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Register a new userHigh fidelity blood flow in a patient-specific arteriovenous fistula
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An arteriovenous fistula, created by artificially connecting segments of a patients vasculature, is the preferred way to gain access to the bloodstream for kidney dialysis. The increasing power and availability of supercomputing infrastructure means that it is becoming more realistic to use simulations to help identify the best type and location of a fistula for a specific patient. We describe a 3D fistula model that uses the lattice Boltzmann method to simultaneously resolve blood flow in patient-specific arteries and veins. The simulations conducted here, comprising vasculatures of the whole forearm, demonstrate qualified validation against clinical data. Ongoing research to further encompass complex biophysics on realistic time scales will permit the use of human-scale physiological models for basic and clinical medicine.
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A finite element analysis of flows of an Oldroyd-B fluid is developed, to simulate blood flow in an arteriovenous fistula. The model uses a combination of a standard conforming finite element approximation for the momentum equation, and the discontinuous Galerkin method, with upwinding, for the equation governing the evolution of the extra stress. The model is verified for a range of values of Weissenberg number We by applying it to the benchmark problem of flow past a cylinder in a channel. The main application is to flow in an arteriovenous fistula, the geometry of which is based on patient-specific data. Results for Oldroyd-B fluids are compared with those for a Newtonian fluid as well as with data from patient-specific velocity MRI scans. Features such as streamlines and regions of recirculation are similar across a range of values of We and the Newtonian case. There is however a strong dependence of maximum wall shear stress on We, with values for the viscoelastic fluid in all cases being higher than that for the Newtonian case.
A patient-specific fluid-structure interaction (FSI) model of a phase-contrast magnetic resonance angiography (PC-MRA) imaged arteriovenous fistula is presented. The numerical model is developed and simulated using a commercial multiphysics simulation package where a semi-implicit FSI coupling scheme combines a finite volume method blood flow model and a finite element method vessel wall model. A pulsatile mass-flow boundary condition is prescribed at the artery inlet of the model, and a three-element Windkessel model at the artery and vein outlets. The FSI model is freely available for analysis and extension. This work shows the effectiveness of combining a number of stabilisation techniques to simultaneously overcome the added-mass effect and optimise the efficiency of the overall model. The PC-MRA data, fluid model, and FSI model results show almost identical flow features in the fistula; this applies in particular to a flow recirculation region in the vein that could potentially lead to fistula failure.
Many scientific and medical researchers are working towards the creation of a virtual human - a personalised digital copy of an individual - that will assist in a patients diagnosis, treatment and recovery. The complex nature of living systems means that the development of this remains a major challenge. We describe progress in enabling the HemeLB lattice Boltzmann code to simulate 3D macroscopic blood flow on a full human scale. Significant developments in memory management and load balancing allow near linear scaling performance of the code on hundreds of thousands of computer cores. Integral to the construction of a virtual human, we also outline the implementation of a self-coupling strategy for HemeLB. This allows simultaneous simulation of arterial and venous vascular trees based on human-specific geometries.
This work reports on a study to develop a patient-specific finite element model of the Transcatheter Aortic Valve Implantation procedure, using a model of a balloon-expandable percutaneous prosthetic aortic valve as a framework for the prediction of its performance. An experimentally measured left ventricle and aortic pressure profile of a single systolic-diastolic cycle of a resting heart are used to assess the performance of the stent after its deployment. The results of the simulation show that the stent maintains its structural integrity after deployment, and successfully pushes the native leaflets back to keep the aortic root clear of all impediments.
Invasive intracranial electroencephalography (iEEG) or electrocorticography (ECoG) measures electrical potential directly on the surface of the brain, and, combined with numerical modeling, can be used to inform treatment planning for epilepsy surgery. Accurate solution of the iEEG or ECoG forward problem, which is a crucial prerequisite for solving the inverse problem in epilepsy seizure onset localization, requires accurate representation of the patients brain geometry and tissue electrical conductivity after implantation of electrodes. However, implantation of subdural grid electrodes causes the brain to deform, which invalidates preoperatively acquired image data. Moreover, postoperative MRI is incompatible with implanted electrodes and CT has insufficient range of soft tissue contrast, which precludes both MRI and CT from being used to obtain the deformed postoperative geometry. In this paper, we present a biomechanics-based image warping procedure using preoperative MRI for tissue classification and postoperative CT for locating implanted electrodes to perform non-rigid registration of the preoperative image data to the postoperative configuration. We solve the iEEG forward problem on the predicted postoperative geometry using the finite element method (FEM) which accounts for patient-specific inhomogeneity and anisotropy of tissue conductivity. Results for the simulation of a current source in the brain show large differences in electrical potential predicted by the models based on the original images and the deformed images corresponding to the brain geometry deformed by placement of invasive electrodes. Computation of the leadfield matrix also showed significant differences between the different models. The results suggest that significant improvements in source localization accuracy may be realized by the application of the proposed modeling methodology.
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