Non-parametric dynamical estimation of blood flow rate, pressure difference and viscosity for a miniaturized blood pump.

Blood pumps are becoming increasingly important for medical devices. They are used to assist and control the blood flow and blood pressure in the patient's body. To accurately control blood pumps, information about important hydrodynamic parameters such as blood flow rate, pressure difference and viscosity is needed. These parameters are difficult to measure online. Therefore, an accurate estimation of these parameters is crucial for the effective operation of implantable blood pumps. In this study, in vitro tests with bovine blood were conducted to collect data about the non-linear dependency of blood flow rate, flow resistance (pressure difference) and whole blood viscosity on motor current and rotation speed of a prototype blood pump. Gaussian process regression models are then used to model the non-linear mappings from motor current and rotation speed to the hydrodynamic variables of interest. The performance of the estimation is evaluated for all three variables and shows very high accuracy. For blood flow rate - correlation coefficient (r2) = 1, root mean squared error (RMSE) = 0.31 ml min-1, maximal error (ERRmax) = 9.31 ml min-1; for pressure r2 = 1, RMSE = 0.09 mmHg, ERRmax = 8.34 mmHg; and for viscosity r2 = 1,RMSE = 0.09 mPa.s, ERRmax = 0.31 mPa⋅s. The current findings suggest that this method can be employed for highly accurate online estimation of essential hydrodynamic parameters for implantable blood pumps.

Microstructured Hollow Fiber Membranes: Potential Fiber Shapes for Extracorporeal Membrane Oxygenators.

Extracorporeal membrane oxygenators are essential medical devices for the treatment of patients with respiratory failure. A promising approach to improve oxygenator performance is the use of microstructured hollow fiber membranes that increase the available gas exchange surface area. However, by altering the traditional circular fiber shape, the risk of low flow, stagnating zones that obstruct mass transfer and encourage thrombus formation, may increase. Finding an optimal fiber shape is therefore a significant task. In this study, experimentally validated computational fluid dynamics simulations were used to investigate transverse flow within fiber packings of circular and microstructured fiber geometries. A numerical model was applied to calculate the local Sherwood number on the membrane surface, allowing for qualitative comparison of gas exchange capacities in low-velocity areas caused by the microstructured geometries. These adverse flow structures lead to a tradeoff between increased surface area and mass transfer. Based on our simulations, we suggest an optimal fiber shape for further investigations that increases potential mass transfer by up to 48% in comparison to the traditional, circular hollow fiber shape.

Water as a Blood Model for Determination of CO2 Removal Performance of Membrane Oxygenators.

CO2 removal via membrane oxygenators has become an important and reliable clinical technique. Nevertheless, oxygenators must be further optimized to increase CO2 removal performance and to reduce severe side effects. Here, in vitro tests with water can significantly reduce costs and effort during development. However, they must be able to reasonably represent the CO2 removal performance observed with blood. In this study, the deviation between the CO2 removal rate determined in vivo with porcine blood from that determined in vitro with water is quantified. The magnitude of this deviation (approx. 10%) is consistent with results reported in the literature. To better understand the remaining difference in CO2 removal rate and in order to assess the application limits of in vitro water tests, CFD simulations were conducted. They allow to quantify and investigate the influences of the differing fluid properties of blood and water on the CO2 removal rate. The CFD results indicate that the main CO2 transport resistance, the diffusional boundary layer, behaves generally differently in blood and water. Hence, studies of the CO2 boundary layer should be preferably conducted with blood. In contrast, water tests can be considered suitable for reliable determination of the total CO2 removal performance of oxygenators.

Animal blood in translational research: How to adjust animal blood viscosity to the human standard.

Animal blood is used in mock circulations or in forensic bloodstain pattern analysis. Blood viscosity is important in these settings as it determines the driving pressure through biomedical devices and the shape of the bloodstain. However, animal blood can never exactly mimic human blood due to erythrocyte properties differing among species. This results in the species-specific shear thinning behavior of blood suspensions, and it is therefore not enough to adjust the hematocrit of an animal blood sample to mimic the behavior of human blood over the entire range of shear rates that are present in the body. In order to optimize experiments that require animal blood, we need models to adapt the blood samples. We here offer mathematical models derived for each species using a multi linear regression approach to describe the influence of shear rate, hematocrit, and temperature on blood viscosity. Results show that pig blood cannot be recommended for experiments at low flow conditions (<200 s-1 ) even though erythrocyte properties are similar in pigs and humans. However, pig blood mimics human blood excellently at high flow condition. Horse blood is unsuitable as experimental model in this regard. For several studied conditions, sheep blood was the closest match to human blood viscosity among the tested species.

Suitable CO2 Solubility Models for Determination of the CO2 Removal Performance of Oxygenators.

CO2 removal via membrane oxygenators during lung protective ventilation has become a reliable clinical technique. For further optimization of oxygenators, accurate prediction of the CO2 removal rate is necessary. It can either be determined by measuring the CO2 content in the exhaust gas of the oxygenator (sweep flow-based) or using blood gas analyzer data and a CO2 solubility model (blood-based). In this study, we determined the CO2 removal rate of a prototype oxygenator utilizing both methods in in vitro trials with bovine and in vivo trials with porcine blood. While the sweep flow-based method is reliably accurate, the blood-based method depends on the accuracy of the solubility model. In this work, we quantified performances of four different solubility models by calculating the deviation of the CO2 removal rates determined by both methods. Obtained data suggest that the simplest model (Loeppky) performs better than the more complex ones (May, Siggaard-Anderson, and Zierenberg). The models of May, Siggaard-Anderson, and Zierenberg show a significantly better performance for in vitro bovine blood data than for in vivo porcine blood data. Furthermore, the suitability of the Loeppky model parameters for bovine blood (in vitro) and porcine blood (in vivo) is evaluated.

Estimation Methods for Viscosity, Flow Rate and Pressure from Pump-Motor Assembly Parameters.

Blood pumps have found applications in heart support devices, oxygenators, and dialysis systems, among others. Often, there is no room for sensors, or the sensors are simply unreliable when long-term operation is required. However, control systems rely on those hard-to-measure parameters, such as blood flow rate and pressure difference, thus their estimation takes a central role in the development process of such medical devices. The viscosity of the blood not only influences the estimation of those parameters but is often a parameter that is of great interest to both doctors and engineers. In this work, estimation methods for blood flow rate, pressure difference, and viscosity are presented using Gaussian process regression models. Different water-glycerol mixtures were used to model blood. Data was collected from a custom-built blood pump, designed for intracorporeal oxygenators in an in vitro test circuit. The estimation was performed from motor current and motor speed measurements and its accuracy was measured for: blood flow rate r2 = 0.98, root mean squared error (RMSE) = 46 mL.min-1; pressure difference r2 = 0.98, RMSE = 8.7 mmHg; and viscosity r2 = 0.98, RMSE = 0. 0.049 mPa.s. The results suggest that the presented methods can be used to accurately predict blood flow rate, pressure, and viscosity online.