This study published in Insights into Imaging highlighted the potential of a multiparametric MRI-based radiomic model that integrated intratumoral and peritumoral features as a tool to predict differentiation in hepatocellular carcinoma (HCC). The authors found that the IntraPeri model showed an outstanding ability to predict individualized HCC differentiation through integrating intratumoral and optimal peritumoral features. Key points: Both the intratumoral radiomics model and clinical features were useful for predicting HCC differentiation. The Peri_10mm radiomics model demonstrated better diagnostic ability than other peritumoral region-based models. The IntraPeri radiomics fusion model outperformed the other models for predicting HCC differentiation. Article: Multiparametric MRI-based intratumoral and peritumoral radiomics for predicting the pathological differentiation of hepatocellular carcinoma Authors: Hai-Feng Liu, Min Wang, Qing Wang, Yang Lu, Yu-Jie Lu, Ye Sheng, Fei Xing, Ji-Lei Zhang, Sheng-Nan Yu & Wei Xing
Impact of deep learning reconstruction on radiation dose reduction and cancer risk in CT examinations
Deep‑learning reconstruction (DLR) shifts CT image formation from a hardware‑limited process to a data‑driven one. In our real‑world cohort of >10,000 body scans, we observed a
28. April 2025
