In vitro measurement of the permeability of endovascular coils deployed in cerebral aneurysms

Modeling Flow in Cerebral Aneurysm After Coils Embolization Treatment: A Realistic Patient-Specific Porous Model Approach

PURPOSE

Computational fluid dynamics (CFD) has been used to evaluate the efficiency of endovascular treatment in coiled cerebral aneurysms. The explicit geometry of the coil mass cannot typically be incorporated into CFD simulations since the coil mass cannot be reconstructed from clinical images due to its small size and beam hardening artifacts. The existing methods use imprecise porous medium representations. We propose a new porous model taking into account the porosity heterogeneity of the coils deployed in the aneurysm.

METHODS

The porosity heterogeneity of the coil mass deployed inside two patients' cerebral aneurysm phantoms is first quantified based on 3D X-ray synchrotron images. These images are also used to compute the permeability and the inertial factor arising in porous models. A new homogeneous porous model (porous crowns model), considering the coil's heterogeneity, is proposed to recreate the flow within the coiled aneurysm. Finally, the validity of the model is assessed through comparisons with coil-resolved simulations.

RESULTS

The strong porosity gradient of the coil measured close to the aneurysmal wall is well captured by the porous crowns model. The permeability and the inertial factor values involved in this model are closed to the ideal homogeneous porous model leading to a mean velocity in the aneurysmal sac similar as in the coil-resolved model.

CONCLUSION

The porous crowns model allows for an accurate description of the mean flow within the coiled cerebral aneurysm.

Endovascular treatment of medium and large intracranial aneurysms with large volume coils: A single-center experience

Background:

Large volume coils are an alternative to conventional coils for the treatment of intracranial aneurysms. However, there are no published reports documenting occlusion and complication rates in medium and large intracranial aneurysms. Therefore, we present our results in this subgroup of aneurysms.

Methods:

A single-center, retrospective analysis of consecutive patients treated with Penumbra coils 400 in aneurysms ≥7 mm was performed. Demographics, aneurysm features, procedural details, intraoperative complications, clinical outcomes, and occlusion rates were analyzed.

Results:

Thirty-three patients were included for analysis, and a total of 33 intracranial aneurysms were analyzed. Mean age was 57.6 years (SD ± 12.4) and 85% of the patients were women. Large aneurysms represented 46% of cases. Paraclinoid (55%) followed by posterior communicating (30.3%) aneurysms was the most frequently treated. Ruptured and saccular aneurysms were found in 49% and 63% of the cases, respectively. The mean aneurysmal dimensions were 14.2 mm width, 11.9 mm length, 5.4 mm neck, and 2.4 dome-to-neck ratio. A dome-neck ratio <2 was identified in 39% of cases. The mean number of coils per aneurysm was 4.8. Immediate modified Raymond–Roy Grades 1, 2, and 3A were achieved in 15%, 21%, and 64%, respectively. Twenty-six patients were evaluated at a mean follow-up period of 11 months, with an adequate occlusion of 92% and a good clinical outcome (modified Rankin score ≤2) in 96% of patients.

Conclusion:

Endovascular treatment with PC400 coils is an effective and safe option for medium and large intracranial aneurysms with high occlusion rates, few complications, and good clinical outcomes at follow-up.

Improving accuracy for finite element modeling of endovascular coiling of intracranial aneurysm

BACKGROUND

Computer modeling of endovascular coiling intervention for intracranial aneurysm could enable a priori patient-specific treatment evaluation. To that end, we previously developed a finite element method (FEM) coiling technique, which incorporated simplified assumptions. To improve accuracy in capturing real-life coiling, we aimed to enhance the modeling strategies and experimentally test whether improvements lead to more accurate coiling simulations.

METHODS

We previously modeled coils using a pre-shape based on mathematical curves and mechanical properties based on those of platinum wires. In the improved version, to better represent the physical properties of coils, we model coil pre-shapes based on how they are manufactured, and their mechanical properties based on their spring-like geometric structures. To enhance the deployment mechanics, we include coil advancement to the aneurysm in FEM simulations. To test if these new strategies produce more accurate coil deployments, we fabricated silicone phantoms of 2 patient-specific aneurysms in duplicate, deployed coils in each, and quantified coil distributions from intra-aneurysmal cross-sections using coil density (CD) and lacunarity (L). These deployments were simulated 9 times each using the original and improved techniques, and CD and L were calculated for cross-sections matching those in the experiments. To compare the 2 simulation techniques, Euclidean distances (dMin, dMax, and dAvg) between experimental and simulation points in standardized CD-L space were evaluated. Univariate tests were performed to determine if these distances were significantly different between the 2 simulations.

RESULTS

Coil deployments using the improved technique agreed better with experiments than the original technique. All dMin, dMax, and dAvg values were smaller for the improved technique, and the average values across all simulations for the improved technique were significantly smaller than those from the original technique (dMin: p = 0.014, dMax: p = 0.013, dAvg: p = 0.045).

CONCLUSION

Incorporating coil-specific physical properties and mechanics improves accuracy of FEM simulations of endovascular intracranial aneurysm coiling.