Literature DB >> 29501225

Quantification of disturbed coronary flow by disturbed vorticity index and relation with fractional flow reserve.

Miao Chu1, Clemens von Birgelen2, Yingguang Li3, Jelmer Westra4, Junqing Yang5, Niels R Holm4, Johan H C Reiber3, William Wijns6, Shengxian Tu7.   

Abstract

BACKGROUND AND AIMS: The relation between FFR and local coronary flow patterns is incompletely understood. We aimed at developing a novel hemodynamic index to quantify disturbed coronary flow, and to investigate its relationship with lesion-associated pressure-drop, and fractional flow reserve (FFR).
METHODS: Three-dimensional angiographic reconstruction and computational fluid dynamics were applied to simulate pulsatile coronary flow. Disturbed vorticity index (DVI) was derived to quantify the stenosis-induced flow disturbance. The relation between DVI and pressure-drop was assessed in 9 virtual obstruction models. Furthermore, we evaluated the correlation between DVI, FFR, hyperemic flow velocity, and anatomic parameters in 84 intermediate lesions from 73 patients.
RESULTS: In virtual models, DVI increased with increasing flow rate, stenosis severity, and lesion complexity. The correlation between DVI and pressure-drop across all models was excellent (determination coefficient R2 = 0.85, p < 0.001). In vivo, DVI showed a correlation with FFR (rho (ρ) = -0.74, p < 0.001) that was stronger than the relations of FFR with hyperemic flow velocity (ρ = -0.27, p=0.015), lesion length (ρ = -0.36, p=0.001) and percent diameter stenosis (ρ = -0.40, p < 0.001).
CONCLUSIONS: DVI, a novel index to quantify disturbed flow, was related to pressure-drop in virtual obstruction models and showed a strong inverse relation with FFR in intermediate lesions in vivo. It supports the prognostic value of FFR and may provide additional information about sources of energy loss when measuring FFR.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Coronary angiography; Coronary artery disease; Flow patterns; Fractional flow reserve; Vascular hemodynamics

Mesh:

Year:  2018        PMID: 29501225     DOI: 10.1016/j.atherosclerosis.2018.02.023

Source DB:  PubMed          Journal:  Atherosclerosis        ISSN: 0021-9150            Impact factor:   5.162


  6 in total

1.  Fluid shear stress modulates endothelial inflammation by targeting LIMS2.

Authors:  Junyao Wang; Shiyanjin Zhang
Journal:  Exp Biol Med (Maywood)       Date:  2020-08-04

2.  Coronary flow disturbance assessed by vorticity as a cause of functionally significant stenosis.

Authors:  Nobuo Tomizawa; Yui Nozaki; Shinichiro Fujimoto; Daigo Takahashi; Ayako Kudo; Yuki Kamo; Chihiro Aoshima; Yuko Kawaguchi; Kazuhisa Takamura; Makoto Hiki; Tomotaka Dohi; Shinya Okazaki; Kanako K Kumamaru; Tohru Minamino; Shigeki Aoki
Journal:  Eur Radiol       Date:  2022-07-02       Impact factor: 7.034

3.  Coronary artery decision algorithm trained by two-step machine learning algorithm.

Authors:  Young Woo Kim; Hee-Jin Yu; Jung-Sun Kim; Jinyong Ha; Jongeun Choi; Joon Sang Lee
Journal:  RSC Adv       Date:  2020-01-24       Impact factor: 4.036

4.  Simultaneous evaluation of plaque stability and ischemic potential of coronary lesions in a fluid-structure interaction analysis.

Authors:  Xinlei Wu; Clemens von Birgelen; Su Zhang; Daixin Ding; Jiayue Huang; Shengxian Tu
Journal:  Int J Cardiovasc Imaging       Date:  2019-05-03       Impact factor: 2.357

5.  The Holistic Coronary Physiology Display: Calculation of the Flow Separation Index in Vessel-Specific Individual Flow Range during Fractional Flow Reserve Measurement Using 3D Coronary Reconstruction.

Authors:  Gábor Tamás Szabó; Áron Üveges; Balázs Tar; András Ágoston; Azzaya Dorj; Csaba Jenei; Rudolf Kolozsvári; Benjamin Csippa; Dániel Czuriga; Zsolt Kőszegi
Journal:  J Clin Med       Date:  2021-04-28       Impact factor: 4.241

6.  Numerical modelling of blood rheology and platelet activation through a stenosed left coronary artery bifurcation.

Authors:  David G Owen; Diana C de Oliveira; Emma K Neale; Duncan E T Shepherd; Daniel M Espino
Journal:  PLoS One       Date:  2021-11-03       Impact factor: 3.240

  6 in total

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