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Author:

Hou, Qianwen (Hou, Qianwen.) | Tao, Keyi (Tao, Keyi.) | Du, Tianming (Du, Tianming.) | Wei, Hongge (Wei, Hongge.) | Zhang, Honghui (Zhang, Honghui.) | Chen, Shiliang (Chen, Shiliang.) | Pan, Youlian (Pan, Youlian.) | Qiao, Aike (Qiao, Aike.)

Indexed by:

EI Scopus SCIE

Abstract:

Background and objectives: The bicuspid aortic valve (BAV) is a major risk factor for the progression of aortic dilation (AD) because of the induced abnormal blood flow environment in aorta. The differences in the development of AD induced by BAV phenotypes remains unclear. Therefore, the objective of this study was to assess the potential locations of AD induced by different phenotypes of BAV. The different effects of opening orifice area and leaflet orientation on ascending aortic hemodynamics in Type-1 BAV was investigated by means of numerical simulation. Methods: Finite element dynamic analysis was performed on tricuspid aortic valve (TAV) and BAV models to simulate the motion of the leaflets and obtain the geometrical characteristics of AV at peak systole as a reference, which were used for aortic models. Then, four sets of aortic fluid models were designed according to the leaflet fusion types [TAV; BAV (left-right-coronary cusp fusion, LR; right-non-coronary cusp fusion, RN; left-non-coronary cusp fusion, LN)], and the computational fluid dynamics method was applied to compare the hemodynamic differences within the aorta at peak systole. Results: The maximum opening area of BAV was significantly reduced, resulting in alterations in aortic hemodynamics compared with TAV. The velocity streamlines were essentially parallel to the aortic wall in TAV. The average pressure and wall shear stress in aorta tend to be stable. In contrary, the eccentricity of BAV orifice jet resulted in high-velocity flow directed toward the ascending aorta (AA) wall and aortic arch for LR and LN; RN features an asymmetrical velocity distribution toward the outer bend of the middle AA, and eccentric flow tends to impact the distal AA. As the flow angle is associated with distinct flow impingement locations, different degrees of WSS and pressure concentration occur along the aortic wall from the AA to the aortic arch in three BAV types. Conclusions: The BAV morphotype affects the aortic hemodynamics, and the abnormal blood flow associated with BAV may play a role in AD. The different BAV phenotypes determine the direction of blood flow jet and change the expression of dilation. LR is likely to cause dilation of the tubular AA; RN results in dilation of the middle AA to proximal aortic arch; and LN causes an increased incidence of the tubular AA and the proximal aortic arch. © 2022 Elsevier B.V.

Keyword:

Blood vessels Orifices Numerical models Computational fluid dynamics Velocity distribution Blood Arches Hemodynamics Shear flow Shear stress

Author Community:

  • [ 1 ] [Hou, Qianwen]Faculty of Environment and Life, Beijing University of Technology, Beijing, China
  • [ 2 ] [Hou, Qianwen]Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, China
  • [ 3 ] [Tao, Keyi]Faculty of Environment and Life, Beijing University of Technology, Beijing, China
  • [ 4 ] [Tao, Keyi]Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, China
  • [ 5 ] [Du, Tianming]Faculty of Environment and Life, Beijing University of Technology, Beijing, China
  • [ 6 ] [Du, Tianming]Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, China
  • [ 7 ] [Wei, Hongge]Faculty of Environment and Life, Beijing University of Technology, Beijing, China
  • [ 8 ] [Wei, Hongge]Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, China
  • [ 9 ] [Zhang, Honghui]Faculty of Environment and Life, Beijing University of Technology, Beijing, China
  • [ 10 ] [Zhang, Honghui]Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, China
  • [ 11 ] [Chen, Shiliang]Faculty of Environment and Life, Beijing University of Technology, Beijing, China
  • [ 12 ] [Chen, Shiliang]Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, China
  • [ 13 ] [Pan, Youlian]Faculty of Environment and Life, Beijing University of Technology, Beijing, China
  • [ 14 ] [Pan, Youlian]Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, China
  • [ 15 ] [Qiao, Aike]Faculty of Environment and Life, Beijing University of Technology, Beijing, China
  • [ 16 ] [Qiao, Aike]Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, China

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Source :

Computer Methods and Programs in Biomedicine

ISSN: 0169-2607

Year: 2022

Volume: 220

6 . 1

JCR@2022

6 . 1 0 0

JCR@2022

ESI Discipline: COMPUTER SCIENCE;

ESI HC Threshold:46

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 11

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 7

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