Metabolic Imaging and Molecular Signatures Reveal Metabolic Phenotypes in Recurrent Glioblastoma

Recurrent glioblastoma remains a clinical challenge because of metabolic heterogeneity and the difficulty in differentiating true progression from therapy-related changes. Methods: We conducted a prospective study with 30 patients, combining dynamic ¹⁸F-fluciclovine PET, perfusion MRI, and transcriptome profiling. Results: Kinetic PET parameters and MRI-derived blood volume measures correlated with overall survival. RNA sequencing revealed that high tracer uptake was associated with amino acid transport and autophagy pathways, whereas low uptake was linked to glycolysis signatures. Conclusion: In this cohort, molecular imaging metrics were closely connected to metabolic programs in glioblastoma, providing mechanistic insights into tumor biology in vivo. Beyond glioblastoma, this integrated imaging-omics approach may have potential applications in biomarker-driven patient stratification and targeted therapy in precision oncology.