Evaluation of the Impact of Iterative Reconstruction Algorithms on Computed Tomography Texture Features of the Liver Parenchyma Using the Filtration-Histogram Method

Pamela Sung, Jeong Min Lee, Ijin Joo, Sang Hyup Lee, Tae‐Hyung Kim, Balaji Ganeshan

Korean Journal of Radiology · 2019 · 16 citations · 26 references

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Abstract

OBJECTIVE: To evaluate whether computed tomography (CT) reconstruction algorithms affect the CT texture features of the liver parenchyma. MATERIALS AND METHODS: This retrospective study comprised 58 patients (normal liver, n = 34; chronic liver disease [CLD], n = 24) who underwent liver CT scans using a single CT scanner. All CT images were reconstructed using filtered back projection (FBP), hybrid iterative reconstruction (IR) (iDOSE⁴), and model-based IR (IMR). On arterial phase (AP) and portal venous phase (PVP) CT imaging, quantitative texture analysis of the liver parenchyma using a single-slice region of interest was performed at the level of the hepatic hilum using a filtration-histogram statistic-based method with different filter values. Texture features were compared among the three reconstruction methods and between normal livers and those from CLD patients. Additionally, we evaluated the inter- and intra-observer reliability of the CT texture analysis by calculating intraclass correlation coefficients (ICCs). RESULTS: < 0.05). Comparison between normal livers and those from CLD patients revealed that AP images depend more strongly on the reconstruction method used than PVP images. For both inter- and intra-observer reliability, ICCs were acceptable (> 0.75) for CT imaging without filtration. CONCLUSION: CT texture features of the liver parenchyma evaluated using the filtration-histogram method were significantly affected by the CT reconstruction algorithm used.

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