Virtual Flow-T Stenting for Two Patient-Specific Bifurcation Aneurysms

Abstract

The effective treatment of wide necked cerebral aneurysms located at vessel bifurcations (WNBAs) remains a significant challenge. Such aneurysm geometries have typically been approached with Y or T stenting configurations of stents and/or flow diverters, often with the addition of endovascular coils. In this study, two WNBAs were virtually treated by a novel T-stenting technique (Flow-T) with a number of braided stents and flow-diverter devices. Multiple possible device deployment configurations with varying device compression levels were tested, using fast-deployment algorithms, before a steady state computational hemodynamic simulation was conducted to examine the efficacy and performance of each scenario. The virtual fast deployment algorithm based on a linear and torsional spring analogy is used to accurately deploy nine stents in two WNBAs geometries. The devices expand from the distal to proximal side of the devices with respect to aneurysm sac. In the WNBAs modelled, all configurations of Flow-T device placement were shown to reduce factors linked with increased aneurysm rupture risk including aneurysm inflow jets and high aneurysm velocity, along with areas of flow impingement and elevated wall shear stress (WSS). The relative position of the flow-diverting device in the secondary daughter vessel in the Flow-T approach was found to have a negligible effect on overall effectiveness of the procedure in the two geometries considered. The level of interventionalist-applied compression in the braised stent that forms the other arm of the Flow-T approach was shown to impact the aneurysm inflow reduction and aneurysm flow pattern more substantially. In the Flow-T approach the relative position of the secondary daughter vessel flow-diverter device (the SVB) was found to have a negligible effect on inflow reduction, aneurysm flow pattern, or WSS distribution in both aneurysm geometries. This suggests that the device placement in this vessel may be of secondary importance. By contrast, substantially more variation in inflow reduction and aneurysm flow pattern was seen due to variations in braided stent (LVIS EVO or Baby Leo) compression at the aneurysm neck. As such we conclude that the success of a Flow-T procedure is primarily dictated by the level of compression that the interventionalist applies to the braided stent. Similar computationally predicted outcomes for both aneurysm geometries studied suggest that adjunct coiling approach taken in the clinical intervention of the second geometry may have been unnecessary for successful aneurysm isolation. Finally, the computational modelling framework proposed offers an effective planning platform for complex endovascular techniques, such as Flow-T, where the scope of device choice and combination is large and selecting the best strategy and device combination from several candidates is vital.

Keywords: T-stenting technique (Flow-T); hemodynamic simulation; inflow reduction; virtual fast deployment algorithm; wide necked cerebral aneurysms.

Figure 1

WNBA geometries I and II reconstructed from CT angiography pre-intervention with Flow-T for virtual stenting (left) and post-intervention for reference (right). Flow diverters placed in the secondary daughter vessel (right-hand in both orientations) are fully visible while the stent placed in the primary daughter vessel is indicated with end (LVIS EVO) or helical (Baby Leo) markers.

Figure 2

SVB, LVIS EVO, and BABY LEO designs to be virtually deployed in each WNBA geometry. Stent I is flow-diverting stent whereas stent II–VIII are low-profile braided stents with different compression level at mid third part of the devices.

Figure 3

Virtual deployment process. (A) Crimped LVIS EVO flow-diverter placed on the centerline of the target vessel. (B) Half way through the LVIS EVO expansion process, starting from the distal to proximal side of the device with respect to aneurysm sac. (C) Configuration of full expanded LVIS EVO. (D–F) The deployment of BABY LEO in WNBA II.

Figure 4

Deployed device positions in WNBA I. (A) Ideal deployment of LVIS EVO in the side daughter vessel. (B) Realistic deployment of LVIS EVO in the side daughter vessel. (C) Poor deployment of LVIS EVO in the side daughter vessel. (D–F) The deployment of LVIS EVO with 33, 50, 67% compression rate in the mid third part of the devices.

Figure 5

Deployed device positions in WNBA II. (A) Ideal deployment of SVB in the side daughter vessel. (B) Realistic deployment of SVB in the side daughter vessel. (C) Poor deployment of SVB in the side daughter vessel. (D–F) The deployment of BABY LEO with 33, 50, 67% compression rate in the mid third part of the devices.

Figure 6

Velocity streamlines and WSS distributions for the No Device (ND) and selected device configurations (cases A, D, and F) for the WNBA I geometry.

Figure 7

Velocity streamlines and WSS distributions for the No Device (ND) and selected device configurations (cases A, D, and F) for the WNBA II geometry.