Study of Flow-Induced Hemolysis Using Novel Couette-Type Blood-Shearing Devices

Abstract

To assist the development and application of blood-contacting medical devices, two novel flow-through Couette-type blood-shearing devices have been developed to study the quantitative relationship between blood damage indexes and flow-dependent parameters. One device is an axial flow-through Couette-type device supported by a pair of pin bearings adapted from the adult Jarvik 2000 blood pump. The other is a centrifugal flow-through Couette-type device supported with magnetic bearings adapted from the CentriMag blood pump. In both devices, a rotor spindle was used to replace the original impeller blades so that a small gap was created between the housing and the rotating spindle surface. Computational fluid dynamics simulations have shown that a uniform, high shear stress region can be generated inside the small gap while the shear stresses elsewhere are relatively low. The possibility of secondary blood damage caused by mechanical seals was eliminated due to the use of a magnetic rotor system. Blood flow through the gap was driven by an externally pressurized reservoir. By adjusting the rotational speed and blood flow rate, shear-induced hemolysis was quantified at a matrix of exposure time (0.039 to 1.48 s) and shear stress (50 to 320 Pa). All of the experiments were conducted at room temperature using heparinized ovine blood with a hematocrit value of 30%. The measured hemolysis levels were much lower than those published in the literature, and the overestimation of those earlier studies may be attributable to device-related secondary blood-damaging effects. A new set of coefficients for the power law model was derived from the regression of the experimental data.

Reynolds Stresses and Hemolysis in Turbulent Flow Examined by Threshold Analysis

“…Therefore, cells are assumed to spend on average the same amount of time in any location inside of the flow field. Four different power law models [10,11,18,23] were used to investigate the effect of time-averaged and area-averaged Reynolds, in addition to total, viscous and wall shear stresses to hemolysis.…”

“…Standard error (SE) calculation [24] was performed using the formula SE = sdev √ N where sdev is the standard deviation and N is the number of observations that correspond to the four different experiments of Kameneva et al [4]. Hemolysis predictions show that the power law model of Zhang [11] gives the lowest standard error. The highest error was obtained by using Giersiepen's [23] power law model.…”

“…In order to explore this question further, we have used commonly accepted power law models [10,11,18,23] in the form of Equation (1) to investigate the effects of area-averaged, timeaveraged RS, viscous, total, and wall shear stresses on hemolysis (see Table 4). …”

“…Constants α, β, and C were determined from regression analysis applied to experimental data for shear stresses less than 255 Pa and exposure times less than 700 ms. Heuser and Opitz [10] obtained their set of coefficients using laminar flow in a Couette viscometer to determine hemolysis of porcine blood for exposure times less than 700 ms and shear stresses less than 255 Pa. Zhang et al [11] examined hemolysis of ovine blood for exposure times of less than 1500 ms and shear stresses between 50-320 Pa and obtained power law constants by fitting the hemolysis results to Equation (1). It has, however, been argued that since power law models were obtained by using viscometer experiments with steady, uniform laminar flow shear stress, the models often fail when capturing the general flow features of typical medical devices [26] which usually impose multiple, shorter term exposures.…”

Modelagem matemática da fluidodinâmica não-newtoniana e bifásica simplificada da hemólise induzida mecanicamente em sistemas de bombeamento centrífugo de sangue

“…Também utilizando viscosímetro de Couette em escoamento laminar, mas com sangue ovino e em uma faixa de tensões de cisalhamento entre 50-320 Pa durante tempos de exposição até 1480 ms (Zhang et al, 2011), obteve-se a seguinte equação:…”