[Value of texture analysis in evaluating liver cancer recurrence after transarterial chemoembolization].

To investigate the feasibility of contrast-enhanced computer tomography (CT) texture analysis in predicting early recurrence after transarterial chemoembolization (TACE) in patients with liver cancer. A retrospective analysis was performed for 47 patients with liver cancer confirmed by liver biopsy and digital subtraction angiography who underwent upper abdominal contrast-enhanced CT scan before TACE, and according to the presence or absence of focal recurrence within half a year, these patients were divided into early recurrence (ER) group and non-early recurrence (NER) group. The texture analysis was used to delineate tumor boundary layer by layer on the axial contrast-enhanced CT image before liver cancer surgery, and related parameters of tumor heterogeneity, including entropy, mean, non-uniformity, skewness, and kurtosis, were obtained. The independent samples t-test was used for comparison of texture parameters between the two groups. The receiver operating characteristic (ROC) curve was used for the analysis of entropy, mean, and non-uniformity, and the area under the ROC curve (ROC), optical cut-off value, sensitivity, and specificity were calculated to evaluate the efficiency of texture analysis in predicting early focal recurrence after TACE. There were 20 patients in the ER group and 27 in the NER group. The ER group had a maximum major axis length of 88.2±36.3 mm and a maximum minor axis length of 41.4±21.4 mm, and the NER group had a maximum major axis length of 66.9±30.2 mm and a maximum minor axis length of 29.3±19.8 mm; the ER group had significantly higher maximum major and minor axis lengths than the NER group ( = 4.89 and 4.62, < 0.001). The ER group had significantly higher entropy and non-uniformity values than the NER group, and there were no significant differences in skewness and kurtosis between the two groups. Entropy, non-uniformity, and mean had high efficiency in predicting early recurrence after TACE, and the optimal cut-off value of entropy was 4.135. Volumetric texture analysis of contrast-enhanced CT images before liver cancer surgery has a high value in predicting early recurrence after TACE.