Characterization of Portal Vein Thrombosis (Neoplastic Versus Bland) on CT Images Using Software-Based Texture Analysis and Thrombus Density (Hounsfield Units).

Abstract

The purpose of this study was to investigate the role of CT texture analysis and thrombus density (measured in Hounsfield units) in distinguishing between neoplastic and bland portal vein thrombosis (PVT) on portal venous phase CT. In this retrospective study, 117 contrast-enhanced CT studies of 109 patients were included for characterization of PVT. Assessment of PVT was performed by estimation of CT textural features using CT texture analysis software and measurement of attenuation values. For CT texture analysis, filtered and unfiltered images were assessed to quantify heterogeneity using a set of predefined histogram-based texture parameters. The Mann-Whitney U test and binary logistic regression were applied for statistical significance. ROC curves were used to identify accuracy and optimal cutoff values. Of the 117 CT studies, 63 neoplastic thrombi and 54 bland thrombi were identified on the images. The two most discriminative CT texture analysis parameters to differentiate neoplastic from bland thrombus were mean value of positive pixels (without filtration, p < 0.001) and entropy (with fine filtration, p < 0.001). Mean thrombus density values could also reliably distinguish neoplastic (81.39 HU) and bland (32.88 HU) thrombi (p < 0.001). The AUCs were 0.97 for mean value of positive pixels (p < 0.001), 0.93 for entropy (p < 0.001), 0.99 for the model combining mean value of positive pixels and entropy (p < 0.001), 0.91 for thrombus density (p < 0.001), and 0.61 for the radiologist's subjective evaluation (p = 0.037). The optimal cutoffs values were 56.9 for mean value of positive pixels, 4.50 for entropy, and 54.0 HU for thrombus density. CT texture analysis and CT attenuation values allow reliable differentiation between neoplastic and bland thrombi on a single portal venous phase CT examination.