CFD-driven optimization and experimental validation of venturi-based thrombectomy devices in a circle of willis

I Iham F. Zidane X Xiaochen Wang (Center for Systems and Control, School of Advanced Manufacturing and Robotics) H Hainan He X Xianghong Ma

Abstract

Abstract The geometry of the Circle of Willis poses major challenges for mechanical thrombectomy, where device navigability and effective thrombus removal determine treatment success. This study investigated the performance of venturi-inspired aspiration thrombectomy devices in a simplified cerebral artery segment representative of the middle cerebral artery (MCA), a frequent site of occlusion. Five designs (30°, 45°, 60° venturi, 7/11° taper, and cylindrical control) were assessed using a combined computational–experimental framework. On the computational side, unsteady Reynolds-averaged Navier–Stokes (URANS) simulations were performed in ANSYS Fluent 19.2 with k–ε turbulence closure. Blood–clot interactions were modeled using a Volume of Fluid (VOF) multiphase formulation with Carreau–Yasuda non-Newtonian rheology. In vitro, stereolithography-fabricated prototypes were tested with porcine thrombi in silicone arterial phantoms. CFD predicted extraction times of 2.12 s for the control and 1.64 s for the 45° venturi, with efficiency plateauing beyond 45°. Experimental results confirmed this trend, showing the 45° design as optimal and all venturi devices outperforming the control. Fragmentation analysis revealed a trade-off, with the 60° venturi producing more than twice the fragments of the 30°. These findings demonstrate that venturi taper geometry critically influences aspiration efficiency and fragmentation and establish CFD–experiment integration as a foundation for optimizing next-generation thrombectomy devices.

Article Details

Volume / Issue Vol. 16, Issue 1
Published June 18, 2026
ISSN 2045-2322
Publisher Nature Portfolio

Journal Info

Scientific Reports

Nature Portfolio

ISSN: 2045-2322 Open Access Life Sciences

Authors (4)

I

Iham F. Zidane

X

Xiaochen Wang

Center for Systems and Control, School of Advanced Manufacturing and Robotics

H

Hainan He

X

Xianghong Ma