A new combined parameter predicts re-treatment for coil-embolized aneurysms: a computational fluid dynamics multivariable analysis study

Impact Exploration of Spatiotemporal Feature Derivation and Selection on Machine Learning-Based Predictive Models for Post-Embolization Cerebral Aneurysm Recanalization

PURPOSE

To enhance the performance of machine learning (ML) models for the post-embolization recanalization of cerebral aneurysms, we evaluated the impact of hemodynamic feature derivation and selection method on six ML algorithms.

METHODS

We utilized computational fluid dynamics (CFD) to simulate hemodynamics in 66 cerebral aneurysms from 65 patients, including 57 stable and nine recanalized aneurysms. We derived a total of 107 features for each aneurysm, encompassing four clinical features, 12 morphological features, and 91 hemodynamic features. To investigate the influence of feature derivation and selection methods on the ML models, we employed two derivation methods, simplified and fully derived, in combination with four selection methods: all features, statistically significant analysis, stepwise multivariate logistic regression analysis (stepwise-LR), and recursive feature elimination (RFE). Model performance was assessed using the area under the receiver operating characteristic curve (AUROC) and precision-recall curve (AUPRC) on both the training and testing datasets.

RESULTS

The AUROC values on the testing dataset exhibited a wide-ranging spectrum, spanning from 0.373 to 0.863. Fully derived features and the RFE selection method demonstrated superior performance in intra-model comparisons. The multi-layer perceptron (MLP) model, trained with RFE-selected fully derived features, achieved the best performance on the testing dataset, with an AUROC value of 0.863 (95% CI: 0.684- 1.000).

CONCLUSION

Our study demonstrated the importance of feature derivation and selection in determining the performance of ML models. This enabled the development of accurate decision-making models without the need to invade the patient.

Evaluation of the shrinkage process of a neck remnant after stent-coil treatment of a cerebral aneurysm using silent magnetic resonance angiography and computational fluid dynamics analysis: illustrative case

BACKGROUND

Silent magnetic resonance angiography (MRA) mitigates metal artifacts, facilitating clear visualization of neck remnants after stent and coil embolization of cerebral aneurysms. This study aims to scrutinize hemodynamics at the neck remnant by employing silent MRA and computational fluid dynamics.

OBSERVATIONS

The authors longitudinally tracked images of a partially thrombosed anterior communicating artery aneurysm's neck remnant, which had been treated with stent-assisted coil embolization, using silent MRA over a decade. Computational fluid dynamics delineated the neck remnant's reduction process, evaluating hemodynamic parameters such as flow rate, wall shear stress magnitude and vector, and streamlines. The neck remnant exhibited diminishing surface area, volume, neck size, dome depth, and aspect ratio. Its reduction correlated with a decline in the flow rate ratio of the remnant dome to the inflow parent artery. Analysis delineated regions within the contracting neck remnant characterized by consistently low average wall shear stress magnitude and variation, accompanied by notable variations in wall shear stress vector directionality.

LESSONS

Evaluation of neck remnants after stent-coil embolization is possible through silent MRA and computational fluid dynamics. Predicting the neck remnant reduction may be achievable through hemodynamic parameter analysis.

Determination of Significant Three-Dimensional Hemodynamic Features for Postembolization Recanalization in Cerebral Aneurysms Through Explainable Artificial Intelligence

BACKGROUND

Recanalization poses challenges after coil embolization in cerebral aneurysms. Establishing predictive models for postembolization recanalization is important for clinical decision making. However, conventional statistical and machine learning (ML) models may overlook critical parameters during the initial selection process.

METHODS

In this study, we automated the identification of significant hemodynamic parameters using a PointNet-based deep neural network (DNN), leveraging their three-dimensional spatial features. Further feature analysis was conducted using saliency mapping, an explainable artificial intelligence (XAI) technique. The study encompassed the analysis of velocity, pressure, and wall shear stress in both precoiling and postcoiling models derived from computational fluid dynamics simulations for 58 aneurysms.

RESULTS

Velocity was identified as the most pivotal parameter, supported by the lowest P value from statistical analysis and the highest area under the receiver operating characteristic curves/precision-recall curves values from the DNN model. Moreover, visual XAI analysis showed that robust injection flow zones, with notable impingement points in precoiling models, as well as pronounced interplay between flow dynamics and the coiling plane, were important three-dimensional features in identifying the recanalized aneurysms.

CONCLUSIONS

The combination of DNN and XAI was found to be an accurate and explainable approach not only at predicting postembolization recanalization but also at discovering unknown features in the future.

Fluid dynamic analysis in predicting the recanalization of intracranial aneurysms after coil embolization - A study of spatiotemporal characteristics

Purpose

Hemodynamics play a key role in the management of cerebral aneurysm recanalization after coil embolization; however, the most reliable hemodynamic parameter remains unknown. Previous studies have explored the use of both spatiotemporally averaged and maximal definitions for hemodynamic parameters, based on computational fluid dynamics (CFD) analysis, to build predictive models for aneurysmal recanalization. In this study, we aimed to assess the influence of different spatiotemporal characteristics of hemodynamic parameters on predictive performance.

Methods

Hemodynamics were simulated using CFD for 66 cerebral aneurysms from 65 patients. We evaluated 14 types of spatiotemporal definitions for two hemodynamic parameters in the pre-coiling model and five in virtual post-coiling model (VM) created by cutting the aneurysm from the pre-coiling model. A total of 91 spatiotemporal hemodynamic features were derived and utilized to develop univariate predictor (UP) and multivariate logistic regression (LR) models. The model's performance was assessed using two metrics: the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC).

Results

Different spatiotemporal hemodynamic features exhibited a wide range of AUROC values ranging from 0.224 to 0.747, with 22 feature pairs showing a significant difference in AUROC value (P-value <0.05), despite being derived from the same hemodynamic parameter. PDave,q1 was identified as the strongest UP with AUROC/AUPRC values of 0.747/0.385, yielding sensitivity and specificity value of 0.889 and 0.614 at the optimal cut-off value, respectively. The LR model further improved the prediction performance, having AUROC/AUPRC values of 0.890/0.903. At the optimal cut-off value, the LR model achieved a specificity of 0.877, sensitivity of 0.719, outperforming the UP model.

Conclusion

Our research indicated that the characteristics of hemodynamic parameters in terms of space and time had a significant impact on the development of predictive model. Our findings suggest that LR model based on spatiotemporal hemodynamic features could be clinically useful in predicting recanalization after coil embolization in patients, without the need for invasive procedures.

Improving the accuracy of computational fluid dynamics simulations of coiled cerebral aneurysms using finite element modeling

Cerebral aneurysms are a serious clinical challenge, with ∼half resulting in death or disability. Treatment via endovascular coiling significantly reduces the chances of rupture, but the techniquehas failure rates of ∼20 %. This presents a pressing need to develop a method fordetermining optimal coildeploymentstrategies. Quantification of the hemodynamics of coiled aneurysms using computational fluid dynamics (CFD) has the potential to predict post-treatment outcomes, but representing the coil mass in CFD simulations remains a challenge. We use the Finite Element Method (FEM) for simulating patient-specific coil deployment for n = 4 ICA aneurysms for which 3D printed in vitro models were also generated, coiled, and scanned using ultra-high resolution synchrotron micro-CT. The physical and virtual coil geometries were voxelized onto a binary structured grid and porosity maps were generated for geometric comparison. The average binary accuracy score is 0.8623 and the average error in porosity map is 4.94 %. We then conduct patient-specific CFD simulations of the aneurysm hemodynamics using virtual coils geometries, micro-CT generated oil geometries, and using the porous medium method to represent the coil mass. Hemodynamic parameters including Neck Inflow Rate (Qneck) and Wall Shear Stress (WSS) were calculated for each of the CFD simulations. The average relative error in Qneck and WSS from CFD using FEM geometry were 6.6 % and 21.8 % respectively, while the error from CFD using a porous media approximation resulted in errors of 55.1 % and 36.3 % respectively; demonstrating a marked improvement in the accuracy of CFD simulations using FEM generated coil geometries.

Modeling the Mechanical Microenvironment of Coiled Cerebral Aneurysms

Successful occlusion of cerebral aneurysms using coil embolization is contingent upon stable thrombus formation, and the quality of the thrombus depends upon the biomechanical environment. The goal of this study was to investigate how coil embolization alters the mechanical micro-environment within the aneurysm dome. Inertialess particles were injected in three-dimensional, computational simulations of flow inside patient aneurysms using patient-specific boundary conditions. Coil embolization was simulated as a homogenous porous medium of known permeability and inertial constant. Lagrangian particle tracking was used to calculate the residence time and shear stress history for particles in the flow before and after treatment. The percentage of particles entering the aneurysm dome correlated with the neck surface area before and after treatment (pretreatment: R2 = 0.831, P < 0.001; post-treatment: R2 = 0.638, P < 0.001). There was an inverse relationship between the change in particles entering the dome and coil packing density (R2 = 0.600, P < 0.001). Following treatment, the particles with the longest residence times tended to remain within the dome even longer while accumulating lower shear stress. A significant correlation was observed between the treatment effect on residence time and the ratio of the neck surface area to porosity (R2 = 0.390, P = 0.007). The results of this study suggest that coil embolization triggers clot formation within the aneurysm dome via a low shear stress-mediated pathway. This hypothesis links independently observed findings from several benchtop and clinical studies, furthering our understanding of this treatment strategy.

Effects of different stent wire mesh densities on hemodynamics in aneurysms of different sizes

Background

Intracranial stents are used to treat aneurysms by diverting the blood flow from entering into the aneurysmal dome. Although delayed rupture is rare, clinical outcomes are extremely poor in such cases. Hemodynamics after stent deployment may be related to delayed rupture and a better understanding of the basic characteristics of pressure changes resulting from stent deployment is needed; therefore, this study investigated the relationships between hemodynamics in aneurysms of different sizes treated using stents of different wire mesh densities.

Methods

Using computational fluid dynamics analysis, parameters related to velocity, volume flow rate, pressure, and residual volume inside the aneurysm were evaluated in digital models of 5 basic aneurysms of differing sizes (Small, Medium, Medium-Large, Large, and Giant) and using 6 different types of stent (varying number of wires, stent pitch and wire mesh density) for each aneurysm.

Results

Regardless of the aneurysm size, the velocity inside the aneurysm and the volume flow rate into the aneurysm were observed to continuously decrease up to 89.2% and 78.1%, respectively, with increasing stent mesh density. In terms of pressure, for giant aneurysms, the pressure on the aneurysmal surface elevated to 10.3%, then decreased to 5.1% with increasing stent mesh density. However, in smaller aneurysms, this pressure continuously decreased with increasing stent mesh density. The flow-diverting effect of the stents was limited when a stent with low mesh density (under 20%) was used with a giant aneurysm.

Conclusions

The present results indicate that the selection of appropriate stents according to aneurysm size may contribute to reduced risks of hemodynamic alternations related to stent deployment, which could reduce the incidence of delayed rupture.

Computational fluid dynamics (CFD) analysis in a ruptured vertebral artery dissecting aneurysm implanted by Pipeline when recurrent after LVIS-assisted coiling treatment: Case report and review of the literatures

BACKGROUNDS

Hemodynamics plays an important role in the natural history of the process of rupture and recurrence of intracranial aneurysms. This study aimed to investigate the role of hemodynamics for recurrence in a vertebral artery dissecting aneurysm (VADA).

METHODS

A patient with a ruptured VADA firstly treated by low-profile visualized intraluminal support (LVIS)-assisted coiling, and was implanted with a Pipeline Embolization Device (PED) after aneurysm recurrence. Finite element analysis and computational fluid dynamics simulations were conducted in 6 serial imaging procedures, and the calculated hemodynamics was correlated with aneurysm recurrence.

RESULTS

Wall shear stress (WSS) was not effectively suppressed, resulting in aneurysm recurrence with initial entry tear to occur above the protuberance after 7 months of LVIS stent-assisted coiling. With the implantation of PED, WSS, inflow stream and velocity at the aneurysm neck significantly decreased. During the 3-month follow-up after PED deployment, there was significant shrinkage of the sac and the blood flow in the sac was reduced considerably. The 27-month follow-up after PED deployment indicated the aneurysm was stable.

CONCLUSIONS

The present case study suggests that insufficient suppression of high WSS and high inflow velocity at the neck of the parent artery, especially near the posterior inferior cerebellar artery, might be associated with aneurysm recurrence.

Extraction of patient-specific boundary conditions from 4D-DSA and their influence on CFD simulations of cerebral aneurysms

We developed a new technique for extracting patient-specific inflow conditions, such as the pulse cycle duration and blood flow velocity, from four-dimensional digital subtraction angiography images and experimentally examined its validity. The maximum error between the values extracted by the technique and measured values was 14.3%. We performed blood flow simulations and calculated representative haemodynamic parameters. The maximum differences between the parameters obtained using general and patient-specific inflow conditions were approximately 400%, 150%, and 50% for the velocity, normalised wall shear stress, and pressure loss coefficient, respectively. These results indicate that patient-specific conditions are critical for accurately reproducing aneurysmal haemodynamics.

Quantitative angiography prognosis of intracranial aneurysm treatment failure using parametric imaging and distal vessel analysis

PURPOSE

Data-driven methods based on x-ray angiographic parametric imaging (API) have been successfully used to provide prognosis for intracranial aneurysm (IA) treatment outcome. Previous studies have mainly focused on embolization devices where the flow pattern visualization is in the aneurysm dome; however, this is not possible in IAs treated with endovascular coils due to high x-ray attenuation of the devices. To circumvent this challenge, we propose to investigate whether flow changes in the parent artery distal to the coil-embolized IAs could be used to achieve the same accuracy of surgical outcome prognosis.

METHODS

Eighty digital subtraction angiography sequences were acquired from patients with IA embolized with coils. Five API parameters were recorded from a region of interest (ROI) placed distal to the IA neck in the main artery. Average API values were recorded and pre-treatment values. A supervised machine learning algorithm was trained to provide a six-month post procedure binary outcome (occluded/not occluded). Receiver operating characteristic (ROC) analysis was used to assess the accuracy of the method.

RESULTS

Use of API parameters with data driven methods yielded an area under the ROC curve of 0.77 ±0.11 and accuracy of 78.6%. Single parameter-based analysis yielded accuracies which were suboptimal for clinical acceptance.

CONCLUSIONS

We determined that data-driven method based on API analysis of flow in the parent artery of IA treated with coils provide clinically acceptable accuracy for the prognosis of six months occlusion outcome.

Hemodynamic Characteristics and Clinical Outcome for Intracranial Aneurysms treated with the Derivo Embolization Device, a Novel Second-Generation Flow Diverter

BACKGROUND AND PURPOSE

We investigated the relationship between hemodynamic characteristics and clinical outcomes for aneurysms treated by the Derivo Embolization Device (DED), a novel second-generation Flow-Diverter Stent, using computational fluid dynamics (CFD).

MATERIALS AND METHODS

Data were retrospectively obtained from two centers between 2017 and 2019. During the period, 23 patients were treated for 23 aneurysms with DED. In 17 patients we were able to conduct CFD analysis as six were excluded due to pre-coiling, unsuitable arterial geometry, and complex geometric form. Aneurysm occlusion was rated with the O`Kelly-Marotta (OKM) grading scale on DSA 6 months after stent placement in all patients. Hemodynamic and morphological parameters were statistically compared between two groups: with full occlusion and with a remnant.

RESULTS

Full occlusion was observed in 17 out of 23 (73.9%) patients. In the group suitable for CFD analysis, we observed 13 fully occluded aneurysms and 4 with any remnant (specifically 1 OKM C, 1 B and 2 A). The energy loss per volume (ELV), which indicates the energy loss through the aneurysm, was significantly larger in pre and post stenting (p<.05) in the complete occlusion cases. In addition, the inflow concentration index (ICI) and inflow area ratio (IAR) of the remnant cases were significantly larger and lower, respectively (p<.05).

CONCLUSION

Our CFD results indicate that the energy loss involved with the blood flow passing through an aneurysm and concentrated inflow into aneurysm were the most important factors to determine whether an aneurysm will become a complete occlusion or remnant case.

Automated Machine Learning Model Development for Intracranial Aneurysm Treatment Outcome Prediction: A Feasibility Study

Background: The prediction of aneurysm treatment outcomes can help to optimize the treatment strategies. Machine learning (ML) has shown positive results in many clinical areas. However, the development of such models requires expertise in ML, which is not an easy task for surgeons.

Objectives: The recently emerged automated machine learning (AutoML) has shown promise in making ML more accessible to non-computer experts. We aimed to evaluate the feasibility of applying AutoML to develop the ML models for treatment outcome prediction.

Methods: The patients with aneurysms treated by endovascular treatment were prospectively recruited from 2016 to 2020. Treatment was considered successful if angiographic complete occlusion was achieved at follow-up. A statistical prediction model was developed using multivariate logistic regression. In addition, two ML models were developed. One was developed manually and the other was developed by AutoML. Three models were compared based on their area under the precision-recall curve (AUPRC) and area under the receiver operating characteristic curve (AUROC).

Results: The aneurysm size, stent-assisted coiling (SAC), and posterior circulation were the three significant and independent variables associated with treatment outcome. The statistical model showed an AUPRC of 0.432 and AUROC of 0.745. The conventional manually trained ML model showed an improved AUPRC of 0.545 and AUROC of 0.781. The AutoML derived ML model showed the best performance with AUPRC of 0.632 and AUROC of 0.832, significantly better than the other two models.

Conclusions: This study demonstrated the feasibility of using AutoML to develop a high-quality ML model, which may outperform the statistical model and manually derived ML models. AutoML could be a useful tool that makes ML more accessible to the clinical researchers.

Hemodynamic and Morphological Factors Related to Coil Compaction in Basilar Artery Tip Aneurysms

PURPOSE

Coil compaction is directly related to the degree of cerebral aneurysmal recanalization. The Degree of Recanalization (DoR) was quantified by measuring the volume vacated by coil deformation. The purpose of this study was to clarify the hemodynamic and morphological factors associated with coil compaction.

METHODS

Computational fluid dynamics (CFD) simulations were performed on 28 middle size (5-10 mm), unruptured basilar artery tip aneurysms. The DoR was measured by comparing the coil mass shape obtained from three-dimensional digital subtraction angiography data immediately after coil embolization and again within 1 to 2 years of follow-up. Deployed coils were modeled using a virtual coiling technique for CFD simulations. Hemodynamic and morphological factors to predict the DoR were derived using multiple linear regression.

RESULTS

Aneurysmal neck area, the maximum pressure generated on the neck surface after coil embolization, and the high-pressure position on the neck surface predicted DoR with statistical significance (p<0.001, p<0.001, p=0.004, respectively). DoR tended to increase when the neck area was large, the pressure generated on the coils was high, and the high-pressure position was close to the center of the neck surface. The volume embolization ratio was not statistically relevant for the DoR in the cases of this study.

CONCLUSIONS

Coil compaction occurs in cerebral aneurysms with a wide neck, high pressure generated on the coils, and high pressure in the center of the neck surface. Establishing the DoR can contribute to the prediction of recanalization after coil embolization.

Assessing the Hemodynamics in Residual Cavities of Intracranial Aneurysm after Coil Embolization with Combined Computational Flow Dynamics and Silent Magnetic Resonance Angiography

BACKGROUND AND PURPOSE

Metal artifacts limit computational fluid dynamics analysis after coil embolization. Silent magnetic resonance angiography reduces metal artifacts and improves visualization of the residual cavity of coil-embolized aneurysms. This study investigated the flow dynamics of the residual cavity after coil embolization using silent magnetic resonance angiography and computational fluid dynamics to elucidate the hemodynamic characteristics of recanalization.

METHODS

Twenty internal carotid-posterior communicating aneurysm cases treated with coil embolization and without stent assistance were followed up (mean±standard deviation, 13.0±6.1 months) and assessed using silent magnetic resonance angiography. The hemodynamic characteristics of the residual cavities in both types of aneurysms were compared between neck remnants, which persisted for >12 months (NR group), and those treated with coil compaction-induced body filling (BF group). Computational fluid dynamics analysis of each aneurysm was performed using morphological data obtained from silent magnetic resonance angiography. Pressure, pressure difference, normalized wall shear stress, and flow velocity were measured.

RESULTS

The residual cavity was well-visualized using silent magnetic resonance angiography and compared with those imaged using conventional time-of-flight magnetic resonance angiography, and eight internal carotid-posterior communicating aneurysms with neck remnants and body filling were investigated. The maximum pressure area was localized to the aneurysm wall in the NR group (n=4) and to sides of the coil surface in the BF group (n=4). No significant differences were observed for each hemodynamic parameter.

CONCLUSIONS

Combination of silent magnetic resonance angiography and computational fluid dynamics helps to understand the hemodynamic characteristics of residual cavity in coil- embolized aneurysms. The flow-impingement zone at the coil surface (maximum pressure area) may influence the risk for future coil compaction.

Prediction of internal carotid artery aneurysm recurrence by pressure difference at the coil mass surface

PURPOSE

A previous study on computational fluid dynamics reported that a high pressure difference (PD) at the surface of a coil mass is a strong predictor of aneurysm recurrence after coil embolization. PD was calculated using a virtual post-coiling model (VM), created by manually cutting the aneurysm by the flat plane from an anatomic model created with pre-coil embolization data; however, its credibility has not been fully evaluated. This study aims to clarify whether PD values calculated using the post-coiling model, which reflects the actual coil plane, are a strong predictor of aneurysm recurrence.

METHODS

Fifty internal carotid artery aneurysms treated with endovascular coil embolization were analyzed (7 recanalized, 43 stable). We created and subjected two post-coiling models, namely, VM and the real post-coiling model (RM), constructed from the post-coil embolization data. The relationship between PD and aneurysm recurrence was examined using these models. PD and its constituent three parameters were compared between VM and RM.

RESULTS

PD values calculated using RM showed significantly higher aneurysm recurrence in recurrence group than stable group (p < 0.001), and multivariate analysis showed that PD in RM (p = 0.02; odds ratio, 36.24) was significantly associated with aneurysm recurrence. The receiver operating characteristic analysis revealed that PD values accurately predicted aneurysm recurrence (area under the curve, 0.977; cutoff value, 3.08; sensitivity, 100%; specificity, 97.7%). All four parameters showed a significant correlation with VM and RM (p < 0.001).

CONCLUSION

Use of PD to predict recurrence after coil embolization can be clinically relevant.

Computational fluid dynamics as a risk assessment tool for aneurysm rupture

OBJECTIVE

The authors reviewed the clinical role of computational fluid dynamics (CFD) in assessing the risk of intracranial aneurysm rupture.

METHODS

A literature review was performed to identify reports on CFD assessment of aneurysms using PubMed. The usefulness of various hemodynamic parameters, such as wall shear stress (WSS) and the Oscillatory Shear Index (OSI), and their role in aneurysm rupture risk analysis, were analyzed.

RESULTS

The authors identified a total of 258 published articles evaluating rupture risk, growth, and endovascular device assessment. Of these 258 articles, 113 matching for CFD and hemodynamic parameters that contribute to the risk of rupture (such as WSS and OSI) were identified. However, due to a lack of standardized methodology, controversy remains on each parameter's role.

CONCLUSIONS

Although controversy continues to exist on which risk factors contribute to predict aneurysm rupture, CFD can provide additional parameters to assess this rupture risk. This technology can contribute to clinical decision-making or evaluation of efficacy for endovascular methods and devices.

High frequency optical coherence tomography assessment of homogenous neck coverage by intrasaccular devices predicts successful aneurysm occlusion

BACKGROUND

High frequency optical coherence tomography (HF-OCT) is a novel intravascular imaging technology developed for use in the cerebral vasculature. We hypothesize that HF-OCT characterization of intrasaccular device neck coverage can prognosticate exclusion of the aneurysm from the circulation.

METHODS

Bifurcation and sidewall aneurysms were made in six dogs. Seven aneurysms were treated with next generation intrasaccular devices (NGID) and four with traditional platinum coils. HF-OCT was performed to interrogate gaps in the neck coverage, coil herniation, or acute thrombus formation. Animals were re-imaged at 7, 30, 90, and 180 days following aneurysm embolization. An automated image processing method segmented the devices at the neck of the aneurysm and quantified neck coverage. The largest coverage gap was used to predict aneurysm occlusion at 180 days.

RESULTS

No difference was found in occlusion rates between the coil and NGID groups (P=0.45). Successful segmentation of the NGID construct was achieved in all cases. A coverage gap >1 mm2 was found to predict failed aneurysm occlusion (P=0.047). This threshold was able to predict all cases of failed occlusion. The average number of devices needed to treat the aneurysm was lower in the NGID group (1.9 vs 6.75, P=0.009). HF-OCT showed strong agreement with scanning electron microscopy (bias 0.0024 mm2 (95% CI -0.0279, 0.0327)).

CONCLUSIONS

HF-OCT enables precise and accurate measurement of coverage gaps at the neck of aneurysms treated with intrasaccular devices in vivo. We provide in vivo evidence that uniform aneurysm neck coverage by intrasaccular devices is critical for aneurysm occlusion.

Does Systemic Hypertension Impact Recanalization of Coiled Aneurysms?

PURPOSE

It is well known that hypertension is a significant factor in the formation, growth, and rupture of aneurysms and recanalization of coiled aneurysms is affected by hemodynamic stress. At present, however, the impact of hypertension on recanalization of coiled aneurysms has not been adequately investigated. This study examined the relation between hypertension and subsequent outcomes of coiled aneurysms, using a matched patient analysis.

METHODS

A total of 715 subjects undergoing coil embolization of intracranial aneurysms between 2011 and 2013 were selected for study. Time-of-flight magnetic resonance or conventional angiography was used (singly or together) to gauge degrees of occlusion after coiling, applying the Raymond classification in grading recanalization. Patients with hypertension were grouped as controlled or uncontrolled, based on blood pressure readings at outpatient clinics. Hypertensive and non-hypertensive subjects were matched (1:1) for several relevant variables.

RESULTS

Overall, 484 patients (67.7%) were hypertensive (controlled 338; uncontrolled 146). During the follow-up period (28.6 ± 9.7 months), 129 aneurysms (18.0%) displayed recanalization (minor 58; major 71). Patient age, concomitant diabetes, hyperlipidemia, aneurysm size, neck size, depth-to-neck ratio, and aneurysm type differed significantly in hypertensive and non-hypertensive groups; however, group incidences of cumulative recanalization were similar (p = 0.297). After 1:1 matching the cumulative recanalization rate (13.5%) in hypertensive and non-hypertensive counterparts (14.3%) again proved similar (p = 0.578). In the hypertensive group, in addition, recanalization showed no relation to controlled and uncontrolled subgroup (odds ratio, OR = 1.000, p > 0.999).

CONCLUSION

Unlike other aspects of evolving aneurysms (e.g. formation, growth, or rupture), recanalization of coiled aneurysms seems to be unaffected by systemic hypertension.

Hemodynamic Differences Between Recurrent and Nonrecurrent Intracranial Aneurysms: Fluid Dynamics Simulations Based on MR Angiography

BACKGROUND AND PURPOSE

Although the role of wall shear stress (WSS) in the initiation, growth, and rupture of intracranial aneurysms has been well studied, its influence on aneurysm recurrence after endovascular treatment requires further investigation. We aimed to compare WSS at necks of recurrent and nonrecurrent aneurysms.

METHODS

Nine recurrent coil-embolized aneurysms were identified and matched with nine nonrecurrent aneurysms. Patient-specific vessel geometries reconstructed from follow-up 3-D time-of-flight magnetic resonance angiography were analyzed using computational fluid dynamics (CFD) simulations. Absolute WSS and the percentage of abnormally low and high WSS at the aneurysm neck compared to the near artery were measured.

RESULTS

The median percentage of abnormal WSS at the aneurysm neck was 49.3% for recurrent and 34.7% for nonrecurrent aneurysms (P = .011). The area under the receiver-operating-characteristic curve for distinguishing these aneurysms according to the percentage of abnormal WSS was .86 (95% CI .62 to .98). The optimal cut-off value of 45.1% resulted in a sensitivity and a specificity of 88.89% (95% CI 51.8% to 99.7%).

CONCLUSION

Our findings indicate that necks of recurrent aneurysms are exposed to abnormal WSS to a larger extent. Abnormal WSS may serve as a metric to distinguish them from nonrecurrent aneurysms with CFD simulations a priori.

Blood Flow Analysis in Coil Embolized Aneurysms: Difference between Porous Media and Real Coil Geometry Model

To clarify the mechanism of aneurysmal recanalization, it is necessary to understand the characteristics of the blood flow inside the aneurysm in particular the flow resistance generated by the coil. In studies using computational fluid dynamics (CFD), mainly two approaches have been used to model the coil embolized aneurysm; modeling the coils as porous media or by real coil geometries. In this study, we calculated the pressure drop along a vessel through a coiled region modeled as porous media or by real coil geometry and compared the pressure drop generated by the two coil models. The porous media model was described by Darcy's law and Ergun's equation, while the real coil geometry was generated using finite element method (FEM) structural analysis. We calculated the pressure drop for inlet velocities from 0.1 m/s to 1.0 m/s in steps of 0.1 m/s. Our results indicated that the porous media model may produce larger pressure drops than the real coil geometry model under low packing density. The value of the pressure drop was also changed due to the difference of coil distribution even if the packing density was the same.