Characterization of Hepatocellular Carcinoma and Ablation-Induced Immune Response Using Machine Learning and Molecular MRI Biomarkers

This research aimed to establish and analyze magnetic resonance imaging (MRI) bi-omarkers for two purposes: outcome prediction in patients with hepatocellular carcinoma (HCC) undergoing radiofrequency (RF) ablation, and characterization of the immune response to hepatic RF ablation in a mouse model. The first study analyzed Liver Imaging Reporting and Data System (LI-RADS) features and developed a radiomics-based machine learning (ML) algorithm in pretreatment MRI to predict progression-free survival (PFS). The second study focused on establishing MRI contrast agents such as rhodamine-labeled superparamagnetic iron nanoparticles (SPIONs) and Gadolinium-160 (160Gd)-labeled CD68 antibodies for in vivo visualization of macrophages. In the first study, 65 patients with 85 nodular HCC tumors