Simulation of the human intracranial arterial tree

Grinberg, Leopold; Anor, Tomer; Cheever, Elizabeth; Madsen, Joseph R.; Karniadakis, George Em

doi:10.1098/rsta.2008.0307

Cited by 48 publications

(41 citation statements)

References 35 publications

(45 reference statements)

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“…The 3D high-resolution simulations provide fundamental insight into the dynamics of the global and local flow patterns, 13,14,18,21 quantify levels of Wall Shear Stress (WSS), and can also be used for simulation of advection-diffusion of injected drugs instead of using dye angiograms. The 1D model allows to simulate large-scale features, such as pressure drop and flowrates at multiple segments of large arterial networks.…”

Section: Introductionmentioning

confidence: 99%

Modeling Blood Flow Circulation in Intracranial Arterial Networks: A Comparative 3D/1D Simulation Study

et al. 2010

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We compare results from numerical simulations of pulsatile blood flow in two patient-specific intracranial arterial networks using one-dimensional (1D) and three-dimensional (3D) models. Specifically, we focus on the pressure and flowrate distribution at different segments of the network computed by the two models. Results obtained with 1D and 3D models with rigid walls show good agreement in massflow distribution at tens of arterial junctions and also in pressure drop along the arteries. The 3D simulations with the rigid walls predict higher amplitude of the flowrate and pressure temporal oscillations than the 1D simulations with compliant walls at various segments even for small time-variations in the arterial cross-sectional areas. Sensitivity of the flow and pressure with respect to variation in the elasticity parameters is investigated with the 1D model.

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Section: Introductionmentioning

confidence: 99%

Modeling Blood Flow Circulation in Intracranial Arterial Networks: A Comparative 3D/1D Simulation Study

et al. 2010

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“…On the one hand, we can simulate in 3D large portions of the cardiovascular system of a real patient properly including simplified models for the peripheral sites (see e.g. [73,72,33,23,65]). On the other hand, thanks to new instruments, images and measures nowadays provide doctors and bioengineers with a huge amount of data.…”

Section: Introductionmentioning

confidence: 99%

Applications of variational data assimilation in computational hemodynamics

D’Elia

Mirabella

Passerini

et al. 2012

MS&A

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The development of new technologies for acquiring measures and images in order to investigate cardiovascular diseases raises new challenges in scientific computing. These data can be in fact merged with the numerical simulations for improving the accuracy and reliability of the computational tools. Assimilation of measured data and numerical models is well established in meteorology, whilst it is relatively new in computational hemodynamics. Different approaches are possible for the mathematical setting of this problem. Among them, we follow here a variational formulation, based on the minimization of the mismatch between data and numerical results by acting on a suitable set of control variables. Several modeling and methodological problems related to this strategy are open, such as the analysis of the impact of the noise affecting the data, and the design of effective numerical solvers. In this chapter we present three examples where a mathematically sound (variational) assimilation of data can significantly improve the reliability of the numerical models. Accuracy and reliability of computational models are increasingly important features in view of the progressive adoption of numerical tools in the design of new therapies and, more in general, in the decision making process of medical doctors.

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“…The range illustrated in this issue goes from ion channel and transporter function (Fink & Noble 2009;Koivumäki et al 2009) and their interactions with the extracellular environment (Severi et al 2009), to integration of behaviour at the level of cells (Stewart et al 2009), tissues (Grinberg et al 2009;Moss et al 2009) and organs (Darquenne et al 2009;Lee et al 2009;Plotkowiak et al 2009), to models that take into account individual histo-anatomical features (MacLeod et al 2009;Plank et al 2009) and assess high-level complex functional activity, from fly brain activity (Armstrong & van Hemert 2009) to human speech generation (Eickhoff et al 2009). …”

Section: Introductionmentioning

confidence: 99%

“…These applications cover diverse organ systems, from kidney function Moss et al 2009) to cardiac structure (MacLeod et al 2009;Plank et al 2009), electrophysiology (Fink & Noble 2009;Koivumäki et al 2009;Severi et al 2009;Stewart et al 2009) and mechanics (Lee et al 2009), and from pulmonary ventilation (Darquenne et al 2009;Plotkowiak et al 2009) to vascular supply (Grinberg et al 2009) of the brain, and its structure and function (Armstrong & van Hemert 2009;Eickhoff et al 2009). …”

Section: Introductionmentioning

confidence: 99%