A sharp interface Lagrangian-Eulerian method for flexible-body fluid-structure interaction.

This paper introduces a sharp-interface approach to simulating fluid-structure interaction (FSI) involving flexible bodies described by general nonlinear material models and across a broad range of mass density ratios. This new flexible-body immersed Lagrangian-Eulerian (ILE) scheme extends our prior work on integrating partitioned and immersed approaches to rigid-body FSI. Our numerical approach incorporates the geometrical and domain solution flexibility of the immersed boundary (IB) method with an accuracy comparable to body-fitted approaches that sharply resolve flows and stresses up to the fluid-structure interface. Unlike many IB methods, our ILE formulation uses distinct momentum equations for the fluid and solid subregions with a Dirichlet-Neumann coupling strategy that connects fluid and solid subproblems through simple interface conditions. As in earlier work, we use approximate Lagrange multiplier forces to treat the kinematic interface conditions along the fluid-structure interface. This penalty approach simplifies the linear solvers needed by our formulation by introducing two representations of the fluid-structure interface, one that moves with the fluid and another that moves with the structure, that are connected by stiff springs. This approach also enables the use of multi-rate time stepping, which allows us to use different time step sizes for the fluid and structure subproblems. Our fluid solver relies on an immersed interface method (IIM) for discrete surfaces to impose stress jump conditions along complex interfaces while enabling the use of fast structured-grid solvers for the incompressible Navier-Stokes equations. The dynamics of the volumetric structural mesh are determined using a standard finite element approach to large-deformation nonlinear elasticity via a nearly incompressible solid mechanics formulation. This formulation also readily accommodates compressible structures with a constant total volume, and it can handle fully compressible solid structures for cases in which at least part of the solid boundary does not contact the incompressible fluid. Selected grid convergence studies demonstrate second-order convergence in volume conservation and in the pointwise discrepancies between corresponding positions of the two interface representations as well as between first and second-order convergence in the structural displacements. The time stepping scheme is also demonstrated to yield second-order convergence. To assess and validate the robustness and accuracy of the new algorithm, comparisons are made with computational and experimental FSI benchmarks. Test cases include both smooth and sharp geometries in various flow conditions. We also demonstrate the capabilities of this methodology by applying it to model the transport and capture of a geometrically realistic, deformable blood clot in an inferior vena cava filter.

Practical implications of the erroneous treatment of exposure time in the Eulerian hemolysis power law model.

BACKGROUND: Eulerian and Lagrangian power-law formulations are both widely used for computational fluid dynamics (CFD) to predict flow-induced hemolysis in blood-contacting medical devices. Both are based on the same empirical power-law correlation between hemolysis and the shear stress and exposure time. In the Lagrangian approach, blood damage is predicted by tracking both the stress and exposure time along a finite number of pathlines in the domain. In the Eulerian approach, a scalar transport equation is solved for a time-linearized damage index within the entire domain. Previous analytical work has demonstrated that there is a fundamental problem with the treatment of exposure time in the Eulerian model formulation such that the only condition under which the model correctly represents the true exposure time is in a flow field with no streamwise velocity variation. However, the practical implications of this limitation have yet to be thoroughly investigated. METHODS: In this study, we demonstrate the inaccuracy of Eulerian hemolysis power-law model predictions due to the erroneous treatment of exposure time by systematically considering four benchmark test cases with increasing degrees of flow acceleration: Poiseuille flow through a straight tube, inclined Couette flow, and flow through a converging tube with two different convergence ratios. RESULTS: Compared with Lagrangian predictions, we show that, as flow acceleration becomes more pronounced, the resultant inaccuracy in the Eulerian predictions increases. For the inclined Couette flow case, there is a small degree of flow acceleration that yields a discrepancy in the range of 10% between Lagrangian and Eulerian predictions. For flows with a larger degree of acceleration, as occurs in the converging tube flow cases, the discrepancy is considerably larger (up to 257%). CONCLUSION: The inaccuracy of hemolysis predictions due to the erroneous treatment of exposure time in the Eulerian power-law model can be significant when there is streamwise velocity variation in the flow field. These results may partially explain the extremely large variability in CFD hemolysis predictions reported in the literature between Lagrangian and Eulerian models.

Modeling flow in an in vitro anatomical cerebrovascular model with experimental validation.

Acute ischemic stroke (AIS) is a leading cause of mortality that occurs when an embolus becomes lodged in the cerebral vasculature and obstructs blood flow in the brain. The severity of AIS is determined by the location and how extensively emboli become lodged, which are dictated in large part by the cerebral flow and the dynamics of embolus migration which are difficult to measure in vivo in AIS patients. Computational fluid dynamics (CFD) can be used to predict the patient-specific hemodynamics and embolus migration and lodging in the cerebral vasculature to better understand the underlying mechanics of AIS. To be relied upon, however, the computational simulations must be verified and validated. In this study, a realistic in vitro experimental model and a corresponding computational model of the cerebral vasculature are established that can be used to investigate flow and embolus migration and lodging in the brain. First, the in vitro anatomical model is described, including how the flow distribution in the model is tuned to match physiological measurements from the literature. Measurements of pressure and flow rate for both normal and stroke conditions were acquired and corresponding CFD simulations were performed and compared with the experiments to validate the flow predictions. Overall, the CFD simulations were in relatively close agreement with the experiments, to within ±7% of the mean experimental data with many of the CFD predictions within the uncertainty of the experimental measurement. This work provides an in vitro benchmark data set for flow in a realistic cerebrovascular model and is a first step towards validating a computational model of AIS.

Modeling Flow in an In Vitro Anatomical Cerebrovascular Model with Experimental Validation.

Acute ischemic stroke (AIS) is a leading cause of mortality that occurs when an embolus becomes lodged in the cerebral vasculature and obstructs blood flow in the brain. The severity of AIS is determined by the location and how extensively emboli become lodged, which are dictated in large part by the cerebral flow and the dynamics of embolus migration which are difficult to measure in vivo in AIS patients. Computational fluid dynamics (CFD) can be used to predict the patient-specific hemodynamics and embolus migration and lodging in the cerebral vasculature to better understand the underlying mechanics of AIS. To be relied upon, however, the computational simulations must be verified and validated. In this study, a realistic in vitro experimental model and a corresponding computational model of the cerebral vasculature are established that can be used to investigate flow and embolus migration and lodging in the brain. First, the in vitro anatomical model is described, including how the flow distribution in the model is tuned to match physiological measurements from the literature. Measurements of pressure and flow rate for both normal and stroke conditions were acquired and corresponding CFD simulations were performed and compared with the experiments to validate the flow predictions. Overall, the CFD simulations were in relatively close agreement with the experiments, to within ±7% of the mean experimental data with many of the CFD predictions within the uncertainty of the experimental measurement. This work provides an in vitro benchmark data set for flow in a realistic cerebrovascular model and is a first step towards validating a computational model of AIS.

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.

Examining the universality of the hemolysis power law model from simulations of the FDA nozzle using calibrated model coefficients.

Computational fluid dynamics (CFD) is widely used to predict mechanical hemolysis in medical devices. The most popular hemolysis model is the stress-based power law model that is based on an empirical correlation between hemoglobin release from red blood cells (RBCs) and the magnitude of flow-induced stress and exposure time. Empirical coefficients are traditionally calibrated using data from experiments in simplified Couette-type blood-shearing devices with uniform-shear laminar flow and well-defined exposure times. Use of such idealized coefficients in simulations of real medical devices with complex hemodynamics is thought to be a primary reason for the historical inaccuracy of absolute hemolysis predictions using the power law model. Craven et al. (Biomech Model Mechanobiol 18:1005-1030, 2019) recently developed a CFD-based Kriging surrogate modeling approach for calibrating empirical coefficients in real devices that could potentially be used to more accurately predict absolute hemolysis. In this study, we use the FDA benchmark nozzle to investigate whether utilizing such calibrated coefficients improves the predictive accuracy of the standard Eulerian power law model. We first demonstrate the credibility of our CFD flow simulations by comparing with particle image velocimetry measurements. We then perform hemolysis simulations and compare the results with in vitro experiments. Importantly, the simulations use coefficients calibrated for the flow of a suspension of bovine RBCs through a small capillary tube, which is relatively comparable to the flow of bovine blood through the FDA nozzle. The results show that the CFD predictions of relative hemolysis in the FDA nozzle are reasonably accurate. The absolute predictions are, however, highly inaccurate with modified index of hemolysis values from CFD in error by roughly three orders of magnitude compared with the experiments, despite using calibrated model coefficients from a relatively similar geometry. We rigorously examine the reasons for the inaccuracy that include differences in the flow conditions in the hemolytic regions of each device and the lack of universality of the hemolysis power law model that is entirely empirical. Thus, while the capability to predict relative hemolysis is valuable for product development, further improvements are needed before the power law model can be relied upon to accurately predict the absolute hemolytic potential of a medical device.

Mechanistic modeling of generic orally inhaled drug products: A workshop summary report.

In silico mechanistic modeling approaches have been designed by various stakeholders with the goal of supporting development and approval of generic orally inhaled drug products in the United States. This review summarizes the presentations and panel discussion that comprised a workshop session concentrated on the use of in silico models to predict various outcomes following orally inhaled drug product administration, including the status of such models and how model credibility may be effectively established.

"Mucosal maps" of the canine nasal cavity: Micro-computed tomography and histology.

Nasal turbinals, delicate and complex bones of the nasal cavity that support respiratory or olfactory mucosa (OM), are now easily studied using high resolution micro-computed tomography (µ-CT). Standard µ-CT currently lacks the capacity to identify OM or other mucosa types without additional radio-opaque staining techniques. However, even unstained mucosa is more radio-opaque than air, and thus mucosal thickness can be discerned. Here, we assess mucosal thickness of the nasal fossa using the cranium of a cadaveric adult dog that was µ-CT scanned with an isotropic resolution of 30 µm, and subsequently histologically sectioned and stained. After co-alignment of µ-CT slice planes to that of histology, mucosal thickness was estimated at four locations. Results based on either µ-CT or histology indicate olfactory mucosa is thicker on average compared with non-olfactory mucosa (non-OM). In addition, olfactory mucosa has a lesser degree of variability than the non-OM. Variability in the latter appears to relate mostly to the varying degree of vascularity of the lamina propria. Because of this, in structures with both specialized vascular respiratory mucosa and OM, such as the first ethmoturbinal (ET I), the range of thickness of OM and non-OM may overlap. Future work should assess the utility of diffusible iodine-based contrast enhanced CT techniques, which can differentiate epithelium from the lamina propria, to enhance our ability to differentiate mucosa types on more rostral ethmoturbinals. This is especially critical for structures such as ET I, which have mixed functional roles in many mammals.

Full-field microscale strain measurements of a nitinol medical device using digital image correlation.

Computational modeling and simulation are commonly used during the development of cardiovascular implants to predict peak strains and strain amplitudes and to estimate the associated durability and fatigue life of these devices. However, simulation validation has historically relied on comparison with surrogate quantities like force and displacement due to barriers to direct strain measurement-most notably, the small spatial scale of these devices. We demonstrate the use of microscale two-dimensional digital image correlation (2D-DIC) to directly characterize full-field surface strains on a nitinol medical device coupon under emulated physiological and hyperphysiological loading. Experiments are performed using a digital optical microscope and a custom, temperature-controlled load frame. Following applicable recommendations from the International DIC Society, hardware and environmental heating studies, noise floor analyses, and in- and out-of-plane rigid body translation studies are first performed to characterize the microscale DIC setup. Uniaxial tension experiments are also performed using a polymeric test specimen to characterize the strain accuracy of the approach up to nominal stains of 5%. Sub-millimeter fields of view and sub-micron displacement accuracies (9nm mean error) are achieved, and systematic (mean) and random (standard deviation) errors in strain are each estimated to be approximately 1,000µÏµ. The system is then demonstrated by acquiring measurements at the root of a 300µm-wide nitinol medical device strut undergoing fixed-free cantilever bending motion. Lüders-like transformation bands are observed originating from the tensile side of the strut that spread toward the neutral axis at an angle of approximately 55°. Despite the inherent limitations of optical microscopy and 2D-DIC, simple and relatively economical setups like that demonstrated herein could provide a practical and accessible solution for characterizing cardiovascular implant micromechanics, validating computational model strain predictions, and guiding the development of next-generation material models for simulating superelastic nitinol.

Fluid-Structure Interaction Models of Bioprosthetic Heart Valve Dynamics in an Experimental Pulse Duplicator.

Computer modeling and simulation is a powerful tool for assessing the performance of medical devices such as bioprosthetic heart valves (BHVs) that promises to accelerate device design and regulation. This study describes work to develop dynamic computer models of BHVs in the aortic test section of an experimental pulse-duplicator platform that is used in academia, industry, and regulatory agencies to assess BHV performance. These computational models are based on a hyperelastic finite element extension of the immersed boundary method for fluid-structure interaction (FSI). We focus on porcine tissue and bovine pericardial BHVs, which are commonly used in surgical valve replacement. We compare our numerical simulations to experimental data from two similar pulse duplicators, including a commercial ViVitro system and a custom platform related to the ViVitro pulse duplicator. Excellent agreement is demonstrated between the computational and experimental results for bulk flow rates, pressures, valve open areas, and the timing of valve opening and closure in conditions commonly used to assess BHV performance. In addition, reasonable agreement is demonstrated for quantitative measures of leaflet kinematics under these same conditions. This work represents a step towards the experimental validation of this FSI modeling platform for evaluating BHVs.

An Immersed Interface Method for Discrete Surfaces.

Fluid-structure systems occur in a range of scientific and engineering applications. The immersed boundary (IB) method is a widely recognized and effective modeling paradigm for simulating fluid-structure interaction (FSI) in such systems, but a difficulty of the IB formulation of these problems is that the pressure and viscous stress are generally discontinuous at fluid-solid interfaces. The conventional IB method regularizes these discontinuities, which typically yields low-order accuracy at these interfaces. The immersed interface method (IIM) is an IB-like approach to FSI that sharply imposes stress jump conditions, enabling higher-order accuracy, but prior applications of the IIM have been largely restricted to numerical methods that rely on smooth representations of the interface geometry. This paper introduces an immersed interface formulation that uses only a C 0 representation of the immersed interface, such as those provided by standard nodal Lagrangian finite element methods. Verification examples for models with prescribed interface motion demonstrate that the method sharply resolves stress discontinuities along immersed boundaries while avoiding the need for analytic information about the interface geometry. Our results also demonstrate that only the lowest-order jump conditions for the pressure and velocity gradient are required to realize global second-order accuracy. Specifically, we demonstrate second-order global convergence rates along with nearly second-order local convergence in the Eulerian velocity field, and between first- and second-order global convergence rates along with approximately first-order local convergence for the Eulerian pressure field. We also demonstrate approximately second-order local convergence in the interfacial displacement and velocity along with first-order local convergence in the fluid traction along the interface. As a demonstration of the method's ability to tackle more complex geometries, the present approach is also used to simulate flow in a patient-averaged anatomical model of the inferior vena cava, which is the large vein that carries deoxygenated blood from the lower extremities back to the heart. Comparisons of the general hemodynamics and wall shear stress obtained by the present IIM and a body-fitted discretization approach show that the present method yields results that are in good agreement with those obtained by the body-fitted approach.

Nasal airflow in the pygmy slow loris (Nycticebus pygmaeus) based on a combined histological, computed tomographic and computational fluid dynamics methodology.

'Macrosmatic' mammals have dedicated olfactory regions within their nasal cavity and segregated airstreams for olfaction and respiratory air-conditioning. Here, we examined the 3D distribution of olfactory surface area (SA) and nasal airflow patterns in the pygmy slow loris (Nycticebus pygmaeus), a primate with primitive nasal cavities, except for enlarged eyes that converge upon the posterodorsal nasal region. Using the head of an adult loris cadaver, we co-registered micro-computed tomography (CT) slices and histology sections to create a 3D reconstruction of the olfactory mucosa distribution. Histological sections were used to measure olfactory surface area and to annotate CT reconstructions. The loris has a complex olfactory recess (∼19% of total nasal SA) with multiple olfactory turbinals. However, the first ethmoturbinal has a rostral projection that extends far anterior to the olfactory recess, lined by ∼90% non-olfactory epithelium. Only one (of three) frontoturbinals bears olfactory mucosa. Computational fluid dynamics simulations of nasal airflow and odorant deposition revealed that there is some segregation of respiratory and olfactory flow in the loris nose, but that it is not as distinct as in well-studied 'macrosmats' (e.g. the dog). In the loris, airflow is segregated medially and laterally to vertically elongated, plate-like first ethmoturbinals. Thus, lorises may be said to have certain macrosmatic anatomical characteristics (e.g. olfactory recess), but not segregated nasal airflow patterns that are optimized for olfaction, as in canids. These results imply that a binary 'microsmatic/macrosmatic' dichotomy does not exist. Rather, mammals appear to exhibit complex trends with respect to specialization of the turbinals and recesses.

Tests of the chromatographic theory of olfaction with highly soluble odors: a combined electro-olfactogram and computational fluid dynamics study in the mouse.

The idea that the vertebrate nasal cavity operates like a gas chromatograph to separate and discriminate odors, referred to herein as the 'chromatographic theory' (CT), has a long and interesting history. Though the last decade has seen renewed interest in the notion, its validity remains in question. Here we examine a necessary condition of the theory: a correlation between nasal odor deposition patterns based on mucus solubility and the distribution of olfactory sensory neuron odotypes. Our recent work in the mouse failed to find such a relationship even across large sorption gradients within the olfactory epithelium (OE). However, these studies did not test extremely soluble odorants or low odor concentrations, factors that could explain our inability to find supporting evidence for the CT. The current study combined computational fluid dynamics (CFD) simulations of odor sorption patterns and electro-olfactogram (EOG) measurements of olfactory sensory neuron responses. The odorants tested were at the extremes of mucus solubility and at a range of concentrations. Results showed no relationship between local odor sorption patterns and EOG response maps. Together, results again failed to support a necessary condition of the CT casting further doubt on the viability of this classical odor coding mechanism.

A CFD-based Kriging surrogate modeling approach for predicting device-specific hemolysis power law coefficients in blood-contacting medical devices.

Most stress-based hemolysis models used in computational fluid dynamics (CFD) are based on an empirical power law correlation between hemolysis generation and the flow-induced stress and exposure time. Empirical model coefficients are typically determined by fitting global hemolysis measurements in simplified blood shearing devices under uniform shear conditions and with well-defined exposure times. CFD simulations using these idealized global empirical coefficients are then performed to predict hemolysis in a medical device with complex hemodynamics. The applicability, however, of this traditional approach of using idealized coefficients for a real device with varying exposure times and non-uniform shear is currently unknown. In this study, we propose a new approach for determining device- and species-specific hemolysis power law coefficients (C, a, and b). The approach consists of calculating multiple hemolysis solutions using different sets of coefficients to map the hemolysis response field in three-dimensional (C, a, b) parameter space. The resultant response field is then compared with experimental data in the same device to determine the coefficients that when incorporated into the locally defined power law model yield correct global hemolysis predictions. We first develop the generalized approach by deriving analytical solutions for simple uniform and non-uniform shear flows (planar Couette flow and circular Poiseuille flow, respectively) that allow us to continuously map the hemolysis solution in (C, a, b) parameter space. We then extend our approach to more practical cases relevant to blood-contacting medical devices by replacing the requirement for an analytical solution in our generalized approach with CFD and Kriging surrogate modeling. Finally, we apply our verified CFD-based Kriging surrogate modeling approach to predict the device- and species-specific power law coefficients for developing laminar flow in a small capillary tube. We show that the resultant coefficients are much different than traditional idealized coefficients obtained from simplified uniform shear experiments and that using such idealized coefficients yields a highly inaccurate prediction of hemolysis that is in error by more than 2000% compared to experiments. Our approach and surrogate modeling framework may be applied to more complex medical devices and readily extended to determine empirical coefficients for other continuum-based models of hemolysis and other forms of flow-induced blood damage (e.g., platelet activation and thrombosis).

Steady Flow in a Patient-Averaged Inferior Vena Cava-Part II: Computational Fluid Dynamics Verification and Validation.

PURPOSE: The embolus trapping performance of inferior vena cava (IVC) filters critically depends on how emboli flow through the IVC and, thereby, on the underlying hemodynamics. Most previous studies of IVC hemodynamics have used computational fluid dynamics (CFD), but few have validated their results by comparing with quantitative experimental measurements of the flow field and none have validated in an anatomical model of the IVC that includes the primary morphological features that influence the hemodynamics (iliac veins, infrarenal curvature, and non-circular vessel cross-section). In this study, we perform verification and validation of CFD simulations in a patient-averaged anatomical model of the IVC. METHODS: Because we are most interested in the fluid dynamics that influence embolus transport and IVC filter embolus trapping, we focus our analyses on the velocity distribution and the amount of swirl and mixing in the infrarenal IVC. A rigorous mesh refinement study is first conducted at the highest flow rate condition to verify the computed solutions. To validate the CFD predictions of the flow patterns, we then compare with particle image velocimetry (PIV) data acquired in the same model in two planes (coronal and sagittal) within the infrarenal IVC at two flow rates corresponding to rest and exercise conditions. RESULTS: Using unstructured hexahedral meshes ranging in size from 800,000 to 102.5 million computational cells, we demonstrate that a coarse mesh may be used to resolve the gross flow patterns and velocity distribution in the IVC. A finer mesh is, however, required to obtain asymptotic mesh convergence of swirl and mixing in the IVC, as quantified by the local normalized helicity, LNH, and the volume-averaged helicity intensity, [Formula: see text]. Based on the results of the mesh refinement study, we use a moderately fine mesh containing approximately 26 million cells for comparison with experimental data. The validation study demonstrates excellent qualitative agreement between CFD predictions and PIV measurements of the velocity field at both conditions. Quantitatively, we show that the global relative comparison error, E, between CFD and PIV ranges from 3 to 11%. By performing sensitivity studies, we demonstrate that the quantitative discrepancy is attributable to a combination of uncertainty in the inlet flow rates and uncertainty associated with precisely aligning the PIV data with the CFD geometry. CONCLUSIONS: Overall, the study demonstrates mesh-convergent CFD simulations that predict IVC flow patterns that agree reasonably well with PIV data, even at exercise conditions where the flow in the IVC is extremely complex.

Steady Flow in a Patient-Averaged Inferior Vena Cava-Part I: Particle Image Velocimetry Measurements at Rest and Exercise Conditions.

PURPOSE: Although many previous computational fluid dynamics (CFD) studies have investigated the hemodynamics in the inferior vena cava (IVC), few studies have compared computational predictions to experimental data, and only qualitative comparisons have been made. Herein, we provide particle image velocimetry (PIV) measurements of flow in a patient-averaged IVC geometry under idealized conditions typical of those used in the preclinical evaluation of IVC filters. METHODS: Measurements are acquired under rest and exercise flow rate conditions in an optically transparent model fabricated using 3D printing. To ensure that boundary conditions are well-defined and to make follow-on CFD validation studies more convenient, fully-developed flow is provided at the inlets (i.e., the iliac veins) by extending them with straight rigid tubing longer than the estimated entrance lengths. Velocity measurements are then obtained at the downstream end of the tubing to confirm Poiseuille inflow boundary conditions. RESULTS: Measurements in the infrarenal IVC reveal that flow profiles are blunter in the sagittal plane (minor axis) than in the coronal plane (major axis). Peak in-plane velocity magnitudes are 4.9 cm/s and 27 cm/s under the rest and exercise conditions, respectively. Flow profiles are less parabolic and exhibit more inflection points at the higher flow rate. Bimodal velocity peaks are also observed in the sagittal plane at the elevated flow condition. CONCLUSIONS: The IVC geometry, boundary conditions, and infrarenal velocity measurements are provided for download on a free and publicly accessible repository at https://doi.org/10.6084/m9.figshare.7198703 . These data will facilitate future CFD validation studies of idealized, in vitro IVC hemodynamics and of similar laminar flows in vascular geometries.

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).

Predicting patient exposure to nickel released from cardiovascular devices using multi-scale modeling.

Many cardiovascular device alloys contain nickel, which if released in sufficient quantities, can lead to adverse health effects. However, in-vivo nickel release from implanted devices and subsequent biodistribution of nickel ions to local tissues and systemic circulation are not well understood. To address this uncertainty, we have developed a multi-scale (material, tissue, and system) biokinetic model. The model links nickel release from an implanted cardiovascular device to concentrations in peri-implant tissue, as well as in serum and urine, which can be readily monitored. The model was parameterized for a specific cardiovascular implant, nitinol septal occluders, using in-vitro nickel release test results, studies of ex-vivo uptake into heart tissue, and in-vivo and clinical measurements from the literature. Our results show that the model accurately predicts nickel concentrations in peri-implant tissue in an animal model and in serum and urine of septal occluder patients. The congruity of the model with these data suggests it may provide useful insight to establish nickel exposure limits and interpret biomonitoring data. Finally, we use the model to predict local and systemic nickel exposure due to passive release from nitinol devices produced using a wide range of manufacturing processes, as well as general relationships between release rate and exposure. These relationships suggest that peri-implant tissue and serum levels of nickel will remain below 5 µg/g and 10 µg/l, respectively, in patients who have received implanted nitinol cardiovascular devices provided the rate of nickel release per device surface area does not exceed 0.074 µg/(cm2 d) and is less than 32 µg/d in total. STATEMENT OF SIGNIFICANCE: The uncertainty in whether in-vitro tests used to evaluate metal ion release from medical products are representative of clinical environments is one of the largest roadblocks to establishing the associated patient risk. We have developed and validated a multi-scale biokinetic model linking nickel release from cardiovascular devices in-vivo to both peri-implant and systemic levels. By providing clinically relevant exposure estimates, the model vastly improves the evaluation of risk posed to patients by the nickel contained within these devices. Our model is the first to address the potential for local and systemic metal ion exposure due to a medical device and can serve as a basis for future efforts aimed at other metal ions and biomedical products.

The Influence of Sniffing on Airflow and Odorant Deposition in the Canine Nasal Cavity.

Nasal airflow plays a critical role in olfaction by transporting odorant from the environment to the olfactory epithelium, where chemical detection occurs. Most studies of olfaction neglect the unsteadiness of sniffing and assume that nasal airflow and odorant transport are "quasi-steady," wherein reality most mammals "sniff." Here, we perform computational fluid dynamics simulations of airflow and odorant deposition in an anatomically accurate model of the coyote (Canis latrans) nasal cavity during quiet breathing, a notional quasi-steady sniff, and unsteady sniffing to: quantify the influence of unsteady sniffing, assess the validity of the quasi-steady assumption, and investigate the functional advantages of sniffing compared to breathing. Our results reveal that flow unsteadiness during sniffing does not appreciably influence qualitative (gross airflow and odorant deposition patterns) or quantitative (time-averaged olfactory flow rate and odorant uptake) measures of olfactory function. A quasi-steady approximation is, therefore, justified for simulating time-averaged olfactory function in the canine nose. Simulations of sniffing versus quiet breathing demonstrate that sniffing delivers about 2.5 times more air to the olfactory recess and results in 2.5-3 times more uptake of highly- and moderately-soluble odorants in the sensory region per unit time, suggesting one reason why dogs actively sniff. Simulations also reveal significantly different deposition patterns in the olfactory region during inspiration for different odorants, and that during expiration there is little retronasal odorant deposition in the sensory region. These results significantly improve our understanding of canine olfaction, and have several practical implications regarding computer simulation of olfactory function.

Tests of the sorption and olfactory "fovea" hypotheses in the mouse.

The spatial distribution of receptors within sensory epithelia (e.g., retina and skin) is often markedly nonuniform to gain efficiency in information capture and neural processing. By contrast, odors, unlike visual and tactile stimuli, have no obvious spatial dimension. What need then could there be for either nearest-neighbor relationships or nonuniform distributions of receptor cells in the olfactory epithelium (OE)? Adrian (Adrian ED. J Physiol 100: 459-473, 1942; Adrian ED. Br Med Bull 6: 330-332, 1950) provided the only widely debated answer to this question when he posited that the physical properties of odors, such as volatility and water solubility, determine a spatial pattern of stimulation across the OE that could aid odor discrimination. Unfortunately, despite its longevity, few critical tests of the "sorption hypothesis" exist. Here we test the predictions of this hypothesis by mapping mouse OE responses using the electroolfactogram (EOG) and comparing these response "maps" to computational fluid dynamics (CFD) simulations of airflow and odorant sorption patterns in the nasal cavity. CFD simulations were performed for airflow rates corresponding to quiet breathing and sniffing. Consistent with predictions of the sorption hypothesis, water-soluble odorants tended to evoke larger EOG responses in the central portion of the OE than the peripheral portion. However, sorption simulation patterns along individual nasal turbinates for particular odorants did not correlate with their EOG response gradients. Indeed, the most consistent finding was a rostral-greater to caudal-lesser response gradient for all the odorants tested that is unexplained by sorption patterns. The viability of the sorption and related olfactory "fovea" hypotheses are discussed in light of these findings.NEW & NOTEWORTHY Two classical ideas concerning olfaction's receptor-surface two-dimensional organization-the sorption and olfactory fovea hypotheses-were found wanting in this study that afforded unprecedented comparisons between electrophysiological recordings in the mouse olfactory epithelium and computational fluid dynamic simulations of nasal airflow. Alternatively, it is proposed that the olfactory receptor layouts in macrosmatic mammals may be an evolutionary contingent state devoid of the functional significance found in other sensory epithelia like the cochlea and retina.