# Prediction of Histopathological Grade of Hepatocellular Carcinoma by Gadoxetic Acid–Enhanced Magnetic Resonance Imaging Radiomics Features

## TL;DR

This study shows that MRI radiomics features can predict the severity of liver cancer before surgery, helping doctors make better treatment decisions.

## Contribution

The novel contribution is the development of a combined radiomics and clinical model for predicting hepatocellular carcinoma differentiation grade using Gd-EOB-DTPA-enhanced MRI.

## Key findings

- The combined clinical-radiomics model achieved an AUC of 0.827 for predicting HCC differentiation grade.
- Radiomics features were significantly lower in well-differentiated tumors compared to non-well-differentiated ones.
- The albumin-bilirubin score was an independent risk factor in the clinical model.

## Abstract

This study aimed to evaluate preoperative models based on gadoxetic acid (Gd-EOB-DTPA [gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid])–enhanced magnetic resonance imaging (MRI) radiomics for predicting the histopathological grade of hepatocellular carcinoma (HCC).

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.

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 predictors in the CCR model (P = .005).

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 validation; therefore, further multicenter studies are necessary.