Literature DB >> 30747461

Reconciling PC-MRI and CFD: An in-vitro study.

Thomas Puiseux1,2, Anou Sewonu2,3, Olivier Meyrignac3,4, Hervé Rousseau3,4, Franck Nicoud1, Simon Mendez1, Ramiro Moreno2,3.   

Abstract

Several well-resolved 4D Flow MRI acquisitions of an idealized rigid flow phantom featuring an aneurysm, a curved channel as well as a bifurcation were performed under pulsatile regime. The resulting hemodynamics were processed to remove MRI artifacts. Subsequently, they were compared with CFD predictions computed on the same flow domain, using an in-house high-order low dissipative flow solver. Results show that reaching a good agreement is not straightforward but requires proper treatments of both techniques. Several sources of discrepancies are highlighted and their impact on the final correlation evaluated. While a very poor correlation (r2  = 0.63) is found in the entire domain between raw MRI and CFD data, correlation as high as r2  = 0.97 is found when artifacts are removed by post-processing the MR data and down sampling the CFD results to match the MRI spatial and temporal resolutions. This work demonstrates that, in a well-controlled environment, both PC-MRI and CFD might bring reliable and correlated flow quantities when a proper methodology to reduce the errors is followed.
© 2019 John Wiley & Sons, Ltd.

Entities:  

Keywords:  cardiovascular blood flows; computational fluid dynamics; large eddy simulation; phase contrast magnetic resonance imaging; validation work flow

Year:  2019        PMID: 30747461     DOI: 10.1002/nbm.4063

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  7 in total

1.  Derivation of vascular wall shear stress from 1000 fps high-speed angiography (HSA) velocity distributions.

Authors:  A Shields; S V Setlur Nagesh; V Chivukula; C Ionita; D R Bednarek; S Rudin
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2022-04-04

2.  Assessment of turbulent blood flow and wall shear stress in aortic coarctation using image-based simulations.

Authors:  Romana Perinajová; Joe F Juffermans; Jonhatan Lorenzo Mercado; Jean-Paul Aben; Leon Ledoux; Jos J M Westenberg; Hildo J Lamb; Saša Kenjereš
Journal:  Biomed Eng Online       Date:  2021-08-21       Impact factor: 2.819

3.  Impact of extra-anatomical bypass on coarctation fluid dynamics using patient-specific lumped parameter and Lattice Boltzmann modeling.

Authors:  Reza Sadeghi; Benjamin Tomka; Seyedvahid Khodaei; MohammadAli Daeian; Krishna Gandhi; Julio Garcia; Zahra Keshavarz-Motamed
Journal:  Sci Rep       Date:  2022-06-11       Impact factor: 4.996

4.  Enhancement of cerebrovascular 4D flow MRI velocity fields using machine learning and computational fluid dynamics simulation data.

Authors:  David R Rutkowski; Alejandro Roldán-Alzate; Kevin M Johnson
Journal:  Sci Rep       Date:  2021-05-13       Impact factor: 4.379

5.  Numerical simulation of time-resolved 3D phase-contrast magnetic resonance imaging.

Authors:  Thomas Puiseux; Anou Sewonu; Ramiro Moreno; Simon Mendez; Franck Nicoud
Journal:  PLoS One       Date:  2021-03-26       Impact factor: 3.240

6.  A novel MRI-based data fusion methodology for efficient, personalised, compliant simulations of aortic haemodynamics.

Authors:  Catriona Stokes; Mirko Bonfanti; Zeyan Li; Jiang Xiong; Duanduan Chen; Stavroula Balabani; Vanessa Díaz-Zuccarini
Journal:  J Biomech       Date:  2021-10-09       Impact factor: 2.712

7.  Evaluation of Computational Methodologies for Accurate Prediction of Wall Shear Stress and Turbulence Parameters in a Patient-Specific Aorta.

Authors:  Emily Louise Manchester; Selene Pirola; Mohammad Yousuf Salmasi; Declan P O'Regan; Thanos Athanasiou; Xiao Yun Xu
Journal:  Front Bioeng Biotechnol       Date:  2022-03-24
  7 in total

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