Biomedical subjects

J G Georgiadis

Publications and source records attributed to J G Georgiadis.

6 recordsLinked to original sources

PubMed2006

Differential ion transport induced electroosmosis and internal recirculation in heterogeneous osmosis membranes.

Water and ion transport through a heterogeneous membrane separating two electrolyte solutions at different concentrations is investigated by using molecular dynamics simulations. The membrane features pairs of oppositely charged pores with identical diameters. Simulation results indicate that the differential transport of K(+) and Cl(-) ions through the membrane pores creates an electrical potential difference across the membrane, which then induces an electroosmotic water flux. The induced electroosmosis creates an internal recirculation loop of water between adjacent pores. The implications of these new observations are discussed.

Chlorides↗

PubMed2001

Tomographic study of helical modes in bifurcating Taylor-Couette-Poiseuille flow using magnetic resonance imaging.

The quantitative visualization of flow in a wide-gap annulus (radius ratio 0.5) between concentric cylinders with the inner cylinder rotating and a superimposed axial flow reveals a novel mixed-mode state at relatively high flow rates. A fast magnetic resonance imaging sequence allows the cinematographic dissection and three-dimensional reconstruction of supercritical nonaxisymmetric modes in a regime where stationary helical and propagating toroidal vortices coexist. The findings shed light on symmetry-breaking instabilities, flow pattern selection, and their consequences for hydrodynamic mixing in a complex laminar flow that constitutes a celebrated prototype of many mixing or fractionation processes.

Journal Article↗

PubMed2001

On the use of optical flow methods with spin-tagging magnetic resonance imaging.

Magnetic resonance imaging (MRI) is a versatile noninvasive tool for achieving full-field quantitative visualization of biomedical fluid flows. In this study, two MRI velocimetry techniques (spin tagging and phase contrast) are used to obtain velocity measurements in a Poiseuille flow for Reynolds numbers below 1,000. Spin-tagging MRI velocimetry supplies the displacement of tagged grids of nuclear spins from which the velocity field can be inferred, while phase contrast MRI velocimetry directly provides velocity data for every pixel in the field of view. Although the phase contrast method is more accurate for this flow, this technique is more sensitive to errors from magnetic susceptibility gradients, higher order motions, and has limited dynamic range. Spin-tagging MRI velocimetry is a viable alternative if automatic methods for extracting velocity fields from the tags can be found. Optical flow, a technique originally developed for machine vision applications, is proposed here as a postprocessing step to obtain two-dimensional velocity fields from spin-tagging MRI images. Results with artificially generated grids demonstrate the robustness of the optical flow algorithm to noise and indicate that a 7%-10% average error can be expected from the optical flow calculations alone, independent of MRI image artifacts. Experiments on spin-tagging MRI images for a Re=230 Poiseuille flow gave an average error of 6.41%, which was consistent with the measurement error of the generated (synthetic) images with the same level of random noise superimposed.

Algorithms↗

PubMed2000

On the accuracy of EPI-based phase contrast velocimetry.

For over a decade, echo-planar imaging (EPI) has been used in both the medical and applied sciences to capture velocity fields of fluid flows. However, previous studies have not rigorously confirmed the accuracy of the measurements or sought to understand the limitations of the technique. In this study, a bipolar gradient was added to a flow-compensated EPI pulse sequence to obtain rapid phase contrast images of steady and unsteady flows through two step stenoses. For steady Re = 100 and 258 flows, accuracy was measured through systematic comparisons with CFD simulations, mass flow rate measurements, and spin echo phase contrast images. On average, the EPI image data exhibited velocity errors of 5 to 10 percent, while mass was conserved to within 5.6 percent at each axial position. Compared to spin-echo phase contrast images, the EPI images have 50 percent lower signal-to-noise ratio, larger local velocity errors, and similar mass conservation characteristics. An unsteady flow was then examined by starting a pump and allowing it to reach a steady Re = 100 flow. Accuracy in this case was measured by the consistency between mass flow rate measurements at different axial positions. Images taken at 0.3 s intervals captured the velocity field evolution and showed that 50 to 100 percent errors occur when the flow changes on a time scale faster than the image acquisition time.

Blood Flow Velocity↗

PubMed1993

Pressure propagation in pulsatile flow through random microvascular networks.

A microvascular network with random dimensions of vessels is built on the basis of statistical analysis of conjunctival beds reported in the literature. Our objective is to develop a direct method of evaluating the statistics of the pulsatile hydrodynamic field starting from a priori statistics which mimic the large-scale heterogeneity of the network. The model consists of a symmetric diverging-converging dentritic network of ten levels of vessels, each level described by a truncated Gaussian distribution of vessel diameters and lengths. In each vascular segment, the pressure distribution is given by a diffusion equation with random parameters, while the blood flow rate depends linearly on the pressure gradient. The results are presented in terms of the mean value and standard deviation of the pressure and flow rate waveforms at two positions along the network. It is shown that the assumed statistical variation of vessel lengths results in flow rate deviations as high as 50 percent of the mean, while the corresponding effect of vessel diameter variation is much smaller. For a given pressure drop, the statistical variation of lengths increases the mean flow while the effect on the mean pressure distribution is negligible.

Blood Pressure↗

PubMed1992

Computational fluid dynamics of left ventricular ejection.

The present investigation addresses the effects of simple geometric variations on intraventricular ejection dynamics, by methods from computational fluid dynamics. It is an early step in incorporating more and more relevant characteristics of the ejection process, such as a continuously changing irregular geometry, in numerical simulations. We consider the effects of varying chamber eccentricities and outflow valve orifice-to-inner surface area ratios on instantaneous ejection gradients along the axis of symmetry of the left ventricle. The equation of motion for the streamfunction was discretized and solved iteratively with specified boundary conditions on a boundary-fitted adaptive grid, using an alternating-direction-implicit (ADI) algorithm. The unsteady aspects of the ejection process were subsequently introduced into the numerical simulation. It was shown that for given chamber volume and outflow orifice area, higher chamber eccentricities require higher ejection pressure gradients for the same velocity and local acceleration values at the aortic anulus than more spherical shapes. This finding is referable to the rise in local acceleration effects across the outflow axis. This is to be contrasted with the case of outflow orifice stenosis, in which it was shown that it is the convective acceleration effects that are intensified strongly.

Algorithms↗