European Radiology

, Volume 26, Issue 2, pp 459–468 | Cite as

Optimizing radiation dose by using advanced modelled iterative reconstruction in high-pitch coronary CT angiography

  • Sonja Gordic
  • Lotus Desbiolles
  • Martin Sedlmair
  • Robert Manka
  • André Plass
  • Bernhard Schmidt
  • Daniela B. Husarik
  • Francesco Maisano
  • Simon Wildermuth
  • Hatem Alkadhi
  • Sebastian Leschka



To evaluate the potential of advanced modeled iterative reconstruction (ADMIRE) for optimizing radiation dose of high-pitch coronary CT angiography (CCTA).


High-pitch 192-slice dual-source CCTA was performed in 25 patients (group 1) according to standard settings (ref. 100 kVp, ref. 270 mAs/rot). Images were reconstructed with filtered back projection (FBP) and ADMIRE (strength levels 1–5). In another 25 patients (group 2), high-pitch CCTA protocol parameters were adapted according to results from group 1 (ref. 160 mAs/rot), and images were reconstructed with ADMIRE level 4. In ten patients of group 1, vessel sharpness using full width at half maximum (FWHM) analysis was determined. Image quality was assessed by two independent, blinded readers.


Interobserver agreements for attenuation and noise were excellent (r = 0.88/0.85, p < 0.01). In group 1, ADMIRE level 4 images were most often selected (84 %, 21/25) as preferred data set; at this level noise reduction was 40 % compared to FBP. Vessel borders showed increasing sharpness (FWHM) at increasing ADMIRE levels (p < 0.05). Image quality in group 2 was similar to that of group 1 at ADMIRE levels 2–3. Radiation dose in group 2 (0.3 ± 0.1 mSv) was significantly lower than in group 1 (0.5 ± 0.3 mSv; p < 0.05).


In a selected population, ADMIRE can be used for optimizing high-pitch CCTA to an effective dose of 0.3 mSv.

Key points

• Advanced modeled IR (ADMIRE) reduces image noise up to 50 % as compared to FBP.

• Coronary artery vessel borders show an increasing sharpness at higher ADMIRE levels.

• High-pitch CCTA with ADMIRE is possible at a radiation dose of 0.3 mSv.


Computed tomography Radiation dose Iterative reconstruction Coronary angiography Image quality 



The scientific guarantor of this publication is H. Alkadhi. The authors of this manuscript declare relationships with the following companies: M. Sedlmair and B. Schmidt with Siemens Healthcare.

All other authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. The authors state that this work has not received any funding. One of the authors has significant statistical expertise. No complex statistical methods were necessary for this paper. Institutional review board approval was obtained. Written informed consent was waived by the institutional review board. Methodology: retrospective, case-control study, performed at one institution.


  1. 1.
    Tamm EP, Rong XJ, Cody DD, Ernst RD, Fitzgerald NE, Kundra V (2011) Quality initiatives: CT radiation dose reduction: how to implement change without sacrificing diagnostic quality. Radiographics 31:1823–1832PubMedCrossRefGoogle Scholar
  2. 2.
    Layritz C, Muschiol G, Flohr T et al (2013) Automated attenuation-based selection of tube voltage and tube current for coronary CT angiography: reduction of radiation exposure versus a BMI-based strategy with an expert investigator. J Cardiovasc Comput Tomogr 7:303–310PubMedCrossRefGoogle Scholar
  3. 3.
    Vardhanabhuti V, Riordan RD, Mitchell GR, Hyde C, Roobottom CA (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. Invest Radiol 49:209–216PubMedCrossRefGoogle Scholar
  4. 4.
    Meyer M, Haubenreisser H, Schoepf UJ et al (2014) Closing in on the K edge: coronary CT angiography at 100, 80, and 70 kV-initial comparison of a second- versus a third-generation dual-source CT system. Radiology. doi: 10.1148/radiol.14140244:140244 Google Scholar
  5. 5.
    Morsbach F, Gordic S, Desbiolles L et al (2014) Performance of turbo high-pitch dual-source CT for coronary CT angiography: first ex vivo and patient experience. Eur Radiol 24:1889–1895PubMedCrossRefGoogle Scholar
  6. 6.
    Gordic S, Husarik DB, Desbiolles L, Leschka S, Frauenfelder T, Alkadhi H (2014) High-pitch coronary CT angiography with third generation dual-source CT: limits of heart rate. Int J Cardiovasc Imaging 30:1173–1179PubMedCrossRefGoogle Scholar
  7. 7.
    Gordic S, Morsbach F, Schmidt B et al (2014) Ultralow-dose chest computed tomography for pulmonary nodule detection: first performance evaluation of single energy scanning with spectral shaping. Invest Radiol 49:465–473PubMedCrossRefGoogle Scholar
  8. 8.
    Gordic S, Desbiolles L, Stolzmann P et al (2014) Advanced modelled iterative reconstruction for abdominal CT: qualitative and quantitative evaluation. Clin Radiol 69:e497–e504PubMedCrossRefGoogle Scholar
  9. 9.
    Pontana F, Pagniez J, Flohr T et al (2011) Chest computed tomography using iterative reconstruction vs filtered back projection (Part 1): evaluation of image noise reduction in 32 patients. Eur Radiol 21:627–635PubMedCrossRefGoogle Scholar
  10. 10.
    Thibault JB, Sauer KD, Bouman CA, Hsieh J (2007) A three-dimensional statistical approach to improved image quality for multislice helical CT. Med Phys 34:4526–4544PubMedCrossRefGoogle Scholar
  11. 11.
    Taylor AJ, Cerqueira M, Hodgson JM et al (2010) ACCF/SCCT/ACR/AHA/ASE/ASNC/NASCI/SCAI/SCMR 2010 appropriate use criteria for cardiac computed tomography. A report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, the Society of Cardiovascular Computed Tomography, the American College of Radiology, the American Heart Association, the American Society of Echocardiography, the American Society of Nuclear Cardiology, the North American Society for Cardiovascular Imaging, the Society for Cardiovascular Angiography and Interventions, and the Society for Cardiovascular Magnetic Resonance. Circulation 122:e525–e555PubMedCrossRefGoogle Scholar
  12. 12.
    Pontana F, Duhamel A, Pagniez J et al (2011) Chest computed tomography using iterative reconstruction vs filtered back projection (Part 2): image quality of low-dose CT examinations in 80 patients. Eur Radiol 21:636–643PubMedCrossRefGoogle Scholar
  13. 13.
    Morsbach F, Desbiolles L, Plass A et al (2013) Stenosis quantification in coronary CT angiography: impact of an integrated circuit detector with iterative reconstruction. Invest Radiol 48:32–40PubMedCrossRefGoogle Scholar
  14. 14.
    Wang R, Schoepf UJ, Wu R et al (2014) Diagnostic accuracy of coronary CT angiography: comparison of filtered back projection and iterative reconstruction with different strengths. J Comput Assist Tomogr 38:179–184PubMedCrossRefGoogle Scholar
  15. 15.
    Richard S, Husarik DB, Yadava G, Murphy SN, Samei E (2012) Towards task-based assessment of CT performance: system and object MTF across different reconstruction algorithms. Med Phys 39:4115–4122PubMedCrossRefGoogle Scholar
  16. 16.
    Menzel HG, Schibilla H, Teunen D (eds) (2000) European guidelines on quality criteria for computed tomography, EUR 16262 EN. European Commission, LuxembourgGoogle Scholar
  17. 17.
    Einstein AJ, Elliston CD, Arai AE et al (2010) Radiation dose from single-heartbeat coronary CT angiography performed with a 320-detector row volume scanner. Radiology 254:698–706PubMedPubMedCentralCrossRefGoogle Scholar
  18. 18.
    Boone JM, Strauus KJ, Cody DD, McCollough CH, McNitt-Gray MF, Toth TL (2011) Size specific dose estimates (SSDE) in pediatric and adult CT examinations. American Association of Physicists in Medicine, report of AAPM Task Group 204. AAPM, College Park, MDGoogle Scholar
  19. 19.
    Hou Y, Liu X, Xv S, Guo W, Guo Q (2012) Comparisons of image quality and radiation dose between iterative reconstruction and filtered back projection reconstruction algorithms in 256-MDCT coronary angiography. AJR Am J Roentgenol 199:588–594PubMedCrossRefGoogle Scholar
  20. 20.
    Leipsic J, Labounty TM, Heilbron B et al (2010) Adaptive statistical iterative reconstruction: assessment of image noise and image quality in coronary CT angiography. AJR Am J Roentgenol 195:649–654PubMedCrossRefGoogle Scholar
  21. 21.
    Schuhbaeck A, Achenbach S, Layritz C et al (2013) Image quality of ultra-low radiation exposure coronary CT angiography with an effective dose <0.1 mSv using high-pitch spiral acquisition and raw data-based iterative reconstruction. Eur Radiol 23:597–606PubMedCrossRefGoogle Scholar
  22. 22.
    Singh S, Khawaja RD, Pourjabbar S, Padole A, Lira D, Kalra MK (2013) Iterative image reconstruction and its role in cardiothoracic computed tomography. J Thorac Imaging 28:355–367PubMedCrossRefGoogle Scholar
  23. 23.
    Yin WH, Lu B, Hou ZH et al (2013) Detection of coronary artery stenosis with sub-milliSievert radiation dose by prospectively ECG-triggered high-pitch spiral CT angiography and iterative reconstruction. Eur Radiol 23:2927–2933PubMedCrossRefGoogle Scholar
  24. 24.
    Ebersberger U, Tricarico F, Schoepf UJ et al (2013) CT evaluation of coronary artery stents with iterative image reconstruction: improvements in image quality and potential for radiation dose reduction. Eur Radiol 23:125–132PubMedCrossRefGoogle Scholar
  25. 25.
    Renker M, Nance JW Jr, Schoepf UJ et al (2011) Evaluation of heavily calcified vessels with coronary CT angiography: comparison of iterative and filtered back projection image reconstruction. Radiology 260:390–399PubMedCrossRefGoogle Scholar
  26. 26.
    Husarik DB, Schindera ST, Morsbach F et al (2014) Combining automated attenuation-based tube voltage selection and iterative reconstruction: a liver phantom study. Eur Radiol 24:657–667PubMedCrossRefGoogle Scholar
  27. 27.
    Winklehner A, Goetti R, Baumueller S et al (2011) Automated attenuation-based tube potential selection for thoracoabdominal computed tomography angiography: improved dose effectiveness. Invest Radiol 46:767–773PubMedCrossRefGoogle Scholar

Copyright information

© European Society of Radiology 2015

Authors and Affiliations

  • Sonja Gordic
    • 1
  • Lotus Desbiolles
    • 1
    • 2
  • Martin Sedlmair
    • 3
  • Robert Manka
    • 1
    • 4
    • 5
  • André Plass
    • 6
  • Bernhard Schmidt
    • 3
  • Daniela B. Husarik
    • 1
  • Francesco Maisano
    • 6
  • Simon Wildermuth
    • 2
  • Hatem Alkadhi
    • 1
  • Sebastian Leschka
    • 1
    • 2
  1. 1.Institute of Diagnostic and Interventional RadiologyUniversity Hospital Zurich, University of ZurichZurichSwitzerland
  2. 2.Divison of Radiology and Nuclear MedicineKantonsspitalSt. GallenSwitzerland
  3. 3.Siemens Healthcare, Computed Tomography DivisionForchheimGermany
  4. 4.Clinic of CardiologyUniversity Hospital Zurich, University of ZurichZurichSwitzerland
  5. 5.Institute for Biomedical EngineeringUniversity and ETH ZurichZurichSwitzerland
  6. 6.Clinic for Cardiovascular SurgeryUniversity Hospital Zurich, University of ZurichZurichSwitzerland

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