Evaluation of 4D vascular flow and tissue perfusion in cerebral arteriovenous malformations: influence of Spetzler-Martin grade, clinical presentation, and AVM risk factors.

BACKGROUND AND PURPOSE: The role of intracranial hemodynamics in the pathophysiology and risk stratification of brain AVMs remains poorly understood. The purpose of this study was to assess the influence of Spetzler-Martin grade, clinical history, and risk factors on vascular flow and tissue perfusion in cerebral AVMs.

MATERIALS AND

METHODS

4D flow and perfusion MR imaging was performed in 17 patients with AVMs. Peak velocity and blood flow were quantified in AVM feeding and contralateral arteries, draining veins, and the straight sinus. Regional perfusion ratios (CBF, CBV, and MTT) were calculated between affected and nonaffected hemispheres.

RESULTS

Regarding flow parameters, high-grade AVMs (Spetzler-Martin grade of >2) demonstrated significantly increased peak velocity and blood flow in the major feeding arteries (P < .001 and P = .004) and straight sinus (P = .003 and P = .012) and increased venous draining flow (P = .001). The Spetzler-Martin grade significantly correlated with cumulative feeding artery flow (r = 0.85, P < .001) and draining vein flow (r = 0.80, P < .001). Regarding perfusion parameters, perinidal CBF and CBV ratios were significantly lower (P < .001) compared with the remote ratios and correlated negatively with cumulative feeding artery flow (r = -0.60, P = .014 and r = -0.55, P = .026) and draining vein flow (r = -0.60, P = .013 and r = -0.56, P = .025). Multiple regression analysis revealed no significant association of AVM flow or perfusion parameters with clinical presentation (rupture and seizure history) and AVM risk factors.

CONCLUSIONS

Macrovascular flow was significantly associated with increasing Spetzler-Martin grade and correlated with perinidal microvascular perfusion in cerebral AVMs. Future longitudinal studies are needed to evaluate the potential of comprehensive cerebral flow and perfusion MR imaging for AVM risk stratification.