A computational model for prediction of clot platelet content in flow-diverted intracranial aneurysms

Treatment of intracranial aneurysms with flow-diverting stents is a safe and minimally invasive technique. The goal is stable embolisation that facilitates stent endothelialisation, and elimination of the aneurysm. However, it is not fully understood why some aneurysms fail to develop a stable clot even with sufficient levels of flow reduction. Computational prediction of thrombus formation dynamics can help predict the post-operative response in such challenging cases. In this work, we propose a new model of thrombus formation and platelet dynamics inside intracranial aneurysms. Our novel contribution combines platelet activation and transport with fibrin generation, which is key to characterising stable and unstable thrombus. The model is based on two types of thrombus inside aneurysms: red thrombus (fibrin- and erythrocyte-rich) can be found in unstable clots, while white thrombus (fibrin- and platelet-rich) can be found in stable clots. The thrombus generation model is coupled to a CFD model and the flow-induced platelet index (FiPi) is defined as a quantitative measure of clot stability. Our model is validated against an in vitro phantom study of two flow-diverting stents with different sizing. We demonstrate that our model accurately predicts the lower thrombus stability in the oversized stent scenario. This opens possibilities for using computational simulations to improve endovascular treatment planning and reduce adverse events, such as delayed haemorrhage of flow-diverted aneurysms

Patient-specific modelling of blood-flow in cerebral aneurysms

Cerebral aneurysms are a pathology of the cerebral vasculature in which an area of the blood vessel wall weakens and balloons. These pose a serious risk of rupture and can result in life-threatening cerebral haemorrhages. Treatment of cerebral aneurysms is either by surgical clipping or by coils or stents inserted by interventional radiological techniques. The choice of treatment is currently based on clinical experience and on the position and size of the aneurysm. Combining medical imaging with computational fluid dynamics (CFD) analysis makes possible patient-specific modelling of blood-flow within the aneurysm and surrounding vasculature and the potential to model different treatment options. A first stage in this research was to determine the feasibility of patient-specific modelling and the use of in-silico techniques to study flow for the first time in the same vessels with and without an aneurysm. Three-dimensional renderings of the cerebral blood vessels were reconstructed from computed tomography angiograms of the head using Matlab (The MathWorks) for image processing and ScanIP (Simpleware Inc.) for 3D rendering and meshing. Meshes were then imported into COMSOL Multiphysics for finite element analysis. Pulsatile blood-flow was simulated through the cerebrovascular vessels and the velocity, pressure and wall shear stress determined. This was done for both the vessels with the aneurysm and where the aneurysm had been ‘virtually’ removed. The results show a reduced shear stress on the vessel wall without the aneurysm which is consistent with the hypothesis that the wall is weakened and then subsequently balloons with the onset of hypertension