Predicting isocitrate dehydrogenase (IDH) mutations in gliomas using magnetic resonance imaging (MRI) is clinically important for treatment planning. This study compared two artificial intelligence (AI) models, GliomaDepth-IDH (ResNet34-based) and GliomaVista-IDH (Vision Transformer-based), with 18 physicians (eight neuroradiologists, five neurosurgeons, and five neurosurgery residents) in predicting IDH mutation status. On the Brain Tumor Segmentation Challenge dataset, the GliomaVista-IDH AI model achieved an area under the curve (AUC) value of 0.97, significantly outperforming all physician groups. However, external validation on a Japanese cohort revealed performance degradation: GliomaDepth-IDH declined to an AUC of 0.75 and GliomaVista-IDH to 0.82, with GliomaVista-IDH showing significant calibration issues (Brier score = 0.32). High-performing physicians achieved comparable results (AUC = 0.88) with superior calibration (Brier score = 0.19). Inter-rater reliability analysis revealed substantial variability across physician groups. These findings suggest that AI models can assist many physicians, while experienced practitioners remain competitive with better-calibrated predictions in challenging domains.

Hepatobiliary contrast agents (HBAs) are gadolinium-based contrast agent characterized by hepatocellular uptake and hepatobiliary excretion. The hepatobiliary phase has become an essential tool of modern magnetic resonance imaging (MRI) of the liver and refines the diagnostic capabilities of MRI. The specific characteristic of HBAs allows the combination of MRI dynamic vascular imaging with unique lesion characterization, biliary anatomy and liver functional assessment. The practical use of HBAs in the non-invasive diagnosis of benign hepatocellular lesions must be known, as imaging patterns are specific for focal nodular hyperplasia and hepatic adenomas, and may vary according to adenoma subtypes. HBAs for the non-invasive diagnosis of hepatocellular carcinomas are integrated into Western and Eastern guidelines and on specific criteria for use and interpretation. Metastatic liver disease also represents a major application. Emerging applications include advanced biliary imaging, functional assessment of the liver, and potential role in surveillance strategies. This review summarizes the properties of HBAs, including their pharmacokinetics, safety, and technical considerations for image acquisition. It also discusses their role in characterizing focal liver lesions, highlighting their strengths and limitations.