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ABSTRACT: A flow diverter (FD) is a flexible, densely braided stent-mesh device placed endoluminally across an intracranial aneurysm to induce its thrombotic occlusion. FD treatment planning using computational virtual stenting and flow simulation requires accurate representation of the expanded FD geometry. We have recently developed a high fidelity virtual stenting (HiFiVS) technique based on finite element analysis to simulate detailed FD deployment processes in patient-specific aneurysms (Ma et al. J. Biomech. 45:2256-2263, 2012). This study tests if HiFiVS simulation can recapitulate real-life FD implantation. We deployed two identical FDs (Pipeline Embolization Device) into phantoms of a wide-necked segmental aneurysm using a clinical push-pull technique with different delivery wire advancements. We then simulated these deployment processes using HiFiVS and compared results against experimental recording. Stepwise comparison shows that the simulations precisely reproduced the FD deployment processes recorded in vitro. The local metal coverage rate and pore density quantifications demonstrated that simulations reproduced detailed FD mesh geometry. These results provide validation of the HiFiVS technique, highlighting its unique capability of accurately representing stent intervention in silico.
Annals of biomedical engineering 04/2013; · 2.41 Impact Factor
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ABSTRACT: Flow diverter (FD) is an emerging neurovascular device based on self-expandable braided stent for treating intracranial aneurysms. Variability in FD outcome has underscored a need for investigating the hemodynamic effect of fully deployed FD in patient-specific aneurysms. Image-based computational fluid dynamics, which can provide important hemodynamic insight, requires accurate representation of FD in deployed states. We developed a finite element analysis (FEA) based workflow for simulating mechanical deployment of FD in patient-specific aneurysms. We constructed FD models of interlaced wires emulating the Pipeline Embolization Device, using 3D finite beam elements to account for interactions between stent strands, and between the stent and other components. The FEA analysis encompasses all steps that affect the final deployed configuration including stent crimping, delivery and expansion. Besides the stent, modeling also includes key components of the FD delivery system such as microcatheter, pusher, and distal coil. Coordinated maneuver of these components allowed the workflow to mimic clinical operation of FD deployment and to explore clinical strategies. The workflow was applied to two patient-specific aneurysms. Parametric study indicated consistency of the deployment result against different friction conditions, but excessive intra-stent friction should be avoided. This study demonstrates for the first time mechanical modeling of braided FD stent deployment in cerebral vasculature to produce realistic deployed configuration, thus paving the way for accurate CFD analysis of flow diverters for reliable prediction and optimization of treatment outcome.
Journal of biomechanics 07/2012; 45(13):2256-63. · 2.66 Impact Factor
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ABSTRACT: the purpose of this study was to identify significant morphological and hemodynamic parameters that discriminate intracranial aneurysm rupture status using 3-dimensional angiography and computational fluid dynamics.
one hundred nineteen intracranial aneurysms (38 ruptured, 81 unruptured) were analyzed from 3-dimensional angiographic images and computational fluid dynamics. Six morphological and 7 hemodynamic parameters were evaluated for significance with respect to rupture. Receiver operating characteristic analysis identified area under the curve (AUC) and optimal thresholds separating ruptured from unruptured aneurysms for each parameter. Significant parameters were examined by multivariate logistic regression analysis in 3 predictive models-morphology only, hemodynamics only, and combined-to identify independent discriminants, and the AUC receiver operating characteristic of the predicted probability of rupture status was compared among these models.
morphological parameters (size ratio, undulation index, ellipticity index, and nonsphericity index) and hemodynamic parameters (average wall shear stress [WSS], maximum intra-aneurysmal WSS, low WSS area, average oscillatory shear index, number of vortices, and relative resident time) achieved statistical significance (P<0.01). Multivariate logistic regression analysis demonstrated size ratio to be the only independently significant factor in the morphology model (AUC, 0.83; 95% CI, 0.75 to 0.91), whereas WSS and oscillatory shear index were the only independently significant variables in the hemodynamics model (AUC, 0.85; 95% CI, 0.78 to 0.93). The combined model retained all 3 variables, size ratio, WSS, and oscillatory shear index (AUC, 0.89; 95% CI, 0.82 to 0.96).
all 3 models-morphological (based on size ratio), hemodynamic (based on WSS and oscillatory shear index), and combined-discriminate intracranial aneurysm rupture status with high AUC values. Hemodynamics is as important as morphology in discriminating aneurysm rupture status.
Stroke 01/2011; 42(1):144-52. · 5.73 Impact Factor
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ABSTRACT: We previously used three-dimensional (3D) volumetric analysis to identify a novel intracranial aneurysm (IA) morphological metric, aneurysm-to-parent vessel size ratio (SR), which strongly correlated with aneurysm rupture. However, complex 3D analysis is not easily obtained, and ubiquitous IA risk assessment is traditionally performed with two-dimensional (2D) imaging, typically with size being the sole considered morphometric. Because only easily applicable 2D measurements will be of clinical value, we sought to investigate the correlation of SR determined from 2D angiography with IA rupture status.
SR and traditional aspect ratio (AR) and aneurysm size parameters were measured in a retrospective cohort of 38 IA cases (16 ruptured) with 2D rotational angiographic images. These parameters were analysed for correlation with IA rupture status. Student's t-test or Wilcoxon rank-sum test was used for normally or non-normally distributed data respectively. Logistic regression was performed for independently statistically significant parameters to generate an effect size estimate (odds ratio). Area-under-the-curve (AUC) calculated from the receiver-operating-characteristic curve was additionally obtained for each index to describe differentiating capabilities.
Only SR achieved statistical significance (p=0.05) in Wilcoxon rank-sum test. Logistic regression generated an SR odds ratio of 3.52 (p=0.04; 95% confidence interval: 1.035-11.938) for every doubling of SR value. The AUC value of SR (0.688) was higher than that of AR (0.642) and size (0.585).
SR had the strongest correlation with IA rupture and was demonstrated to be a valuable parameter in 2D, where it can be easily obtained from angiographic images. When eventually evaluated in a prospective data set, SR may prove to be an important tool for aneurysm rupture-risk assessment.
Neurological Research 06/2010; 32(5):482-6. · 1.52 Impact Factor
