BACKGROUND AND PURPOSE:Flow-diverting approaches to intracranial aneurysm treatment had many promising early results, but recent apparently successful treatments have been complicated by later aneurysm hemorrhage. We analyzed 7 cases of aneurysms treated with flow diversion to explore the possible rupture mechanisms.

The occlusion time of cerebral aneurysms treated with flow diverters can be predicted by the hemodynamic conditions created immediately after device implantation. Specifically, low post-implantation flow velocity, inflow rate, and shear rate are associated with fast occlusion times.

The purpose of this article is to review studies of aneurysm risk factors and the suggested hypotheses that connect the different risk factors and the underlying mechanisms governing the aneurysm natural history. The result of this work suggests that at the center of aneurysm evolution there is a cycle of wall degeneration and weakening in response to changing hemodynamic loading and biomechanic stress. This progressive wall degradation drives the geometrical evolution of the aneurysm until it stabilizes or ruptures. Risk factors such as location, genetics, smoking, co-morbidities, and hypertension seem to affect different components of this cycle. However, details of these interactions or their relative importance are still not clearly understood.

Purpose to investigate the relationship between hemodynamic conditions created immediately after flow diversion and subsequent occlusion of experimental aneurysms in rabbits. Methods The hemodynamic environment before and after flow diversion treatment of elastase induced aneurysms in 20 rabbits was modeled using image-based computational fluid dynamics. Local aneurysm occlusion was quantified using a voxelization technique on 3D images acquired 8 weeks after treatment. Global and local voxel-by-voxel hemodynamic variables were used to statistically compare aneurysm regions that later thrombosed to regions that remained patent. Results Six aneurysms remained patent at 8 weeks while 14 were completely or nearly completely occluded. Patent aneurysms had statistically larger neck sizes (p=0.0015) and smaller mean transit times (p=0.02). The velocity, vorticity and shear rate were about 2.8 times (p<0.0001) larger in patent regions, i.e. had larger “flow activity”, than regions that progressed to occlusion. Statistical models based on local hemodynamic variables were capable of predicting local occlusion with good precision (84% accuracy), especially away from the neck (92–94%). Predictions near the neck were poorer (73% accuracy). Conclusion These results suggests that the dominant healing mechanism of occlusion within the aneurysm dome are related to slow flow induced thrombosis while near the neck other processes could be at play simultaneously.

Hemodynamics is thought to be a fundamental factor in the formation, progression and rupture of cerebral aneurysms. Understanding these mechanisms is important to improve their rupture risk assessment and treatment. In this study we analyze the blood flow field in a growing cerebral aneurysm using experimental particle image velocimetry (PIV) and computational fluid dynamics (CFD) techniques. Patient-specific models were constructed from longitudinal 3D computed tomography angiography (CTA) images acquired at one-year intervals. Physical silicone models were constructed from the CTA images using rapid prototyping techniques and pulsatile flow fields were measured with PIV. Corresponding CFD models were created and run under matching flow conditions. Both flow fields were aligned, interpolated, and compared qualitatively by inspection and quantitatively by defining similarity measures between the PIV and CFD vector fields. Results showed that both flow fields were in good agreement. Specifically, both techniques provided consistent representations of the main intra-aneurysmal flow structures, and their change during the geometric evolution of the aneurysm. Despite differences observed mainly in the near wall region and the inherent limitations of each technique, the information derived is consistent and can be used to study the role of hemodynamics in the natural history of intracranial aneurysms.

Simulations using the patient-specific geometry of the aneurysm may help in a better planning of the treatment and in a consequent reduction of the associated risks. We propose, evaluate, and implement a methodology for the simulation of flow diverter (FD) devices in intracranial aneurysms by using a porous medium method (PMM), which greatly reduces the computational cost of these simulations compared with immersed method (IMM) approaches used to model complex FDs. The method relies on parameters from an empirical correlation derived from experimental observations in wire screens, consistent with CFD simulations. The verification of our PMM strategy was carried out by comparing the results of simulations in different (patient-specific) geometries and FDs, to those obtained under identical conditions by the IMM. Overall, both quantitative and qualitative results are consistent between IMM and PMM in cases where the local porosity remains roughly uniform throughout the neck, with differences in the reduction of the observables lower than 10%. This PMM strategy is up to 10 times faster than the IMM, which allows for a runtime of hours instead of days, bringing it closer for its application in the clinic.

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article.

A High-Performance Reduced-Order Model (HPROM) technique, previously presented by the authors in the context of hierarchical multiscale models for non linear-materials undergoing infinitesimal strains, is generalized to deal with large deformation elasto-plastic problems. The proposed HPROM technique uses a Proper Orthogonal Decomposition (POD) procedure to build a reduced basis of the primary kinematical variable of the micro-scale problem, defined in terms of the micro-deformation gradient fluctuations. Then a Galerkin-projection, onto this reduced basis, is utilized to reduce the dimensionality of the micro-force balance equation, the stress homogenization equation and the effective macro-constitutive tangent tensor equation. Finally, a reduced goal-oriented quadrature rule is introduced to compute the non-affine terms of these equations. Main importance in this paper is given to the numerical assessment of the developed HPROM technique. The numerical experiments are performed on a micro-cell simulating a randomly distributed set of elastic inclusions embedded into an elasto-plastic matrix. This micro-structure is representative of a typical ductile metallic alloy. The HPROM technique applied to this type of problem displays high computational speed-ups, increasing with the complexity of the finite element model. From these results, we conclude that the proposed HPROM technique is an effective computational tool for modeling, with very large speed-ups and acceptable accuracy levels with respect to the high-fidelity case, the multiscale behavior of heterogeneous materials subjected to large deformations involving two well-separated scales of length.