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European Radiology

, Volume 28, Issue 9, pp 3922–3928 | Cite as

Helical CT with variable target noise levels for dose reduction in chest, abdomen and pelvis CT

  • Patrik Rogalla
  • Madhusudan Paravasthu
  • Christin Farrell
  • Sonja Kandel
Computed Tomography
  • 148 Downloads

Abstract

Objectives

To evaluate a contiguous helical CT protocol with two different target noise levels in chest/abdomen/pelvis CT.

Methods

41 patients (study group) underwent a helical scan (P1) with two different target noise levels (SDs), SD = 16 for chest and SD = 13 for abdomen/pelvis. Two further protocols were planned but not executed: a single helical scan with only one SD (SD = 13) for the entire scan range (P2), and two separate helical scans overlapping over the liver and same SD settings as for P1 (P3). All DLPs were recorded. Image quality was assessed qualitatively and quantitatively on all scans. The control group consisted of 40 patients, was scanned with protocol P3 and analysed using the same metrics.

Results

DLPs (mean/SD) for P1, P2 and P3 were 859.5/392.9, 1040.2/510.5 and 1027.4/469.4, respectively. P1 offered a mean dose reduction of 17.4% compared to P2, and 16.3% compared to P3 (both p < 0.001). There were no differences in image quality between both patient groups (p > 0.3).

Conclusion

Contiguous helical scanning of the chest/abdomen/pelvis with variable target noise levels results in approximately 17% dose reduction if compared to a single acquisition with only abdominal dose settings or two separate acquisitions of the chest and abdomen/pelvis.

Key Points

• Low dose chest and standard abdomen CTs can be combined.

• Variable SD CT scanning allows for radiation dose reduction.

• Variable SD CT scanning maintains image quality.

Keywords

Whole body CT Dose reduction Dose modulation Image quality CT technique 

Abbreviations

AEC

Automatic exposure control

AP

Exposure direction for the scout view, anteroposterior

BMI

Body mass index

DLP

Dose length product measured in mGy cm

HU

Hounsfield units

mA

Tube current measured in milliampere

MIP

Maximum intensity projection

ROI

Region of interest

SD

Standard deviation of image noise expressed in Hounsfield units

Notes

Funding

The authors state that this work has not received any funding.

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Patrik Rogalla.

Conflict of interest

The authors of this manuscript declare relationships with the following companies: Toshiba Medical Systems, Canon Group.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Ethical approval

Institutional review board approval was obtained.

Methodology

• prospective

• diagnostic or prognostic study

• performed at one institution

References

  1. 1.
    Amis ES Jr, Butler PF, Applegate KE et al (2007) American College of Radiology white paper on radiation dose in medicine. J Am Coll Radiol 4:272–284CrossRefPubMedGoogle Scholar
  2. 2.
    Cohen BL (2002) Cancer risk from low-level radiation. AJR Am J Roentgenol 179:1137–1143CrossRefPubMedGoogle Scholar
  3. 3.
    Siegel JA, Welsh JS (2016) Does imaging technology cause cancer? Debunking the linear no-threshold model of radiation carcinogenesis. Technol Cancer Res Treat 15:249–256CrossRefPubMedGoogle Scholar
  4. 4.
    Brodoefel H, Bender B, Schabel C, Fenchel M, Ernemann U, Korn A (2015) Potential of combining iterative reconstruction with noise efficient detector design: aggressive dose reduction in head CT. Br J Radiol 88:20140404CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Omotayo A, Elbakri I (2016) Objective performance assessment of five computed tomography iterative reconstruction algorithms. J Xray Sci Technol 24:913–930PubMedGoogle Scholar
  6. 6.
    McCollough CH (2005) Automatic exposure control in CT: are we done yet? Radiology 237:755–756CrossRefPubMedGoogle Scholar
  7. 7.
    Song JS, Choi EJ, Kim EY, Kwak HS, Han YM (2015) Attenuation-based automatic kilovoltage selection and sinogram-affirmed iterative reconstruction: effects on radiation exposure and image quality of portal-phase liver CT. Korean J Radiol 16:69–79CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Lee CH, Goo JM, Ye HJ et al (2008) Radiation dose modulation techniques in the multidetector CT era: from basics to practice. Radiographics 28:1451–1459CrossRefPubMedGoogle Scholar
  9. 9.
    Manssor E, Abuderman A, Osman S et al (2015) Radiation doses in chest, abdomen and pelvis CT procedures. Radiat Prot Dosim 165:194–198CrossRefGoogle Scholar
  10. 10.
    Naidich DP, Marshall CH, Gribbin C, Arams RS, McCauley DI (1990) Low-dose CT of the lungs: preliminary observations. Radiology 175:729–731CrossRefPubMedGoogle Scholar
  11. 11.
    Rampinelli C, De Marco P, Origgi D et al (2017) Exposure to low dose computed tomography for lung cancer screening and risk of cancer: secondary analysis of trial data and risk-benefit analysis. BMJ 356:j347CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Rogalla P, Stover B, Scheer I, Juran R, Gaedicke G, Hamm B (1999) Low-dose spiral CT: applicability to paediatric chest imaging. Pediatr Radiol 29:565–569CrossRefPubMedGoogle Scholar
  13. 13.
    Papadakis AE, Perisinakis K, Damilakis J (2014) Automatic exposure control in CT: the effect of patient size, anatomical region and prescribed modulation strength on tube current and image quality. Eur Radiol 24:2520–2531CrossRefPubMedGoogle Scholar
  14. 14.
    Kanal KM, Butler PF, Sengupta D, Bhargavan-Chatfield M, Coombs LP, Morin RL (2017) U.S. diagnostic reference levels and achievable doses for 10 adult CT examinations. Radiology 284:120–133CrossRefPubMedGoogle Scholar
  15. 15.
    McCollough CH, Primak AN, Braun N, Kofler J, Yu L, Christner J (2009) Strategies for reducing radiation dose in CT. Radiol Clin N Am 47:27–40CrossRefPubMedGoogle Scholar
  16. 16.
    Elbakri IA, Kirkpatrick ID (2013) Dose-length product to effective dose conversion factors for common computed tomography examinations based on Canadian clinical experience. Can Assoc Radiol J 64:15–17CrossRefPubMedGoogle Scholar
  17. 17.
    Christner JA, Kofler JM, McCollough CH (2010) Estimating effective dose for CT using dose-length product compared with using organ doses: consequences of adopting International Commission on Radiological Protection publication 103 or dual-energy scanning. AJR Am J Roentgenol 194:881–889CrossRefPubMedGoogle Scholar
  18. 18.
    Papadakis AE, Perisinakis K, Damilakis J (2007) Angular on-line tube current modulation in multidetector CT examinations of children and adults: the influence of different scanning parameters on dose reduction. Med Phys 34:2864–2874CrossRefPubMedGoogle Scholar
  19. 19.
    Kalra MK, Maher MM, Toth TL et al (2004) Techniques and applications of automatic tube current modulation for CT. Radiology 233:649–657CrossRefPubMedGoogle Scholar
  20. 20.
    Soderberg M, Gunnarsson M (2010) Automatic exposure control in computed tomography–an evaluation of systems from different manufacturers. Acta Radiol 51:625–634CrossRefPubMedGoogle Scholar
  21. 21.
    Mulkens TH, Bellinck P, Baeyaert M et al (2005) Use of an automatic exposure control mechanism for dose optimization in multi-detector row CT examinations: clinical evaluation. Radiology 237:213–223CrossRefPubMedGoogle Scholar
  22. 22.
    Schindera ST, Odedra D, Mercer D et al (2014) Hybrid iterative reconstruction technique for abdominal CT protocols in obese patients: assessment of image quality, radiation dose, and low-contrast detectability in a phantom. AJR Am J Roentgenol 202:W146–W152CrossRefPubMedGoogle Scholar

Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  1. 1.Joint Department of Medical ImagingUniversity of TorontoTorontoCanada

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