Mechanical and leakage integrity testing considerations for evaluating the performance of tissue containment systems.

Tissue containment systems (TCS) are medical devices that may be used during morcellation procedures during minimally invasive laparoscopic surgery. TCS are not new devices but their use as a potential mitigation for the spread of occult malignancy during laparoscopic power morcellation of fibroids and/or the uterus has been the subject of interest following reports of upstaging of previously undetected sarcoma in women who underwent a laparoscopic hysterectomy. Development of standardized test methods and acceptance criteria to evaluate the safety and performance of these devices will speed development, allowing for more devices to benefit patients. As a part of this study, a series of preclinical experimental bench test methods were developed to evaluate the mechanical and leakage performance of TCS that may be used in power morcellation procedures. Experimental tests were developed to evaluate mechanical integrity, e.g., tensile, burst, puncture, and penetration strengths for the TCS, and leakage integrity, e.g., dye and microbiological leakage (both acting as surrogates for blood and cancer cells) through the TCS. In addition, to evaluate both mechanical integrity and leakage integrity as a combined methodology, partial puncture and dye leakage was conducted on the TCS to evaluate the potential for leakage due to partial damage caused by surgical tools. Samples from 7 different TCSs were subjected to preclinical bench testing to evaluate leakage and mechanical performance. The performance of the TCSs varied significantly between different brands. The leakage pressure of the TCS varied between 26 and > 1293 mmHg for the 7 TCS brands. Similarly, the tensile force to failure, burst pressure, and puncture force varied between 14 and 80 MPa, 2 and 78 psi, and 2.5 N and 47 N, respectively. The mechanical failure and leakage performance of the TCS were different for homogeneous and composite TCSs. The test methods reported in this study may facilitate the development and regulatory review of these devices, may help compare TCS performance between devices, and increase provider and patient accessibility to improved tissue containment technologies.

Results of the Interlaboratory Computational Fluid Dynamics Study of the FDA Benchmark Blood Pump.

Computational fluid dynamics (CFD) is widely used to simulate blood-contacting medical devices. To be relied upon to inform high-risk decision making, however, model credibility should be demonstrated through validation. To provide robust data sets for validation, researchers at the FDA and collaborators developed two benchmark medical device flow models: a nozzle and a centrifugal blood pump. Experimental measurements of the flow fields and hemolysis were acquired using each model. Concurrently, separate open interlaboratory CFD studies were performed in which participants from around the world, who were blinded to the measurements, submitted CFD predictions of each benchmark model. In this study, we report the results of the interlaboratory CFD study of the FDA benchmark blood pump. We analyze the results of 24 CFD submissions using a wide range of different flow solvers, methods, and modeling parameters. To assess the accuracy of the CFD predictions, we compare the results with experimental measurements of three quantities of interest (pressure head, velocity field, and hemolysis) at different pump operating conditions. We also investigate the influence of different CFD methods and modeling choices used by the participants. Our analyses reveal that, while a number of CFD submissions accurately predicted the pump performance for individual cases, no single participant was able to accurately predict all quantities of interest across all conditions. Several participants accurately predicted the pressure head at all conditions and the velocity field in all but one or two cases. Only one of the eight participants who submitted hemolysis results accurately predicted absolute plasma free hemoglobin levels at a majority of the conditions, though most participants were successful at predicting relative hemolysis levels between conditions. Overall, this study highlights the need to validate CFD modeling of rotary blood pumps across the entire range of operating conditions and for all quantities of interest, as some operating conditions and regions (e.g., the pump diffuser) are more challenging to accurately predict than others. All quantities of interest should be validated because, as shown here, it is possible to accurately predict hemolysis despite having relatively inaccurate predictions of the flow field.

In Silico Fit Evaluation of Additively Manufactured Face Coverings.

In response to the respiratory protection device shortage during the COVID-19 pandemic, the additive manufacturing (AM) community designed and disseminated numerous AM face masks. Questions regarding the effectiveness of AM masks arose because these masks were often designed with limited (if any) functional performance evaluation. In this study, we present a fit evaluation methodology in which AM face masks are virtually donned on a standard digital headform using finite element-based numerical simulations. We then extract contour plots to visualize the contact patches and gaps and quantify the leakage surface area for each mask frame. We also use the methodology to evaluate the effects of adding a foam gasket and variable face mask sizing, and finally propose a series of best practices. Herein, the methodology is focused only on characterizing the fit of AM mask frames and does not considering filter material or overall performance. We found that AM face masks may provide a sufficiently good fit if the sizing is appropriate and if a sealing gasket material is present to fill the gaps between the mask and face. Without these precautions, the rigid nature of AM materials combined with the wide variation in facial morphology likely results in large gaps and insufficient adaptability to varying user conditions which may render the AM face masks ineffective.

Clinical evaluation of non-contact infrared thermometers.

Non-contact infrared thermometers (NCITs) are being widely used during the COVID-19 pandemic as a temperature-measurement tool for screening and isolating patients in healthcare settings, travelers at ports of entry, and the general public. To understand the accuracy of NCITs, a clinical study was conducted with 1113 adult subjects using six different commercially available NCIT models. A total of 60 NCITs were tested with 10 units for each model. The NCIT-measured temperature was compared with the oral temperature obtained using a reference oral thermometer. The mean difference between the reference thermometer and NCIT measurement (clinical bias) was different for each NCIT model. The clinical bias ranged from just under - 0.9 °C (under-reporting) to just over 0.2 °C (over-reporting). The individual differences ranged from - 3 to + 2 °C in extreme cases, with the majority of the differences between - 2 and + 1 °C. Depending upon the NCIT model, 48% to 88% of the individual temperature measurements were outside the labeled accuracy stated by the manufacturers. The sensitivity of the NCIT models for detecting subject's temperature above 38 °C ranged from 0 to 0.69. Overall, our results indicate that some NCIT devices may not be consistently accurate enough to determine if subject's temperature exceeds a specific threshold of 38 °C. Model-to-model variability and individual model accuracy in the displayed temperature were found to be outside of acceptable limits. Accuracy and credibility of the NCITs should be thoroughly evaluated before using them as an effective screening tool.

Depth of thermal dispersion of monopolar radiofrequency heating in the vaginal wall.

The use of energy-based devices to treat genitourinary syndrome of menopause, termed vaginal thermotherapy (VTT), has gained significant interest in recent years. Among the primary safety concerns of this relatively new procedure is the possibility of unintentionally heating tissues adjacent to the vaginal wall, i.e., heating too deeply. Herein we use numerical simulations to evaluate monopolar radiofrequency-based (RF) VTT specifically focusing on the resultant depth of heating through a range of input parameters. Varying RF power, exposure time, and the simulated rate of blood perfusion, we map the parameter space identifying which combinations of input parameters are likely to heat past the depth of the vaginal wall and affect adjacent tissue. We found that the device parameters commonly used in the literature are likely to heat past the vaginal wall and merit further investigation. In addition, we found that the parameter typically used to describe VTT devices, total energy delivered, does not reliably indicate the resultant depth of heat dispersion.

Performance characterization of non-contact infrared thermometers (NCITs) for forehead temperature measurement.

The ability to assess the performance of a non-contact infrared thermometer (NCIT) may be limited due to the algorithms necessary to predict a reference site temperature (e.g., oral) from a measurement of the forehead skin temperature. The algorithm not only adjusts for the difference between the reference site temperature and forehead temperature, but may also account for hardware corrections, bias adjustments and emissivity settings. These algorithms are proprietary to the manufacturer and can be unique for each device. ASTM E1965-98 (2016) is a standard test method for the evaluation of NCITs. It includes forehead thermometers; however, the algorithm must be known or an unadjusted calibration mode must be accessible. This study evaluates 6 NCIT models (10 units of each) against the ASTM standard error criterion using a blackbody source. Units were tested within the manufacturer's operating and temperature measurement range specification. A method to evaluate measurement outliers and characterize each model's performance when the adjustment algorithm is unknown is proposed. Using this method, 5 of the 6 models had a predicted error > 0.3°C.

A computational model for predicting changes in infection dynamics due to leakage through N95 respirators.

In the absence of fit-testing, leakage of aerosolized pathogens through the gaps between the face and N95 respirators could compromise the effectiveness of the device and increase the risk of infection for the exposed population. To address this issue, we have developed a model to estimate the increase in risk of infection resulting from aerosols leaking through gaps between the face and N95 respirators. The gaps between anthropometric face-geometry and N95 respirators were scanned using computed tomography. The gap profiles were subsequently input into CFD models. The amount of aerosol leakage was predicted by the CFD simulations. Leakage levels were validated using experimental data obtained using manikins. The computed amounts of aerosol transmitted to the respiratory system, with and without leaks, were then linked to a risk-assessment model to predict the infection risk for a sample population. An influenza outbreak in which 50% of the population deployed respirators was considered for risk assessment. Our results showed that the leakage predicted by the CFD model matched the experimental data within about 13%. Depending upon the fit between the headform and the respirator, the inward leakage for the aerosols ranged between 30 and 95%. In addition, the non-fit-tested respirator lowered the infection rate from 97% (for no protection) to between 42 and 80%, but not to the same level as the fit-tested respirators (12%). The CFD-based leakage model, combined with the risk-assessment model, can be useful in optimizing protection strategies for a given population exposed to a pathogenic aerosol.

In Vitro Leakage Testing of Tissue Containment Bags When Subjected to Power Morcellation Forces.

STUDY OBJECTIVE: To determine the ability of tissue containment systems to prevent leakage of cancer cell surrogates when subjected to forces encountered during power morcellation procedures. DESIGN: In vitro study. SETTING: Medical device research laboratory. INTERVENTIONS: Samples from 7 different legally marketed tissue containment bags (1 of which is indicated for power morcellation) were subjected to dye and bacteriophage penetration tests at pressures ranging from 0.5 to 50 times the insufflation pressure. The minimum pressure required to cause bag leakage was measured. Subsequently, the morcellation leakage safety factor for each bag was determined as the ratio of the minimum leakage pressure of the bag to the total pressure contributed from insufflation pressure and mechanical forces acting during the power morcellation procedure. MEASUREMENT AND MAIN RESULTS: The leakage performance of the bags varied markedly from brand to brand. No correlation was found between leakage pressure and the bag material or the total bag thickness. The leakage pressures ranged from 26 mmHg to >1293 mmHg for the 7 bags, and safety factors ranged from 1 to 50 when only the insufflation pressure was considered. However, if the morcellation forces were included in the calculation, the safety factor dropped by 6-fold for all brands and dropped below 1, indicating likelihood of leakage, for 2 of the 7 brands. CONCLUSION: This study provides a mechanism for more realistically simulating the conditions experienced by containment bags during morcellation and quantifying the level of safety provided by the bags.

Assessing Computational Model Credibility Using a Risk-Based Framework: Application to Hemolysis in Centrifugal Blood Pumps.

Medical device manufacturers using computational modeling to support their device designs have traditionally been guided by internally developed modeling best practices. A lack of consensus on the evidentiary bar for model validation has hindered broader acceptance, particularly in regulatory areas. This has motivated the US Food and Drug Administration and the American Society of Mechanical Engineers (ASME), in partnership with medical device companies and software providers, to develop a structured approach for establishing the credibility of computational models for a specific use. Charged with this mission, the ASME V&V 40 Subcommittee on Verification and Validation (V&V) in Computational Modeling of Medical Devices developed a risk-informed credibility assessment framework; the main tenet of the framework is that the credibility requirements of a computational model should be commensurate with the risk associated with model use. This article provides an overview of the ASME V&V 40 standard and an example of the framework applied to a generic centrifugal blood pump, emphasizing how experimental evidence from in vitro testing can support computational modeling for device evaluation. Two different contexts of use for the same model are presented, which illustrate how model risk impacts the requirements on the V&V activities and outcomes.

Modeling the Effectiveness of Respiratory Protective Devices in Reducing Influenza Outbreak.

Outbreaks of influenza represent an important health concern worldwide. In many cases, vaccines are only partially successful in reducing the infection rate, and respiratory protective devices (RPDs) are used as a complementary countermeasure. In devising a protection strategy against influenza for a given population, estimates of the level of protection afforded by different RPDs is valuable. In this article, a risk assessment model previously developed in general form was used to estimate the effectiveness of different types of protective equipment in reducing the rate of infection in an influenza outbreak. It was found that a 50% compliance in donning the device resulted in a significant (at least 50% prevalence and 20% cumulative incidence) reduction in risk for fitted and unfitted N95 respirators, high-filtration surgical masks, and both low-filtration and high-filtration pediatric masks. An 80% compliance rate essentially eliminated the influenza outbreak. The results of the present study, as well as the application of the model to related influenza scenarios, are potentially useful to public health officials in decisions involving resource allocation or education strategies.

A test method to assess the contribution of fluid shear stress to the cleaning of reusable device surfaces.

Adequate cleaning of reusable medical devices is critical for preventing cross-infection among patients. For reusable medical devices, cleaning using mechanical brushes and detergent may not be sufficient to completely remove the infectious contaminants from the surfaces. This study evaluates the role of fluid flow-induced shear stress in the detachment and removal of contaminants from device surfaces. A stainless-steel test coupon, acting as a surrogate for a device surface, was coated with artificial clot of varying mass. The test coupon was exposed to fluid shear stress both with and without an enzymatic detergent. The relationship between clot removal quantity and the applied shear stress was obtained for multiple clot masses. Our results showed that fluid shear increased the effectiveness of the cleaning process. In the absence of flow, soaking the clot surface in the enzymatic detergent removed 67%, 77%, and 95% of the clot for 16 mg, 6.8 mg, and 1 mg initial masses, respectively. In the presence of fluid shear (0.3 Pa for 5 min), approximately 85%, 97%, and 99% of the clot was removed from the surface. The clot mass removed followed a linear relationship (R2 = 0.98) versus the applied fluid shear stress. This study showed that different cleaning processes such as fluid shear and detergent action contribute to the soil removal process. This method could be used to evaluate cleaning protocols for minimizing contaminant residue after the reprocessing of medical devices. © 2018 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater 107B: 1132-1140, 2019.

Inter-Laboratory Characterization of the Velocity Field in the FDA Blood Pump Model Using Particle Image Velocimetry (PIV).

PURPOSE: A credible computational fluid dynamics (CFD) model can play a meaningful role in evaluating the safety and performance of medical devices. A key step towards establishing model credibility is to first validate CFD models with benchmark experimental datasets to minimize model-form errors before applying the credibility assessment process to more complex medical devices. However, validation studies to establish benchmark datasets can be cost prohibitive and difficult to perform. The goal of this initiative sponsored by the U.S. Food and Drug Administration is to generate validation data for a simplified centrifugal pump that mimics blood flow characteristics commonly observed in ventricular assist devices. METHODS: The centrifugal blood pump model was made from clear acrylic and included an impeller, with four equally spaced, straight blades, supported by mechanical bearings. Particle Image Velocimetry (PIV) measurements were performed at several locations throughout the pump by three independent laboratories. A standard protocol was developed for the experiments to ensure that the flow conditions were comparable and to minimize systematic errors during PIV image acquisition and processing. Velocity fields were extracted at the pump entrance, blade passage area, back gap region, and at the outlet diffuser regions. A Newtonian blood analog fluid composed of sodium iodide, glycerin, and water was used as the working fluid. Velocity measurements were made for six different pump flow conditions, with the blood-equivalent flow rate ranging between 2.5 and 7 L/min for pump speeds of 2500 and 3500 rpm. RESULTS: Mean intra- and inter-laboratory variabilities in velocity were ~ 10% at the majority of the measurement locations inside the pump. However, the inter-laboratory variability increased to more than ~ 30% in the exit diffuser region. The variability between the three laboratories for the peak velocity magnitude in the diffuser region ranged from 5 to 25%. The bulk velocity field near the impeller changed proportionally with the rotational speed but was relatively unaffected by the pump flow rate. In contrast, flow in the exit diffuser region was sensitive to both the flow rate and the rotational speed. Specifically, at 3500 rpm, the exit jet tilted toward the inner wall of the diffuser at a flow rate of 2.5 L/min, but the jet tilted towards the outer wall when the flow rate was 7 L/min. CONCLUSIONS: Inter-laboratory experimental mean velocity data (and the corresponding variance) were obtained for the FDA pump model and are available for download at https://nciphub.org/wiki/FDA_CFD . Experimental datasets from the inter-laboratory characterization of benchmark flow models, including the blood pump model presented herein and our previous nozzle model, can be used for validating future CFD studies and to collaboratively develop guidelines on best practices for verification, validation, uncertainty quantification, and credibility assessment of CFD simulations in the evaluation of medical devices (e.g. ASME V&V 40 standards working group).

A mathematical model for assessing the effectiveness of protective devices in reducing risk of infection by inhalable droplets.

Respiratory protective devices (RPDs) are critical for reducing the spread of infection via inhalable droplets. In determining the type of RPD to deploy, it is important to know the reduction in the infection rate that the RPD enables for the given pathogen and population. This paper extends a previously developed susceptible-infected-recovered (SIR) epidemic model to analyse the effect of a protection strategy. An approximate solution to the modified SIR equations, which compares well with a full numerical solution to the equations, was used to derive a simple threshold equation for predicting when growth of the infected population will occur for a given protection strategy. The threshold equation is cast in terms of a generalized reproduction number, which contains the characteristics of the RPDs deployed by the susceptible and infected populations, as well as the degree of compliance in wearing the equipment by both populations. An example calculation showed that with 50% of the susceptible population deploying RPDs that transmit 15% of pathogens, and an unprotected infected population, an otherwise growing infection rate can be converted to one that decays. When the infected population deploys RPDs, the transmission rate for the RPDs worn by the susceptible population can be higher.

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.

Model for Porosity Changes Occurring during Ultrasound-Enhanced Transcorneal Drug Delivery.

Ultrasound-enhanced drug delivery through the cornea has considerable therapeutic potential. However, our understanding of how ultrasound enhances drug transport is poor, as is our ability to predict the increased level of transport for given ultrasound parameters. Described here is a computational model for quantifying changes in corneal porosity during ultrasound exposure. The model is calibrated through experiments involving sodium fluorescein transport through rabbit cornea. Validation was performed using nylon filters, for which the properties are known. It was found that exposure to 800-kHz ultrasound at an intensity 2 W/cm2 for 5 min increased the porosity of the epithelium by a factor of 5. The model can be useful for determining the extent to which ultrasound enhances the amount of drug transported through biological barriers, and the time at which a therapeutic dose is achieved at a given location, for different drugs and exposure strategies.

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.

Quantification of leakage of sub-micron aerosols through surgical masks and facemasks for pediatric use.

Surgical respirators, surgical masks (SMs), and facemasks for pediatric use (FPUs) are routinely used in the U.S. healthcare industry as personal protective equipment (PPE) against infectious diseases. While N95s including surgical respirators have been routinely studied, SMs and FPUs have not received as much attention, particularly in the context of aerosolized threats. This is because SMs and PFUs are not designed to protect against sub-micron aerosols. However, with the possibility of new or re-emerging airborne diseases or bio-aerosol weapons lingering, combined with the limited availability of respirators and logistical issues associated with fit-testing millions, the general adult and pediatric populations may elect to wear SMs and FPUs, respectively, in the case of a pandemic or a bio-terrorist attack. When a person dons a PPE, gaps are created between the wearer's face and the PPE, and aerosols leaking through these gaps can be an important contributor to the risk of infection compared to filtered aerosols. To understand and quantify the contribution of leakage of aerosols through gaps, with particular emphasis on SMs and FPUs, this study investigated leakage of charge-neutralized, polydispersed, dried sodium-chloride aerosols across different brands of PPE. Different breathing rates, aerosol particle sizes, and gap sizes were considered. A few major findings of this study were: (a) leakage, is not a strong function of sub-micron aerosol size; (b) for the same gap size, leakage of aerosols through surgical respirators can often be higher than in SMs and FPUs; and (c) as the gap size increases, the increase in leakage through surgical respirators is higher compared for SMs and FPUs, implying that some SMs and FPUs that possess electret layers may be preferable to N95s that have not been fit-tested. The results obtained can also be used to explain conflicting findings from clinical studies on the effectiveness of SMs when compared to N95s and can be input into risk-assessment models to determine the increase in infection rate resulting from deployment of PPE under less-than-ideal conditions.

Analysis of Transitional and Turbulent Flow Through the FDA Benchmark Nozzle Model Using Laser Doppler Velocimetry.

Transitional and turbulent flow through a simplified medical device model is analyzed as part of the FDA's Critical Path Initiative, designed to improve the process of bringing medical products to market. Computational predictions are often used in the development of devices and reliable in vitro data is needed to validate computational results, particularly estimations of the Reynolds stresses that could play a role in damaging blood elements. The high spatial resolution of laser Doppler velocimetry (LDV) is used to collect two component velocity data within the FDA benchmark nozzle model. Two flow conditions are used to produce flow encompassing laminar, transitional, and turbulent regimes, and viscous stresses, principal Reynolds stresses, and turbulence intensities are calculated from the measured LDV velocities. Axial velocities and viscous stresses are compared to data from a prior inter-laboratory study conducted with particle image velocimetry. Large velocity gradients are observed near the wall in the nozzle throat and in the jet shear layer located in the expansion downstream of the throat, with axial velocity changing as much as 4.5 m/s over 200 µm. Additionally, maximum Reynolds shear stresses of 1000-2000 Pa are calculated in the high shear regions, which are an order of magnitude higher than the peak viscous shear stresses (<100 Pa). It is important to consider the effects of both viscous and turbulent stresses when simulating flow through medical devices. Reynolds stresses above commonly accepted hemolysis thresholds are measured in the nozzle model, indicating that hemolysis may occur under certain flow conditions. As such, the presented turbulence quantities from LDV, which are also available for download at https://fdacfd.nci.nih.gov/ , provide an ideal validation test for computational simulations that seek to characterize the flow field and to predict hemolysis within the FDA nozzle geometry.

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

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.