MRI‐Based Radiomics: Associations With the Recurrence‐Free Survival of Patients With Hepatocellular Carcinoma Treated With Conventional Transcatheter Arterial Chemoembolization

Abstract

BackgroundPreoperative estimation of hepatocellular carcinoma (HCC) recurrence after conventional transcatheter arterial chemoembolization (c‐TACE) is crucial for subsequent follow‐up and therapy decisions.PurposeTo evaluate the associations of radiomics models based on pretreatment contrast‐enhanced MRI, a clinical‐radiological model and a combined model with the recurrence‐free survival (RFS) of patients with HCC after c‐TACE, and to develop a radiomics nomogram for individual RFS estimations and risk stratification.Study TypeRetrospective.PopulationIn all, 184 consecutive HCC patients.Field Strength/Sequence1.5T or 3.0T, including T2WI, T1WI, and contrast‐enhanced T1WI.AssessmentAll HCC patients were randomly divided into the training (n = 110) and validation datasets (n = 74). Radiomics signatures capturing intratumoral and peritumoral expansion (1, 3, and 5 mm) were constructed, and the radiomics models were set up using least absolute shrinkage and selection operator (LASSO) Cox regression. Clinical‐radiological features were identified by univariate and multivariate Cox regression. The clinical‐radiological model and the combined model fusing the radiomics signature with the clinical‐radiological risk factors were developed by a multivariate Cox proportional hazard model. A radiomics nomogram derived from the combined model was established.Statistical TestsLASSO Cox regression, univariate and multivariate Cox regression, Kaplan–Meier analysis were performed. The discrimination performance of each model was quantified by the C‐index.ResultsAmong the different peritumoral expansion models, only the 3‐mm peritumoral expansion model (C‐index, 0.714) showed a comparable performance (P = 0.4087) to that of the portal venous phase intratumoral model (C‐index, 0.727). The combined model showed the best performance and the C‐index was 0.802. Kaplan–Meier analysis showed that the cutoff values of the combined model relative to a median value (1.7426) perfectly stratified these patients into high‐risk and low‐risk subgroups.Data ConclusionThe combined model is more valuable than the clinical‐radiological model or radiomics model alone for evaluating the RFS of HCC patients after c‐TACE, and the radiomics nomogram can be used to preoperatively and individually estimate RFS.Level of Evidence: 3Technical Efficacy Stage: 4J. Magn. Reson. Imaging 2020;52:461–473.

Radiomics Analysis on Multiphase Contrast-Enhanced CT: A Survival Prediction Tool in Patients With Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization

“…Interestingly, the proposed radiomics signature included two peritumoral radiomics features from arterial phase imaging rather than the portal venous phase image. This finding was consistent with previous studies, in which the presence of peritumoral enhancement in arterial phase images indicated tumor biological aggressiveness ( 22 , 35 ). Unlike previous studies, in which a peritumoral expansion distance of 1, 3, or 5 mm was set ( 21 , 22 ), we selected a radial distance of 10 mm in this study.…”

“…This finding was consistent with previous studies, in which the presence of peritumoral enhancement in arterial phase images indicated tumor biological aggressiveness ( 22 , 35 ). Unlike previous studies, in which a peritumoral expansion distance of 1, 3, or 5 mm was set ( 21 , 22 ), we selected a radial distance of 10 mm in this study. According to the guideline of pathological sampling of HCC specimens, liver tissue within a 10 mm distance was defined as the adjacent peritumoral region ( 36 ).…”

“…However, applying radiomics on multiphasic contrast-enhanced CT imaging to predict survival after TACE is rarely investigated. Some studies demonstrated that analyzing the texture of both the intratumoral plus peritumoral regions provided superior prognosis prediction for patients with HCC compared to the intratumoral region alone ( 21 , 22 ). Therefore, we hypothesized that a radiomics pattern from peritumoral regions might be valuable for prognosis prediction.…”

Radiomics Analysis Based on Multiparametric MRI for Predicting Early Recurrence in Hepatocellular Carcinoma After Partial Hepatectomy

“…Some conventional image features, such as non‐smooth tumor margin, vascular invasion, and peritumoral hypointensity on hepatobiliary phase (HBP) have been shown to be related to the prognosis of HCC 11–13 . However, the imaging features obtained by conventional MR images are limited, cannot comprehensively reflect intratumor heterogeneity, and are subjective 14,15 . Therefore, the accurate prediction of ER using such qualitative imaging characteristics remains challenging for clinicians.…”

AI-Based Radiological Imaging for HCC: Current Status and Future of Ultrasound

“…The integration of multimodal data with contrast-enhanced CT also appears effective in predicting prognosis after TACE, showing an accuracy (concordance index) of 0.73 and AUCs ranging from 0.85 to 0.90 in predicting 3-to 10-year survival [72]. The last study in 184 HCC patients used pretreatment contrast-enhanced MRI with gadodiamide for recurrence-free survival, and the combined model was the best with a C-index of 0.802 [73].…”