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Adaptive statistical iterative reconstruction for volume-rendered computed tomography portovenography: improvement of image quality

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Japanese Journal of Radiology Aims and scope Submit manuscript

Abstract

Purpose

Adaptive statistical iterative reconstruction (ASIR) is a reconstruction technique for computed tomography (CT) that reduces image noise. The purpose of our study was to investigate whether ASIR improves the quality of volume-rendered (VR) CT portovenography.

Materials and methods

Institutional review board approval, with waived consent, was obtained. A total of 19 patients (12 men, 7 women; mean age 69.0 years; range 25–82 years) suspected of having liver lesions underwent three-phase enhanced CT. VR image sets were prepared with both the conventional method and ASIR. The required time to make VR images was recorded. Two radiologists performed independent qualitative evaluations of the image sets. The Wilcoxon signed-rank test was used for statistical analysis. Contrast-noise ratios (CNRs) of the portal and hepatic vein were also evaluated.

Results

Overall image quality was significantly improved by ASIR (P < 0.0001 and P = 0.0155 for each radiologist). ASIR enhanced CNRs of the portal and hepatic vein significantly (P < 0.0001). The time required to create VR images was significantly shorter with ASIR (84.7 vs. 117.1 s; P = 0.014).

Conclusion

ASIR enhances CNRs and improves image quality in VR CT portovenography. It also shortens the time required to create liver VR CT portovenographs.

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Authors and Affiliations

  1. Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan

    Izuru Matsuda, Shohei Hanaoka, Masaaki Akahane, Jiro Sato, Shuuhei Komatsu, Shinichi Inoh & Kuni Ohtomo

  2. Department of Radiology, Institute of Medical Science, The University of Tokyo, Tokyo, Japan

    Shigeru Kiryu

  3. Department of Integrated Imaging Informatics, The University of Tokyo Hospital, Tokyo, Japan

    Naoki Yoshioka

  4. Department of Clinical Radiology, The University of Tokyo Hospital, Tokyo, Japan

    Kenji Ino

Authors
  1. Izuru Matsuda
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  2. Shohei Hanaoka
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  3. Masaaki Akahane
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  4. Jiro Sato
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  5. Shuuhei Komatsu
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  6. Shinichi Inoh
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  7. Shigeru Kiryu
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  8. Naoki Yoshioka
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  9. Kenji Ino
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  10. Kuni Ohtomo
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Corresponding author

Correspondence to Izuru Matsuda.

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Matsuda, I., Hanaoka, S., Akahane, M. et al. Adaptive statistical iterative reconstruction for volume-rendered computed tomography portovenography: improvement of image quality. Jpn J Radiol 28, 700–706 (2010). https://doi.org/10.1007/s11604-010-0490-5

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  • DOI: https://doi.org/10.1007/s11604-010-0490-5

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