European Radiology

, Volume 22, Issue 12, pp 2597–2606 | Cite as

Low-dose CT of the lung: potential value of iterative reconstructions

  • Stephan Baumueller
  • Anna Winklehner
  • Christoph Karlo
  • Robert Goetti
  • Thomas Flohr
  • Erich W. Russi
  • Thomas Frauenfelder
  • Hatem AlkadhiEmail author
Computed Tomography



To prospectively assess the impact of sinogram-affirmed iterative reconstruction (SAFIRE) on image quality of nonenhanced low-dose lung CT as compared to filtered back projection (FBP).


Nonenhanced low-dose chest CT (tube current-time product: 30 mAs) was performed on 30 patients at 100 kVp and on 30 patients at 80 kVp. Images were reconstructed with FBP and SAFIRE. Two blinded, independent readers measured image noise; two readers assessed image quality of normal anatomic lung structures on a five-point scale. Radiation dose parameters were recorded.


Image noise in datasets reconstructed with FBP (57.4 ± 15.9) was significantly higher than with SAFIRE (31.7 ± 9.8, P < 0.001). Image quality was significantly superior with SAFIRE than with FBP (P < 0.01), without significant difference between FBP at 100 kVp and SAFIRE at 80 kVp (P = 0.68). Diagnostic image quality was present with FBP in 96% of images at 100 kVp and 88% at 80 kVp, and with SAFIRE in 100% at 100 kVp and 98% at 80 kVp. There were significantly more datasets with diagnostic image quality with SAFIRE than with FBP (P < 0.01). Mean CTDIvol and effective doses were 1.5 ± 0.7 mGy·cm and 0.7 ± 0.2 mSv at 100 kVp, and 1.4 ± 2.8 mGy·cm and 0.5 ± 0.2 mSv at 80 kVp (P < 0.001, both).


Use of SAFIRE in low-dose lung CT reduces noise, improves image quality, and renders more studies diagnostic as compared to FBP.

Key Points

Low-dose computed tomography is an important thoracic investigation tool.

Radiation dose can be less than 1 mSv with iterative reconstructions.

Iterative reconstructions render more low-dose lung CTs diagnostic compared to conventional reconstructions.


Spiral computed tomography Image reconstruction Image enhancement Lung Radiation dosage 


  1. 1.
    National Lung Screening Trial Research Team, Aberle DR, Adams AM, et al (2011) Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 365:395–409Google Scholar
  2. 2.
    Aberle DR, Berg CD, Black WC et al (2011) The National Lung Screening Trial: overview and study design. Radiology 258:243–253PubMedCrossRefGoogle Scholar
  3. 3.
    Baldwin DR, Duffy SW, Wald NJ, Page R, Hansell DM, Field JK (2011) UK Lung Screen (UKLS) nodule management protocol: modelling of a single screen randomised controlled trial of low-dose CT screening for lung cancer. Thorax 66:308–313PubMedCrossRefGoogle Scholar
  4. 4.
    Bankier AA, Tack D (2010) Dose reduction strategies for thoracic multidetector computed tomography: background, current issues, and recommendations. J Thorac Imaging 25:278–288PubMedCrossRefGoogle Scholar
  5. 5.
    Baumueller S, Alkadhi H, Stolzmann P et al (2011) Computed tomography of the lung in the high-pitch mode: is breath holding still required? Invest Radiol 46:240–245PubMedCrossRefGoogle Scholar
  6. 6.
    Cereser L, Zuiani C, Graziani G et al (2010) Impact of clinical data on chest radiography sensitivity in detecting pulmonary abnormalities in immunocompromised patients with suspected pneumonia. Radiol Med 115:205–214PubMedCrossRefGoogle Scholar
  7. 7.
    Christner JA, Zavaletta VA, Eusemann CD, Walz-Flannigan AI, McCollough CH (2010) Dose reduction in helical CT: dynamically adjustable z-axis X-ray beam collimation. AJR Am J Roentgenol 194:W49–55PubMedCrossRefGoogle Scholar
  8. 8.
    Committee CDDICC (2008) The measurement, reporting, and management of radiation dose in CT. The American Association of Physicists in Medicine report no. 96. AAPM, College Park, MDGoogle Scholar
  9. 9.
    Costello P (1994) Thoracic helical CT. Radiographics 14:913–918PubMedGoogle Scholar
  10. 10.
    Heussel CP, Kauczor HU, Heussel G, Fischer B, Mildenberger P, Thelen M (1997) Early detection of pneumonia in febrile neutropenic patients: use of thin-section CT. AJR Am J Roentgenol 169:1347–1353PubMedGoogle Scholar
  11. 11.
    Kalender WA, Buchenau S, Deak P et al (2008) Technical approaches to the optimisation of CT. Phys Med 24:71–79PubMedCrossRefGoogle Scholar
  12. 12.
    Kalra MK, Maher MM, Sahani DV et al (2003) Low-dose CT of the abdomen: evaluation of image improvement with use of noise reduction filters—pilot study. Radiology 228:251–256PubMedCrossRefGoogle Scholar
  13. 13.
    Kazerooni EA (2001) High-resolution CT of the lungs. AJR Am J Roentgenol 177:501–519PubMedGoogle Scholar
  14. 14.
    Leipsic J, Nguyen G, Brown J, Sin D, Mayo JR (2010) A prospective evaluation of dose reduction and image quality in chest CT using adaptive statistical iterative reconstruction. AJR Am J Roentgenol 195:1095–1099PubMedCrossRefGoogle Scholar
  15. 15.
    McCollough CH, Bruesewitz MR, Kofler JM Jr (2006) CT dose reduction and dose management tools: overview of available options. Radiographics 26:503–512PubMedCrossRefGoogle Scholar
  16. 16.
    McNitt-Gray MF (2002) AAPM/RSNA physics tutorial for residents: topics in CT. Radiation dose in CT. Radiographics 22:1541–1553PubMedCrossRefGoogle Scholar
  17. 17.
    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 21:2130–2138PubMedCrossRefGoogle Scholar
  18. 18.
    Naidich DP (2010) High-resolution computed tomography of the pulmonary parenchyma: past, present, and future? J Thorac Imaging 25:32–33PubMedCrossRefGoogle Scholar
  19. 19.
    Noel PB, Fingerle AA, Renger B, Munzel D, Rummeny EJ, Dobritz M (2011) Initial performance characterization of a clinical noise-suppressing reconstruction algorithm for MDCT. AJR Am J Roentgenol 197:1404–1409PubMedCrossRefGoogle Scholar
  20. 20.
    Paul NS, Blobel J, Prezelj E et al (2010) The reduction of image noise and streak artifact in the thoracic inlet during low dose and ultra-low dose thoracic CT. Phys Med Biol 55:1363–1380PubMedCrossRefGoogle Scholar
  21. 21.
    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
  22. 22.
    Pontana F, Pagniez J, Flohr T et al (2011) Chest computed tomography using iterative reconstruction vs filtered back projection (part1): evaluation of image noise reduction in 32 patients. Eur Radiol 21:627–635PubMedCrossRefGoogle Scholar
  23. 23.
    Prakash P, Kalra MK, Ackman JB et al (2010) Diffuse lung disease: CT of the chest with adaptive statistical iterative reconstruction technique. Radiology 256:261–269PubMedCrossRefGoogle Scholar
  24. 24.
    Prakash P, Kalra MK, Digumarthy SR et al (2010) Radiation dose reduction with chest computed tomography using adaptive statistical iterative reconstruction technique: initial experience. J Comput Assist Tomogr 34:40–45PubMedCrossRefGoogle Scholar
  25. 25.
    Schueller G, Matzek W, Kalhs P, Schaefer-Prokop C (2005) Pulmonary infections in the late period after allogeneic bone marrow transplantation: chest radiography versus computed tomography. Eur J Radiol 53:489–494PubMedCrossRefGoogle Scholar
  26. 26.
    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
  27. 27.
    Vock P, Soucek M, Daepp M, Kalender WA (1990) Lung: spiral volumetric CT with single-breath-hold technique. Radiology 176:864–867PubMedGoogle Scholar
  28. 28.
    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
  29. 29.
    Winklehner A, Karlo C, Puippe G et al (2011) Raw data-based iterative reconstruction in body CTA: evaluation of radiation dose saving potential. Eur Radiol 21:2521–2526PubMedCrossRefGoogle Scholar
  30. 30.
    Yanagawa M, Honda O, Yoshida S et al (2010) Adaptive statistical iterative reconstruction technique for pulmonary CT: image quality of the cadaveric lung on standard- and reduced-dose CT. Acad Radiol 17:1259–1266PubMedCrossRefGoogle Scholar

Copyright information

© European Society of Radiology 2012

Authors and Affiliations

  • Stephan Baumueller
    • 1
  • Anna Winklehner
    • 1
  • Christoph Karlo
    • 1
  • Robert Goetti
    • 1
  • Thomas Flohr
    • 2
  • Erich W. Russi
    • 3
  • Thomas Frauenfelder
    • 1
  • Hatem Alkadhi
    • 1
    Email author
  1. 1.Institute for Diagnostic and Interventional RadiologyUniversity Hospital ZurichZurichSwitzerland
  2. 2.Computed Tomography DivisionSiemens HealthcareForchheimGermany
  3. 3.Pulmonary Division, Department of Internal MedicineUniversity Hospital ZurichZurichSwitzerland

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