This session showcases cutting-edge advances in quantitative MRI and artificial intelligence for precision brain tumor diagnosis, characterization, and treatment monitoring. Research presentations span ultra-high-field imaging (7T and 9.4T), advanced diffusion techniques (DKI, CEST, PETRA), radiomics, and deep learning applications that enable molecular classification, prognostic assessment, and treatment response evaluation in gliomas, meningiomas, and CNS lymphomas. Key clinical applications include differentiating tumor types, detecting pseudoprogression versus recurrence, grading gliomas, predicting genetic mutations, and assessing radiation-induced changes—all driven by quantitative biomarkers that move beyond binary classification toward continuous, clinically actionable insights.

Skill Level: Intermediate