Fluid-structure coupled biotransport processes in aortic valve disease

Sadrabadi, Mohammadreza Soltany; Hedayat, Mohammadali; Borazjani, Iman; Arzani, Amirhossein

doi:10.1016/j.jbiomech.2021.110239

Cited by 19 publications

(10 citation statements)

References 49 publications

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“…In particular, LCS were extracted to delineate the boundaries of the outflow jet downstream of aortic valves and used as a measure of the severity of the valve's stenosis [54,55]. In a very recent study [56], FTLE-based LCS detection on computational hemodynamics models of aortic bicuspid and mechanical heart valves was used to study mass transport processes that might be related to valve disease. The analysis of the fluid dynamics in the neighborhood of blood clots was another effective application of LCS to hemodynamics [57].…”

Section: Lcs Application To Intravascular Flowsmentioning

confidence: 99%

Wall Shear Stress Topological Skeleton Analysis in Cardiovascular Flows: Methods and Applications

Mazzi¹,

Morbiducci²,

Calò³

et al. 2021

Mathematics

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A marked interest has recently emerged regarding the analysis of the wall shear stress (WSS) vector field topological skeleton in cardiovascular flows. Based on dynamical system theory, the WSS topological skeleton is composed of fixed points, i.e., focal points where WSS locally vanishes, and unstable/stable manifolds, consisting of contraction/expansion regions linking fixed points. Such an interest arises from its ability to reflect the presence of near-wall hemodynamic features associated with the onset and progression of vascular diseases. Over the years, Lagrangian-based and Eulerian-based post-processing techniques have been proposed aiming at identifying the topological skeleton features of the WSS. Here, the theoretical and methodological bases supporting the Lagrangian- and Eulerian-based methods currently used in the literature are reported and discussed, highlighting their application to cardiovascular flows. The final aim is to promote the use of WSS topological skeleton analysis in hemodynamic applications and to encourage its application in future mechanobiology studies in order to increase the chance of elucidating the mechanistic links between blood flow disturbances, vascular disease, and clinical observations.

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Section: Lcs Application To Intravascular Flowsmentioning

confidence: 99%

Wall Shear Stress Topological Skeleton Analysis in Cardiovascular Flows: Methods and Applications

Mazzi¹,

Morbiducci²,

Calò³

et al. 2021

Mathematics

View full text Add to dashboard Cite

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“…[15][16][17][18] The high incidence of coronary atherosclerosis has led to numerous studies of hemodynamics and LDL transport in the coronary artery, [19][20][21][22][23][24][25][26][27][28][29][30][31] demonstrating high LDL concentration in regions prone to atherosclerotic plaque formation. LDL accumulation is also suggested to promote plaque formation in the aorta [32][33][34] and carotid artery. [35][36][37][38] In the case of restenosis, recent reports suggest that the process starts with neoatherosclerosis after stenting, characterized by the accumulation of lipid-laden foamy macrophages within the neointimal layer.…”

Section: Introductionmentioning

confidence: 99%

Computational modeling of low‐density lipoprotein accumulation at the carotid artery bifurcation after stenting

Johari,

Menichini,

Hamady

et al. 2023

Numer Methods Biomed Eng

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Restenosis typically occurs in regions of low and oscillating wall shear stress, which also favor the accumulation of atherogenic macromolecules such as low‐density lipoprotein (LDL). This study aims to evaluate LDL transport and accumulation at the carotid artery bifurcation following carotid artery stenting (CAS) by means of computational simulation. The computational model consists of coupled blood flow and LDL transport, with the latter being modeled as a dilute substance dissolved in the blood and transported by the flow through a convection‐diffusion transport equation. The endothelial layer was assumed to be permeable to LDL, and the hydraulic conductivity of LDL was shear‐dependent. Anatomically realistic geometric models of the carotid bifurcation were built based on pre‐ and post‐stent computed tomography (CT) scans. The influence of stent design was investigated by virtually deploying two different types of stents (open‐ and closed‐cell stents) into the same carotid bifurcation model. Predicted LDL concentrations were compared between the post‐stent carotid models and the relatively normal contralateral model reconstructed from patient‐specific CT images. Our results show elevated LDL concentration in the distal section of the stent in all post‐stent models, where LDL concentration is 20 times higher than that in the contralateral carotid. Compared with the open‐cell stents, the closed‐cell stents have larger areas exposed to high LDL concentration, suggesting an increased risk of stent restenosis. This computational approach is readily applicable to multiple patient studies and, once fully validated against follow‐up data, it can help elucidate the role of stent strut design in the development of in‐stent restenosis after CAS.

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“…Most of the computational studies on CAVD reported in the literature utilized computational fluid dynamics (CFD) and fluid-structure interaction (FSI) methods. While these approaches are useful to evaluate aortic valve hemodynamics, they do not analyze cellular interactions and tissue remodeling processes (Mirza & Ramaswamy, 2022;Sadrabadi, Hedayat, Borazjani, & Arzani, 2021;Amindari, Saltik, Kirkkopru, Yacoub, & Yalcin, 2017;Luraghi et al, 2019;Chandra et al, 2012). The focus of this study is to develop a new computational modeling framework for aortic valve calcification based on TGFβ stimulation.…”

Section: Introductionmentioning

confidence: 99%

Multiscale Computational Modeling of Aortic Valve Calcification

Azimi-Boulali

Mahler

Murray

et al. 2023

Preprint

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Calcific aortic valve disease (CAVD) is a common cardiovascular disease that affects millions of peopleworldwide. The disease is characterized by the formation of calcium nodules on the aortic valve leaflets,which can lead to stenosis and heart failure if left untreated. The pathogenesis of CAVD is still notwell understood, but involves several signaling pathways, including the transforming growth factorbeta (TGFβ) pathway. In this study, we developed a multiscale computational model for TGFβ-stimulated CAVD. The model framework comprises cellular behavior dynamics, subcellular signalingpathways, and tissue-level diffusion fields of pertinent chemical species, where information is sharedamong different scales. Processes such as endothelial to mesenchymal transition (EndMT), fibrosis, andcalcification are incorporated. The results indicate that the majority of myofibroblasts and osteoblastlikecells ultimately die due to lack of nutrients as they become trapped in areas with higher levels offibrosis or calcification, and they subsequently act as sources for calcium nodules, which contributeto a polydispersed nodule size distribution. Additionally, fibrosis and calcification processes occurmore frequently in regions closer to the endothelial layer where the cell activity is higher. Our resultsprovide insights into the mechanisms of CAVD and TGFβ signaling and could aid in the developmentof novel therapeutic approaches for CAVD and other related diseases such as cancer. More broadly,this type of modeling framework can pave the way for unraveling the complexity of biological systemsby incorporating several signaling pathways in subcellular models to simulate tissue remodeling indiseases involving cellular mechanobiology.

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Fluid-structure coupled biotransport processes in aortic valve disease

Cited by 19 publications

References 49 publications

Wall Shear Stress Topological Skeleton Analysis in Cardiovascular Flows: Methods and Applications

Wall Shear Stress Topological Skeleton Analysis in Cardiovascular Flows: Methods and Applications

Computational modeling of low‐density lipoprotein accumulation at the carotid artery bifurcation after stenting

Multiscale Computational Modeling of Aortic Valve Calcification

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