Literature DB >> 22884968

Patient-specific mean pressure drop in the systemic arterial tree, a comparison between 1-D and 3-D models.

Philippe Reymond1, Fabienne Perren, François Lazeyras, Nikos Stergiopulos.   

Abstract

One-dimensional models of the systemic arterial tree are useful tools for studying wave propagation phenomena, however, their formulation for frictional losses is approximate and often based on solutions for developed flow in straight non-tapered arterial segments. Thus, losses due to bifurcations, tortuosity, non-planarity and complex geometry effects cannot be accounted for in 1-D models. This may lead to errors in the estimation of mean pressure. To evaluate these errors, we simulated steady flow in a patient specific model of the entire systemic circulation using a standard CFD code with Newtonian and non-Newtonian blood properties and compared the pressure evolution along three principal and representative arterial pathlines with the prediction of mean pressure, as given by the 1-D model. Pressure drop computed from aortic root up to iliac bifurcation and to distal brachial is less than 1 mmHg and 1-D model predictions agree well with the 3-D model. In smaller vessels like the precerebral and cerebral arteries, the losses are higher (mean pressure drop over 10 mmHg from mean aortic pressure) and are consistently underestimated by the 1-D model. Complex flow patterns resulting from tortuosity, non-planarity and branching yield shear stresses, which are higher than the ones predicted by the 1-D model. In consequence, the 1-D model overestimates mean pressure in peripheral arteries and especially in the cerebral circulation.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 22884968     DOI: 10.1016/j.jbiomech.2012.07.020

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  11 in total

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Journal:  J Physiol       Date:  2016-09-29       Impact factor: 5.182

4.  Automated generation of 0D and 1D reduced-order models of patient-specific blood flow.

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5.  On the Periodicity of Cardiovascular Fluid Dynamics Simulations.

Authors:  Martin R Pfaller; Jonathan Pham; Nathan M Wilson; David W Parker; Alison L Marsden
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Authors:  Bradley Feiger; Adebayo Adebiyi; Amanda Randles
Journal:  Comput Biol Med       Date:  2020-12-09       Impact factor: 4.589

7.  Characterization of intrathecal cerebrospinal fluid geometry and dynamics in cynomolgus monkeys (macaca fascicularis) by magnetic resonance imaging.

Authors:  Mohammadreza Khani; Braden J Lawrence; Lucas R Sass; Christina P Gibbs; Joshua J Pluid; John N Oshinski; Gregory R Stewart; Jillynne R Zeller; Bryn A Martin
Journal:  PLoS One       Date:  2019-02-27       Impact factor: 3.240

8.  Blood flow rate and wall shear stress in seven major cephalic arteries of humans.

Authors:  Roger S Seymour; Qiaohui Hu; Edward P Snelling
Journal:  J Anat       Date:  2019-11-11       Impact factor: 2.610

9.  The impact of shape uncertainty on aortic-valve pressure-drop computations.

Authors:  M J M M Hoeijmakers; W Huberts; M C M Rutten; F N van de Vosse
Journal:  Int J Numer Method Biomed Eng       Date:  2021-08-23       Impact factor: 2.648

10.  Blood pressure gradients in cerebral arteries: a clue to pathogenesis of cerebral small vessel disease.

Authors:  Pablo J Blanco; Lucas O Müller; J David Spence
Journal:  Stroke Vasc Neurol       Date:  2017-06-08
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