Improved visualization of a fine intrahepatic biliary duct on drip infusion cholangiography-computed tomography: Impact of knowledge-based iterative model reconstruction

Seiichiro Takao, Akihiro Nishie, Yoshiki Asayama, Kousei Ishigami, Yasuhiro Ushijima, Daisuke Kakihara, Tomohiro Nakayama, Nobuhiro Fujita, Koichiro Morita, Keisuke Ishimatsu, Tomoharu Yoshizumi, Toru Ikegami, Masatoshi Kondo, Hiroshi Honda

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Aim: The purpose of this study was to investigate the visualization of fine biliary ducts with knowledge-based iterative model reconstruction (IMR) in low-dose drip infusion computed tomography (CT) cholangiography (DIC-CT) as compared with filtered back projection (FBP) and hybrid iterative reconstruction (iDose4). Methods: A total of 38 patients underwent DIC-CT for living donor liver transplantation. CT was performed approximately 20 min after the end of the infusion of meglumine iotroxate (100 mL). Images were reconstructed using FBP, iDose4, and IMR, and 1-mm slice images at fixed window level and width were prepared for assessment. Two reviewers independently evaluated the quality of visualization of the fine biliary ducts of the caudate lobe (B1) using a 5-point scale. The visualization scores of three reconstructed images were compared using the Kruskal–Wallis test and Mann–Whitney U-test. Results: For reviewer 1, the visualization score of IMR was significantly higher than that of FBP (P = 0.012), and tended to be higher than that of iDose4 (P = 0.078). For reviewer 2, the visualization score of IMR was significantly higher than those of both FBP and iDose4 (P < 0.01). Conclusions: IMR showed better visualization of B1 on DIC-CT than FBP or iDose4. DIC-CT reconstructed with IMR may be useful to the anatomical grasp of biliary tracts in cases of hepatectomy.

Original languageEnglish
Pages (from-to)629-634
Number of pages6
JournalHepatology Research
Volume50
Issue number5
DOIs
Publication statusPublished - May 1 2020

All Science Journal Classification (ASJC) codes

  • Hepatology
  • Infectious Diseases

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