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Background/Aims: This study aimed to evaluate preoperative models based on gadoxetic acid (Gd-EOB-DTPA [gadolinium ethoxyben zyl diethylenetriamine pentaacetic acid])–enhanced magnetic resonance imaging (MRI) radiomics for predicting the histopathological grade of hepatocellular carcinoma (HCC).
Materials and Methods: This retrospective study included 68 treatment-naïve patients with histopathologically confirmed HCC from September 2015 to November 2021. Tumors were categorized into well-differentiated and non-well-differentiated groups. Radiomics features were extracted from preoperative hepatobiliary phase MRI images. Logistic regression (LR) with least absolute shrinkage and selection operator selection was used to identify key radiomics features and clinical parameters. Three models—radiomics, clinical, and combined clinical-radiomics (CCR)—were developed to predict HCC differentiation.
Results: The radiomics and clinical models achieved area under the curve (AUC) values of 0.803 and 0.749, respectively, while the CCR model showed superior performance (AUC 0.827). In the clinical model, the albumin-bilirubin score was an independent risk factor (P < .05). The radiomics score was significantly lower in well-differentiated tumors (P < .001). Radiomics features were independent predic tors in the CCR model (P = .005).
Conclusion: Radiomics features from hepatobiliary phase MRI and clinical parameters can effectively predict the differentiation grade of HCC, aiding in preoperative decision-making. However, the study is limited by its small sample size and the absence of external vali dation; therefore, further multicenter studies are necessary.
Cite this article as: Akbas B, Balli T, Aikimbaev K, et al. Prediction of histopathological grade of hepatocellular carcinoma by gadoxetic acid–enhanced magnetic resonance imaging radiomics features. Turk J Gastroenterol. Published online November 21, 2025. doi:10.5152/tjg.2025.25431.