Development of a patient-specific cerebral vasculature fluid–structure-interaction model

Moerman, Kevin M.; Konduri, Praneeta; Fereidoonnezhad, Behrooz; Marquering, Henk A.; Lugt, Aad van der; Luraghi, Giulia; Bridio, Sara; Migliavacca, Francesco; Matas, José Félix Rodríguez; McGarry, Patrick

doi:10.1016/j.jbiomech.2021.110896

Cited by 6 publications

(4 citation statements)

References 31 publications

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“…From there, continuous surface geometries can be obtained through the calculation of isosurfaces. A detailed description of this method can be found in [10] and an implementation of it already exists in GIBBON . Based on the graph network’s size and the desired level of precision, calculating the distance function between the network nodes and the image voxel grid can become significantly time-consuming.…”

Section: Methodsmentioning

confidence: 99%

“…They extend further to the biomedical realm from the modelling of flows in blood vessels [9,10,11] and within lung airways [12,13] to understanding tissue perfusion dynamics [14,15,16,17,18,19,20]. The relevance of (embedded) tubular structures also extends to industrial applications, for example the design and optimisation of heat exchangers [21], the efficiency of oil extraction processes at the scale of wells and reservoirs [22,23], and safety considerations in tunnel ventilation systems [24] through to the engineering complexity involved in ensuring the stability and integrity of pipeline-soil systems [25,26].…”

Section: Introductionmentioning

confidence: 99%

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Tube2FEM: a general-purpose highly-automated pipeline for flow related processes in (embedded) tubular objects

Sleimana,

Moerman,

de Oliveira

et al. 2024

Preprint

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This paper presents a comprehensive and highly-automated open-source pipeline for simulating flow and flow-related processes in (embedded) tubular structures. Addressing a critical gap in computational fluid dynamics (CFD) and simulation sciences, it facilitates the transition from raw three-dimensional imaging, graph networks, or CAD models of tubular objects to refined, simulation-ready meshes. This transition, traditionally labor-intensive and challenging, is streamlined and highly-automated through a series of innovative steps that include surface mesh processing, centre-line construction, anisotropic mesh generation, and volumetric meshing, leading to Finite Element Method (FEM) simulations. The pipeline leverages a range of open-source software and libraries, notablyGIBBON,FEniCS, andParaview, to provide flexibility and broad applicability across different simulation scenarios, ranging from biomedical to industrial applications. We demonstrate the versatility of our approach through five distinct applications, including the mesh generation for soil-root systems, lung airways, microcirculation networks, and portal vein networks, each originating from a different data source. Moreover, for several of these cases, we incorporate Computational Fluid Dynamics (CFD) simulations and strategies for 3D-1D coupling between the embedding domain and the embedded structures. Finally, we outline some future perspectives aimed at enhancing accuracy, reducing computational time, and incorporating advanced modeling and boundary condition strategies to further refine the framework’s capabilities.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Tube2FEM: a general-purpose highly-automated pipeline for flow related processes in (embedded) tubular objects

Sleimana,

Moerman,

de Oliveira

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…[ 22 ]) but extensions to model large portions of the cardiovascular system in this way are computationally demanding, particularly for networks composed of multiple generations (e.g. [ 23 ]). A more computationally tractable approach is to cross-sectionally average the three-dimensional governing equations and use a closure condition to derive a spatially one-dimensional representation of the flow.…”

Section: Introductionmentioning

confidence: 99%

Elastic jump propagation across a blood vessel junction

Spelman,

Onah,

MacTaggart

et al. 2024

R. Soc. Open Sci.

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The theory of small-amplitude waves propagating across a blood vessel junction has been well established with linear analysis. In this study, we consider the propagation of large-amplitude, nonlinear waves (i.e. shocks and rarefactions) through a junction from a parent vessel into two (identical) daughter vessels using a combination of three approaches: numerical computations using a Godunov method with patching across the junction, analysis of a nonlinear Riemann problem in the neighbourhood of the junction and an analytical theory which extends the linear analysis to the following order in amplitude. A unified picture emerges: an abrupt (prescribed) increase in pressure at the inlet to the parent vessel generates a propagating shock wave along the parent vessel which interacts with the junction. For modest driving, this shock wave divides into propagating shock waves along the two daughter vessels and reflects a rarefaction wave back towards the inlet. However, for larger driving the reflected rarefaction wave becomes transcritical, generating an additional shock wave. Just beyond criticality this new shock wave has zero speed, pinned to the junction, but for further increases in driving this additional shock divides into two new propagating shock waves in the daughter vessels.

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“…Thrombolysis [2] and thrombectomy [1] revolutionised stroke treatment but up to 66% of patients remain functionally dependent [3,4]. The IN Silico clinical trials for the treatment of acute Ischaemic STroke (INSIST) consortium [5,6] set out to improve existing stroke treatments based on computational models [7][8][9][10][11]. In AIS, perfusion shortage is the primary driver of infarct formation associated with irreversible brain tissue and function loss.…”

Section: Introductionmentioning

confidence: 99%

MRI-based computational model generation for cerebral perfusion simulations in health and ischaemic stroke

Jozsa

Petr

Barkhof

et al. 2022

Preprint

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Cerebral perfusion models were found to be promising research tools to predict the impact of acute ischaemic stroke and related treatments on cerebral blood flow (CBF) linked to patients' functional outcome. To provide insights relevant to clinical trials, perfusion simulations need to become suitable for group-level investigations, but computational studies to date have been limited to a few patient-specific cases. This study set out to overcome issues related to automated parameter inference, that restrict the sample size of perfusion simulations, by integrating neuroimaging data. Seventy-five brain models were generated using measurements from a cohort of 75 healthy elderly individuals to model resting state CBF distributions. Computational perfusion model geometries were adjusted using healthy reference subjects' T1-weighted MRI. Haemodynamic model parameters were determined from CBF measurements corresponding to arterial spin labelling perfusion MRI. Thereafter, perfusion simulations were conducted for 150 acute ischaemic stroke cases by simulating an occlusion and cessation of blood flow in the left and right middle cerebral arteries. The anatomical (geometrical) fitness of the brain models was evaluated by comparing the simulated grey and white matter (GM and WM) volumes to measurements in healthy reference subjects. Statistically significant, strong positive correlations were found in both cases (GM: Pearson's r 0.74, P-value< 0.001; WM: Pearson's r 0.84, P-value< 0.001). Haemodynamic parameter tuning was verified by comparing total volumetric blood flow rate to the brain in reference subjects and simulations resulting in Pearson's r 0.89, and P-value< 0.001. In acute ischaemic stroke cases, the simulated infarct volume using a perfusion-based proxy was 197±25 ml. Computational results showed excellent agreement with anatomical and haemodynamic literature data corresponding to T1-weighted, T2-weighted, and phase-contrast MRI measurements both in healthy scenarios and in acute ischaemic stroke cases. Simulation results represented solely worst-case stroke scenarios with large infarcts because compensatory mechanisms, e.g. collaterals, were neglected. The established computational brain model generation framework provides a foundation for population-level cerebral perfusion simulations and for in silico clinical stroke trials which could assist in medical device and drug development.

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Development of a patient-specific cerebral vasculature fluid–structure-interaction model

Cited by 6 publications

References 31 publications

Tube2FEM: a general-purpose highly-automated pipeline for flow related processes in (embedded) tubular objects

Tube2FEM: a general-purpose highly-automated pipeline for flow related processes in (embedded) tubular objects

Elastic jump propagation across a blood vessel junction

MRI-based computational model generation for cerebral perfusion simulations in health and ischaemic stroke

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