Multi-Region MRI-Based Radiomics Predictive Model for METTL3 Expression in Hepatocellular Carcinoma

Motivation: To the best of our knowledge, our study is the first to non-invasively assess methyltransferase-like 3 (METTL3) expression in hepatocellular carcinoma (HCC) using multi-sequence MRI-based radiomics. Goal(s): To develop a multi-region radiomics-based predictive model using multi-sequence MRI to assess METTL3 expression in HCC. Approach: Three Models (Tumor, Tumor-Expand5, Tumor-Expand10) were constructed and evaluated. Results: The Tumor-Expand5 model showed the highest efficacy with an AUC of 0.71 in the test set, outperforming both the Tumor and Tumor-Expand10 models. Multi-sequence MRI-based radiomics models hold the potential for preoperatively assessing METTL3 expression in HCC, aiding clinical decision-making. Impact: This study introduces a novel multi-region radiomics-based model for predicting METTL3 expression in HCC using multi-sequence MRI. The results demonstrate the potential of radiomics, with an emphasis on the Tumor-Expand5 model, highlighting its promise for enhancing clinical decision-making in HCC.