Richard A. Malinauskas

Multilaboratory Particle Image Velocimetry Analysis of the FDA Benchmark Nozzle Model to Support Validation of Computational Fluid Dynamics Simulations

This study is part of a FDA-sponsored project to evaluate the use and limitations of computational fluid dynamics (CFD) in assessing blood flow parameters related to medical device safety. In an interlaboratory study, fluid velocities and pressures were measured in a nozzle model to provide experimental validation for a companion round-robin CFD study. The simple benchmark nozzle model, which mimicked the flow fields in several medical devices, consisted of a gradual flow constriction, a narrow throat region, and a sudden expansion region where a fluid jet exited the center of the nozzle with recirculation zones near the model walls. Measurements of mean velocity and turbulent flow quantities were made in the benchmark device at three independent laboratories using particle image velocimetry (PIV). Flow measurements were performed over a range of nozzle throat Reynolds numbers (Re(throat)) from 500 to 6500, covering the laminar, transitional, and turbulent flow regimes. A standard operating procedure was developed for performing experiments under controlled temperature and flow conditions and for minimizing systematic errors during PIV image acquisition and processing. For laminar (Re(throat)=500) and turbulent flow conditions (Re(throat)≥3500), the velocities measured by the three laboratories were similar with an interlaboratory uncertainty of ∼10% at most of the locations. However, for the transitional flow case (Re(throat)=2000), the uncertainty in the size and the velocity of the jet at the nozzle exit increased to ∼60% and was very sensitive to the flow conditions. An error analysis showed that by minimizing the variability in the experimental parameters such as flow rate and fluid viscosity to less than 5% and by matching the inlet turbulence level between the laboratories, the uncertainties in the velocities of the transitional flow case could be reduced to ∼15%. The experimental procedure and flow results from this interlaboratory study (available at http://fdacfd.nci.nih.gov) will be useful in validating CFD simulations of the benchmark nozzle model and in performing PIV studies on other medical device models.

Fda Benchmark Medical Device Flow Models for Cfd Validation.

Computational fluid dynamics (CFD) is increasingly being used to develop blood-contacting medical devices. However, the lack of standardized methods for validating CFD simulations and blood damage predictions limits its use in the safety evaluation of devices. Through a U.S. Food and Drug Administration (FDA) initiative, two benchmark models of typical device flow geometries (nozzle and centrifugal blood pump) were tested in multiple laboratories to provide experimental velocities, pressures, and hemolysis data to support CFD validation. In addition, computational simulations were performed by more than 20 independent groups to assess current CFD techniques. The primary goal of this article is to summarize the FDA initiative and to report recent findings from the benchmark blood pump model study. Discrepancies between CFD predicted velocities and those measured using particle image velocimetry most often occurred in regions of flow separation (e.g., downstream of the nozzle throat, and in the pump exit diffuser). For the six pump test conditions, 57% of the CFD predictions of pressure head were within one standard deviation of the mean measured values. Notably, only 37% of all CFD submissions contained hemolysis predictions. This project aided in the development of an FDA Guidance Document on factors to consider when reporting computational studies in medical device regulatory submissions. There is an accompanying podcast available for this article. Please visit the journal’s Web site (www.asaiojournal.com) to listen.

Limitations of using synthetic blood clots for measuring in vitro clot capture efficiency of inferior vena cava filters

The purpose of this study was first to evaluate the clot capture efficiency and capture location of six currently-marketed vena cava filters in a physiological venous flow loop, using synthetic polyacrylamide hydrogel clots, which were intended to simulate actual blood clots. After observing a measured anomaly for one of the test filters, we redirected the focus of the study to identify the cause of poor clot capture performance for large synthetic hydrogel clots. We hypothesized that the uncharacteristic low clot capture efficiency observed when testing the outlying filter can be attributed to the inadvertent use of dense, stiff synthetic hydrogel clots, and not as a result of the filter design or filter orientation. To study this issue, sheep blood clots and polyacrylamide (PA) synthetic clots were injected into a mock venous flow loop containing a clinical inferior vena cava (IVC) filter, and their captures were observed. Testing was performed with clots of various diameters (3.2, 4.8, and 6.4 mm), length-to-diameter ratios (1:1, 3:1, 10:1), and stiffness. By adjusting the chemical formulation, PA clots were fabricated to be soft, moderately stiff, or stiff with elastic moduli of 805 ± 2, 1696 ± 10 and 3295 ± 37 Pa, respectively. In comparison, the elastic moduli for freshly prepared sheep blood clots were 1690 ± 360 Pa. The outlying filter had a design that was characterized by peripheral gaps (up to 14 mm) between its wire struts. While a low clot capture rate was observed using large, stiff synthetic clots, the filter effectively captured similarly sized sheep blood clots and soft PA clots. Because the stiffer synthetic clots remained straight when approaching the filter in the IVC model flow loop, they were more likely to pass between the peripheral filter struts, while the softer, physiological clots tended to fold and were captured by the filter. These experiments demonstrated that if synthetic clots are used as a surrogate for animal or human blood clots for in vitro evaluation of vena cava filters, the material properties (eg, elastic modulus) and dynamic behavior of the surrogate should first be assessed to ensure that they accurately mimic an actual blood clot within the body.

Time-Resolved Particle Image Velocimetry Measurements with Wall Shear Stress and Uncertainty Quantification for the FDA Nozzle Model

Abstract We present advanced particle image velocimetry (PIV) processing, post-processing, and uncertainty estimation techniques to support the validation of computational fluid dynamics analyses of medical devices. This work is an extension of a previous FDA-sponsored multi-laboratory study, which used a medical device mimicking geometry referred to as the FDA benchmark nozzle model. Experimental measurements were performed using time-resolved PIV at five overlapping regions of the model for Reynolds numbers in the nozzle throat of 500, 2000, 5000, and 8000. Images included a twofold increase in spatial resolution in comparison to the previous study. Data was processed using ensemble correlation, dynamic range enhancement, and phase correlations to increase signal-to-noise ratios and measurement accuracy, and to resolve flow regions with large velocity ranges and gradients, which is typical of many blood-contacting medical devices. Parameters relevant to device safety, including shear stress at the wall and in bulk flow, were computed using radial basis functions. In addition, in-field spatially resolved pressure distributions, Reynolds stresses, and energy dissipation rates were computed from PIV measurements. Velocity measurement uncertainty was estimated directly from the PIV correlation plane, and uncertainty analysis for wall shear stress at each measurement location was performed using a Monte Carlo model. Local velocity uncertainty varied greatly and depended largely on local conditions such as particle seeding, velocity gradients, and particle displacements. Uncertainty in low velocity regions in the sudden expansion section of the nozzle was greatly reduced by over an order of magnitude when dynamic range enhancement was applied. Wall shear stress uncertainty was dominated by uncertainty contributions from velocity estimations, which were shown to account for 90–99% of the total uncertainty. This study provides advancements in the PIV processing methodologies over the previous work through increased PIV image resolution, use of robust image processing algorithms for near-wall velocity measurements and wall shear stress calculations, and uncertainty analyses for both velocity and wall shear stress measurements. The velocity and shear stress analysis, with spatially distributed uncertainty estimates, highlights the challenges of flow quantification in medical devices and provides potential methods to overcome such challenges.

Use of the FDA nozzle model to illustrate validation techniques in computational fluid dynamics (CFD) simulations

A “credible” computational fluid dynamics (CFD) model has the potential to provide a meaningful evaluation of safety in medical devices. One major challenge in establishing “model credibility” is to determine the required degree of similarity between the model and experimental results for the model to be considered sufficiently validated. This study proposes a “threshold-based” validation approach that provides a well-defined acceptance criteria, which is a function of how close the simulation and experimental results are to the safety threshold, for establishing the model validity. The validation criteria developed following the threshold approach is not only a function of Comparison Error, E (which is the difference between experiments and simulations) but also takes in to account the risk to patient safety because of E. The method is applicable for scenarios in which a safety threshold can be clearly defined (e.g., the viscous shear-stress threshold for hemolysis in blood contacting devices). The applicability of the new validation approach was tested on the FDA nozzle geometry. The context of use (COU) was to evaluate if the instantaneous viscous shear stress in the nozzle geometry at Reynolds numbers (Re) of 3500 and 6500 was below the commonly accepted threshold for hemolysis. The CFD results (“S”) of velocity and viscous shear stress were compared with inter-laboratory experimental measurements (“D”). The uncertainties in the CFD and experimental results due to input parameter uncertainties were quantified following the ASME V&V 20 standard. The CFD models for both Re = 3500 and 6500 could not be sufficiently validated by performing a direct comparison between CFD and experimental results using the Student’s t-test. However, following the threshold-based approach, a Student’s t-test comparing |S-D| and |Threshold-S| showed that relative to the threshold, the CFD and experimental datasets for Re = 3500 were statistically similar and the model could be considered sufficiently validated for the COU. However, for Re = 6500, at certain locations where the shear stress is close the hemolysis threshold, the CFD model could not be considered sufficiently validated for the COU. Our analysis showed that the model could be sufficiently validated either by reducing the uncertainties in experiments, simulations, and the threshold or by increasing the sample size for the experiments and simulations. The threshold approach can be applied to all types of computational models and provides an objective way of determining model credibility and for evaluating medical devices.

Uncertainty Estimations for Particle Image Velocimetry in a Medical Device Analog (Nozzle) Model

Particle Image Velocimetry (PIV) is currently the most widely used and well-established tool for non-invasive flow field velocity measurements, and a valuable method for validating computational fluid dynamics (CFD) models of medical devices. One of the critical steps in the CFD validation process is quantification of the experimental uncertainties. This work utilizes a new uncertainty estimation methodology developed by Charonko et al.1 for quantifying the PIV cross-correlation uncertainties. Uncertainties from experimental sources, including image magnification and acquisition timing, were propagated using Taylor series expansion for PIV data within the FDA benchmark Nozzle model2.Copyright

Multi-Laboratory Uncertainty Analysis of PIV-Measured Flow Quantities Relevant to Blood Damage in the FDA Nozzle Model

Particle image velocimetry (PIV) has been used in regulatory submissions to the FDA for pre-clinical and post-market evaluations of flow fields in medical devices, such as artificial heart valves, blood pumps, and stents. The velocity and shear fields obtained from the PIV experiments are also used to validate computational fluid dynamics (CFD) data accompanying the submissions. However, previous studies have questioned the accuracy of PIV measurements in regions of high shear and low velocity (regions prone to hemolysis and thrombosis). Currently, there is no clear estimate of the amount of uncertainty involved in measuring various flow parameters in these high-risk regions. The objective of this study was to perform an inter-laboratory PIV study in a simplified nozzle model and quantify the uncertainties involved in measuring flow quantities relevant to blood damage, such as near-wall velocity, viscous and Reynolds shear stresses, size and velocity within recirculation regions, and for estimating an index of hemolysis.© 2011 ASME