Preoperative CECT-based Radiomic Signature for Predicting the Response of Transarterial Chemoembolization (TACE) Therapy in Hepatocellular Carcinoma.

Abstract

To evaluate the efficiency of radiomics signatures in predicting the response of transarterial chemoembolization (TACE) therapy based on preoperative contrast-enhanced computed tomography (CECT). This study consisted of 111 patients with intermediate-stage hepatocellular carcinoma who underwent CECT at both the arterial phase (AP) and venous phase (VP) before and after TACE. According to mRECIST 1.1, patients were divided into an objective-response group (n = 38) and a non-response group (n = 73). Among them, 79 patients were assigned as the training dataset, and the remaining 32 cases were assigned as the test dataset. Radiomics features were extracted from CECT images. Two feature ranking methods and three classifiers were used to find the best single-phase radiomics signatures for both AP and VP on the training set. Meanwhile, multi-phase radiomics signatures were built upon integration of images from two CECT phases by decision-level fusion and feature-level fusion. Finally, multivariable logistic regression was used to develop a nomogram by combining radiomics signatures and clinic-radiologic characteristics. The prediction performance was evaluated by AUC on the test dataset. The multi-phase radiomics signature (AUC = 0.883) performed better in predicting TACE therapy response compared to the best single-phase radiomics signature (AUC = 0.861). The nomogram (AUC = 0.913) showed better performance than any radiomics signatures. The radiomics signatures and nomogram were developed and validated for predicting responses to TACE therapy, and the radiomics model may play a positive role in identifying patients who may benefit from TACE therapy in clinical practice.