ArticleCardiovascular engineering and technology2018
Steady Flow in a Patient-Averaged Inferior Vena Cava-Part I: Particle Image Velocimetry Measurements at Rest and Exercise Conditions.
Article in Cardiovascular engineering and technology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 27 citations in OpenAlex.
- Computational Modeling of Flow in an in Vitro Cerebrovascular Model Under Pulsatile Conditions with Experimental Validation.Cardiovascular engineering and technology · 2026Article
- Correlation of clinical and laboratory findings of dehydration with ultrasonographic measurements.Saudi medical journal · 2025Article
- Fluid Dynamic and in Vitro Blood Study to Understand Catheter-Related Thrombosis.Cardiovascular engineering and technology · 2025Article
- Numerical simulation and in vitro experimental study of the hemodynamic performance of vena cava filters with helical forms.Scientific reports · 2024Article
- Clinical situations for which 3D Printing is considered an appropriate representation or extension of data contained in a medical imaging examination: vascular conditions.3D printing in medicine · 2023Review
- Modeling Flow in anbioRxiv : the preprint server for biology · 2023Article
- Modeling flow in anFrontiers in medical technology · 2023Article
- A sharp interface Lagrangian-Eulerian method for rigid-body fluid-structure interaction.Journal of computational physics · 2021Article
- Time-Resolved PIV Measurements and Turbulence Characteristics of Flow Inside an Open-Cell Metal Foam.Materials (Basel, Switzerland) · 2021Article
- Computational evaluation of inferior vena cava filters through computational fluid dynamics methods.Diagnostic and interventional radiology (Ankara, Turkey) · 2021Article
- An Immersed Interface Method for Discrete Surfaces.Journal of computational physics · 2020Article
- Over-the-wire deployment techniques of option elite inferior vena cava filter: 3D printing vena cava phantom study.European journal of radiology open · 2020Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
purposeAlthough many previous computational fluid dynamics (CFD) studies have investigated the hemodynamics in the inferior vena cava (IVC), few studies have compared computational predictions to experimental data, and only qualitative comparisons have been made. Herein, we provide particle image velocimetry (PIV) measurements of flow in a patient-averaged IVC geometry under idealized conditions typical of those used in the preclinical evaluation of IVC filters.
methodsMeasurements are acquired under rest and exercise flow rate conditions in an optically transparent model fabricated using 3D printing. To ensure that boundary conditions are well-defined and to make follow-on CFD validation studies more convenient, fully-developed flow is provided at the inlets (i.e., the iliac veins) by extending them with straight rigid tubing longer than the estimated entrance lengths. Velocity measurements are then obtained at the downstream end of the tubing to confirm Poiseuille inflow boundary conditions.
resultsMeasurements in the infrarenal IVC reveal that flow profiles are blunter in the sagittal plane (minor axis) than in the coronal plane (major axis). Peak in-plane velocity magnitudes are 4.9 cm/s and 27 cm/s under the rest and exercise conditions, respectively. Flow profiles are less parabolic and exhibit more inflection points at the higher flow rate. Bimodal velocity peaks are also observed in the sagittal plane at the elevated flow condition.
conclusionsThe IVC geometry, boundary conditions, and infrarenal velocity measurements are provided for download on a free and publicly accessible repository at https://doi.org/10.6084/m9.figshare.7198703 . These data will facilitate future CFD validation studies of idealized, in vitro IVC hemodynamics and of similar laminar flows in vascular geometries.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.