A Narrative Review of Theranostics in Neuro-Oncology: Advancing Brain Tumor Diagnosis and Treatment Through Nuclear Medicine and Artificial Intelligence
Rafail C. Christodoulou, Platon S. Papageorgiou, Rafael Pitsillos, Amanda Woodward, Sokratis G. Papageorgiou, Elena E. Solomou, Michalis F. Georgiou
Abstract
This narrative review explores the integration of theranostics and artificial intelligence (AI) in neuro-oncology, addressing the urgent need for improved diagnostic and treatment strategies for brain tumors, including gliomas, meningiomas, and pediatric central nervous system neoplasms. A comprehensive literature search was conducted through PubMed, Scopus, and Embase for articles published between January 2020 and May 2025, focusing on recent clinical and preclinical advancements in personalized neuro-oncology. The review synthesizes evidence on novel theranostic agents-such as Lu-177-based radiopharmaceuticals, CXCR4-targeted PET tracers, and multifunctional nanoparticles-and highlights the role of AI in enhancing tumor detection, segmentation, and treatment planning through advanced imaging analysis, radiogenomics, and predictive modeling. Key findings include the emergence of nanotheranostics for targeted drug delivery and real-time monitoring, the application of AI-driven algorithms for improved image interpretation and therapy guidance, and the identification of current limitations such as data standardization, regulatory challenges, and limited multicenter validation. The review concludes that the convergence of AI and theranostic technologies holds significant promise for advancing precision medicine in neuro-oncology, but emphasizes the need for collaborative, multidisciplinary research to overcome existing barriers and enable widespread clinical adoption.