Beyond Size: Advanced MRI Breakthroughs in Predicting Intracranial Aneurysm Rupture Risk

Intracranial aneurysms (IAs) are present in approximately 3–5% of the global population and carry a significant risk of rupture, leading to subarachnoid haemorrhage (SAH), a condition associated with high morbidity and mortality. Even with developments in neuroimaging, fundamental clinical difficulty remains in precisely predicting which aneurysms will rupture. Although aneurysm size, location, and patient history define traditional risk assessment, these elements by themselves have insufficient predictive ability. Key elements in rupture risk are aneurysm wall biology, haemodynamics, and inflammation; recent developments in magnetic resonance imaging (MRI) including high-resolution vascular wall imaging (VWI), 4D flow MRI, and quantitative susceptibility mapping (QSM) provide fresh insights on these aspects. The present evidence on these sophisticated MRI techniques is synthesised in this review of the literature, which also analyses their clinical relevance and addresses newly developed computational methods like machine learning for better risk stratification. I underline important studies showing the diagnostic and prognostic worth of MRI-based biomarkers, discuss present constraints, and suggest future lines of research. Personalised aneurysm care could benefit from the combination of multiparametric MRI data with artificial intelligence (AI), hence improving patient outcomes.