Intracranial Aneurysm Rupture Risk Prediction and Endovascular Virtual Intervention
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This study focuses on identifying morphological and hemodynamic predictors for intracranial aneurysm rupture and also investigating the virtual stenting interventional treatment of aneurysms. Intracranial aneurysm has high prevalence, affecting 2∼5% of entire population. The annual rupture risk is relative low, around 1% of aneurysm patients. However, aneurysm rupture caused subarachnoid hemorrhage is the most severe form of stroke, resulting in 50% death from initial hemorrhage and 20∼25% have permanent disability among survivors. At the same time, surgical clipping and endovascular intervention always do carry a risk. Thus, the best aneurysm patient care would be only to treat the ones that are likely to rupture. How do we know which aneurysms are likely to rupture? The first part of this study tries to identify the rupture risk predictors from morphology and hemodynamics. In Chapter 2, 119 aneurysms were studied for both morphological and hemodynamic aspects aiming to find the rupture prediction models. We built 3 aneurysm rupture probability stratification models based on morphology only, hemodynamics only, and combined. High rupture risk was found to be associated with a large size ratio defined as the ratio between aneurysm and parent vessel diameter, low wall shear stress (WSS), and high oscillatory shear index (OSI). In Chapter 3, we validated these three rupture prediction models by a prospectively collected new cohort of 85 aneurysms. These models were able to correctly predict the rupture status around 80%. There are two types of treatments for aneurysms: surgical clipping and endovascular intervention. Since surgical clipping requires long time for patients to recover, more and more aneurysms are treated by endovascular interventions now. Flow diverters are emerging as novel devices to treat wide-necked, fusiform, and giant cerebral aneurysms since these types of aneurysms are either untreatable otherwise or have high recurrence rate when treated by endovascular coils, with up to approximately 50% recurrence rates for giant and wide-necked aneurysms. Thus in the second part of this study, we firstly investigated the flow diversion using Enterprise and Vision stents. By placement of multiple stents, aneurysmal hemodynamic activity was significantly reduced, thereby increasing the likelihood of inducing aneurysm thrombotic occlusion. Furthermore, in Chapter 5, we investigated the flow modification by flow diverting stents (Pipeline Embolization Device, PED). We demonstrated that denser packing has much better flow diversion ability than the uniform packing fashion. At the last part, effects of blood rehology and inlet waveform boundary condition were investigated. In Chapter 6, we demonstrated that the Newtonian blood rheology assumption is usually acceptable for CFD simulation of cerebral aneurysm hemodynamics, but could underestimate viscosity and overestimate shear rate and WSS in the slowly recirculating flow regions. In Chapter 7, the study showed that different waveforms with the same flow rate for inlet boundary conditions will give the same WSS distribution and quantifications, and give the same trend for OSI with different OSI values for individual aneurysm. Thus, WSS and OSI are reliable parameters in intracranial aneurysm rupture risk assessment.