Literature DB >> 26795978

A Predictive Model of High Shear Thrombus Growth.

Marmar Mehrabadi1, Lauren D C Casa1, Cyrus K Aidun1, David N Ku2.   

Abstract

The ability to predict the timescale of thrombotic occlusion in stenotic vessels may improve patient risk assessment for thrombotic events. In blood contacting devices, thrombosis predictions can lead to improved designs to minimize thrombotic risks. We have developed and validated a model of high shear thrombosis based on empirical correlations between thrombus growth and shear rate. A mathematical model was developed to predict the growth of thrombus based on the hemodynamic shear rate. The model predicts thrombus deposition based on initial geometric and fluid mechanic conditions, which are updated throughout the simulation to reflect the changing lumen dimensions. The model was validated by comparing predictions against actual thrombus growth in six separate in vitro experiments: stenotic glass capillary tubes (diameter = 345 µm) at three shear rates, the PFA-100(®) system, two microfluidic channel dimensions (heights = 300 and 82 µm), and a stenotic aortic graft (diameter = 5.5 mm). Comparison of the predicted occlusion times to experimental results shows excellent agreement. The model is also applied to a clinical angiography image to illustrate the time course of thrombosis in a stenotic carotid artery after plaque cap rupture. Our model can accurately predict thrombotic occlusion time over a wide range of hemodynamic conditions.

Entities:  

Keywords:  Arterial thrombosis; Model; Occlusion; Platelet aggregation

Mesh:

Year:  2016        PMID: 26795978     DOI: 10.1007/s10439-016-1550-5

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  16 in total

1.  The Margination of Particles in Areas of Constricted Blood Flow.

Authors:  Erik J Carboni; Brice H Bognet; David B Cowles; Anson W K Ma
Journal:  Biophys J       Date:  2018-05-08       Impact factor: 4.033

2.  Shear-induced platelet aggregation: 3D-grayscale microfluidics for repeatable and localized occlusive thrombosis.

Authors:  Michael T Griffin; Dongjune Kim; David N Ku
Journal:  Biomicrofluidics       Date:  2019-10-01       Impact factor: 2.800

3.  Mathematical and Computational Modeling of Device-Induced Thrombosis.

Authors:  Keefe B Manning; Franck Nicoud; Susan M Shea
Journal:  Curr Opin Biomed Eng       Date:  2021-09-28

4.  Thrombosis and Hemodynamics: external and intrathrombus gradients.

Authors:  Noelia Grande Gutiérrez; Kaushik N Shankar; Talid Sinno; Scott L Diamond
Journal:  Curr Opin Biomed Eng       Date:  2021-06-26

5.  Platelet α-granules are required for occlusive high-shear-rate thrombosis.

Authors:  Dongjune A Kim; Katrina J Ashworth; Jorge Di Paola; David N Ku
Journal:  Blood Adv       Date:  2020-07-28

6.  Influence of shear rate and surface chemistry on thrombus formation in micro-crevice.

Authors:  Mansur Zhussupbekov; Wei-Tao Wu; Megan A Jamiolkowski; Mehrdad Massoudi; James F Antaki
Journal:  J Biomech       Date:  2021-03-26       Impact factor: 2.789

7.  Blood Flow Velocimetry in a Microchannel During Coagulation Using Particle Image Velocimetry and Wavelet-Based Optical Flow Velocimetry.

Authors:  E Kucukal; Y Man; Umut A Gurkan; B E Schmidt
Journal:  J Biomech Eng       Date:  2021-09-01       Impact factor: 1.899

8.  High fidelity computational simulation of thrombus formation in Thoratec HeartMate II continuous flow ventricular assist device.

Authors:  Wei-Tao Wu; Fang Yang; Jingchun Wu; Nadine Aubry; Mehrdad Massoudi; James F Antaki
Journal:  Sci Rep       Date:  2016-12-01       Impact factor: 4.379

9.  A General Shear-Dependent Model for Thrombus Formation.

Authors:  Alireza Yazdani; He Li; Jay D Humphrey; George Em Karniadakis
Journal:  PLoS Comput Biol       Date:  2017-01-17       Impact factor: 4.475

10.  Multi-Constituent Simulation of Thrombus Deposition.

Authors:  Wei-Tao Wu; Megan A Jamiolkowski; William R Wagner; Nadine Aubry; Mehrdad Massoudi; James F Antaki
Journal:  Sci Rep       Date:  2017-02-20       Impact factor: 4.379

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