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PMID: 39103664 Published · ppublish English Journal Article Review

A Pseudo-Spectral Method for Wall Shear Stress Estimation from Doppler Ultrasound Imaging in Coronary Arteries.

Cardiovascular engineering and technology ·Vol. 15 ·No. 6 ·2024-12-00 ·页码 647-666

Martín Tempestti J, Kim S, Lindsey BD, Veneziani A

Abstract

The Wall Shear Stress (WSS) is the component tangential to the boundary of the normal stress tensor in an incompressible fluid, and it has been recognized as a quantity of primary importance in predicting possible adverse events in cardiovascular diseases, in general, and in coronary diseases, in particular. The quantification of the WSS in patient-specific settings can be achieved by performing a Computational Fluid Dynamics (CFD) analysis based on patient geometry, or it can be retrieved by a numerical approximation based on blood flow velocity data, e.g., ultrasound (US) Doppler measurements. This paper presents a novel method for WSS quantification from 2D vector Doppler measurements. Images were obtained through unfocused plane waves and transverse oscillation to acquire both in-plane velocity components. These velocity components were processed using pseudo-spectral differentiation techniques based on Fourier approximations of the derivatives to compute the WSS. Our Pseudo-Spectral Method (PSM) is tested in two vessel phantoms, straight and stenotic, where a steady flow of 15 mL/min is applied. The method is successfully validated against CFD simulations and compared against current techniques based on the assumption of a parabolic velocity profile. The PSM accurately detected Wall Shear Stress (WSS) variations in geometries differing from straight cylinders, and is less sensitive to measurement noise. In particular, when using synthetic data (noise free, e.g., generated by CFD) on cylindrical geometries, the Poiseuille-based methods and PSM have comparable accuracy; on the contrary, when using the data retrieved from US measures, the average error of the WSS obtained with the PSM turned out to be 3 to 9 times smaller than that obtained by state-of-the-art methods. The pseudo-spectral approach allows controlling the approximation errors in the presence of noisy data. This gives a more accurate alternative to the present standard and a less computationally expensive choice compared to CFD, which also requires high-quality data to reconstruct the vessel geometry.

Keywords
Computational fluid dynamics Doppler imaging Interpolation Numerical differentiation Wall shear stress
MeSH 主题词
Humans Stress, Mechanical Coronary Vessels/diagnostic imaging,physiology,physiopathology Models, Cardiovascular Blood Flow Velocity Phantoms, Imaging Computer Simulation Coronary Circulation Reproducibility of Results Fourier Analysis Coronary Stenosis/physiopathology,diagnostic imaging Predictive Value of Tests Ultrasonography, Doppler
作者与单位
共 4 位作者,点击展开单位 / ORCID
Martín Tempestti Jimena ORCID
Department of Mathematics, Emory University, 400 Dowman Dr, Atlanta, 30322, GA, USA. [email protected].
Kim Saeyoung
George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 801 Ferst Dr., Atlanta, GA, 30332, USA. | Interdisciplinary BioEngineering Graduate Program, Georgia Institute of Technology, 315 Ferst Dr., Atlanta, GA, 30332, USA.
Lindsey Brooks D
George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 801 Ferst Dr., Atlanta, GA, 30332, USA. | Interdisciplinary BioEngineering Graduate Program, Georgia Institute of Technology, 315 Ferst Dr., Atlanta, GA, 30332, USA. | Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 313 Ferst Dr NW, Atlanta, GA, 30332, USA.
Veneziani Alessandro
Department of Mathematics, Emory University, 400 Dowman Dr, Atlanta, 30322, GA, USA. | Department of Computer Science, Emory University, 400 Dowman Dr, Atlanta, GA, 30322, USA.
Article Info
Journal
Cardiovascular engineering and technology
Abbr.
Cardiovasc Eng Technol
ISSN
1869-4098
Corresponding email
Published
2024-12-00
电子出版
2024-00-05
页码
647-666
Language
English
Country/Region
United States
NLM ID
101531846
基金资助
National Science Foundation · DMS2012286
National Science Foundation · DMS2038118
Foundation for the National Institutes of Health · R01EB031101
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