Analysis of early thrombus dynamics in a humanized mouse laser injury model

Wang, Weiwei; Lindsey, John P.; Chen, Shiguo; Diacovo, Thomas G.; King, Michael R.

doi:10.3233/bir-130648

Cited by 10 publications

(15 citation statements)

References 28 publications

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“…The mechanism of platelet deposition and removal represented in our model by the empirical function S g is shown to be in general agreement with the results of Wang et al [32,33], since simulations demonstrated platelet attachment to the upstream portions of the surface of a clot and detachment from its downstream surface. Wang et al [33] also found that platelets were rolling mostly on the upstream side of the clot surface while tethering/detaching platelets were primarily found on the downstream side, leading to clot continuously changing its shape.…”

Section: Discussion Of Model Limitations and Future Extensions Of The Modelsupporting

confidence: 89%

“…Additionally, the results of [32] suggested that flow disturbances generated by RBCs were capable of enhancing attachment of platelets to the blood clot surface. A similar approach was used in [33] to graphically represent in real time in vivo physiological shear stress environment revealing that clot continuous shape changes were mostly due to its local growth. At the same time, growth or decay dominated in the high shear stress region.…”

Section: Introductionmentioning

confidence: 99%

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Model predictions of deformation, embolization and permeability of partially obstructive blood clots under variable shear flow

Kim

et al. 2017

J. R. Soc. Interface.

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Thromboembolism, one of the leading causes of morbidity and mortality worldwide, is characterized by formation of obstructive intravascular clots (thrombi) and their mechanical breakage (embolization). A novel two-dimensional multi-phase computational model is introduced that describes active interactions between the main components of the clot, including platelets and fibrin, to study the impact of various physiologically relevant blood shear flow conditions on deformation and embolization of a partially obstructive clot with variable permeability. Simulations provide new insights into mechanisms underlying clot stability and embolization that cannot be studied experimentally at this time. In particular, model simulations, calibrated using experimental intravital imaging of an established arteriolar clot, show that flow-induced changes in size, shape and internal structure of the clot are largely determined by two shear-dependent mechanisms: reversible attachment of platelets to the exterior of the clot and removal of large clot pieces. Model simulations predict that blood clots with higher permeability are more prone to embolization with enhanced disintegration under increasing shear rate. In contrast, less permeable clots are more resistant to rupture due to shear rate-dependent clot stiffening originating from enhanced platelet adhesion and aggregation. These results can be used in future to predict risk of thromboembolism based on the data about composition, permeability and deformability of a clot under specific local haemodynamic conditions.

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Section: Discussion Of Model Limitations and Future Extensions Of The Modelsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Model predictions of deformation, embolization and permeability of partially obstructive blood clots under variable shear flow

Kim

et al. 2017

J. R. Soc. Interface.

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show abstract

“…These studies demonstrated that the deformation of a thrombus and its propensity to generate emboli depend strongly on thrombus mechanical properties and the hemodynamics. Whereas, there is a lack of quantitative information for thrombus deformation and embolization from in vivo studies [31], computational modeling can complement experimental studies by simulating thrombus formation while including sub-processes such as platelet aggregation and coagulation kinetics [32][33][34][35], as well as thrombus biomechanics in flow [31,[36][37][38]; see also reviews [39][40][41][42]. There are, however, few studies dedicated to quantifying the integrated process of thrombus initiation and development as well as its deformation and possible embolization under different hemodynamic conditions due to two primary computational challenges: first, thrombus formation is a slow biological process, with the time scale of platelet aggregation on the order of seconds while that of clot remodeling is on the order of days to weeks; second, a constitutive equation describing poro-viscoelastic properties of blood clots with different fibrin concentrations is lacking.…”

Section: Introductionmentioning

confidence: 99%

A three-dimensional phase-field model for multiscale modeling of thrombus biomechanics in blood vessels

Zheng

Yazdani

et al. 2020

PLoS Comput Biol

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Mechanical interactions between flowing and coagulated blood (thrombus) are crucial in dictating the deformation and remodeling of a thrombus after its formation in hemostasis. We propose a fully-Eulerian, three-dimensional, phase-field model of thrombus that is calibrated with existing in vitro experimental data. This phase-field model considers spatial variations in permeability and material properties within a single unified mathematical framework derived from an energy perspective, thereby allowing us to study effects of thrombus microstructure and properties on its deformation and possible release of emboli under different hemodynamic conditions. Moreover, we combine this proposed thrombus model with a particle-based model which simulates the initiation of the thrombus. The volume fraction of a thrombus obtained from the particle simulation is mapped to an input variable in the proposed phase-field thrombus model. The present work is thus the first computational study to integrate the initiation of a thrombus through platelet aggregation with its subsequent viscoelastic responses to various shear flows. This framework can be informed by clinical data and potentially be used to predict the risk of diverse thromboembolic events under physiological and pathological conditions.

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“…and local concentration of activated platelets and pro-thrombotic factors 5 6 . Despite the development of several theoretical models that describe the many contributors to thrombus formation and growth 7 , with special emphasis on the platelet aggregation process 3 8 9 10 11 12 as well as the spatial and temporal aspects of early stage thrombus dynamics 13 , the role of each of the aforementioned variables on thrombus formation is still not clear thus hindering the development of comprehensive and computationally fast multiscale models 14 15 16 .…”

mentioning

confidence: 99%

“…To cover this gap, we analyze the ability of different computational approaches to predict platelet deposition values for a large variety of empirical conditions. Note that as a first step, we focus on total platelet deposition counts and do not take into account the spatial dimension of thrombus formation 13 . Specifically, we consider the following approaches: a) a mechanistic modeling approach, b) a machine learning approach; and c) a phenomenological approach.…”

mentioning

confidence: 99%

A comprehensive study on different modelling approaches to predict platelet deposition rates in a perfusion chamber

Pallarès

Senan

Guimerà

et al. 2015

Sci Rep

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Thrombus formation is a multiscale phenomenon triggered by platelet deposition over a protrombotic surface (eg. a ruptured atherosclerotic plaque). Despite the medical urgency for computational tools that aid in the early diagnosis of thrombotic events, the integration of computational models of thrombus formation at different scales requires a comprehensive understanding of the role and limitation of each modelling approach. We propose three different modelling approaches to predict platelet deposition. Specifically, we consider measurements of platelet deposition under blood flow conditions in a perfusion chamber for different time periods (3, 5, 10, 20 and 30 minutes) at shear rates of 212 s−1, 1390 s−1 and 1690 s−1. Our modelling approaches are: i) a model based on the mass-transfer boundary layer theory; ii) a machine-learning approach; and iii) a phenomenological model. The results indicate that the three approaches on average have median errors of 21%, 20.7% and 14.2%, respectively. Our study demonstrates the feasibility of using an empirical data set as a proxy for a real-patient scenario in which practitioners have accumulated data on a given number of patients and want to obtain a diagnosis for a new patient about whom they only have the current observation of a certain number of variables.

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Analysis of early thrombus dynamics in a humanized mouse laser injury model

Cited by 10 publications

References 28 publications

Model predictions of deformation, embolization and permeability of partially obstructive blood clots under variable shear flow

Model predictions of deformation, embolization and permeability of partially obstructive blood clots under variable shear flow

A three-dimensional phase-field model for multiscale modeling of thrombus biomechanics in blood vessels

A comprehensive study on different modelling approaches to predict platelet deposition rates in a perfusion chamber

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