Improvement of Image Quality Using Hybrid Iterative Reconstruction with Noise Power Spectrum Model in Computed Tomography during Hepatic Arteriography

Hiroshi Hamasaki, Takashi Shirasaka, Yasuhiro Ushijima, Hiroshi Akamine, Yukihisa Takayama, yuichiro kubo, Keisuke Ishimatsu, Akihiro Nishie, Toyoyuki Kato

Research output: Contribution to journalArticlepeer-review

Abstract

Objectives: In CT during hepatic arteriography (CTHA), the addition of a noise power spectrum (NPS) model to conventional hybrid iterative reconstruction (HIR) may improve spatial resolution and reduce image noise. This study aims at assessing the image quality provided by HIR with a NPS model at CTHA. Methods: This institutional review board-approved retrospective analysis included 26 patients with hepatocellular carcinomas (HCCs) who underwent CTHA. In all acquisitions, images were reconstructed with filtered back projection (FBP), adaptive iterative dose reduction 3D (AIDR), and AIDR enhanced (eAIDR) with the NPS model. Four radiologists analyzed the signal-to-noise ratio (SNR) of HCC nodules and its associated feeding arteries. The radiologists used a semiquantitative scale (−3 to +3) to rate the subjective image quality comparing both the FBP and eAIDR images with the AIDR images. Results: The feeding arteries’ attenuation was significantly higher in eAIDR compared to AIDR [514.3 ± 121.4 and 448.3 ± 107.3 Hounsfield units (HU), p < 0.05]. The image noise of eAIDR was significantly lower than that of FBP (15.2 ± 2.2 and 28.5 ± 4.8 HU, p < 0.05) and comparable to that of AIDR. The SNR of feeding arteries on eAIDR was significantly higher than on AIDR (34.1 ± 7.9 and 27.4 ± 6.3, p < 0.05). Subjective assessment scores showed that eAIDR provided better visibility of feeding arteries and overall image quality compared to AIDR (p < 0.05). The HCC nodule visibility was not significantly different among the three reconstructions. Conclusion: In CTHA, eAIDR improved the visibility of feeding arteries associated with HCC nodules without compromising nodule detection.

Original languageEnglish
Article number43
JournalJournal of the Belgian Society of Radiology
Volume105
Issue number1
DOIs
Publication statusPublished - 2021

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

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