A critical comparison of different residence time measures in aneurysms

Reza, Symon; Arzani, Amirhossein

doi:10.1016/j.jbiomech.2019.03.028

Cited by 39 publications

(39 citation statements)

References 42 publications

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“…RT method was also used to find zones with high potential of flow stagnation and restenosis in coronary artery with stenosis or stent. While both the method measure RT using Eulerian method and measure flow stagnation based on velocity and WSS ( Rayz et al, 2010 ; Suh et al, 2011 ; Long et al, 2014 ; Reza and Arzani, 2019 ), each method has a different concept of RT. The results presented in this work demonstrate the differences between the two methods.…”

Section: Discussionmentioning

confidence: 99%

Study of Coronary Atherosclerosis Using Blood Residence Time

et al. 2021

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Computational fluid dynamic-based modeling is commonly used in stenosed and stented coronary artery to characterize blood flow and identify hemodynamics factors that could lead to coronary stenosis. One such factor is the residence time (RT), which is important for investigating stenosis and restenosis progression. The current method to calculate RT, known as the relative residence time (RRT) method, does not provide the original scale of RT and only provides a relative value. We recently introduced a novel method, designated as RT method, based on developing the advection-diffusion equation with a scalar to calculate the absolute residence time. The goal of this study was to compare both methods. Our results show that both could detect regions with a high risk of stenosis and restenosis, but the RT method is also able to show the recirculation zone using pathlines in the lumen and quantify actual RT. Moreover, RT method also provided blood flow pathlines, and is correlated to wall shear stress (WSS), oscillatory shear index (OSI), RRT, and Localized Normalized Helicity (LNH) which are other critical factors to gauge stenosis severity and assess stenting in bifurcations coronary.

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Section: Discussionmentioning

confidence: 99%

Study of Coronary Atherosclerosis Using Blood Residence Time

et al. 2021

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“…Complex flow patterns are frequently observed in aneurysms (Xiang et al, 2011). Flow stagnation in an aneurysm can be quantified by the residence time (RT), which is the average time a particle remains within the aneurysm (Reza and Arzani, 2019). Higher RT indicates flow stagnation and retention of platelets and inflammatory cells, which may contribute to thrombus formation ( Figure 2D; Rayz et al, 2010;Reza and Arzani, 2019).…”

Section: Modelingmentioning

confidence: 99%

“…Flow stagnation in an aneurysm can be quantified by the residence time (RT), which is the average time a particle remains within the aneurysm (Reza and Arzani, 2019). Higher RT indicates flow stagnation and retention of platelets and inflammatory cells, which may contribute to thrombus formation ( Figure 2D; Rayz et al, 2010;Reza and Arzani, 2019). It is important to note that all models require assumptions, which can influence simulation results and model fidelity.…”

Section: Modelingmentioning

confidence: 99%

Computational Hemodynamic Modeling of Arterial Aneurysms: A Mini-Review

et al. 2020

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Arterial aneurysms are pathological dilations of blood vessels, which can be of clinical concern due to thrombosis, dissection, or rupture. Aneurysms can form throughout the arterial system, including intracranial, thoracic, abdominal, visceral, peripheral, or coronary arteries. Currently, aneurysm diameter and expansion rates are the most commonly used metrics to assess rupture risk. Surgical or endovascular interventions are clinical treatment options, but are invasive and associated with risk for the patient. For aneurysms in locations where thrombosis is the primary concern, diameter is also used to determine the level of therapeutic anticoagulation, a treatment that increases the possibility of internal bleeding. Since simple diameter is often insufficient to reliably determine rupture and thrombosis risk, computational hemodynamic simulations are being developed to help assess when an intervention is warranted. Created from subjectspecific data, computational models have the potential to be used to predict growth, dissection, rupture, and thrombus-formation risk based on hemodynamic parameters, including wall shear stress, oscillatory shear index, residence time, and anomalous blood flow patterns. Generally, endothelial damage and flow stagnation within aneurysms can lead to coagulation, inflammation, and the release of proteases, which alter extracellular matrix composition, increasing risk of rupture. In this review, we highlight recent work that investigates aneurysm geometry, model parameter assumptions, and other specific considerations that influence computational aneurysm simulations. By highlighting modeling validation and verification approaches, we hope to inspire future computational efforts aimed at improving our understanding of aneurysm pathology and treatment risk stratification.

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“…Therefore, the source term represents the time that is being integrated in an Eulerian framework [21]. The last cycle ERT accumulation was calculated similar to the SC model.…”

Section: Thrombogenic Risk Estimationmentioning

confidence: 99%

Numerical models for assessing the risk of leaflet thrombosis post-transcatheter aortic valve-in-valve implantation

Mayo

Yaakobovich

Finkelstein³

et al. 2020

R. Soc. open sci.

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Leaflet thrombosis has been suggested as the reason for the reduced leaflet motion in cases of hypoattenuated leaflet thickening of bioprosthetic aortic valves. This work aimed to estimate the risk of leaflet thrombosis in two post-valve-in-valve (ViV) configurations, using five different numerical approaches. Realistic ViV configurations were calculated by modelling the deployments of the latest version of transcatheter aortic valve devices (Medtronic Evolut PRO, Edwards SAPIEN 3) in the surgical Sorin Mitroflow. Computational fluid dynamics simulations of blood flow followed the dry models. Lagrangian and Eulerian measures of near-wall stagnation were implemented by particle and concentration tracking, respectively, to estimate the thrombogenicity and to predict the risk locations. Most of the numerical approaches indicate a higher leaflet thrombosis risk in the Edwards SAPIEN 3 device because of its intra-annular implantation. The Eulerian approaches estimated high-risk locations in agreement with the wall sheer stress (WSS) separation points. On the other hand, the Lagrangian approaches predicted high-risk locations at the proximal regions of the leaflets matching the low WSS magnitude regions of both transcatheter aortic valve implantation models and reported clinical and experimental data. The proposed methods can help optimizing future designs of transcatheter aortic valves with minimal thrombotic risks.

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A critical comparison of different residence time measures in aneurysms

Cited by 39 publications

References 42 publications

Study of Coronary Atherosclerosis Using Blood Residence Time

Study of Coronary Atherosclerosis Using Blood Residence Time

Computational Hemodynamic Modeling of Arterial Aneurysms: A Mini-Review

Numerical models for assessing the risk of leaflet thrombosis post-transcatheter aortic valve-in-valve implantation

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