Helical toroid phantom for 3D flow imaging investigations

Abstract

The medical physics community has hitherto lacked an effective calibration phantom to holistically evaluate the performance of three-dimensional (3D) flow imaging techniques. Here, we present the design of a new omnidirectional, three-component (3-C) flow phantom whose lumen is consisted of a helical toroid structure (4 mm lumen diameter; helically winded for 5 revolutions over a torus with 10 mm radius; 5 mm helix radius). This phantom’s intraluminal flow trajectory embraces all combinations of x, y, and z directional components, as confirmed using computational fluid dynamics (CFD) simulations. The phantom was physically fabricated via lost-core casting with polyvinyl alcohol cryogel (PVA) as the tissue mimic. 3D ultrasound confirmed that the phantom lumen expectedly resembled a helical toroid geometry. Pulsed Doppler measurements showed that the phantom, when operating under steady flow conditions (3 ml s−1 flow rate), yielded flow velocity magnitudes that agreed well with those derived from CFD at both the inner torus (−47.6 ± 5.7 versus −52.0 ± 2.2 cm s−1; mean ± 1 S.D.) and the outer torus (49.5 ± 4.2 versus 48.0 ± 1.7 cm s−1). Additionally, 3-C velocity vectors acquired from multi-angle pulsed Doppler showed good agreement with CFD-derived velocity vectors (<7% and 10° difference in magnitude and flow angle, respectively). Ultrasound color flow imaging further revealed that the phantom’s axial flow pattern was aligned with the CFD-derived flow profile. Overall, the helical toroid phantom has strong potential as an investigative tool in 3D flow imaging innovation endeavors, such as the development of flow vector estimators and visualization algorithms.

Quality Assuring a Ring Vortex Flow Phantom in Real-Time

“…Phantoms in the literature employ reference flows ranging from laminar, parabolic flow to complex profiles incorporating eddies and recirculation zones. Simple flows are famously well-behaved and have been shown to be accurately predicted using analytical [28] [29] [30] or Open Journal of Medical Imaging CFD methods [31] [32]. These will rarely deviate from reference behaviour due to tightly constrained and simple geometries, hence non-real-time fluid predictions are sufficient, particularly when combined with real-time motor QA.…”