MRI and Meningioma Research: Hotspots and Trends via Bibliometric Analysis

We systematically delineate three evolutionary stages: structural imaging, functional integration, and intelligent analysis. AI-driven models have achieved enhanced diagnostic accuracy (AUC 0.82-0.97), but remain limited by heterogeneous data standards, low algorithm interpretability, and uneven global resources. Multicentre standardized protocols, interpretable AI frameworks, and lightweight algorithms compatible with ≤1.5 T scanners should be prioritised. By integrating burst-sigma mapping with global equipment metrics, we provide quantitative evidence supporting a field-strength-agnostic strategy for equitable AI deployment.