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Abstract-Intrinsic flow instability has recently been reported in the blood flow pathways of the surgically created total-cavopulmonary connection. Besides its contribution to the hydrodynamic power loss and hepatic blood mixing, this flow unsteadiness causes enormous challenges in its computational fluid dynamics (CFD) modeling. This paper investigates the applicability of hybrid unstructured meshing and solver options of a commercially available CFD package (FLUENT, ANSYS Inc., NH) to model such complex flows. Two patient-specific anatomies with radically different transient flow dynamics are studied both numerically and experimentally (via unsteady particle image velocimetry and flow visualization). A new unstructured hybrid mesh layout consisting of an internal core of hexahedral elements surrounded by transition layers of tetrahedral elements is employed to mesh the flow domain. The numerical simulations are carried out using the parallelized second-order accurate upwind scheme of FLUENT. The numerical validation is conducted in two stages: first, by comparing the overall flow structures and velocity magnitudes of the numerical and experimental flow fields, and then by comparing the spectral content at different points in the connection. The numerical approach showed good quantitative agreement with experiment, and total simulation time was well within a clinically relevant time-scale of our surgical planning application. It also further establishes the ability to conduct accurate numerical simulations using hybrid unstructured meshes, a format that is attractive if one ever wants to pursue automated flow analysis in a large number of complex (patient-specific) geometries.

The complexities of modern biomedicine are rapidly increasing. Thus, modeling and simulation have become increasingly important as a strategy to understand and predict the trajectory of pathophysiology, disease genesis, and disease spread in support of clinical and policy decisions. In such cases, inappropriate or ill-placed trust in the model and simulation outcomes may result in negative outcomes, and hence illustrate the need to formalize the execution and communication of modeling and simulation practices. Although verification and validation have been generally accepted as significant components of a model’s credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the development and reuse of the models. For the past several years, the Committee on Credible Practice of Modeling and Simulation in Healthcare, an interdisciplinary group seeded from a U.S. interagency initiative, has worked to codify best practices. Here, we provide Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative analysis by the Committee’s multidisciplinary membership, followed by a large stakeholder community survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. While biomedical science and clinical care domains have somewhat different requirements and expectations for credible practice, our study converged on rules that would be useful across a broad swath of model types. In brief, the rules are: (1) Define context clearly. (2) Use contextually appropriate data. (3) Evaluate within context. (4) List limitations explicitly. (5) Use version control. (6) Document appropriately. (7) Disseminate broadly. (8) Get independent reviews. (9) Test competing implementations. (10) Conform to standards. Although some of these are common sense guidelines, we have found that many are often missed or misconstrued, even by seasoned practitioners. Computational models are already widely used in basic science to generate new biomedical knowledge. As they penetrate clinical care and healthcare policy, contributing to personalized and precision medicine, clinical safety will require established guidelines for the credible practice of modeling and simulation in healthcare.

By experiments and supporting computations we investigate two methods of transport enhancement in two-dimensional open cellular flows with inertia. First, we introduce a spatial dependence in the velocity field by periodic modulation of the shape of the wall driving the flow; this perturbs the steady-state streamlines in the direction perpendicular to the main flow. Second, we introduce a time dependence through transient acceleration–deceleration of a flat wall driving the flow; surprisingly, even though the streamline portrait changes very little during the transient, there is still significant transport enhancement. The range of Reynolds and Reynolds–Strouhal numbers studied is 7.7[les ]Re[les ]46.5 and 0.52[les ]ReSr[les ]12.55 in the spatially dependent mode and 12[les ]Re[les ]93 and 0.26[les ]ReSr[les ]5.02 in the time-dependent mode. The transport is described theoretically via lobe dynamics. For both modifications, a curve with one maximum characterizes the various transport enhancement measures when plotted as a function of the forcing frequency. A qualitative analysis suggests that the exchange first increases linearly with the forcing frequency and then decreases as 1/Sr for large frequencies.

Modeling and simulation in computational neuroscience is currently a research enterprise to better understand neural systems. It is not yet directly applicable to the problems of patients with brain disease. To be used for clinical applications, there must not only be considerable progress in the field but also a concerted effort to use best practices in order to demonstrate model credibility to regulatory bodies, to clinics and hospitals, to doctors, and to patients. In doing this for neuroscience, we can learn lessons from long-standing practices in other areas of simulation (aircraft, computer chips), from software engineering, and from other biomedical disciplines. In this manuscript, we introduce some basic concepts that will be important in the development of credible clinical neuroscience models: reproducibility and replicability; verification and validation; model configuration; and procedures and processes for credible mechanistic multiscale modeling. We also discuss how garnering strong community involvement can promote model credibility. Finally, in addition to direct usage with patients, we note the potential for simulation usage in the area of Simulation-Based Medical Education, an area which to date has been primarily reliant on physical models (mannequins) and scenario-based simulations rather than on numerical simulations.

As part of an ongoing effort to develop verification and validation (V&V) standards for using computational fluid dynamics (CFD) in the evaluation of medical devices, we have developed idealized flow-based verification benchmarks to assess the implementation of commonly cited power-law based hemolysis models in CFD. Verification process ensures that all governing equations are solved correctly and the model is free of user and numerical errors. To perform verification for power-law based hemolysis modeling, analytical solutions for the Eulerian power-law blood damage model (which estimates hemolysis index (HI) as a function of shear stress and exposure time) were obtained for Couette and inclined Couette flow models, and for Newtonian and non-Newtonian pipe flow models. Subsequently, CFD simulations of fluid flow and HI were performed using Eulerian and three different Lagrangian-based hemolysis models and compared with the analytical solutions. For all the geometries, the blood damage results from the Eulerian-based CFD simulations matched the Eulerian analytical solutions within ∼1%, which indicates successful implementation of the Eulerian hemolysis model. Agreement between the Lagrangian and Eulerian models depended upon the choice of the hemolysis power-law constants. For the commonly used values of power-law constants (α  = 1.9-2.42 and β  = 0.65-0.80), in the absence of flow acceleration, most of the Lagrangian models matched the Eulerian results within 5%. In the presence of flow acceleration (inclined Couette flow), moderate differences (∼10%) were observed between the Lagrangian and Eulerian models. This difference increased to greater than 100% as the beta exponent decreased. These simplified flow problems can be used as standard benchmarks for verifying the implementation of blood damage predictive models in commercial and open-source CFD codes. The current study only used power-law model as an illustrative example to emphasize the need for model verification. Similar verification problems could be developed for other types of hemolysis models (such as strain-based and energy dissipation-based methods). However, since the current study did not include experimental validation, the results from the verified models do not guarantee accurate hemolysis predictions. This verification step must be followed by experimental validation before the hemolysis models can be used for actual device safety evaluations.

The SynCardia total artificial heart (TAH) is the only FDA approved device for replacing hearts in patients with congestive heart failure. It pumps blood via pneumatically driven diaphragms and controls the flow with mechanical valves. While it has been successfully implanted in more than 1,300 patients, its size precludes implantation in smaller patients. This study’s aim was to evaluate the viability of scaled-down TAHs by quantifying thrombogenic potentials from flow patterns. Simulations of systole were first conducted with stationary valves, followed by an advanced full-cardiac-cycle model with moving valves. All the models included deforming diaphragms and platelet suspension in the blood flow. Flow stress-accumulations were computed for the platelet trajectories and thrombogenic potentials were assessed. The simulations successfully captured complex flow patterns during various phases of the cardiac-cycle. Increased stress-accumulations, but within the safety margin of acceptable thrombogenicity, were found in smaller TAHs, indicating that they are clinically viable.