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

Purpose: To evaluate the efficiency of radiomics signatures in predicting the response of transarterial chemoembolization (TACE) therapy based on preoperative contrast-enhanced computed tomography (CECT).

Materials: 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.

Methods: 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.

Results: 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.

Conclusion: 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.