Skip to main content

Advertisement

Log in

Comparison of iterative model, hybrid iterative, and filtered back projection reconstruction techniques in low-dose brain CT: impact of thin-slice imaging

  • Diagnostic Neuroradiology
  • Published:
Neuroradiology Aims and scope Submit manuscript

Abstract

Introduction

The purpose of this study was to evaluate the utility of iterative model reconstruction (IMR) in brain CT especially with thin-slice images.

Methods

This prospective study received institutional review board approval, and prior informed consent to participate was obtained from all patients. We enrolled 34 patients who underwent brain CT and reconstructed axial images with filtered back projection (FBP), hybrid iterative reconstruction (HIR) and IMR with 1 and 5 mm slice thicknesses. The CT number, image noise, contrast, and contrast noise ratio (CNR) between the thalamus and internal capsule, and the rate of increase of image noise in 1 and 5 mm thickness images between the reconstruction methods, were assessed. Two independent radiologists assessed image contrast, image noise, image sharpness, and overall image quality on a 4-point scale.

Results

The CNRs in 1 and 5 mm slice thickness were significantly higher with IMR (1.2 ± 0.6 and 2.2 ± 0.8, respectively) than with FBP (0.4 ± 0.3 and 1.0 ± 0.4, respectively) and HIR (0.5 ± 0.3 and 1.2 ± 0.4, respectively) (p < 0.01). The mean rate of increasing noise from 5 to 1 mm thickness images was significantly lower with IMR (1.7 ± 0.3) than with FBP (2.3 ± 0.3) and HIR (2.3 ± 0.4) (p < 0.01). There were no significant differences in qualitative analysis of unfamiliar image texture between the reconstruction techniques.

Conclusion

IMR offers significant noise reduction and higher contrast and CNR in brain CT, especially for thin-slice images, when compared to FBP and HIR.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Sodickson A, Baeyens PF, Andriole KP, Prevedello LM, Nawfel RD, Hanson R et al (2009) Recurrent CT, cumulative radiation exposure, and associated radiation-induced cancer risks from CT of adults. Radiology 251:175–184

    Article  PubMed  Google Scholar 

  2. Berrington de Gonzalez A, Mahesh M, Kim KP, Bhargavan M, Lewis R, Mettler F et al (2009) Projected cancer risks from computed tomographic scans performed in the United States in 2007. Arch Intern Med 169:2071–2077

    Article  PubMed  Google Scholar 

  3. Brenner DJ, Hall EJ (2007) Computed tomography—an increasing source of radiation exposure. N Engl J Med 357:2277–2284

    Article  CAS  PubMed  Google Scholar 

  4. Barber PA, Demchuk AM, Zhang J, Buchan AM (2000) Validity and reliability of a quantitative computed tomography score in predicting outcome of hyperacute stroke before thrombolytic therapy. ASPECTS study group. Alberta stroke programme early CT score. Lancet 355:1670–1674

    Article  CAS  PubMed  Google Scholar 

  5. Hill MD, Demchuk AM, Tomsick TA, Palesch YY, Broderick JP (2006) Using the baseline CT scan to select acute stroke patients for IV-IA therapy. AJNR Am J Neuroradiol 27:1612–1616

    CAS  PubMed  Google Scholar 

  6. 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 31:1823–1832

    Article  PubMed  Google Scholar 

  7. Lee B, Newberg A (2005) Neuroimaging in traumatic brain imaging. NeuroRx 2:372–383

    Article  PubMed  PubMed Central  Google Scholar 

  8. Joseph PM, Ruth C (1997) A method for simultaneous correction of spectrum hardening artifacts in CT images containing both bone and iodine. Med Phys 24:1629–1634

    Article  CAS  PubMed  Google Scholar 

  9. Doczi T, Schwarcz A (2003) Correlation of apparent diffusion coefficient and computed tomography density in acute ischemic stroke. Stroke 34:e17–18, author reply e17-18

    Article  CAS  PubMed  Google Scholar 

  10. Kucinski T, Vaterlein O, Glauche V, Fiehler J, Klotz E, Eckert B et al (2002) Correlation of apparent diffusion coefficient and computed tomography density in acute ischemic stroke. Stroke 33:1786–1791

    Article  PubMed  Google Scholar 

  11. Pickhardt PJ, Lubner MG, Kim DH, Tang J, Ruma JA, del Rio AM et al (2012) Abdominal CT with model-based iterative reconstruction (MBIR): initial results of a prospective trial comparing ultralow-dose with standard-dose imaging. AJR Am J Roentgenol 199:1266–1274

    Article  PubMed  PubMed Central  Google Scholar 

  12. Katsura M, Matsuda I, Akahane M, Sato J, Akai H, Yasaka K et al (2012) Model-based iterative reconstruction technique for radiation dose reduction in chest CT: comparison with the adaptive statistical iterative reconstruction technique. Eur Radiol 22:1613–1623

    Article  PubMed  Google Scholar 

  13. Chang W, Lee JM, Lee K, Yoon JH, Yu MH, Han JK et al (2013) Assessment of a model-based, iterative reconstruction algorithm (MBIR) regarding image quality and dose reduction in liver computed tomography. Invest Radiol 48:598–606

    Article  CAS  PubMed  Google Scholar 

  14. Notohamiprodjo S, Deak Z, Meurer F, Maertz F, Mueck FG, Geyer LL et al (2015) Image quality of iterative reconstruction in cranial CT imaging: comparison of model-based iterative reconstruction (MBIR) and adaptive statistical iterative reconstruction (ASiR). Eur Radiol 25:140–146

    Article  CAS  PubMed  Google Scholar 

  15. Machida H, Takeuchi H, Tanaka I, Fukui R, Shen Y, Ueno E et al (2013) Improved delineation of arteries in the posterior fossa of the brain by model-based iterative reconstruction in volume-rendered 3D CT angiography. AJNR Am J Neuroradiol 34:971–975

    Article  CAS  PubMed  Google Scholar 

  16. Huda W, Ogden KM, Khorasani MR (2008) Converting dose-length product to effective dose at CT. Radiology 248:995–1003

    Article  PubMed  PubMed Central  Google Scholar 

  17. McCollough CH, Yu L, Kofler JM, Leng S, Zhang Y, Li Z et al (2015) Degradation of CT low-contrast spatial resolution due to the use of iterative reconstruction and reduced dose levels. Radiology 276:499–506

    Article  PubMed  PubMed Central  Google Scholar 

  18. Schindera ST, Odedra D, Raza SA, Kim TK, Jang HJ, Szucs-Farkas Z et al (2013) Iterative reconstruction algorithm for CT: can radiation dose be decreased while low-contrast detectability is preserved? Radiology 269:511–518

    Article  PubMed  Google Scholar 

  19. Nishizawa M, Tanaka H, Watanabe Y, Kunitomi Y, Tsukabe A, Tomiyama N (2015) Model-based iterative reconstruction for detection of subtle hypoattenuation in early cerebral infarction: a phantom study. Jpn J Radiol 33:26–32

    Article  PubMed  Google Scholar 

  20. Kijewski PK, Bjarngard BE (1978) Correction for beam hardening in computed tomography. Med Phys 5:209–214

    Article  CAS  PubMed  Google Scholar 

  21. De Man B, Nuyts J, Dupont P, Marchal G, Suetens P (2001) An iterative maximum-likelihood polychromatic algorithm for CT. IEEE Trans Med Imaging 20:999–1008

    Article  PubMed  Google Scholar 

  22. De Man B, Basu S (2004) Distance-driven projection and backprojection in three dimensions. Phys Med Biol 49:2463–2475

    Article  PubMed  Google Scholar 

  23. Patzig M, Burke M, Bruckmann H, Fesl G (2014) Comparison of 3D cube FLAIR with 2D FLAIR for multiple sclerosis imaging at 3 tesla. RöFo 186:484–488

    CAS  PubMed  Google Scholar 

  24. Tanaka T, Morimoto Y, Shiiba S, Sakamoto E, Kito S, Matsufuji Y et al (2005) Utility of magnetic resonance cisternography using three-dimensional fast asymmetric spin-echo sequences with multiplanar reconstruction: the evaluation of sites of neurovascular compression of the trigeminal nerve. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 100:215–225

    Article  PubMed  Google Scholar 

  25. Deak Z, Grimm JM, Treitl M, Geyer LL, Linsenmaier U, Korner 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 266:197–206

    Article  PubMed  Google Scholar 

  26. Di Tommaso L, Destro A, Fabbris V, Spagnuolo G, Laura Fracanzani A, Fargion S et al (2011) Diagnostic accuracy of clathrin heavy chain staining in a marker panel for the diagnosis of small hepatocellular carcinoma. Hepatology 53:1549–1557

    Article  PubMed  Google Scholar 

  27. Roger VL, Go AS, Lloyd-Jones DM, Benjamin EJ, Berry JD, Borden WB et al (2012) Executive summary: heart disease and stroke statistics—2012 update: a report from the American heart association. Circulation 125:188–197

    Article  PubMed  Google Scholar 

  28. Love A, Olsson ML, Siemund R, Stalhammar F, Bjorkman-Burtscher IM, Soderberg M (2013) Six iterative reconstruction algorithms in brain CT: a phantom study on image quality at different radiation dose levels. Br J Radiol 86:20130388

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Hurwitz LM, Yoshizumi TT, Goodman PC, Frush DP, Nguyen G, Toncheva G et al (2007) Effective dose determination using an anthropomorphic phantom and metal oxide semiconductor field effect transistor technology for clinical adult body multidetector array computed tomography protocols. J Comput Assist Tomogr 31:544–549

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Takeshi Nakaura.

Ethics declarations

We declare that all human and animal studies have been approved by the Institutional Review Board and have therefore been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. We declare that all patients gave informed consent prior to inclusion in this study.

Conflict of interest

ST is an employee of Philips Electronics.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nakaura, T., Iyama, Y., Kidoh, M. et al. Comparison of iterative model, hybrid iterative, and filtered back projection reconstruction techniques in low-dose brain CT: impact of thin-slice imaging. Neuroradiology 58, 245–251 (2016). https://doi.org/10.1007/s00234-015-1631-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00234-015-1631-4

Keywords

Navigation