Coupling one-dimensional arterial blood flow to three-dimensional tissue perfusion models for
            <i>in silico</i>
            trials of acute ischaemic stroke

Padmos, Raymond M.; Józsa, Tamás; El-Bouri, Wahbi K.; Konduri, Praneeta; Payne, Stephen J.; Hoekstra, Alfons G.

doi:10.1098/rsfs.2019.0125

Cited by 44 publications

(50 citation statements)

References 47 publications

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“…We hypothesise that in healthy cases, leptomeningeal collaterals [2,50,[65][66][67][68] as well as pial arterioles [69][70][71] act to equalise blood pressure in descending arterioles near the cortical surface. This hypothesis could be tested once the present perfusion model and the 1D model incorporating the larger arteries [13] are coupled, and it is supported by pressure data obtained in rodents which suggest small pressure drop in large arteries compared to the microcirculation [72][73][74].…”

Section: Boundary Conditionsmentioning

confidence: 61%

“…The output of the FE model is the spatial distribution of brain tissue perfusion, which can be measured, for example, by ASL perfusion MRI in clinical settings [47]. The porous FE model provides (i) pressure and volumetric blood flow rate inputs for haemodynamic simulations in large arteries [13] which evaluate forces on the thrombus; and (ii) perfusion input for tissue health computation used for infarct volume estimation [52]. Therefore, the output of the FE model is linked indirectly to a statistical module estimating the functional outcome of individual virtual patients based on the computed infarct volume, and other features, such as age.…”

Section: Reflection On the Asme Vandv40 Frameworkmentioning

confidence: 99%

“…Estimating brain perfusion in both healthy and occluded scenarios is an important element of the INSIST pipeline and serves as a bridge between localised treatment effects and patient outcome [8]. To this end, a multi-scale haemodynamic model is under development which combines a one-dimensional (1D) network model of large arteries [12,13] and a threedimensional (3D) porous perfusion model [14] to simulate blood flow in the entire vasculature. The models will be coupled strongly through the cortical surface.…”

Section: Introductionmentioning

confidence: 99%

“…The models will be coupled strongly through the cortical surface. The envisaged interface will facilitate communication between the boundary conditions of the models, namely pressure and volumetric flow rate values averaged over cortical territories [13]. Previously somewhat similar weak-coupling schemes have been established between a lumped parameter model and a porous continuum model to cover arteriole boundary conditions at the brain surface [15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

On the sensitivity analysis of porous finite element models for cerebral perfusion estimation

Jozsa

Padmos

El-Bouri

et al. 2021

Preprint

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Computational physiological models are promising tools to enhance the design of clinical trials and to assist in decision making. Organ-scale haemodynamic models are gaining popularity to evaluate perfusion in a virtual environment both in healthy and diseased patients. Recently, the principles of verification, validation, and uncertainty quantification of such physiological models have been laid down to ensure safe applications of engineering software in the medical device industry. The present study sets out to establish guidelines for the usage of a three-dimensional steady state porous cerebral perfusion model of the human brain following principles detailed in the verification and validation (V&V 40) standard of the American Society of Mechanical Engineers. The model relies on the finite element method and has been developed specifically to estimate how brain perfusion is altered in ischaemic stroke patients before, during, and after treatments. Simulations are compared with exact analytical solutions and a thorough sensitivity analysis is presented covering every numerical and physiological model parameter. The results suggest that such porous models can approximate blood pressure and perfusion distributions reliably even on a coarse grid with first order elements. On the other hand, higher order elements are essential to mitigate errors in volumetric blood flow rate estimation through cortical surface regions. Matching the volumetric flow rate corresponding to major cerebral arteries is identified as a validation milestone. It is found that inlet velocity boundary conditions are hard to obtain and that constant pressure inlet boundary conditions are feasible alternatives. A one-dimensional model is presented which can serve as a computationally inexpensive replacement of the three-dimensional brain model to ease parameter optimisation, sensitivity analyses and uncertainty quantification. The findings of the present study can be generalised to organ-scale porous perfusion models. The results increase the applicability of computational tools regarding treatment development for stroke and other cerebrovascular conditions.

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Section: Boundary Conditionsmentioning

confidence: 61%

Section: Reflection On the Asme Vandv40 Frameworkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

On the sensitivity analysis of porous finite element models for cerebral perfusion estimation

Jozsa

Padmos

El-Bouri

et al. 2021

Preprint

Self Cite

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show abstract

“…This study contributes to INSIST and the VPH by developing a cerebral microcirculation model for the entire human brain, which is capable of predicting perfusion before and after an ischaemic stroke. This model will be coupled to a one-dimensional blood flow simulator governing blood flow in arteries supplying blood to the pial surface [15,16]. The role of the resulting organ-scale cerebral blood flow model in the in silico clinical trial will be to evaluate the impact of stroke treatment (thrombectomy or thrombolysis) on tissue perfusion.…”

Section: Introductionmentioning

confidence: 99%

A porous circulation model of the human brain for in silico clinical trials in ischaemic stroke

et al. 2020

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The advancement of ischaemic stroke treatment relies on resource-intensive experiments and clinical trials. In order to improve ischaemic stroke treatments, such as thrombolysis and thrombectomy, we target the development of computational tools for in silico trials which can partially replace these animal and human experiments with fast simulations. This study proposes a model that will serve as part of a predictive unit within an in silico clinical trial estimating patient outcome as a function of treatment. In particular, the present work aims at the development and evaluation of an organ-scale microcirculation model of the human brain for perfusion prediction. The model relies on a three-compartment porous continuum approach. Firstly, a fast and robust method is established to compute the anisotropic permeability tensors representing arterioles and venules. Secondly, vessel encoded arterial spin labelling magnetic resonance imaging and clustering are employed to create an anatomically accurate mapping between the microcirculation and large arteries by identifying superficial perfusion territories. Thirdly, the parameter space of the problem is reduced by analysing the governing equations and experimental data. Fourthly, a parameter optimization is conducted. Finally, simulations are performed with the tuned model to obtain perfusion maps corresponding to an open and an occluded (ischaemic stroke) scenario. The perfusion map in the occluded vessel scenario shows promising qualitative agreement with computed tomography images of a patient with ischaemic stroke caused by large vessel occlusion. The results highlight that in the case of vessel occlusion (i) identifying perfusion territories is essential to capture the location and extent of underperfused regions and (ii) anisotropic permeability tensors are required to give quantitatively realistic estimation of perfusion change. In the future, the model will be thoroughly validated against experiments.

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A 1D–0D–3D coupled model for simulating blood flow and transport processes in breast tissue

Fritz

Köppl

Oden

et al. 2022

Numer Methods Biomed Eng

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In this work, we present mixed dimensional models for simulating blood flow and transport processes in breast tissue and the vascular tree supplying it. These processes are considered, to start from the aortic inlet to the capillaries and tissue of the breast. Large variations in biophysical properties and flow conditions exist in this system necessitating the use of different flow models for different geometries and flow regimes. In total, we consider four different model types. First, a system of 1D nonlinear hyperbolic partial differential equations (PDEs) is considered to simulate blood flow in larger arteries with highly elastic vessel walls. Second, we assign 1D linearized hyperbolic PDEs to model the smaller arteries with stiffer vessel walls. The third model type consists of ODE systems (0D models). It is used to model the arterioles and peripheral circulation. Finally, homogenized 3D porous media models are considered to simulate flow and transport in capillaries and tissue within the breast volume. Sink terms are used to account for the influence of the venous and lymphatic systems. Combining the four model types, we obtain two different 1D-0D-3D coupled models for simulating blood flow and transport processes: The first model results in a fully coupled 1D-0D-3D model covering the complete path from the aorta to the breast combining a generic arterial network with a patient specific breast network and geometry. The second model is a reduced one based on the separation of the generic and patient specific parts. The information from a calibrated fully coupled model is used as inflow condition for the patient specific sub-model allowing a significant computational cost reduction. Several numerical experiments are conducted to calibrate the generic model parameters and to demonstrate realistic flow simulations compared to existing data on blood flow in the human breast and vascular system. Moreover, we use two different breast vasculature and tissue data sets to illustrate the robustness of our reduced sub-model approach.

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Coupling one-dimensional arterial blood flow to three-dimensional tissue perfusion models for in silico trials of acute ischaemic stroke

Cited by 44 publications

References 47 publications

On the sensitivity analysis of porous finite element models for cerebral perfusion estimation

On the sensitivity analysis of porous finite element models for cerebral perfusion estimation

A porous circulation model of the human brain for in silico clinical trials in ischaemic stroke

A 1D–0D–3D coupled model for simulating blood flow and transport processes in breast tissue

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