Characterizing the arrhythmogenic substrate in personalized models of atrial fibrillation: sensitivity to mesh resolution and pacing protocol in AF models.

AIMS: Computationally guided persistent atrial fibrillation (PsAF) ablation has emerged as an alternative to conventional treatment planning. To make this approach scalable, computational cost and the time required to conduct simulations must be minimized while maintaining predictive accuracy. Here, we assess the sensitivity of the process to finite-element mesh resolution. We also compare methods for pacing site distribution used to evaluate inducibility arrhythmia sustained by re-entrant drivers (RDs). METHODS AND RESULTS: Simulations were conducted in low- and high-resolution models (average edge lengths: 400/350 µm) reconstructed from PsAF patients' late gadolinium enhancement magnetic resonance imaging scans. Pacing was simulated from 80 sites to assess RD inducibility. When pacing from the same site led to different outcomes in low-/high-resolution models, we characterized divergence dynamics by analysing dissimilarity index over time. Pacing site selection schemes prioritizing even spatial distribution and proximity to fibrotic tissue were evaluated. There were no RD sites observed in low-resolution models but not high-resolution models, or vice versa. Dissimilarity index analysis suggested that differences in simulation outcome arising from differences in discretization were the result of isolated conduction block incidents in one model but not the other; this never led to RD sites unique to one mesh resolution. Pacing site selection based on fibrosis proximity led to the best observed trade-off between number of stimulation locations and predictive accuracy. CONCLUSION: Simulations conducted in meshes with 400 µm average edge length and ∼40 pacing sites proximal to fibrosis are sufficient to reveal the most comprehensive possible list of RD sites, given feasibility constraints.

Outcome prediction of intracranial aneurysm treatment by flow diverters using machine learning.

OBJECTIVEFlow diverters (FDs) are designed to occlude intracranial aneurysms (IAs) while preserving flow to essential arteries. Incomplete occlusion exposes patients to risks of thromboembolic complications and rupture. A priori assessment of FD treatment outcome could enable treatment optimization leading to better outcomes. To that end, the authors applied image-based computational analysis to clinically FD-treated aneurysms to extract information regarding morphology, pre- and post-treatment hemodynamics, and FD-device characteristics and then used these parameters to train machine learning algorithms to predict 6-month clinical outcomes after FD treatment.METHODSData were retrospectively collected for 84 FD-treated sidewall aneurysms in 80 patients. Based on 6-month angiographic outcomes, IAs were classified as occluded (n = 63) or residual (incomplete occlusion, n = 21). For each case, the authors modeled FD deployment using a fast virtual stenting algorithm and hemodynamics using image-based computational fluid dynamics. Sixteen morphological, hemodynamic, and FD-based parameters were calculated for each aneurysm. Aneurysms were randomly assigned to a training or testing cohort in approximately a 3:1 ratio. The Student t-test and Mann-Whitney U-test were performed on data from the training cohort to identify significant parameters distinguishing the occluded from residual groups. Predictive models were trained using 4 types of supervised machine learning algorithms: logistic regression (LR), support vector machine (SVM; linear and Gaussian kernels), K-nearest neighbor, and neural network (NN). In the testing cohort, the authors compared outcome prediction by each model trained using all parameters versus only the significant parameters.RESULTSThe training cohort (n = 64) consisted of 48 occluded and 16 residual aneurysms and the testing cohort (n = 20) consisted of 15 occluded and 5 residual aneurysms. Significance tests yielded 2 morphological (ostium ratio and neck ratio) and 3 hemodynamic (pre-treatment inflow rate, post-treatment inflow rate, and post-treatment aneurysm averaged velocity) discriminants between the occluded (good-outcome) and the residual (bad-outcome) group. In both training and testing, all the models trained using all 16 parameters performed better than all the models trained using only the 5 significant parameters. Among the all-parameter models, NN (AUC = 0.967) performed the best during training, followed by LR and linear SVM (AUC = 0.941 and 0.914, respectively). During testing, NN and Gaussian-SVM models had the highest accuracy (90%) in predicting occlusion outcome.CONCLUSIONSNN and Gaussian-SVM models incorporating all 16 morphological, hemodynamic, and FD-related parameters predicted 6-month occlusion outcome of FD treatment with 90% accuracy. More robust models using the computational workflow and machine learning could be trained on larger patient databases toward clinical use in patient-specific treatment planning and optimization.

Methodology for Computational Fluid Dynamic Validation for Medical Use: Application to Intracranial Aneurysm.

Computational fluid dynamics (CFD) is a promising tool to aid in clinical diagnoses of cardiovascular diseases. However, it uses assumptions that simplify the complexities of the real cardiovascular flow. Due to high-stakes in the clinical setting, it is critical to calculate the effect of these assumptions in the CFD simulation results. However, existing CFD validation approaches do not quantify error in the simulation results due to the CFD solver's modeling assumptions. Instead, they directly compare CFD simulation results against validation data. Thus, to quantify the accuracy of a CFD solver, we developed a validation methodology that calculates the CFD model error (arising from modeling assumptions). Our methodology identifies independent error sources in CFD and validation experiments, and calculates the model error by parsing out other sources of error inherent in simulation and experiments. To demonstrate the method, we simulated the flow field of a patient-specific intracranial aneurysm (IA) in the commercial CFD software star-ccm+. Particle image velocimetry (PIV) provided validation datasets for the flow field on two orthogonal planes. The average model error in the star-ccm+ solver was 5.63 ± 5.49% along the intersecting validation line of the orthogonal planes. Furthermore, we demonstrated that our validation method is superior to existing validation approaches by applying three representative existing validation techniques to our CFD and experimental dataset, and comparing the validation results. Our validation methodology offers a streamlined workflow to extract the "true" accuracy of a CFD solver.

Flow diverter effect of LVIS stent on cerebral aneurysm hemodynamics: a comparison with Enterprise stents and the Pipeline device.

BACKGROUND: The aim of this study was to quantify the effect of the new Low-profile Visualized Intraluminal Support (LVIS®D) device and the difference of fluid diverting effect compared with the Pipeline device and the Enterprise stent using computational fluid dynamics (CFD). METHODS: In this research, we simulated three aneurysms constructed from 3D digital subtraction angiography (DSA). The Enterprise, LVIS and the Pipeline device were virtually conformed to fit into the vessel lumen and placed across the aneurysm orifice. Computational fluid dynamics analysis was performed to compare the hemodynamic differences such as WSS, Velocity and Pressure among these stents. RESULTS: Control referred to the unstented model, the percentage of hemodynamic changes were all compared to Control. A single LVIS stent caused more wall shear stress reduction than double Enterprise stents (39.96 vs. 30.51 %) and velocity (23.13 vs. 18.64 %). Significant reduction in wall shear stress (63.88 %) and velocity (46.05 %) was observed in the double-LVIS stents. A single Pipeline showed less reduction in WSS (51.08 %) and velocity (37.87 %) compared with double-LVIS stent. The double-Pipeline stents resulted in the most reduction in WSS (72.37 %) and velocity (54.26 %). Moreover, the pressure increased with minuscule extent after stenting, compared with the unstented model. CONCLUSIONS: This is the first study analyzing flow modifications associated with LVIS stents. We found that the LVIS stent has certain hemodynamic effects on cerebral aneurysms: a single LVIS stent caused more flow reductions than the double-Enterprise stent but less than a Pipeline device. Nevertheless, the double-LVIS stent resulted in a better flow diverting effect than a Pipeline device.

Phantom-based experimental validation of fast virtual deployment of self-expandable stents for cerebral aneurysms.

BACKGROUND: Endovascular intervention using a stent is a mainstream treatment for cerebral aneurysms. To assess the effect of intervention strategies on aneurysm hemodynamics, we have developed a fast virtual stenting (FVS) technique to simulate stent deployment in patient-specific aneurysms. However, quantitative validation of the FVS against experimental data has not been fully addressed. In this study, we performed in vitro analysis of a patient-specific model to illustrate the realism and usability of this novel FVS technique. METHODS: We selected a patient-specific aneurysm and reproduced it in a manufactured realistic aneurismal phantom. Three numerical simulation models of the aneurysm with an Enterprise stent were constructed. Three models were constructed to obtain the stented aneurysms: a physical phantom scanned by micro-CT, fast virtual stenting technique and finite element method. The flow in the three models was simulated using a computational fluid dynamics software package, and the hemodynamics parameters for the three models were calculated and analyzed. RESULTS: The computational hemodynamics in the patient-specific aneurysm of the three models resembled the very well. A qualitative comparison revealed high similarity in the wall shear stress, streamline, and velocity plane among the three different methods. Quantitative comparisons revealed that the difference ratios of the hemodynamic parameters were less than 10%, with the difference ratios for area average of wall shear stress in the aneurysm being very low. CONCLUSIONS: In conclusion, the results of the computational hemodynamics indicate that FVS is suitable for evaluation of the hemodynamic factors that affect treatment outcomes.

Hemodynamic alterations after stent implantation in 15 cases of intracranial aneurysm.

BACKGROUND: Stent-assisted coiling technology has been widely used in the treatment of intracranial aneurysms. In the current study, we investigated the intra-aneurysmal hemodynamic alterations after stent implantation and their association with the aneurysm location. METHODS: We first retrospectively studied 15 aneurysm cases [8 internal carotid artery-ophthalmic artery (ICA-OphA) aneurysms and 7 posterior communicating artery (PcoA) aneurysms] treated with Enterprise stents and coils. Then, based on the patient-specific geometries before and after stenting, we built virtual stenting computational fluid dynamics (CFD) simulation models. RESULTS: Before and after the stent deployment, the average wall shear stress (WSS) on the aneurysmal sac at systolic peak changed from 7.04 Pa (4.14 Pa, 15.77 Pa) to 6.04 Pa (3.86 Pa, 11.13 Pa), P = 0.001; the spatially averaged flow velocity in the perpendicular plane of the aneurysm dropped from 0.5 m/s (0.28 m/s, 0.7 m/s) to 0.33 m/s (0.25 m/s, 0.49 m/s), P = 0.001, respectively. Post stent implantation, the WSS in ICA-OphA aneurysms and PcoA aneurysms decreased by 14.4 % (P = 0.012) and 16.6 % (P = 0.018), respectively, and the flow velocity also reduced by 10.3 % (P = 0.029) and 10.5 % (P = 0.013), respectively. Changes in the WSS, flow velocity, and pressure were not significantly different between ICA-OphA and PcoA aneurysms (P > 0.05). Stent implantation did not significantly change the peak systolic pressure in either aneurysm type. CONCLUSION: After the stent implantation, both the intra-aneurysmal flow velocity and WSS decreased independently of aneurysm type (ICA-OphA and PcoA). Little change was observed in peak systolic pressure.

Slow blood-flow in the left atrial appendage is associated with stroke in atrial fibrillation patients.

Background: Atrial fibrillation (AF) patients are at high risk of stroke with ∼90% clots originating from the left atrial appendage (LAA). Clinical understanding of blood-flow based parameters and their potential association with stroke for AF patients remains poorly understood. We hypothesize that slow blood-flow either in the LA or the LAA could lead to the formation of blood clots and is associated with stroke for AF patients. Methods: We retrospectively collected cardiac CT images of paroxysmal AF patients and dichotomized them based on clinical event of previous embolic event into stroke and non-stroke groups. After image segmentation to obtain 3D LA geometry, patient-specific blood-flow analysis was performed to model LA hemodynamics. In terms of geometry, we calculated area of the pulmonary veins (PVs), mitral valve, LA and LAA, orifice area of LAA and volumes of LA and LAA and classified LAA morphologies. For hemodynamic assessment, we quantified blood flow velocity, wall shear stress (WSS, blood-friction on LA wall), oscillatory shear index (OSI, directional change of WSS) and endothelial cell activation potential (ECAP, ratio of OSI and WSS quantifying slow and oscillatory flow) in the LA as well as the LAA. Statistical analysis was performed to compare the parameters between the groups. Results: Twenty-seven patients were included in the stroke and 28 in the non-stroke group. Examining geometrical parameters, area of left inferior PV was found to be significantly higher in the stroke group as compared to non-stroke group (p = 0.026). In terms of hemodynamics, stroke group had significantly lower blood velocity (p = 0.027), WSS (p = 0.018) and higher ECAP (p = 0.032) in the LAA as compared to non-stroke group. However, LAA morphologic type did not differ between the two groups. This suggests that stroke patients had significantly slow and oscillatory circulating blood-flow in the LAA, which might expose it to potential thrombogenesis. Conclusion: Slow flow in the LAA alone was associated with stroke in this paroxysmal AF cohort. Patient-specific blood-flow analysis can potentially identify such hemodynamic conditions, aiding in clinical stroke risk stratification of AF patients.

Presence of Left Atrial Fibrosis May Contribute to Aberrant Hemodynamics and Increased Risk of Stroke in Atrial Fibrillation Patients.

Atrial fibrillation (AF) patients are at high risk of stroke, with the left atrial appendage (LAA) found to be the most common site of clot formation. Presence of left atrial (LA) fibrosis has also been associated with higher stroke risk. However, the mechanisms for increased stroke risk in patients with atrial fibrotic remodeling are poorly understood. We sought to explore these mechanisms using fluid dynamic analysis and to test the hypothesis that the presence of LA fibrosis leads to aberrant hemodynamics in the LA, contributing to increased stroke risk in AF patients. We retrospectively collected late-gadolinium-enhanced MRI (LGE-MRI) images of eight AF patients (four persistent and four paroxysmal) and reconstructed their 3D LA surfaces. Personalized computational fluid dynamic simulations were performed, and hemodynamics at the LA wall were quantified by wall shear stress (WSS, friction of blood), oscillatory shear index (OSI, temporal directional change of WSS), endothelial cell activation potential (ECAP, ratio of OSI and WSS), and relative residence time (RRT, residence time of blood near the LA wall). For each case, these hemodynamic metrics were compared between fibrotic and non-fibrotic portions of the wall. Our results showed that WSS was lower, and OSI, ECAP, and RRT was higher in the fibrotic region as compared to the non-fibrotic region, with ECAP (p = 0.001) and RRT (p = 0.002) having significant differences. Case-wise analysis showed that these differences in hemodynamics were statistically significant for seven cases. Furthermore, patients with higher fibrotic burden were exposed to larger regions of high ECAP, which represents regions of low WSS and high OSI. Consistently, high ECAP in the vicinity of the fibrotic wall suggest that local blood flow was slow and oscillating that represents aberrant hemodynamic conditions, thus enabling prothrombotic conditions for circulating blood. AF patients with high LA fibrotic burden had more prothrombotic regions, providing more sites for potential clot formation, thus increasing their risk of stroke.

Whole blood transcriptome biomarkers of unruptured intracranial aneurysm.

BACKGROUND: The rupture of an intracranial aneurysm (IA) causes devastating subarachnoid hemorrhages, yet most IAs remain undiscovered until they rupture. Recently, we found an IA RNA expression signature of circulating neutrophils, and used transcriptome data to build predictive models for unruptured IAs. In this study, we evaluate the feasibility of using whole blood transcriptomes to predict the presence of unruptured IAs. METHODS: We subjected RNA from peripheral whole blood of 67 patients (34 with unruptured IA, 33 without IA) to next-generation RNA sequencing. Model genes were identified using the least absolute shrinkage and selection operator (LASSO) in a random training cohort (n = 47). These genes were used to train a Gaussian Support Vector Machine (gSVM) model to distinguish patients with IA. The model was applied to an independent testing cohort (n = 20) to evaluate performance by receiver operating characteristic (ROC) curve. Gene ontology and pathway analyses investigated the underlying biology of the model genes. RESULTS: We identified 18 genes that could distinguish IA patients in a training cohort with 85% accuracy. This SVM model also had 85% accuracy in the testing cohort, with an area under the ROC curve of 0.91. Bioinformatics reflected activation and recruitment of leukocytes, activation of macrophages, and inflammatory response, suggesting that the biomarker captures important processes in IA pathogenesis. CONCLUSIONS: Circulating whole blood transcriptomes can detect the presence of unruptured IAs. Pending additional testing in larger cohorts, this could serve as a foundation to develop a simple blood-based test to facilitate screening and early detection of IAs.

Evaluation of Two Fast Virtual Stenting Algorithms for Intracranial Aneurysm Flow Diversion.

BACKGROUND: Endovascular treatment of intracranial aneurysms (IAs) by flow diverter (FD) stents depends on flow modification. Patient-specific modeling of FD deployment and computational fluid dynamics (CFD) could enable a priori endovascular strategy optimization. We developed a fast, simplistic, expansion-free balls-weeping algorithm to model FDs in patientspecific aneurysm geometry. However, since such strong simplification could result in less accurate simulations, we also developed a fast virtual stenting workflow (VSW) that explicitly models stent expansion using pseudo-physical forces. METHODS: To test which of these two fast algorithms more accurately simulates real FDs, we applied them to virtually treat three representative patient-specific IAs. We deployed Pipeline Embolization Device into 3 patient-specific silicone aneurysm phantoms and simulated the treatments using both balls-weeping and VSW algorithms in computational aneurysm models. We then compared the virtually deployed FD stents against experimental results in terms of geometry and post-treatment flow fields. For stent geometry, we evaluated gross configurations and porosity. For post-treatment aneurysmal flow, we compared CFD results against experimental measurements by particle image velocimetry. RESULTS: We found that VSW created more realistic FD deployments than balls-weeping in terms of stent geometry, porosity and pore density. In particular, balls-weeping produced unrealistic FD bulging at the aneurysm neck, and this artifact drastically increased with neck size. Both FD deployment methods resulted in similar flow patterns, but the VSW had less error in flow velocity and inflow rate. CONCLUSION: In conclusion, modeling stent expansion is critical for preventing unrealistic bulging effects and thus should be considered in virtual FD deployment algorithms. Also endowed with its high computational efficiency and superior accuracy, the VSW algorithm is a better candidate for implementation into a bedside clinical tool for FD deployment simulation.

Aneurysm characteristics, coil packing, and post-coiling hemodynamics affect long-term treatment outcome.

BACKGROUND: Recurrence of intracranial aneurysms after endovascular coiling is a serious clinical concern. OBJECTIVE: We hypothesized that recurrence is associated with aneurysm morphology and flow, as well as the coil intervention and the induced flow modifications. METHODS: We collected 52 primary-coiling aneurysm cases that were either occluded (n=34) or recurrent (n=18) at >1 year follow-up. We created aneurysm models from pre-coiling digital subtraction angiographic images, calculated aneurysm morphology, simulated pre-coiling hemodynamics, modeled coil deployment, and obtained post-coiling hemodynamics for each case. We performed univariable analysis on 26 morphologic, treatment-specific, and hemodynamic parameters to distinguish between recurrent and occluded groups, and multivariable analysis to identify independently significant parameters associated with recurrence. Univariable analysis was also performed on ruptured and unruptured aneurysm subcohorts separately to investigate if they shared specific significant parameters. RESULTS: Recurrence was associated with pre-coiling aneurysm morphologic and flow parameters including larger size (maximum dimension and volume), larger neck (diameter, area, and neck-to-parent-artery ratio), and higher flow momentum and kinetic energy. Recurrence was also associated with lower coil packing (packing density and uncoiled volume), higher post-treatment flow (velocity, momentum, and kinetic energy), lower post-treatment washout time, and higher post-treatment impingement force at the neck. Multivariable analysis identified two aneurysmal characteristics (neck diameter and pre-coiling flow kinetic energy), one coil packing parameter (uncoiled volume), and one post-treatment hemodynamic parameter (flow momentum) that were independently associated with recurrence. In ruptured aneurysms, recurrence was associated with larger neck (diameter and area), whereas in unruptured aneurysms, recurrence was associated with larger size (maximum dimension and volume). In both subcohorts, recurrence was associated with higher post-coiling flow momentum and kinetic energy. CONCLUSION: Recurrence at >1 year after coil treatment is associated with intrinsic aneurysm characteristics, coiling itself, and flow changes induced by coiling. Larger aneurysm size and neck, less coil packing, and higher intra-aneurysmal flow before and after coiling predict recurrence.

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.

Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH)-phase II: rupture risk assessment.

PURPOSE: Assessing the rupture probability of intracranial aneurysms (IAs) remains challenging. Therefore, hemodynamic simulations are increasingly applied toward supporting physicians during treatment planning. However, due to several assumptions, the clinical acceptance of these methods remains limited. METHODS: To provide an overview of state-of-the-art blood flow simulation capabilities, the Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH) was conducted. Seventeen research groups from all over the world performed segmentations and hemodynamic simulations to identify the ruptured aneurysm in a patient harboring five IAs. Although simulation setups revealed good similarity, clear differences exist with respect to the analysis of aneurysm shape and blood flow results. Most groups (12/71%) included morphological and hemodynamic parameters in their analysis, with aspect ratio and wall shear stress as the most popular candidates, respectively. RESULTS: The majority of groups (7/41%) selected the largest aneurysm as being the ruptured one. Four (24%) of the participating groups were able to correctly select the ruptured aneurysm, while three groups (18%) ranked the ruptured aneurysm as the second most probable. Successful selections were based on the integration of clinically relevant information such as the aneurysm site, as well as advanced rupture probability models considering multiple parameters. Additionally, flow characteristics such as the quantification of inflow jets and the identification of multiple vortices led to correct predictions. CONCLUSIONS: MATCH compares state-of-the-art image-based blood flow simulation approaches to assess the rupture risk of IAs. Furthermore, this challenge highlights the importance of multivariate analyses by combining clinically relevant metadata with advanced morphological and hemodynamic quantification.

Modeling hemodynamics in intracranial aneurysms: Comparing accuracy of CFD solvers based on finite element and finite volume schemes.

Image-based computational fluid dynamics (CFD) has shown potential to aid in the clinical management of intracranial aneurysms, but its adoption in the clinical practice has been missing, partially because of lack of accuracy assessment and sensitivity analysis. To numerically solve the flow-governing equations, CFD solvers generally rely on 2 spatial discretization schemes: finite volume (FV) and finite element (FE). Since increasingly accurate numerical solutions are obtained by different means, accuracies and computational costs of FV and FE formulations cannot be compared directly. To this end, in this study, we benchmark 2 representative CFD solvers in simulating flow in a patient-specific intracranial aneurysm model: (1) ANSYS Fluent, a commercial FV-based solver, and (2) VMTKLab multidGetto, a discontinuous Galerkin (dG) FE-based solver. The FV solver's accuracy is improved by increasing the spatial mesh resolution (134k, 1.1m, 8.6m, and 68.5m tetrahedral element meshes). The dGFE solver accuracy is increased by increasing the degree of polynomials (first, second, third, and fourth degree) on the base 134k tetrahedral element mesh. Solutions from best FV and dGFE approximations are used as baseline for error quantification. On average, velocity errors for second-best approximations are approximately 1 cm/s for a [0,125] cm/s velocity magnitude field. Results show that high-order dGFE provides better accuracy per degree of freedom but worse accuracy per Jacobian nonzero entry as compared with FV. Cross-comparison of velocity errors demonstrates asymptotic convergence of both solvers to the same numerical solution. Nevertheless, the discrepancy between underresolved velocity fields suggests that mesh independence is reached following different paths.

Predisposing factors for recanalization of cerebral aneurysms after endovascular embolization: a multivariate study.

BACKGROUND: The recanalization of cerebral aneurysms after endovascular embolization (coiling or stent-assisted coiling) has been a matter of concern. OBJECTIVE: To systematically evaluate the predisposing factors for cerebral aneurysm recanalization using multidimensional analysis in a large patient cohort. METHODS: In 238 patients with 283 aneurysms, patient baseline characteristics, aneurysm morphological characteristics, treatment-related factors, and changes in flow hemodynamics after endovascular treatment (coiling or stent-assisted coiling) were compared between the recanalization and non-recanalization groups. Multivariate logistic regression analysis was performed to determine independent risk factors correlated with recanalization. RESULTS: 16 aneurysms treated by coiling recanalized, with a recurrence rate of 18.6%, and 24 recanalized in the lesions treated by stent-assisted coiling, with a recanalization rate of 12.2%. Large aneurysms (>10 mm, p=0.002) and a follow-up interval >1 year (p=0.027) were shown to be statistically significant between the recanalization and non-recanalization groups. For flow hemodynamic changes, three parameters (velocity on the neck plane, wall shear stress on the neck wall, and wall shear stress on the whole aneurysm) showed a relatively lower amplitude of decrease after endovascular treatment in the recanalization group. Interestingly, the velocity on the neck plane and wall shear stress on the neck wall may be elevated after treatment. Specifically, the reduction ratio (RR) of velocity on the neck plane showed significant difference between the groups in the multivariate analysis (p=0.013), and was considered an independent risk factor for recanalization. CONCLUSIONS: The aneurysm size, follow-up interval, and flow hemodynamic changes, especially the RR of velocity on the neck plane, have important roles in aneurysm recanalization.

Efficient simulation of a low-profile visualized intraluminal support device: a novel fast virtual stenting technique.

BACKGROUND: The low-profile visualized intraluminal support (LVIS) stent has become a promising endovascular option for treating intracranial aneurysms. To achieve better treatment of aneurysms using LVIS, we developed a fast virtual stenting technique for use with LVIS (F-LVIS) to evaluate hemodynamic changes in the aneurysm and validate its reliability. METHODS: A patient-specific aneurysm was selected for making comparisons between the real LVIS (R-LVIS) and the F-LVIS. To perform R-LVIS stenting, a hollow phantom based on a patient-specific aneurysm was fabricated using a three-dimensional printer. An R-LVIS was released in the phantom according to standard procedure. F-LVIS was then applied successfully in this aneurysm model. The computational fluid dynamics (CFD) values were calculated for both the F-LVIS and R-LVIS models. Qualitative and quantitative comparisons of the two models focused on hemodynamic parameters. RESULTS: The hemodynamic characteristics for R-LVIS and F-LVIS were well matched. Representative contours of velocities and wall shear stress (WSS) were consistently similar in both distribution and magnitude. The velocity vectors also showed high similarity, although the R-LVIS model showed faster and more fluid streams entering the aneurysm. Variation tendencies of the velocity in the aneurysm and the WSS on the aneurysm wall were also similar in the two models, with no statistically significant differences in either velocity or WSS. CONCLUSIONS: The results of the computational hemodynamics indicate that F-LVIS is suitable for evaluating hemodynamic factors. This novel F-LVIS is considered efficient, practical, and effective.

Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH): Phase I: Segmentation.

PURPOSE: Advanced morphology analysis and image-based hemodynamic simulations are increasingly used to assess the rupture risk of intracranial aneurysms (IAs). However, the accuracy of those results strongly depends on the quality of the vessel wall segmentation. METHODS: To evaluate state-of-the-art segmentation approaches, the Multiple Aneurysms AnaTomy CHallenge (MATCH) was announced. Participants carried out segmentation in three anonymized 3D DSA datasets (left and right anterior, posterior circulation) of a patient harboring five IAs. Qualitative and quantitative inter-group comparisons were carried out with respect to aneurysm volumes and ostia. Further, over- and undersegmentation were evaluated based on highly resolved 2D images. Finally, clinically relevant morphological parameters were calculated. RESULTS: Based on the contributions of 26 participating groups, the findings reveal that no consensus regarding segmentation software or underlying algorithms exists. Qualitative similarity of the aneurysm representations was obtained. However, inter-group differences occurred regarding the luminal surface quality, number of vessel branches considered, aneurysm volumes (up to 20%) and ostium surface areas (up to 30%). Further, a systematic oversegmentation of the 3D surfaces was observed with a difference of approximately 10% to the highly resolved 2D reference image. Particularly, the neck of the ruptured aneurysm was overrepresented by all groups except for one. Finally, morphology parameters (e.g., undulation and non-sphericity) varied up to 25%. CONCLUSIONS: MATCH provides an overview of segmentation methodologies for IAs and highlights the variability of surface reconstruction. Further, the study emphasizes the need for careful processing of initial segmentation results for a realistic assessment of clinically relevant morphological parameters.

Association between hemodynamic modifications and clinical outcome of intracranial aneurysms treated using flow diverters.

Treatment of intracranial aneurysms (IAs) has been revolutionized by the advent of endovascular Flow Diverters (FDs), which disrupt blood flow within the aneurysm to induce pro-thrombotic conditions, and serves as a scaffold for endothelial ingrowth and arterial remodeling. Despite good clinical success of FDs, complications like incomplete occlusion and post-treatment rupture leading to subarachnoid hemorrhage have been reported. In silico computational fluid dynamic analysis of the pre- and post-treated geometries of IA patients can shed light on the contrasting blood hemodynamics associated with different clinical outcomes. In this study, we analyzed hemodynamic modifications in 15 IA patients treated using a single FD; 10 IAs were completely occluded (successful) and 5 were partially occluded (unsuccessful) at 12-month follow-up. An in-house virtual stenting workflow was used to recapitulate the clinical intervention on these cases, followed by CFD to obtain pre- and post-treatment hemodynamics. Bulk hemodynamic parameters showed comparable reductions in both groups with average inflow rate and aneurysmal velocity reduction of 40.3% and 52.4% in successful cases, and 34.4% and 49.2% in unsuccessful cases. There was a substantial reduction in localized parameter like vortex coreline length and Energy Loss for successful cases, 38.2% and 42.9% compared to 10.1% and 10.5% for unsuccessful cases. This suggest that for successfully treated IAs, the localized complex blood flow is disrupted more prominently by the FD as compared to unsuccessful cases. These localized hemodynamic parameters can be potentially used in prediction of treatment outcome, thus aiding the clinicians in a priori assessment of different treatment strategies.

Successful Retreatment of Recurrent Intracranial Vertebral Artery Dissecting Aneurysms After Stent-Assisted Coil Embolization: A Self-Controlled Hemodynamic Analysis.

BACKGROUND: Intracranial vertebral artery dissecting aneurysms (VADAs) tend to recur despite successful stent-assisted coil embolization (SACE). Hemodynamics is useful in evaluating aneurysmal formation, growth, and rupture. Our aim was to evaluate the hemodynamic patterns of the recurrence of VADA. METHODS: Between September 2009 and November 2013, all consecutive patients with recurrent VADAs after SACE in our institutions were enrolled. Recurrence was defined as recanalization and/or regrowth. We assessed the hemodynamic alterations in wall shear stress (WSS) and velocity after the initial SACE and subsequently after retreatment of the aneurysms that recurred. RESULTS: Five patients were included. After the initial treatment, 3 patients showed recanalization and 2 showed regrowth. In the 2 patients with regrowth, the 2 original aneurysms maintained complete occlusion; however, de novo aneurysm regrowth was confirmed near the previous site. Compared with 3 recanalized aneurysms, the completely occluded aneurysms showed high mean reductions in velocity and WSS after initial treatment (velocity, 77.6% vs. 57.7%; WSS, 74.2% vs. 52.4%); however, WSS remained high at the region near the previous lesion where the new aneurysm originated. After the second retreatment, there was no recurrence in any patient. Compared with the 3 aneurysms that recanalized, the 4 aneurysms that maintained complete occlusion showed higher reductions in velocity (62.9%) and WSS (71.1%). CONCLUSIONS: Our series indicated that hemodynamics might have an important role in recurrence of VADAs. After endovascular treatment, sufficient hemodynamic reduction in aneurysm dome, orifice, and parent vessel may be one of the key factors for preventing recurrence in VADAs.

Hemodynamic Effect of Flow Diverter and Coils in Treatment of Large and Giant Intracranial Aneurysms.

BACKGROUND: This study aimed to investigate the hemodynamic changes induced by a flow diverter (FD) and coils in the treatment of internal carotid artery aneurysms, as well as to evaluate the effect of this treatment by using angiographic follow-up data. METHODS: Six large and giant aneurysms were treated by the Tubridge FD and loose packing coils between June 2013 and May 2015. Patient-specific models were constructed and analyzed using a computational fluid dynamics (CFD) method. The virtual FD deployment method was used to implant the Tubridge stent into a 3-dimensional digital subtraction angiographic image of the aneurysms, and the coils were simulated by a porous medium model. RESULTS: Tubridge FD alone can significantly reduce the intra-aneurysmal flow velocity (0.17 ± 0.05 m/s-0.11 ± 0.06 m/s, P < 0.001) and wall shear stress (WSS, 1.39 ± 0.29 Pa-0.77 ± 0.34 Pa, P = 0.001) and increase the low wall shear area (LSA, 6.38% ± 1.49%-34.60% ± 28.90%, P = 0.047). Coils, as a supplementary measure, further reduced the velocity (0.11 ± 0.06 m/s-0.08 ± 0.05 m/s, P = 0.03) and WSS (0.77 ± 0.34 Pa-0.47 ± 0.35 Pa, P = 0.04) and increased the LSA (34.60% ± 28.90%-63.33% ± 34.82%, P = 0.044). Aneurysm with sustained strong inflow after treatment (case 3, 25% reduction in velocity, 12% reduction in WSS, and 16% increment in LSA) showed partial patency, whereas others with a weaker inflow jet (mean 56% reduction in velocity, 74% reduction in WSS, and 1081% increment in LSA) showed complete occlusion at follow-up. CONCLUSIONS: On the basis of using the CFD method, adjunctive coiling with the Tubridge FD placement may significantly reduce intra-aneurysmal flow velocity and WSS, promoting thrombosis formation and occlusion of aneurysms.