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Hybrid Type iterative reconstruction method vs. filter back projection method: Capability for radiation dose reduction and perfusion assessment on dynamic first-pass contrast-enhanced perfusion chest area-detector CT

  • Yoshiharu Ohno
  • , Hisanobu Koyama
  • , Yasuko Fujisawa
  • , Takeshi Yoshikawa
  • , Hiroyasu Inokawa
  • , Naoki Sugihara
  • , Shinichiro Seki
  • , Kazuro Sugimura

研究成果: ジャーナルへの寄稿 › 学術論文 › 査読

抄録

Purpose To directly compare the capability of hybrid-type iterative reconstruction (i.e., adaptive iterative dose reduction using 3D processing: AIDR 3D) and filter back projection (FBP) for radiation dose reduction during dynamic contrast-enhanced (CE-) perfusion area-detector CT (ADCT) for lung and nodule perfusion assessment. Materials and methods Thirty-six patients with lung cancers who underwent perfusion ADCT (SD-ADCT) at 120 mA and were enrolled in this study. ADCT data at 80 mA (reduced-dose ADCT: RD-ADCT), 60 mA (low-dose ADCT: LD-ADCT) and 40 mA (very low-dose ADCT: VLD-ADCT) were computationally simulated using SD-ADCT data, and reconstructed with and without AIDR 3D. Image noise and lung and nodule perfusion parameters were evaluated using ROI measurements. To determine the utility of AIDR 3D for dose reduction, image noise was compared between each protocol with and without AIDR 3D by means of the t-test. Correlations and limits of agreement for parameters obtained with SD-ADCT and other protocols were also evaluated. Results Image noise of all protocols with AIDR 3D was significantly lower than that of LD-ADCT and VLD-ADCT without AIDR 3D (p < 0.05). Significant correlations for image noise between SD-ADCT and all protocols with AIDR 3D (0.45 ≤ r ≤ 0.99, p < 0.0001) were equal to or better than that without AIDR 3D (0.28 ≤ r ≤ 0.99, p < 0.0001). The limits of agreement for perfusion parameters with AIDR 3D were smaller than those without AIDR 3D for each tube current. Conclusion AIDR 3D is more effective than FBP for dose reduction of perfusion ADCT while maintaining image quality and reducing measurement errors.

本文言語英語
ページ(範囲)164-175
ページ数12
ジャーナルEuropean journal of radiology
巻85
号1
DOI
出版ステータス出版済み - 01-01-2016
外部発表はい

UN SDG

この成果は、次の持続可能な開発目標に貢献しています

  1. SDG 3 - すべての人に健康と福祉を
    SDG 3 すべての人に健康と福祉を

All Science Journal Classification (ASJC) codes

  • 放射線学、核医学およびイメージング

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