations. Pediatr Radiol 39:S4–S26Google Scholar
  17. 17.
    Khawaja RD, Singh S, Otrakji A et al (2015) Dose reduction in pediatric abdominal CT: use of iterative reconstruction techniques across different CT platforms. Pediatr Radiol 45:1046–1055CrossRefGoogle Scholar
  18. 18.
    Goske MJ, Applegate KE, Boylan J et al (2008) The ‘Image Gently’ campaign: increasing CT radiation dose awareness through a national education and awareness program. Pediatr Radiol 38:265–269CrossRefGoogle Scholar
  19. 19.
    Geyer LL, Schoepf UJ, Meinel FG et al (2015) State of the art: iterative CT reconstruction techniques. Radiology 276:339–357CrossRefGoogle Scholar
  20. 20.
    Chen B, Ramirez Giraldo JC, Solomon J, Samei E (2014) Evaluating iterative reconstruction performance in computed tomography. Med Phys 41:121913CrossRefGoogle Scholar
  21. 21.
    Ho C, Oberle R, Wu I, Kim E (2014) Comparison of image quality in pediatric head computed tomography reconstructed using blended iterative reconstruction versus filtered back projection. Clin Imaging 38:231–235CrossRefGoogle Scholar
  22. 22.
    Patino M, Fuentes JM, Singh S et al (2015) Iterative reconstruction techniques in abdominopelvic CT: technical concepts and clinical implementation. AJR Am J Roentgenol 205:W19–W31CrossRefGoogle Scholar
  23. 23.
    Mirro AE, Brady SL, Kaufman RA (2016) Full dose-reduction potential of dtatistical iterative reconstruction for head CT protocols in a predominantly pediatric population. AJNR Am J Neuroradiol 37:1199–1205CrossRefGoogle Scholar
  24. 24.
    Schaller F, Sedlmair M, Raupach R et al (2016) Noise reduction in abdominal computed tomography applying iterative reconstruction (ADMIRE). Acad Radiol 23:1230–1238CrossRefGoogle Scholar
  25. 25.
    Scholtz JE, Kaup M, Husers K et al (2016) Advanced modeled iterative reconstruction in low-tube-voltage contrast-enhanced neck CT: evaluation of objective and subjective image quality. AJNR Am J Neuroradiol 37:143–150CrossRefGoogle Scholar
  26. 26.
    Kim HG, Lee HJ, Lee SK et al (2017) Head CT: image quality improvement with ASIR-V using a reduced radiation dose protocol for children. Eur Radiol 27:3609–3617CrossRefGoogle Scholar
  27. 27.
    Nam SB, Jeong DW, Choo KS et al (2017) Image quality of CT angiography in young children with congenital heart disease: a comparison between the sinogram-affirmed iterative reconstruction (SAFIRE) and advanced modelled iterative reconstruction (ADMIRE) algorithms. Clin Radiol 72:1060–1065CrossRefGoogle Scholar
  28. 28.
    Sagara Y, Hara AK, Pavlicek W et al (2010) Abdominal CT: comparison of low-dose CT with adaptive statistical iterative reconstruction and routine-dose CT with filtered back projection in 53 patients. AJR Am J Roentgenol 195:713–719CrossRefGoogle Scholar
  29. 29.
    Singh S, Kalra MK, Hsieh J et al (2010) Abdominal CT: comparison of adaptive statistical iterative and filtered back projection reconstruction techniques. Radiology 257:373–383CrossRefGoogle Scholar
  30. 30.
    Chang W, Lee JM, Lee K et al (2013) Assessment of a model-based, iterative reconstruction algorithm (MBIR) regarding image quality and dose reduction in liver computed tomography. Investig Radiol 48:598–606CrossRefGoogle Scholar
  31. 31.
    Qiu D, Seeram E (2016) Does iterative reconstruction improve image quality and reduce dose in computed tomography? Radiol Open J 1:42–54CrossRefGoogle Scholar
  32. 32.
    Clinthorne NH, Pan TS, Chiao PC et al (1993) Preconditioning methods for improved convergence rates in iterative reconstructions. IEEE Trans Med Imaging 12:78–83CrossRefGoogle Scholar
  33. 33.
    Dalehaug I, Bolstad KN, Aadnevik D et al (2017) ADMIRE vs. SAFIRE: Objective comparison of CT reconstruction algorithms and their noise properties. arXiv preprint arXiv: 1708.09616, 2017. [Online]. Available: https://arxiv.org/abs/1708.09616
  34. 34.
    Moscariello A, Takx RA, Schoepf UJ et al (2011) Coronary CT angiography: image quality, diagnostic accuracy, and potential for radiation dose reduction using a novel iterative image reconstruction technique-comparison with traditional filtered back projection. Eur Radiol 21:2130–2138CrossRefGoogle Scholar
  35. 35.
    Gordic S, Desbiolles L, Stolzmann P et al (2014) Advanced modelled iterative reconstruction for abdominal CT: qualitative and quantitative evaluation. Clin Radiol 69:e497–e504CrossRefGoogle Scholar
  36. 36.
    Vardhanabhuti V, Riordan RD, Mitchell GR et al (2014) Image comparative assessment using iterative reconstructions: clinical comparison of low-dose abdominal/pelvic computed tomography between adaptive statistical, model-based iterative reconstructions and traditional filtered back projection in 65 patients. Investig Radiol 49:209–216CrossRefGoogle Scholar
  37. 37.
    Deak Z, Grimm JM, Treitl M et al (2013) Filtered back projection, adaptive statistical iterative reconstruction, and a model-based iterative reconstruction in abdominal CT: an experimental clinical study. Radiology 266:197–206CrossRefGoogle Scholar
  38. 38.
    Ellmann S, Kammerer F, Allmendinger T et al (2018) Advanced modeled iterative reconstruction (ADMIRE) facilitates radiation dose reduction in abdominal CT. Acad Radiol 25:1277–1284CrossRefGoogle Scholar
  39. 39.
    Kaul D, Kahn J, Huizing L et al (2016) Dose reduction in paediatric cranial CT via iterative reconstruction: a clinical study in 78 patients. Clin Radiol 71:1168–1177CrossRefGoogle Scholar
  40. 40.
    Vorona GA, Zuccoli G, Sutcavage T et al (2013) The use of adaptive statistical iterative reconstruction in pediatric head CT: a feasibility study. AJNR Am J Neuroradiol 34:205–211CrossRefGoogle Scholar
  41. 41.
    Hwang JY, Do KH, Yang DH et al (2015) A survey of pediatric CT protocols and radiation doses in south Korean hospitals to optimize the radiation dose for pediatric CT scanning. Medicine (Baltimore) 94:e2146CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of RadiologyEwha Womans University Mokdong HospitalSeoulRepublic of Korea
  2. 2.Department of Radiology, School of MedicineKyungpook National University, Kyungpook National University HospitalDaeguSouth Korea
  3. 3.Department of RadiologyChungnam National University HospitalDaejeonRepublic of Korea

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