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Image quality of iterative reconstruction in cranial CT imaging: comparison of model-based iterative reconstruction (MBIR) and adaptive statistical iterative reconstruction (ASiR)

  • Computed Tomography
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

The purpose of this study was to compare cranial CT (CCT) image quality (IQ) of the MBIR algorithm with standard iterative reconstruction (ASiR).

Methods

In this institutional review board (IRB)-approved study, raw data sets of 100 unenhanced CCT examinations (120 kV, 50–260 mAs, 20 mm collimation, 0.984 pitch) were reconstructed with both ASiR and MBIR. Signal-to-noise (SNR) and contrast-to-noise (CNR) were calculated from attenuation values measured in caudate nucleus, frontal white matter, anterior ventricle horn, fourth ventricle, and pons. Two radiologists, who were blinded to the reconstruction algorithms, evaluated anonymized multiplanar reformations of 2.5 mm with respect to depiction of different parenchymal structures and impact of artefacts on IQ with a five-point scale (0: unacceptable, 1: less than average, 2: average, 3: above average, 4: excellent).

Results

MBIR decreased artefacts more effectively than ASiR (p < 0.01). The median depiction score for MBIR was 3, whereas the median value for ASiR was 2 (p < 0.01). SNR and CNR were significantly higher in MBIR than ASiR (p < 0.01).

Conclusions

MBIR showed significant improvement of IQ parameters compared to ASiR. As CCT is an examination that is frequently required, the use of MBIR may allow for substantial reduction of radiation exposure caused by medical diagnostics.

Key Points

• Model-Based iterative reconstruction (MBIR) effectively decreased artefacts in cranial CT.

• MBIR reconstructed images were rated with significantly higher scores for image quality.

• Model-Based iterative reconstruction may allow reduced-dose diagnostic examination protocols.

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Acknowledgments

We thank Mr. P. Deak and Ms. K. Herrmann for their kind support. This study was sponsored by GE Healthcare as a part of a scientific institutional grant. The scientific guarantor of this publication is Mr. Stefan Wirth, MD. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. One of the authors has significant statistical expertise. Institutional Review Board approval was obtained. Written informed consent was obtained from all subjects (patients) in this study. Study subjects or cohorts have not been previously reported. Methodology: prospective non-randomised controlled trial, performed at one institution.

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Authors and Affiliations

  1. Institute for Clinical Radiology, Ludwig-Maximilians University Hospital of Munich, Nussbaumstr. 20, 80336, Munich, Germany

    S. Notohamiprodjo, Z. Deak, F. Meurer, F. Maertz, F. G. Mueck, L. L. Geyer & S. Wirth

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  1. S. Notohamiprodjo
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  2. Z. Deak
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  6. L. L. Geyer
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Correspondence to S. Notohamiprodjo.

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Notohamiprodjo, S., Deak, Z., Meurer, F. et al. 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 (2015). https://doi.org/10.1007/s00330-014-3374-8

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  • DOI: https://doi.org/10.1007/s00330-014-3374-8

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