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The presence of collaterals and high thrombus permeability are associated with good functional outcomes after an acute ischaemic stroke. We aim to understand the combined effect of the collaterals and thrombus permeability on cerebral blood flow during an acute ischaemic stroke. A cerebral blood flow model including the leptomeningeal collateral circulation is used to simulate cerebral blood flow during an acute ischaemic stroke. The collateral circulation is varied to capture the collateral scores: absent, poor, moderate and good. Measurements of the transit time, void fraction and thrombus length in acute ischaemic stroke patients are used to estimate thrombus permeability. Estimated thrombus permeability ranges between 10 −7 and 10 −4 mm 2 . Measured flow rates through the thrombus are small and the effect of a permeable thrombus on brain perfusion during stroke is small compared with the effect of collaterals. Our simulations suggest that the collaterals are a dominant factor in the resulting infarct volume after a stroke.

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.

There is a discrepancy between successful recanalization and good clinical outcome after endovascular treatment (EVT) in acute ischemic stroke patients. During removal of a thrombus, a shower of microemboli may release and lodge to the distal circulation. The objective of this study was to determine the extent of damage on brain tissue caused by microemboli. In a rat model of microembolization, a mixture of microsphere (MS) sizes (15, 25 and 50 µm diameter) was injected via the left internal carotid artery. A 3D image of the left hemisphere was reconstructed and a point-pattern spatial analysis was applied based on G- and K-functions to unravel the spatial correlation between MS and the induced hypoxia or infarction. We show a spatial correlation between MS and hypoxia or infarction spreading up to a distance of 1000–1500 µm. These results imply that microemboli, which individually may not always be harmful, can interact and result in local areas of hypoxia or even infarction when lodged in large numbers.

An in silico trial simulates a disease and its corresponding therapies on a cohort of virtual patients to support the development and evaluation of medical devices, drugs, and treatment. In silico trials have the potential to refine, reduce cost, and partially replace current in vivo studies, namely clinical trials and animal testing. We present the design and implementation of an in silico trial for treatment of acute ischemic stroke. We propose an event-based modelling approach for the simulation of a disease and injury, where changes to the state of the system (the events) are assumed to be instantaneous. Using this approach we are able to combine a diverse set of models, spanning multiple time scales, to model acute ischemic stroke, treatment, and resulting brain tissue injury. The in silico trial is designed to be modular to aid development and reproducibility. It provides a comprehensive framework for application to any potential in silico trial. A statistical population model is used to generate cohorts of virtual patients. Patient functional outcomes are also predicted with a statistical model, using treatment and injury results and the patient's clinical parameters. We demonstrate the functionality of the event-based modelling approach and trial framework by running proof of concept in silico trials. The proof of concept trials simulate the same cohort of patients twice: once with successful treatment (successful recanalisation) and once with unsuccessful treatment (unsuccessful treatment). Ways to overcome some of the challenges and difficulties in setting up such an in silico trial are discussed, such as validation and computational limitations.

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.

Thrombectomy, the mechanical removal of a clot, is the most common way to treat ischaemic stroke with large vessel occlusions. However, perfusion cannot always be restored after such an intervention. It has been hypothesised that the absence of reperfusion is due to the clot fragments that block the downstream vessels. In this paper, we present a new way of quantifying the effects of cerebral microthrombi on oxygen transport to tissue in terms of hypoxia and ischaemia. The oxygen transport was simulated with the Green’s function method on physiologically accurate microvascular cubes, which was found independent of both microvascular geometry and length scale. The microthrombi occlusions were then simulated in the microvasculature, which were extravasated over time with a new vessel extravasation model. The tissue hypoxic fraction was fitted as a sigmoidal function of vessel blockage fraction, which was then taken to be a function of time after the formation of microthrombi occlusions. A novel hypoxia-based 3-state cell death model was finally proposed to simulate the hypoxic tissue damage over time. Using the cell death model, the impact of a certain degree of microthrombi occlusions on tissue viability and microinfarct volume can be predicted over time. Quantifying the impact of microthrombi on oxygen transport and tissue death will play an important role in full brain models of ischaemic stroke and thrombectomy.

Understanding how to decrease the friction drag exerted by a fluid on a solid surface is becoming increasingly important to address key societal challenges, such as decreasing the carbon footprint of transport. Well-established techniques are not yet available for friction drag reduction. Direct numerical simulation results obtained by Jozsa et al. (2019) previously indicated that a passive compliant wall can decrease friction drag by sustaining the drag reduction mechanism of an active control strategy. The proposed compliant wall is driven by wall shear stress fluctuations and responds with streamwise wall velocity fluctuations. The present study aims to clarify the underlying physical mechanism enabling the drag reduction of these active and passive control techniques. Analysis of turbulence statistics and flow fields reveals that both compliant wall and active control amplify streamwise velocity streaks in the viscous sublayer. By doing so, these control methods counteract dominant spanwise vorticity fluctuations in the near-wall region. The lowered vorticity fluctuations lead to an overall weakening of vortical structures which then mitigates momentum transfer and results in lower friction drag. These results might underpin the further development and practical implementation of these control strategies.

The Unified Parallel C (UPC) language from the Partitioned Global Address Space (PGAS) family unifies the advantages of shared and local memory spaces and offers a relatively straightforward code parallelisation with the Central Processing Unit (CPU). In contrast, the Computer Unified Device Architecture (CUDA) development kit gives a tool to make use of the Graphics Processing Unit (GPU). We provide a detailed comparison between these novel techniques through the parallelisation of a two-dimensional lattice Boltzmann method based fluid flow solver. Our comparison between the CUDA and UPC parallelisation takes into account the required conceptual effort, the performance gain, and the limitations of the approaches from the application oriented developers’ point of view. We demonstrated that UPC led to competitive efficiency with the local memory implementation. However, the performance of the shared memory code fell behind our expectations, and we concluded that the investigated UPC compilers could not efficiently treat the shared memory space. The CUDA implementation proved to be more complex compared to the UPC approach mainly because of the complicated memory structure of the graphics card which also makes GPUs suitable for the parallelisation of the lattice Boltzmann method.

Emerging flow control strategies have been proposed to tackle long-lasting problems, for instance, precise mixing of chemicals and turbulent drag reduction. Employing actuators imposing in-plane wall oscillations are particularly popular. This paper investigates incompressible laminar rectangular channel and circular pipe flows driven by uniform and traveling wave in-plane wall oscillations. A comprehensive set of exact analytical solutions are presented describing parallel and concentric flows. Dimensionless groups are identified, and it is described how they characterize the one- and two-dimensional time-dependent velocity and pressure fields. The solutions enable to compute the oscillating boundary layer thickness. It is demonstrated that the dimensionless groups and the boundary layer thickness narrows the region of interest within the parameter space. In particular, the oscillating boundary layer thickness obtained from these laminar flows estimates a “radius of action” within which flow features can be altered to boost mixing or reduce turbulent friction drag. The results are suitable for software validation and verification, may open the way to promising complex wall oscillations, and ease the optimization task that delays the industrial application of flow controls.

Compliant walls offer the tantalising possibility of passive flow control. This paper examines the mechanics of compliant surfaces driven by wall shear stresses, with solely in-plane velocity response. We present direct numerical simulations of turbulent channel flows at low ($Re_{\unicode[STIX]{x1D70F}}\approx 180$) and intermediate ($Re_{\unicode[STIX]{x1D70F}}\approx 1000$) Reynolds numbers. In-plane spanwise and streamwise active controls proposed by Choiet al. (J. Fluid Mech., vol. 262, 1994, pp. 75–110) are revisited in order to characterise beneficial wall fluctuations. An analytical framework is then used to map the parameter space of the proposed compliant surfaces. The direct numerical simulations show that large-scale passive streamwise wall fluctuations can reduce friction drag by at least$3.7\pm 1\,\%$, whereas even small-scale passive spanwise wall motions lead to considerable drag penalty. It is found that a well-designed compliant wall can theoretically exploit the drag-reduction mechanism of an active control; this may help advance the development of practical active and passive control strategies for turbulent friction drag reduction.

Boundary conditions for abdominal aortic aneurysm simulations are problematic both on the fluid and the solid side. In this paper improvements are suggested on existing methodology in both respects. First, a derivation of a hyperelastic wall model is given, taking into account the wall stresses at the diastolic instant. It is demonstrated that this model can be approximated with a simplified linear wall model in the physiologically interesting range. Then a new method for inlet and outlet boundary condition generation is introduced on the fluid side, based on a one-dimensional transient simulator. Finally, the effect of spine support on the intra-aneurysmal flow is studied. Good agreement was found between rigid wall flow simulations on the “systolic” geometry and the fluid–structure interaction simulations. Other authors found much larger differences because earlier the “diastolic” geometry had been used for comparisons and the stresses in the diastolic state were neglected. It was concluded that the spine support does not have a great impact on the flow field. Significant differences were found between the flow behaviour of artificially generated and real aneurysm geometries.

A novel model of the leptomeningeal collateral circulation is created by combining data from multiple sources with statistical scaling laws. The extent of the collateral circulation is varied by defining a collateral vessel probability. Blood flow and pressure are simulated using a one-dimensional steady state blood flow model. The leptomeningeal collateral vessels provide significant flow during a stroke. The pressure drop over an occlusion predicted by the model ranges between 60 and 85 mmHg depending on the extent of the collateral circulation. The linear transport of contrast material was simulated in the circulatory network. The time delay of peak contrast over an occlusion is 3.3 s in the model, and 2.1 s (IQR 0.8–4.0 s) when measured in dynamic CTA data of acute ischaemic stroke patients. Modelling the leptomeningeal collateral circulation could lead to better estimates of infarct volume and patient outcome.

Author summary After an ischaemic stroke—one where a clot blocks a major artery in the brain—patients can undergo a procedure where the clot is removed mechanically via a catheter—a thrombectomy. This reopens the blocked vessel, yet some patients don’t achieve blood flow returning to their tissue downstream. One hypothesis for this phenomenon is that the clot fragments into smaller clots (called micro-emboli) which block smaller vessels downstream. However, this can’t be measured in patients due to the inability of clinical imaging resolving the micro-scale. We therefore develop a computational model here, based on experimental thrombectomy data, to quantify the impact of micro-emboli on blood flow in the brain after the removal of a clot. With this model, we found that micro-emboli are a likely contributor to the no-reflow phenomenon after a thrombectomy. Individual blood vessel geometries, clot composition, and thrombectomy technique all impacted the effect of micro-emboli on blood flow and should be taken into consideration to minimise the impact of micro-emboli in the brain. Furthermore, the computational model developed here allows us to now build large-scale models of blood flow in the brain, and hence simulate stroke and the impact of micro-emboli on the entire brain., Many ischaemic stroke patients who have a mechanical removal of their clot (thrombectomy) do not get reperfusion of tissue despite the thrombus being removed. One hypothesis for this ‘no-reperfusion’ phenomenon is micro-emboli fragmenting off the large clot during thrombectomy and occluding smaller blood vessels downstream of the clot location. This is impossible to observe in-vivo and so we here develop an in-silico model based on in-vitro experiments to model the effect of micro-emboli on brain tissue. Through in-vitro experiments we obtain, under a variety of clot consistencies and thrombectomy techniques, micro-emboli distributions post-thrombectomy. Blood flow through the microcirculation is modelled for statistically accurate voxels of brain microvasculature including penetrating arterioles and capillary beds. A novel micro-emboli algorithm, informed by the experimental data, is used to simulate the impact of micro-emboli successively entering the penetrating arterioles and the capillary bed. Scaled-up blood flow parameters–permeability and coupling coefficients–are calculated under various conditions. We find that capillary beds are more susceptible to occlusions than the penetrating arterioles with a 4x greater drop in permeability per volume of vessel occluded. Individual microvascular geometries determine robustness to micro-emboli. Hard clot fragmentation leads to larger micro-emboli and larger drops in blood flow for a given number of micro-emboli. Thrombectomy technique has a large impact on clot fragmentation and hence occlusions in the microvasculature. As such, in-silico modelling of mechanical thrombectomy predicts that clot specific factors, interventional technique, and microvascular geometry strongly influence reperfusion of the brain. Micro-emboli are likely contributory to the phenomenon of no-reperfusion following successful removal of a major clot.