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KMID : 0880420190200040558
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Korean Journal of Radiology
2019 Volume.20 No. 4 p.558 ~ p.568
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Evaluation of the Impact of Iterative Reconstruction Algorithms on Computed Tomography Texture Features of the Liver Parenchyma Using the Filtration-Histogram Method
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Sung Pamela
Lee Jeong-Min
Joa Kyung-Lim
Lee Sang-Hyup
Kim Tae-Hyung
Ganeshan Balaji
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Abstract
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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: IR techniques affect various CT texture features of the liver parenchyma. In particular, model-based IR frequently showed significant differences compared to FBP or hybrid IR on both AP and PVP CT imaging. Significant variation in entropy was observed between the three reconstruction algorithms on PVP imaging (p < 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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KEYWORD
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Computed tomography, Texture analysis, Histogram analysis, Iterative reconstruction, Liver
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