Hemodynamic risk assessment in brain arteriovenous malformations: a computational fluid dynamics study

Hemodynamic factors are crucial in brain arteriovenous malformation (AVM) hemorrhage. This study aims to investigate the correlation between wall shear stress (WSS) and AVM hemorrhage using computational fluid dynamics (CFD) models. This single-center retrospective study analyzed digital subtraction angiography data from AVM patients undergoing embolization (July 2020 to May 2023). Patient-specific 3D AVM models were reconstructed, and hemodynamic parameters were simulated using CFD. Blood was modeled as a Newtonian fluid, with a steady velocity inlet (0.45 m/s) and a pressure outlet applied as boundary conditions. WSS was separately quantified in feeding arteries, nidus, and draining veins for regional comparison. Demographic characteristics, clinical manifestations, AVM morphological features, Spetzler-Martin grade, feeding artery diameter (FAD) and WSS were compared between hemorrhage ( n = 28) and non-hemorrhage ( n = 17) groups using appropriate statistical tests. Extreme WSS outlier was verified and excluded due to numerical mesh artifact. Forty-five patients (mean age 29.93 ± 18.46 years, 25 men) were evaluated, including 28 cases with hemorrhage and 17 without. Comparative analysis of clinical data between hemorrhage and non-hemorrhage groups revealed statistically significant differences in regional WSS (feeding artery and intranidal WSS: 31.05 vs. 3.00 Pa, p < 0.001) and FAD (2.24 ± 0.68 vs. 3.12 ± 0.87 mm, p = 0.003). These results identified nidal and feeding artery WSS as an independent risk factor for AVM rupture. Furthermore, Pearson’s correlation analysis demonstrated a significant negative correlation between regional WSS and FAD ( r =-0.403, p = 0.005). Regional WSS (feeding artery and nidus) and FAD may serve as important indicators for AVM rupture. Notably, both regional WSS and FAD can be derived from routine angiographic data, offering a clinically feasible approach for hemodynamic risk assessment and may serve as important indicators for AVM rupture risk assessment and personalized treatment planning.