Computational modelling of clot development in patient-specific cerebral aneurysm cases

ESSENTIALS: Clotting in cerebral aneurysms is a process that can either stabilize the aneurysm or lead to rupture. A patient-specific computational model capable of predicting cerebral aneurysm thrombosis is presented. The different clotting outcomes highlight the importance of personalization of treatment. Once validated, the model can be used to tailor treatment and to clarify clotting processes in aneurysms.

In cerebral aneurysms, clotting can either stabilize the aneurysm sac via aneurysm occlusion, or it can have a detrimental effect by giving rise to embolic occlusion.

The work presented in this study details the development of an in silico model that combines all the salient, clinically relevant features of cerebral aneurysm clotting. A comprehensive computational model of clotting that accounts for biochemical complexity coupled with three-dimensional hemodynamics in image-derived patient aneurysms and in the presence of virtually implanted interventional devices is presented.

The model is developed and presented in two stages. First, a two-dimensional computational model of clotting is presented for an idealized geometry. This enables verification of the methods with existing, physiological data before the pathological state is considered. This model is used to compare the results predicted by two different underlying biochemical cascades. The two-dimensional model is then extended to image-derived, three-dimensional aneurysmal topologies by incorporating level set methods, demonstrating the potential use of this model.

As a proof of concept, comparisons are then made between treated and untreated aneurysms. The prediction of different clotting outcomes for different patients demonstrates that with further development, refinement and validation, this methodology could be used for patient-specific interventional planning.