Intratumoral and Peritumoral Radiomics Based on Contrast-enhanced MRI for Preoperatively Predicting Treatment Response of Transarterial Chemoembolization in Hepatocellular Carcinoma

Abstract

Abstract Background Noninvasive and precise methods to estimate treatment response and identify hepatocellular carcinoma (HCC) patients who could benefit from transarterial chemoembolization (TACE) are urgently required. The present study aimed to investigate the ability of intratumoral and peritumoral radiomics based on contrast-enhanced magnetic resonance imaging (CE-MRI) to preoperatively predict tumor response to TACE in HCC patients. Methods This retrospective study involved 138 HCC patients (objective response, n = 73 vs. non-response, n = 65) who were divided into the training (n = 96) and validation (n = 42) cohorts. Total 1206 radiomics features were extracted from arterial, venous, and delayed phases images. Radiomics models on intratumoral region (TR) and peritumoral region (PTR) (3 mm, 5 mm, and 10 mm) were established using logistic regression. Three integrated radiomics models, including intratumoral and peritumoral region (T-PTR) (3 mm), T-PTR (5 mm), and T-PTR (10 mm) models, were constructed by using TR and PTR radiomics scores. A clinical-radiological model and a combined model incorporating the optimal radiomics score and selected clinical-radiological predictors were constructed, and the combined model was presented as a nomogram. The discrimination, calibration, and clinical utilities were evaluated by receiver operating characteristic curve, calibration curve, and decision curve analysis, respectively. Results The (T-PTR) (3 mm) radiomics model demonstrated the best performance among all radiomics models with an area under the curve (AUC) of 0.911 (95% confidence interval(CI), 0.825–0.975) in the validation cohort. The (T-PTR) (3 mm) radiomics score, alkaline phosphatase, tumor size, and satellite nodule were combined to construct a combined nomogram. The combined nomogram outperformed the clinical-radiological model with the AUCs of 0.918 (95%CI, 0.831–0.986) and 0.782 (95%CI, 0.660–0.902) and achieved good calibration capability and clinical utility. Conclusions CE-MRI-based intratumoral and peritumoral radiomics approach can provide an effective tool for the precise and individualized estimation of treatment response for HCC patients treated with TACE.