The optimal stenting technique for coronary artery bifurcations is still debated. With additional advances computational simulations can soon be used to compare stent designs or strategies based on verified structural and hemodynamics results in order to identify the optimal solution for each individual's anatomy. In this study, patient-specific simulations of stent NOT THE PUBLISHED VERSION; this is the author's final, peer-reviewed manuscript. The published version may be accessed by following the link in the citation at the bottom of the page. Biomechanics, Vol 49, No. 11 (July 26, 2016): pg. 2102-2111. DOI. This article is © Elsevier Ltd. and permission has been granted for this version to appear in e-Publications@Marquette. Elsevier Ltd. does not grant permission for this article to be further copied/distributed or hosted elsewhere without the express permission from Elsevier Ltd. Journal of3 deployment were performed for 2 cases to replicate the complete procedure conducted by interventional cardiologists. Subsequent computational fluid dynamics (CFD) analyses were conducted to quantify hemodynamic quantities linked to restenosis.Patient-specific pre-operative models of coronary bifurcations were reconstructed from CT angiography and optical coherence tomography (OCT). Plaque location and composition were estimated from OCT and assigned to models, and structural simulations were performed in Abaqus. Artery geometries after virtual stent expansion of Xience Prime or Nobori stents created in SolidWorks were compared to post-operative geometry from OCT and CT before being extracted and used for CFD simulations in SimVascular. Inflow boundary conditions based on body surface area, and downstream vascular resistances and capacitances were applied at branches to mimic physiology.Artery geometries obtained after virtual expansion were in good agreement with those reconstructed from patient images. Quantitative comparison of the distance between reconstructed and post-stent geometries revealed a maximum difference in area of 20.4%. Adverse indices of wall shear stress were more pronounced for thicker Nobori stents in both patients. These findings verify structural analyses of stent expansion, introduce a workflow to combine software packages for solid and fluid mechanics analysis, and underscore important stent design features from prior idealized studies. The proposed approach may ultimately be useful in determining an optimal choice of stent and position for each patient.
I dentIfyIng risk factors that determine the natural history of unruptured intracranial aneurysms could aid in their clinical management. Morphological characteristics are candidates for such risk factors, because morphology varies in the patient population, the variation can be measured, and morphological variations affect the aneurysm's biomechanical environment (e.g., pressureinduced wall tension and flow-induced shear) in ways that may cause aneurysm enlargement and rupture. In addition, the shape of the aneurysm may reflect the underlying biology of the aneurysm wall. Numerous studies have assessed the differences between unruptured and ruptured aneurysms in regard to morphology, 4,13,16,20,23,33,35,37 blood flow, 4,6,7,12,22,31,32,37 and wall tension. obJective The goal of this prospective longitudinal study was to test whether image-derived metrics can differentiate unruptured aneurysms that will become unstable (grow and/or rupture) from those that will remain stable. methods One hundred seventy-eight patients harboring 198 unruptured cerebral aneurysms for whom clinical observation and follow-up with imaging surveillance was recommended at 4 clinical centers were prospectively recruited into this study. Imaging data (predominantly CT angiography) at initial presentation was recorded. Computational geometry was used to estimate numerous metrics of aneurysm morphology that described the size and shape of the aneurysm. The nonlinear, finite element method was used to estimate uniform pressure-induced peak wall tension. Computational fluid dynamics was used to estimate blood flow metrics. The median follow-up period was 645 days. Longitudinal outcome data on these aneurysm patients-whether their aneurysms grew or ruptured (the unstable group) or remained unchanged (the stable group)-was documented based on follow-up at 4 years after the beginning of recruitment. results Twenty aneurysms (10.1%) grew, but none ruptured. One hundred forty-nine aneurysms (75.3%) remained stable and 29 (14.6%) were lost to follow-up. None of the metrics-including aneurysm size, nonsphericity index, peak wall tension, and low shear stress area-differentiated the stable from unstable groups with statistical significance. coNclusioNs The findings in this highly selected group do not support the hypothesis that image-derived metrics can predict aneurysm growth in patients who have been selected for observation and imaging surveillance. If aneurysm shape is a significant determinant of invasive versus expectant management, selection bias is a key limitation of this study.http://thejns.org/doi/abs/10.3171/2015.2.JNS142265
Typical approaches to patient-specific haemodynamic studies of cerebral aneurysms use image-based computational fluid dynamics (CFD) and seek to statistically correlate parameters such as wall shear stress (WSS) and oscillatory shear index (OSI) to risk of growth and rupture. However, such studies have reported contradictory results, emphasizing the need for in-depth multi-modality haemodynamic metric evaluation. In this work, we used in vivo 4D flow MRI data to inform in vitro particle velocimetry and CFD modalities in two patient-specific cerebral aneurysm models (basilar tip and internal carotid artery). Pulsatile volumetric particle velocimetry experiments were conducted, and the particle images were processed using Shake-the-Box, a particle tracking method. Distributions of normalized WSS and relative residence time were shown to be highly yet inconsistently affected by minor flow field and spatial resolution variations across modalities, and specific relationships among these should be explored in future work. Conversely, OSI, a non-dimensional parameter, was shown to be more robust to the varying assumptions, limitations and spatial resolutions of each subject and modality. These results suggest a need for further multi-modality analysis as well as development of non-dimensional haemodynamic parameters and correlation of such metrics to aneurysm risk of growth and rupture.
There is increasing interest in assessing the role of hemodynamics in aneurysm growth and rupture mechanism. The ability to accurately predict the rupture risk of an aneurysm can help in providing immediate intervention to patients with aneurysms at high rupture risk Also, the small but significant risk associated with the treatment options can be avoided for patients with stable harmless aneurysms. Retrospective studies have been performed in the past to identify indices that differentiate ruptured aneurysms from unruptured aneurysms [1–3]. However, these differences may not necessarily translate to differences between aneurysms that present unruptured but over a period of time (months to years), fork towards growth/rupture and unruptured aneurysms that remain stable. In the present study, the hypothesis that hemodynamic indices of unruptured aneurysms when they first presented are predictive of their longitudinal outcome was tested.
No abstract
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.