Patient-Specific Modelling of Blood Coagulation

Ratto, Nicolas; Bouchnita, Anass; Chelle, Pierre; Marion, Martine; Panteleev, Mikhail A.; Nechipurenko, Dmitry; Tardy‐Poncet, Brigitte; Volpert, Vitaly

doi:10.1007/s11538-021-00890-8

Cited by 13 publications

(20 citation statements)

References 49 publications

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“…Development of novel OAC's can be challenging and expensive, however, modelling tools 10.3389/fcvm.2022.1074562 are often employed in the early stages of pharmacological studies using RDC equations (75). Studies have investigated the patientspecific effects of warfarin and heparin on coagulation mechanisms, providing the scope for these tools to be extended to the most recent range of OACs, and development of new drugs for AF patients (93). The choice of whether to cardiovert is based on detection of an LAA thrombus, which can possibly be predicted using the modelling techniques outlined in this Review and ultimately identified by means of routinely available imaging techniques such as TEE.…”

Section: In-silico Stroke Preventionmentioning

confidence: 99%

Imaging and biophysical modelling of thrombogenic mechanisms in atrial fibrillation and stroke

Qureshi

Lip

Nordsletten

et al. 2023

Front. Cardiovasc. Med.

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Atrial fibrillation (AF) underlies almost one third of all ischaemic strokes, with the left atrial appendage (LAA) identified as the primary thromboembolic source. Current stroke risk stratification approaches, such as the CHA2DS2-VASc score, rely mostly on clinical comorbidities, rather than thrombogenic mechanisms such as blood stasis, hypercoagulability and endothelial dysfunction—known as Virchow’s triad. While detection of AF-related thrombi is possible using established cardiac imaging techniques, such as transoesophageal echocardiography, there is a growing need to reliably assess AF-patient thrombogenicity prior to thrombus formation. Over the past decade, cardiac imaging and image-based biophysical modelling have emerged as powerful tools for reproducing the mechanisms of thrombogenesis. Clinical imaging modalities such as cardiac computed tomography, magnetic resonance and echocardiographic techniques can measure blood flow velocities and identify LA fibrosis (an indicator of endothelial dysfunction), but imaging remains limited in its ability to assess blood coagulation dynamics. In-silico cardiac modelling tools—such as computational fluid dynamics for blood flow, reaction-diffusion-convection equations to mimic the coagulation cascade, and surrogate flow metrics associated with endothelial damage—have grown in prevalence and advanced mechanistic understanding of thrombogenesis. However, neither technique alone can fully elucidate thrombogenicity in AF. In future, combining cardiac imaging with in-silico modelling and integrating machine learning approaches for rapid results directly from imaging data will require development under a rigorous framework of verification and clinical validation, but may pave the way towards enhanced personalised stroke risk stratification in the growing population of AF patients. This Review will focus on the significant progress in these fields.

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Section: In-silico Stroke Preventionmentioning

confidence: 99%

Imaging and biophysical modelling of thrombogenic mechanisms in atrial fibrillation and stroke

Qureshi

Lip

Nordsletten

et al. 2023

Front. Cardiovasc. Med.

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“…Clot growth, that is, the spatial progression of the region filled by fibrin polymer gel, corresponds to the propagation of a reaction-diffusion wave [16]. A simplified model of blood coagulation consisting of three equations for the concentrations of prothrombin, thrombin and activated factor X was developed in [17] with patient-specific parameters. These results are used in the present work to determine the parameters of the one-equation model for the timedependent thrombin concentration T:…”

Section: The Model Of Clot Growthmentioning

confidence: 99%

“…and the values of parameters adjusted to [17] corresponding to the normal level of blood coagulation (Table 1). Calculations of the one-equation model with these parameters without blood flow gives the wave speed of thrombin propagation 0.54 micron/sec corresponding to the physiological range.…”

Section: The Model Of Clot Growthmentioning

confidence: 99%

“…Values of parameters in Equations ( 1)-( 2) for the normal blood coagulation estimated from [17]. The speed of thrombin concentration wave propagation for these parameters is 0.54 micron/s, which corresponds to the evaluative value for the normal blood coagulation [17]. The speed is calculated under the assumption of the absence of blood flow (u = 0).…”

Section: The Model Of Clot Growthmentioning

confidence: 99%

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Blood Clotting Decreases Pulmonary Circulation during the Coronavirus Disease

2021

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Spontaneous blood clotting in pulmonary circulation caused by thrombo-inflammation is one of the main mortality causes during the COVID-19 disease. Blood clotting leads to reduced pulmonary circulation and blood oxygenation. Lung inflammation can be evaluated with noninvasive diagnostic techniques. However, the correlation of the severity of the inflammation with the pulmonary blood flow has not been established. To address this question, in this work, we develop a multiscale model taking into account the interaction of a local model of thrombus growth with 1D hemodynamics in a vessel network. Flux reduction depending on the level of lung obstruction is evaluated. In particular, the model obtains that an obstruction level of 5% leads to a 12% reduction of blood flux. The suggested approach can be used to investigate the interaction of blood clotting and flow not only in the pulmonary network but also in other complex vessel networks.

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“…As pointed out by Chelle et al [14], most of the existing computational models fail to reproduce the thrombin formation dynamics in clinical settings without prior parameter optimization. To avoid this issue, some authors have suggested that instead of trying to find a universal set of reactions, reduced coagulation models are enough to reproduce the coagulation dynamics [9,15,16]. Nevertheless, a prior calibration step is still needed.…”

Section: Introductionmentioning

confidence: 99%

Critical evaluation of kinetic schemes for coagulation

Ranc

S²,

Mendez³

et al. 2021

Preprint

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Computational models of the coagulation cascade are used for a wide range of applications in bio-medical engineering such as drug and bio-medical device developments. However, a lack of robustness of numerical models has been highlighted when studying clinically relevant scenarios. In order to develop more robust models, numerical simulations need to be confronted with realistic situations relevant to clinical practice. In this work, two well-established numerical representations of the coagulation cascade initiated by the intrinsic and extrinsic systems, respectively, were compared with thrombin generation assays considering realistic pathological conditions. Proper modifications were needed to align the in vitro and in silico data, namely; adapting initial conditions to the thrombin assay system, omitting reactions irrelevant to our case study, and improving the fitting of some reaction rates. The modified models were able to capture the experimental trends of thrombin generation for a range of concentrations of factors XII, XI, and VIII for cases in which the coagulation cascade is triggered through the extrinsic and intrinsic systems. Our work emphasizes that when existing coagulation cascade models are extrapolated to experimental settings for which they were not calibrated, careful adjustments must be made. We show that the two coagulation models used in this work can predict physiological conditions, but when studying pathological conditions, proper modifications are needed to improve the numerical results.

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Patient-Specific Modelling of Blood Coagulation

Cited by 13 publications

References 49 publications

Imaging and biophysical modelling of thrombogenic mechanisms in atrial fibrillation and stroke

Imaging and biophysical modelling of thrombogenic mechanisms in atrial fibrillation and stroke

Blood Clotting Decreases Pulmonary Circulation during the Coronavirus Disease

Critical evaluation of kinetic schemes for coagulation

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