Cerebral arteriovenous malformations (cAVMs) are vascular abnormalities associated with a significant risk of rupture and hemorrhage. Endovascular embolization is a potentially curative treatment for a large set of malformations, but its success and safety depend on cAVM hemodynamics. However, hemodynamics is unpredictable in many cases. Therefore, computational models have become a valuable tool for investigating cAVM hemodynamics, offering insights that are otherwise difficult or impossible to obtain before or during interventions. Moreover, these models could be used to optimize the endovascular procedure pre-operatively. This review provides an overview of the two principal computational approaches used to simulate cAVM hemodynamics and embolization, i.e., lumped parameter models and computational fluid dynamics (CFD). Lumped parameter models simplify the complex vasculature by representing it as an electrical analog circuit. These models have evolved from simple, idealized geometries to sophisticated networks informed by patient-specific data, including the implementation of autoregulation mechanisms. In contrast, CFD models offer spatially resolved simulations of fluid flow by solving governing equations on discretized domains. To model the anatomical complexity of the cAVM nidus, several CFD studies employ porous media implementations, approximating the nidus' vascular network as a sponge-like material. Furthermore, the use of multiphase flow allows for the explicit simulation of embolic agent injections, their solidification process, and their occlusive effect. Both modeling approaches have already shown added value regarding validating clinical observations, estimating rupture risk, and predicting embolization effects. Toward the future, we envision that these models could lead to more effective, personalized treatment for cAVM patients.
Duquesne et al. (Fri,) studied this question.