Simulation of Ultrasound Backscattering by Red Cell Aggregates:Effect of Shear Rate and Anisotropy

Fontaine, Isabelle; Savéry, David; Cloutier, Guy

doi:10.1016/s0006-3495(02)75522-7

Cited by 51 publications

(39 citation statements)

References 36 publications

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“…The mathematical model of blood flow and pressure has been presented in [16,17]. Adequate cellular biophysical data can be extracted without invasion due to ultrasound scattering, which allows tissue characterization and determination of red blood cell aggregation [18,19]. Some years ago, power ultrasound was considered too expensive for water treatment in the industry [20].…”

Section: Introductionmentioning

confidence: 99%

Separation of Microparticles from Suspension Utilizing Ultrasonic Standing Waves in a Piezoelectric Cylinder Actuator

et al. 2018

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A method of microparticle separation from larger volumes of suspension is proposed. A piezoelectric cylinder is selected as an ultrasonic wave actuator, the diameter and length of which the volume of the suspension to be purified depends. Numerically and experimentally, it is demonstrated that the low-level pressure field nodal circles of ultrasonic radiation standing waves concentrate microparticles at different velocities depending on the fluid viscosity. Numerical mathematical modeling has allowed us to identify the basic dynamic characteristics of the piezoelectric actuator to ensure a more effective process of microparticle separation. An important feature of the proposed method is that the ultrasonic radiation stresses that are directly applicable to cell membranes are inadequate to cause them damage.

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Section: Introductionmentioning

confidence: 99%

Separation of Microparticles from Suspension Utilizing Ultrasonic Standing Waves in a Piezoelectric Cylinder Actuator

et al. 2018

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“…Numerous in vitro studies have shown that aggregation of blood increases as shear rate decreases. Aggregation also depends on hematocrit and the concentration of macromolecules in the plasma or suspending medium (7,10,15,16,19,25,32). However, the circumstances in which aggregation occurs in vivo and its possible importance in circulatory function are not well understood.…”

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confidence: 99%

Aggregate formation of erythrocytes in postcapillary venules

Kim¹,

Popel²,

Intaglietta³

et al. 2005

American Journal of Physiology-Heart and Circulatory Physiology

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The purpose of the present study was to obtain information on erythrocyte aggregate formation in vivo. The movements of erythrocytes in postcapillary venules of the rat spinotrapezius muscle at various flow rates were recorded with a high-speed video camera before and after infusion of dextran 500. To distinguish aggregates, the following criteria were used: 1) a fixed distance (4 m) between the center points of two adjacent cells, 2) lack of visible separation between the adjacent cells, and 3) movement of the adjacent cells in the same direction. Without dextran 500 infusion, 11 and 5% of erythrocytes formed aggregates in low (33.2 Ϯ 28.3 s) and high pseudoshear (144.2 Ϯ 58.3 s) conditions, respectively, based on the above criteria. After dextran 500 infusion, 53% of erythrocytes satisfied the criteria in the low pseudoshear condition (26.5 Ϯ 17.0 s) and 13% of erythrocytes met the criteria in the high pseudoshear condition (240.0 Ϯ 85.9 s), indicating erythrocyte aggregation is strongly associated with shear rate. Approximately 90% of aggregate formation occurred in a short time period (0.15-0.30 s after entering the venule) in a region 15 to 30 m from the entrance. The time delay may reflect rheological entrance conditions in the venule.hemodynamics; in vivo blood rheology; in vivo microscopy RED BLOOD CELL AGGREGATION is a prominent feature in humans and other athletic species but not sedentary species (30). Numerous in vitro studies have shown that aggregation of blood increases as shear rate decreases. Aggregation also depends on hematocrit and the concentration of macromolecules in the plasma or suspending medium (7,10,15,16,19,25,32). However, the circumstances in which aggregation occurs in vivo and its possible importance in circulatory function are not well understood.Previous whole organ studies in the dog and cat, in which red blood cell aggregation normally occurs, have shown that venous vascular resistance in skeletal muscle increases as arterial pressure and blood flow rate decrease and provided evidence that this effect is dependent on red blood cell aggregation (11,23,24,35). From these studies, it was postulated that aggregate formation increased resistance to flow in the venular network. Recently, Bishop and co-workers (9) reported that, in rodents treated with high molecular mass dextran to induce aggregation, velocity profiles of blood flow in venules became blunted at low flow rates and red blood cells formed aggregates, which would explain, in part, the dependence of venous resistance on flow rate.

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“…aggregating red blood cell distributions) by introducing the frequency dependent structure factor, and called the Structure Factor model (SFM). 15,16 The SFM sums the contributions from individual cells and models the cellular interaction by a statistical mechanics structure factor, which is defined as the Fourier transform of the spatial distribution of the cells. 15,16 Note that the low frequency limit of the structure factor is by definition the packing factor used under Rayleigh conditions.…”

Section: Introductionmentioning

confidence: 99%

“…15,16 The SFM sums the contributions from individual cells and models the cellular interaction by a statistical mechanics structure factor, which is defined as the Fourier transform of the spatial distribution of the cells. 15,16 Note that the low frequency limit of the structure factor is by definition the packing factor used under Rayleigh conditions. 13 Until quite recently, the PM and SFM were only used for blood characterization purposes, but…”

Section: Introductionmentioning

confidence: 99%

Experimental assessment of four ultrasound scattering models for characterizing concentrated tissue-mimicking phantoms

Franceschini

Guillermin

2012

The Journal of the Acoustical Society of America

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Tissue-mimicking phantoms with high scatterer concentrations were examined using quantitative ultrasound techniques based on four scattering models: the Gaussian Model (GM), the Faran Model (FM), the Structure Factor Model (SFM) and the Particle Model (PM). Experiments were conducted using 10-and 17.5-MHz focused transducers on tissue-mimicking phantoms with scatterer concentrations ranging from 1 to 25%.Theoretical BSCs were first compared with the experimentally measured BSCs in the forward problem framework. The measured BSC versus scatterer concentration relationship was predicted satisfactorily by the SFM and the PM. The FM and the PM overestimated the BSC magnitude at actual concentrations greater than 2.5% and 10%, respectively. The SFM was the model that better matched the BSC magnitude at all the scatterer concentrations tested. Secondly, the four scattering models were compared in the inverse problem framework to estimate the scatterer size and concentration from the experimentally measured BSCs. The FM did not predict the concentration accurately at actual concentrations greater than 12.5%. The SFM and PM need to be associated with another quantitative parameter to differentiate between low and high concentrations. In that case, the SFM predicted the concentration satisfactorily with relative errors below 38% at actual concentrations ranging from 10 to 25%.

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Simulation of Ultrasound Backscattering by Red Cell Aggregates:Effect of Shear Rate and Anisotropy

Cited by 51 publications

References 36 publications

Separation of Microparticles from Suspension Utilizing Ultrasonic Standing Waves in a Piezoelectric Cylinder Actuator

Separation of Microparticles from Suspension Utilizing Ultrasonic Standing Waves in a Piezoelectric Cylinder Actuator

Aggregate formation of erythrocytes in postcapillary venules

Experimental assessment of four ultrasound scattering models for characterizing concentrated tissue-mimicking phantoms

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