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PMID: 38701696 Published · ppublish English Journal Article

Numerical study of hemodynamic flow in the aortic vessel of Williams syndrome patient with congenital heart disease.

Journal of biomechanics ·Vol. 168 ·2024-05-00 ·页码 112124

Jack JT, Jensen M, Collins RT, Chan FP, Millett PC

Abstract

Congenital arterial stenosis such as supravalvar aortic stenosis (SVAS) are highly prevalent in Williams syndrome (WS) and other arteriopathies pose a substantial health risk. Conventional tools for severity assessment, including clinical findings and pressure gradient estimations, often fall short due to their susceptibility to transient physiological changes and disease stage influences. Moreover, in the pediatric population, the severity of these and other congenital heart defects (CHDs) often restricts the applicability of invasive techniques for obtaining crucial physiological data. Conversely, evaluating CHDs and their progression requires a comprehensive understanding of intracardiac blood flow. Current imaging modalities, such as blood speckle imaging (BSI) and four-dimensional magnetic resonance imaging (4D MRI) face limitations in resolving flow data, especially in cases of elevated flow velocities. To address these challenges, we devised a computational framework employing zero-dimensional (0D) lumped parameter models coupled with patient-specific reconstructed geometries pre- and post-surgical intervention to execute computational fluid dynamic (CFD) simulations. This framework facilitates the analysis and visualization of intricate blood flow patterns, offering insights into geometry and flow dynamics alterations impacting cardiac function. In this study, we aim to assess the efficacy of surgical intervention in correcting an extreme aortic defect in a patient with WS, leading to reductions in wall shear stress (WSS), maximum velocity magnitude, pressure drop, and ultimately a decrease in cardiac workload.

Keywords
Computational fluid dynamics Lumped parameter model Supravalvular aortic stenosis Williams syndrome
MeSH 主题词
Humans Williams Syndrome/physiopathology,diagnostic imaging Hemodynamics/physiology Models, Cardiovascular Heart Defects, Congenital/physiopathology,complications,diagnostic imaging Aorta/physiopathology,diagnostic imaging Blood Flow Velocity/physiology Male Female Computer Simulation
作者与单位
共 5 位作者,点击展开单位 / ORCID
Jack Justin T
University of Arkansas, Department of Mechanical Engineering, Fayetteville, AR, USA.
Jensen Morten
University of Arkansas, Department of Biomedical Engineering, Fayetteville, AR, USA; University of Arkansas for Medical Sciences, Department of Surgery, Little Rock, AR, USA.
Collins R Thomas
University of Kentucky, Department of Pediatrics, Division of Cardiology, Lexington, KY, USA.
Chan Frandics Pak
Stanford University, Department of Radiology/Cardiovascular Imaging, Palo Alto, CA, USA.
Millett Paul C
University of Arkansas, Department of Mechanical Engineering, Fayetteville, AR, USA. Electronic address: [email protected].
Article Info
Journal
Journal of biomechanics
Abbr.
J Biomech
ISSN
1873-2380
Corresponding email
Published
2024-05-00
电子出版
2024-00-29
页码
112124
Language
English
Country/Region
United States
NLM ID
0157375
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