Possible Assessment of Calf Venous Pump Efficiency by Computational Fluid Dynamics Approach.

STAR CCM + platform calf venous pump computational fluid-dynamics leg veins blood flow venous valvular incompetence

Journal

Frontiers in physiology
ISSN: 1664-042X
Titre abrégé: Front Physiol
Pays: Switzerland
ID NLM: 101549006

Informations de publication

Date de publication:
2020
Historique:
received: 24 11 2019
accepted: 23 07 2020
entrez: 5 10 2020
pubmed: 6 10 2020
medline: 6 10 2020
Statut: epublish

Résumé

Three-dimensional simulations of peripheral, deep venous flow during muscular exercise in limbs of healthy subjects and in those with venous dysfunction were carried out by a computational fluid-dynamics (CFD) approach using the STAR CCM + platform. The aim was to assess the effects of valvular incompetence on the venous calf pump efficiency. The model idealizes the lower limb circulation by a single artery, a capillary bed represented by a porous region and a single vein. The focus is on a segment of the circuit which mimics a typical deep vein at the level of the calf muscle, such as the right posterior tibial vein. Valves are idealized as ball valves, and periodic muscle contractions are given by imposing time-dependent boundary conditions to the calf segment wall. Flow measurements were performed in two cross-sections downstream and upstream of the calf pump. Model results demonstrate a reduced venous return for incompetent valves during calf exercise. Two different degrees of valvular incompetence are considered, by restricting the motion of one or both valves. Model results showed that only the proximal valve is critical, with a 30% reduction of venous return during calf exercise in case of valvular incompetence: the net flow volume ejected by the calf in central direction was 0.14 mL per working cycle, against 0.2 mL for simulated healthy limbs. This finding appeared to be consistent with a 25% reduction of the calf ejection fraction, experimentally observed in chronic venous disease limbs compared with healthy limbs.

Identifiants

pubmed: 33013438
doi: 10.3389/fphys.2020.01003
pmc: PMC7510250
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1003

Informations de copyright

Copyright © 2020 Niccolini, Manuello, Capone, Marongiu, Dell’Osa, Fois, Velluzzi and Concu.

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Auteurs

Gianni Niccolini (G)

Department of Structural, Geotechnical and Building Engineering, Politecnico di Torino, Turin, Italy.

Andrea Manuello (A)

Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy.

Antonio Capone (A)

Orthopedic Clinic, Department of Surgical Sciences, University of Cagliari, Cagliari, Italy.

Giuseppe Marongiu (G)

Orthopedic Clinic, Department of Surgical Sciences, University of Cagliari, Cagliari, Italy.

Antonio Hector Dell'Osa (AH)

Instituto de Desarrollo Economico e Innovación, Universidad Nacional de Tierra del Fuego, Antartida e Islas del Atlantico Sur, Ushuaia, Argentina.

Andrea Fois (A)

Biosignal Acquisition System, Nomadyca Ltd., Kampala, Uganda.

Fernanda Velluzzi (F)

Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.

Alberto Concu (A)

2C Technologies Ltd., Academic Spin-Off, University of Cagliari, Cagliari, Italy.

Classifications MeSH