Bryan C. Good

Bio: Bryan C. Good is an academic researcher from Pennsylvania State University. The author has contributed to research in topics: Medicine & Pulsatile flow. The author has an hindex of 6, co-authored 15 publications receiving 151 citations. Previous affiliations of Bryan C. Good include University of Palermo & University of Pittsburgh.

FDA Benchmark Medical Device Flow Models for CFD Validation.

Abstract: 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.

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

Abstract: 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. 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. 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. 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).

Hemodynamics in a Pediatric Ascending Aorta Using a Viscoelastic Pediatric Blood Model.

Abstract: Congenital heart disease is the leading cause of infant death in the United States with over 36,000 newborns affected each year. Despite this growing problem there are few mechanical circulatory support devices designed specifically for pediatric and neonate patients. Previous research has been done investigating pediatric ventricular assist devices (PVADs) assuming blood to be a Newtonian fluid in computational fluid dynamics (CFD) simulations, ignoring its viscoelastic and shear-thinning properties. In contrast to adult VADs, PVADs may be more susceptible to hemolysis and thrombosis due to altered flow into the aorta, and therefore, a more accurate blood model should be used. A CFD solver that incorporates a modified Oldroyd-B model designed specifically for pediatric blood is used to investigate important hemodynamic parameters in a pediatric aortic model under pulsatile flow conditions. These results are compared to Newtonian blood simulations at three physiological pediatric hematocrits. Minor differences are seen in both velocity and wall shear stress (WSS) during early stages of the cardiac cycle between the Newtonian and viscoelastic models. During diastole, significant differences are seen in the velocities in the descending aorta (up to 12%) and in the aortic branches (up to 30%) between the two models. Additionally, peak WSS differences are seen between the models throughout the cardiac cycle. At the onset of diastole, peak WSS differences of 43% are seen between the Newtonian and viscoelastic model and between the 20 and 60% hematocrit viscoelastic models at peak systole of 41%.

Computational modeling of the Food and Drug Administration's benchmark centrifugal blood pump.

Abstract: In order to simulate hemodynamics within centrifugal blood pumps and to predict pump hemolysis, CFD simulations must be thoroughly validated against experimental data. They must also account for and accurately model the specific working fluid in the pump, whether that is a blood-analog solution to match an experimental PIV study or animal blood in a hemolysis experiment. Therefore, the Food and Drug Administration (FDA) benchmark centrifugal blood pump and its database of experimental PIV and hemolysis data were used to thoroughly validate CFD simulations of the same blood pump. A Newtonian blood model was first used to compare to the PIV data with a blood analog fluid while hemolysis data were compared using a power-law hemolysis model fit to porcine blood data. A viscoelastic blood model was then incorporated into the CFD solver to investigate the importance of modeling blood's viscoelasticity in centrifugal pumps. The established computational framework, including a dynamic rotating mesh, animal blood-specific fluid properties and hemolysis modeling, and a k-ω SST turbulence model, was shown to more accurately predict pump pressure heads, velocity fields, and hemolysis compared to previously published CFD studies of the FDA centrifugal pump. The CFD simulations were able to match the FDA pressure and hemolysis data for multiple pump operating conditions, with the CFD results being within the standard deviations of the experimental results. While CFD radial velocity profiles between the impeller blades also compared well to the PIV velocity results, more work is still needed to address the large variability among both experimental and computational predictions of velocity in the diffuser outlet jet. Small differences were observed between the Newtonian and viscoelastic blood models in pressure head and hemolysis at the higher flow rate cases (FDA Conditions 4 and 5) but were more significant at lower flow rate and pump impeller speeds (FDA Condition 1). These results suggest that the importance of accounting for blood's viscoelasticity may be dependent on the specific blood pump operating conditions. This detailed computational framework with improved modeling techniques and an extensive validation procedure will be used in future CFD studies of centrifugal blood pumps to aid in device design and predictions of their biological responses.

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

Abstract: 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.

FDA Benchmark Medical Device Flow Models for CFD Validation.

Abstract: 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.

Advancing Regulatory Science With Computational Modeling for Medical Devices at the FDA's Office of Science and Engineering Laboratories

Abstract: Protecting and promoting public health is the mission of the U.S. Food and Drug Administration (FDA). FDA's Center for Devices and Radiological Health (CDRH), which regulates medical devices marketed in the U.S., envisions itself as the world's leader in medical device innovation and regulatory science-the development of new methods, standards, and approaches to assess the safety, efficacy, quality, and performance of medical devices. Traditionally, bench testing, animal studies, and clinical trials have been the main sources of evidence for getting medical devices on the market in the U.S. In recent years, however, computational modeling has become an increasingly powerful tool for evaluating medical devices, complementing bench, animal and clinical methods. Moreover, computational modeling methods are increasingly being used within software platforms, serving as clinical decision support tools, and are being embedded in medical devices. Because of its reach and huge potential, computational modeling has been identified as a priority by CDRH, and indeed by FDA's leadership. Therefore, the Office of Science and Engineering Laboratories (OSEL)-the research arm of CDRH-has committed significant resources to transforming computational modeling from a valuable scientific tool to a valuable regulatory tool, and developing mechanisms to rely more on digital evidence in place of other evidence. This article introduces the role of computational modeling for medical devices, describes OSEL's ongoing research, and overviews how evidence from computational modeling (i.e., digital evidence) has been used in regulatory submissions by industry to CDRH in recent years. It concludes by discussing the potential future role for computational modeling and digital evidence in medical devices.

Accounting for residence-time in blood rheology models: do we really need non-Newtonian blood flow modelling in large arteries?

Abstract: Patient-specific computational fluid dynamics (CFD) is a promising tool that provides highly resolved haemodynamics information. The choice of blood rheology is an assumption in CFD models that has been subject to extensive debate. Blood is known to exhibit shear-thinning behaviour, and non-Newtonian modelling has been recommended for aneurysmal flows. Current non-Newtonian models ignore rouleaux formation, which is the key player in blood's shear-thinning behaviour. Experimental data suggest that red blood cell aggregation and rouleaux formation require notable red blood cell residence-time (RT) in a low shear rate regime. This study proposes a novel hybrid Newtonian and non-Newtonian rheology model where the shear-thinning behaviour is activated in high RT regions based on experimental data. Image-based abdominal aortic and cerebral aneurysm models are considered and highly resolved CFD simulations are performed using a minimally dissipative solver. Lagrangian particle tracking is used to define a backward particle RT measure and detect stagnant regions with increased rouleaux formation likelihood. Our novel RT-based non-Newtonian model shows a significant reduction in shear-thinning effects and provides haemodynamic results qualitatively identical and quantitatively close to the Newtonian model. Our results have important implications in patient-specific CFD modelling and suggest that non-Newtonian models should be revisited in large artery flows.

Heart Valve Biomechanics and Underlying Mechanobiology

Abstract: Heart valves control unidirectional blood flow within the heart during the cardiac cycle. They have a remarkable ability to withstand the demanding mechanical environment of the heart, achieving lifetime durability by processes involving the ongoing remodeling of the extracellular matrix. The focus of this review is on heart valve functional physiology, with insights into the link between disease-induced alterations in valve geometry, tissue stress, and the subsequent cell mechanobiological responses and tissue remodeling. We begin with an overview of the fundamentals of heart valve physiology and the characteristics and functions of valve interstitial cells (VICs). We then provide an overview of current experimental and computational approaches that connect VIC mechanobiological response to organ- and tissue-level deformations and improve our understanding of the underlying functional physiology of heart valves. We conclude with a summary of future trends and offer an outlook for the future of heart valve mechanobiology, specifically, multiscale modeling approaches, and the potential directions and possible challenges of research development. © 2016 American Physiological Society. Compr Physiol 6:1743-1780, 2016.

Application of Patient-Specific Computational Fluid Dynamics in Coronary and Intra-Cardiac Flow Simulations: Challenges and Opportunities.

Abstract: The emergence of new cardiac diagnostics and therapeutics of the heart has given rise to the challenging field of virtual design and testing of technologies in a patient-specific environment. Given the recent advances in medical imaging, computational power and mathematical algorithms, patient-specific cardiac models can be produced from cardiac images faster, and more efficiently than ever before. The emergence of patient-specific computational fluid dynamics (CFD) has paved the way for the new field of computer-aided diagnostics. This article provides a review of CFD methods, challenges and opportunities in coronary and intra-cardiac flow simulations. It includes a review of market products and clinical trials. Key components of patient-specific CFD are covered briefly which include image segmentation, geometry reconstruction, mesh generation, fluid-structure interaction, and solver techniques.