Enhanced CT Textures Derived From Computer Mathematic Distribution Analysis Enables Arterial Enhancement Fraction Being an Imaging Biomarker Option of Hepatocellular Carcinoma

Purpose: To explore the imaging-clinic relationship and an optional imaging biomarker of Hepatocellular Carcinoma (HCC) by using texture analysis on Arterial Enhancement Fraction (AEF). Materials and methods: The HCC patients treated in No.2 Interventional Ward, ShengJing Hospital of China Medical University from Jun. 2018 to Jun. 2019 were enrolled, for whom, tri-phasic enhanced CT scan were acquired. Perfusion analysis and texture analysis were then performed on the tri-phasic enhanced CT images. After the Region of Interest (ROI) of viable HCC was drawn, 13 AEF textures describing the values distribution were conducted. Between-group comparison of AEF textures was made where the cases had grouping properties, correlation analysis was made between AEF textures and Alpha-fetoprotein (AFP) as well as other clinical data which were digital, regression analysis was made when a significant correlation was found. SPSS 19.0 (IBM) was utilized for statistical analysis, a significant difference was considered when P<0.05. Results: Twenty-five HCC patients were enrolled. Several AEF textures were found to have correlation with clinical features, including Previous Surgery History, Age, Glutamic Oxaloacetylase, Indirect Bilirubin, Creatinine and AFP. The majority of AEF textures (up to 9/13) were found to have correlation with AFP (StdDeviation, Variance, Uniformity, Energy, Entropy, Inertia, Correlation, InverseDifferenceMoment and ClusterProminence), 6 or 7 textures having linear or cubic relationship with AFP (StdDeviation, Variance, Uniformity, Inertia, Correlation, ClusterProminence, plus InverseDifferenceMoment). Conclusion: The AEF textures of HCC are strongly correlated with and are impacted by AFP, which may enable AEF to act as an optional imaging biomarker of HCC.