Uncertainty quantification of wall shear stress in intracranial aneurysms using a data-driven statistical model of systemic blood flow variability

Adverse wall shear stress (WSS) patterns are known to play a key role in the localisation, formation, and progression of intracranial aneurysms (IAs). Com- plex region-specific and time-varying aneurysmal WSS patterns depend both on vascular morphology as well as on variable systemic ow conditions. Com- putational uid dynamics (CFD) has been proposed for characterising WSS patterns in IAs; however, CFD simulations often rely on deterministic bound- ary conditions that are not representative of the actual variations in blood ow. We develop a data-driven statistical model of internal carotid artery (ICA) ow, which is used to generate a virtual population of waveforms used as inlet bound- ary conditions in CFD simulations. This allows the statistics of the resulting aneurysmal WSS distributions to be computed. It is observed that ICA wave- form variations have limited in uence on the time-averaged WSS (TAWSS) on the IA surface. In contrast, in regions where the ow is locally highly multidi- rectional, WSS directionality and harmonic content are strongly affected by the ICA ow waveform. As a consequence, we argue that the effect of blood ow variability should be explicitly considered in CFD-based IA rupture assessment to prevent confounding the conclusions

Flow complexity in open systems: interlacing complexity index based on mutual information

Flow complexity is related to a number of phenomena in science and engineering and has been approached from the perspective of chaotic dynamical systems, ergodic processes or mixing of fluids, just to name a few. To the best of our knowledge, all existing methods to quantify flow complexity are only valid for infinite time evolution, for closed systems or for mixing of two substances. We introduce an index of flow complexity coined interlacing complexity index (ICI), valid for a single-phase flow in an open system with inlet and outlet regions, involving finite times. ICI is based on Shannon’s mutual information (MI), and inspired by an analogy between inlet–outlet open flow systems and communication systems in communication theory. The roles of transmitter, receiver and communication channel are played, respectively, by the inlet, the outlet and the flow transport between them. A perfectly laminar flow in a straight tube can be compared to an ideal communication channel where the transmitted and received messages are identical and hence the MI between input and output is maximal. For more complex flows, generated by more intricate conditions or geometries, the ability to discriminate the outlet position by knowing the inlet position is decreased, reducing the corresponding MI. The behaviour of the ICI has been tested with numerical experiments on diverse flows cases. The results indicate that the ICI provides a sensitive complexity measure with intuitive interpretation in a diversity of conditions and in agreement with other observations, such as Dean vortices and subjective visual assessments. As a crucial component of the ICI formulation, we also introduce the natural distribution of streamlines and the natural distribution of world-lines, with invariance properties with respect to the cross-section used to parameterize them, valid for any type of mass-preserving flow

Virtual Intracranial Stenting Challenge 2011: Input data

<p>Input data provided to the participants of the Virtual Intracranial Stenting Challenge 2011 (VISC'11).</p> <p> </p> <p>Fileset content:</p> <p>* surface.stl: STL surface mesh (in mm) of vascular geometry</p> <p>* ccs*.stl, ocs*.stl: STL surface meshes (in mm) of deployed stent geometries </p> <p>* geometry.pdf: Image of vascular and stent geometries with labels for inlets/outlets and regions-of-interest</p> <p>* challenge_instructions.txt: Instructions to challenge participants, including flow rate boundary conditions and blood properties</p> <p> </p> <p>More details on VISC'11:</p> <p>Cito S, Geers AJ, Arroyo MP, Palero VR, Pallarés J, Vernet A, Blasco J, San Román L, Fu W, Qiao A, Janiga G, Miura Y, Ohta M, Mendina M, Usera G, Frangi AF. Accuracy and Reproducibility of Patient-Specific Hemodynamics Models of Stented Intracranial Aneurysms: Report on the Virtual Intracranial Stenting Challenge 2011. Annals of Biomedical Engineering, 43(1):154-167, 2015.</p> <p> </p> <p>Contact:</p> <p>Arjan Geers ([email protected])</p> <p> </p> <p>Links:</p> <p>* http://dx.doi.org/10.6084/m9.figshare.1060453 : FigShare fileset "VISC'11: Particle imaging velocimetry data"</p> <p>* http://dx.doi.org/10.6084/m9.figshare.1060464 : FigShare fileset "VISC'11: CFD solutions group E"</p> <p>* https://github.com/ajgeers/visc11 : GitHub repository with code to reproduce the plots of the journal paper</p

Change in aneurysmal flow pulsatility after flow diverter treatment

Motivation: Treatment of intracranial aneurysms with flow diverters (FDs) has recently become an attractive alternative. Although considerable effort has been devoted to understand their effects on the time-averaged or peak systolic flow field, no previous study has analyzed the variability of FD-induced flow reduction along the cardiac cycle. Methods: Fourteen saccular aneurysms, candidates for FD treatment because of their morphology, located on the internal carotid artery were virtually treated with FDs and pre- and post-treatment blood flow was simulated with CFD techniques. Common hemodynamic variables were recorded at each time step of the cardiac cycle and differences between the untreated and treated models were assessed. Results: Flow pulsatility, expressed by the pulsatility index (PI) of the velocity, significantly increased (36.0%; range: 14.6–88.3%) after FD treatment. Peak systole velocity reduction was significantly smaller (30.5%; range: 19.6–51.0%) than time-averaged velocity reduction (43.0%; range: 29.1–69.8%). No changes were observed in the aneurysmal pressure. Conclusions: FD-induced flow reduction varies considerably during the cardiac cycle. FD treatment significantly increased the flow pulsatility in the aneurysm.Fil: Larrabide, Ignacio. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Geers, Arjan J.. Universitat Pompeu Fabra; EspañaFil: Morales; Hernán G.. Medisys; FranciaFil: Bijlenga, Philippe. Universidad de Ginebra; SuizaFil: Rufenacht, Daniel A.. Hirslanden Clinic; Suiz

Effect of aneurysm and ICA morphology on hemodynamics before and after flow diverter treatment

Background: Flow diverter (FD) treatment aims to slow down blood flow inside the aneurysm and increase the average time that blood resides in the aneurysm. Objective: To investigate the relationship between vessel and aneurysm morphology and their influence on the way in which braided FDs change intra-aneurysmal hemodynamics. Materials and methods: Twenty-three patient-specific intracranial aneurysm models at the supraclinoid segment of the internal carotid artery were studied. Vessel and aneurysm morphology was quantified and blood flow was modeled with computational fluid dynamics simulations. The relation between morphologic variables and the hemodynamic variables, WSS (wall shear stress) and totime (ratio between the aneurysm volume and inflow at the aneurysm neck), was assessed statistically. Results: Intra-aneurysmal flow was less dependent on the vessel than on aneurysm morphology. In summary, after treatment with a FD, a greater aneurysm flow reduction and redirection to the vessel main stream should be expected for (a) aneurysms located further away from the curvature peak, (b) aneurysms on the inner side of the bend, (c) aneurysms with no proximal stenosis, and (d) larger aneurysms.Fil: Larrabide, Ignacio. Universitat Pompeu Fabra; España. Networking Biomedical Research Center on Bioengineering, Biomaterials and Nanomedicine; España. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Geers, Arjan J.. Networking Biomedical Research Center on Bioengineering, Biomaterials and Nanomedicine; España. Universitat Pompeu Fabra; EspañaFil: Morales, Hernán G.. Networking Biomedical Research Center on Bioengineering, Biomaterials and Nanomedicine; España. Universitat Pompeu Fabra; EspañaFil: Aguilar, Martha L.. Networking Biomedical Research Center on Bioengineering, Biomaterials and Nanomedicine; España. Universitat Pompeu Fabra; EspañaFil: Rufenacht, Daniel A.. Hirslanden Clinic; Suiz

Change in aneurysmal flow pulsatility after flow diverter treatment

Treatment of intracranial aneurysms with flow diverters (FDs) has recently become an attractive alternative. Although considerable effort has been devoted to understand their effects on the time-averaged or peak systolic flow field, no previous study has analyzed the variability of FD-induced flow reduction along the cardiac cycle

Analysis and quantification of endovascular coil distribution inside saccular aneurysms using histological images

OBJECTIVE: Endovascular coiling is often performed first by placing coils along the aneurysm wall to create a frame and then by filling up the aneurysm core. However, little attention has been paid to quantify this filling strategy and to see how it changes for different packing densities. The purpose of this work is to analyze and quantify endovascular coil distribution inside aneurysms based on serial histological images of experimental aneurysms. METHOD: Seventeen histological images from ten elastase-induced saccular aneurysms in rabbits treated with coils were studied. In-slice coil density, defined as the area taken up by coil winds, was calculated on each histological image. Images were analyzed by partitioning the aneurysm along its longitudinal and radial axis. Coil distribution was quantified by measuring and comparing the in-slice coil density of each partition. RESULTS: Mean total in-slice coil density was 22.0% ± 6.2% (range 10.1% to 30.2%). The density was non-significantly different (p=0.465) along the longitudinal axis. A significant difference (p<0.001) between peripheral and core densities was found. Additionally, peripheral-core density ratio was observed to be inversely proportional to the total in-slice coil density (R(2)=0.57, p<0.001). This ratio was near unity for high in-slice coil density (around 30%). CONCLUSION: Our findings demonstrate and confirm that coils tend to be located near the aneurysm periphery when few are inserted. However, when more coils are added, the radial distribution becomes more homogeneous. Coils are homogeneously distributed along the longitudinal axis

Analysis and quantification of endovascular coil distribution inside saccular aneurysms using histological images

OBJECTIVE: Endovascular coiling is often performed first by placing coils along the aneurysm wall to create a frame and then by filling up the aneurysm core. However, little attention has been paid to quantify this filling strategy and to see how it changes for different packing densities. The purpose of this work is to analyze and quantify endovascular coil distribution inside aneurysms based on serial histological images of experimental aneurysms. METHOD: Seventeen histological images from ten elastase-induced saccular aneurysms in rabbits treated with coils were studied. In-slice coil density, defined as the area taken up by coil winds, was calculated on each histological image. Images were analyzed by partitioning the aneurysm along its longitudinal and radial axis. Coil distribution was quantified by measuring and comparing the in-slice coil density of each partition. RESULTS: Mean total in-slice coil density was 22.0% ± 6.2% (range 10.1% to 30.2%). The density was non-significantly different (p=0.465) along the longitudinal axis. A significant difference (p<0.001) between peripheral and core densities was found. Additionally, peripheral-core density ratio was observed to be inversely proportional to the total in-slice coil density (R(2)=0.57, p<0.001). This ratio was near unity for high in-slice coil density (around 30%). CONCLUSION: Our findings demonstrate and confirm that coils tend to be located near the aneurysm periphery when few are inserted. However, when more coils are added, the radial distribution becomes more homogeneous. Coils are homogeneously distributed along the longitudinal axis