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

<bold>Purpose: </bold>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.<bold>Materials and Methods: </bold>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.<bold>Results: </bold>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).<bold>Conclusion: </bold>ASIR enhances CNRs and improves image quality in VR CT portovenography. It also shortens the time required to create liver VR CT portovenographs. [ABSTRACT FROM AUTHOR]