Numerical investigation of carotid stenosis in three-dimensional aortic-cerebral vasculature: pulsatility index, resistive index, time to peak velocity, and flow characteristics

Haemodynamic correlations among the pulsatility index (PI), resistive index (RI), time to peak velocity (TPV), and mean Reynolds number (ReMean) were numerically investigated during the progression of carotid stenosis (CS), a highly prevalent condition. Fifteen patient-specific CS cases were modeled...

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Autores principales:	Taehak Kang, Debanjan Mukherjee, Jaiyoung Ryu
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2021
Materias:	carotid stenosis (cs) circle of willis (cow) pulsatility index (pi) resistive index (ri) time to peak velocity (tpv) regression model Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/e9ae818d403d43e6b6bd86aba488da0d
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spelling	oai:doaj.org-article:e9ae818d403d43e6b6bd86aba488da0d2021-11-04T15:00:43ZNumerical investigation of carotid stenosis in three-dimensional aortic-cerebral vasculature: pulsatility index, resistive index, time to peak velocity, and flow characteristics1994-20601997-003X10.1080/19942060.2021.1984993https://doaj.org/article/e9ae818d403d43e6b6bd86aba488da0d2021-01-01T00:00:00Zhttp://dx.doi.org/10.1080/19942060.2021.1984993https://doaj.org/toc/1994-2060https://doaj.org/toc/1997-003XHaemodynamic correlations among the pulsatility index (PI), resistive index (RI), time to peak velocity (TPV), and mean Reynolds number (ReMean) were numerically investigated during the progression of carotid stenosis (CS), a highly prevalent condition. Fifteen patient-specific CS cases were modeled in the package, SimVascular, by using computed tomography angiography data for the aortic-cerebral vasculature. Computational fluid domains were solved with a stabilized Petrov–Galerkin scheme under Newtonian and incompressible assumptions. A rigid vessel wall was assumed, and the boundary conditions were pulsatile inflow and three-element lumped Windkessel outlets. During the progression, the increase in the TPV resembled that during aortic stenosis, and the parameter was negatively correlated with PI, RI, and ReMean in the ipsilateral cerebral region. The ReMean was inversely related to PI and RI on the contralateral side. In particular, PI and RI in cerebral arteries showed three second-order regression patterns: ‘constant (Group A)’, ‘moderately decreasing (Group B)’, and ‘decreasing (Group C)’. The patterns were defined using a new parameter, mean ratio (lowest mean index/mean index at 0% CS). This parameter could effectively indicate stenosis-driven tendencies in local haemodynamics. Overall, the haemodynamic indices changed drastically during severe unilateral CS, and they reflected both regional and aortic-cerebral flow characteristics.Taehak KangDebanjan MukherjeeJaiyoung RyuTaylor & Francis Grouparticlecarotid stenosis (cs)circle of willis (cow)pulsatility index (pi)resistive index (ri)time to peak velocity (tpv)regression modelEngineering (General). Civil engineering (General)TA1-2040ENEngineering Applications of Computational Fluid Mechanics, Vol 15, Iss 1, Pp 1645-1665 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	carotid stenosis (cs) circle of willis (cow) pulsatility index (pi) resistive index (ri) time to peak velocity (tpv) regression model Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	carotid stenosis (cs) circle of willis (cow) pulsatility index (pi) resistive index (ri) time to peak velocity (tpv) regression model Engineering (General). Civil engineering (General) TA1-2040 Taehak Kang Debanjan Mukherjee Jaiyoung Ryu Numerical investigation of carotid stenosis in three-dimensional aortic-cerebral vasculature: pulsatility index, resistive index, time to peak velocity, and flow characteristics
description	Haemodynamic correlations among the pulsatility index (PI), resistive index (RI), time to peak velocity (TPV), and mean Reynolds number (ReMean) were numerically investigated during the progression of carotid stenosis (CS), a highly prevalent condition. Fifteen patient-specific CS cases were modeled in the package, SimVascular, by using computed tomography angiography data for the aortic-cerebral vasculature. Computational fluid domains were solved with a stabilized Petrov–Galerkin scheme under Newtonian and incompressible assumptions. A rigid vessel wall was assumed, and the boundary conditions were pulsatile inflow and three-element lumped Windkessel outlets. During the progression, the increase in the TPV resembled that during aortic stenosis, and the parameter was negatively correlated with PI, RI, and ReMean in the ipsilateral cerebral region. The ReMean was inversely related to PI and RI on the contralateral side. In particular, PI and RI in cerebral arteries showed three second-order regression patterns: ‘constant (Group A)’, ‘moderately decreasing (Group B)’, and ‘decreasing (Group C)’. The patterns were defined using a new parameter, mean ratio (lowest mean index/mean index at 0% CS). This parameter could effectively indicate stenosis-driven tendencies in local haemodynamics. Overall, the haemodynamic indices changed drastically during severe unilateral CS, and they reflected both regional and aortic-cerebral flow characteristics.
format	article
author	Taehak Kang Debanjan Mukherjee Jaiyoung Ryu
author_facet	Taehak Kang Debanjan Mukherjee Jaiyoung Ryu
author_sort	Taehak Kang
title	Numerical investigation of carotid stenosis in three-dimensional aortic-cerebral vasculature: pulsatility index, resistive index, time to peak velocity, and flow characteristics
title_short	Numerical investigation of carotid stenosis in three-dimensional aortic-cerebral vasculature: pulsatility index, resistive index, time to peak velocity, and flow characteristics
title_full	Numerical investigation of carotid stenosis in three-dimensional aortic-cerebral vasculature: pulsatility index, resistive index, time to peak velocity, and flow characteristics
title_fullStr	Numerical investigation of carotid stenosis in three-dimensional aortic-cerebral vasculature: pulsatility index, resistive index, time to peak velocity, and flow characteristics
title_full_unstemmed	Numerical investigation of carotid stenosis in three-dimensional aortic-cerebral vasculature: pulsatility index, resistive index, time to peak velocity, and flow characteristics
title_sort	numerical investigation of carotid stenosis in three-dimensional aortic-cerebral vasculature: pulsatility index, resistive index, time to peak velocity, and flow characteristics
publisher	Taylor & Francis Group
publishDate	2021
url	https://doaj.org/article/e9ae818d403d43e6b6bd86aba488da0d
work_keys_str_mv	AT taehakkang numericalinvestigationofcarotidstenosisinthreedimensionalaorticcerebralvasculaturepulsatilityindexresistiveindextimetopeakvelocityandflowcharacteristics AT debanjanmukherjee numericalinvestigationofcarotidstenosisinthreedimensionalaorticcerebralvasculaturepulsatilityindexresistiveindextimetopeakvelocityandflowcharacteristics AT jaiyoungryu numericalinvestigationofcarotidstenosisinthreedimensionalaorticcerebralvasculaturepulsatilityindexresistiveindextimetopeakvelocityandflowcharacteristics
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Numerical investigation of carotid stenosis in three-dimensional aortic-cerebral vasculature: pulsatility index, resistive index, time to peak velocity, and flow characteristics

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