Radiation Necrosis in Neuro-Oncology: Diagnostic Complexity and Precision Radiotherapy Strategies.

BACKGROUND: Radiation necrosis (RN) is a delayed and potentially debilitating complication of radiotherapy for central nervous system (CNS) tumors. It presents significant diagnostic and therapeutic challenges due to the variable clinical manifestations and overlap with tumor recurrence. Although advances in radiotherapy have improved tumor control, RN remains incompletely understood and inadequately addressed. This narrative review synthesizes current evidence on RN pathophysiology, risk factors, diagnostic strategies, and management approaches. METHODS: A literature search was conducted for English-language literature published between January 1990 and December 2024. Studies were included if they addressed RN incidence, diagnosis, treatment, or novel preventive strategies in CNS tumor populations. Relevant findings were synthesized to produce a narrative review summarizing pathophysiology, diagnostic challenges, and treatment strategies. RESULTS: RN results from radiation-induced neurovascular injury, inflammation, and vessel permeability, with incidence ranging from 3 to 26% depending on tumor type, location, and treatment parameters. Risk is influenced by dose, fractionation, cumulative exposure, re-irradiation, and adjuvant therapies. Advanced modalities such as SRS, HFSRT, brachytherapy, proton therapy, and IORT reduce but do not eliminate RN risk. Diagnosis remains challenging despite advanced MRI and PET techniques, with histopathology as the gold standard. Management includes corticosteroids, bevacizumab, surgery, LITT, and experimental therapies. Connectomics-based planning shows promise in minimizing RN by sparing critical brain networks. CONCLUSIONS: RN is a clinically significant and multifactorial complication of CNS radiotherapy. Precision treatment modalities and advanced imaging have improved prevention and detection, but diagnostic uncertainty and recurrence risk persist. Integration of connectomics into treatment planning may offer future promise of a reduction in RN-related morbidity by preserving structural and functional network integrity.