Predictive modeling of the virtual Hemi-Fontan operation for second stage single ventricle palliation: two patient-specific cases

Cell-Driven Fluid Dynamics: A Physical Model of Active Systemic Circulation

Active fluid circulation and transport are key functions of living organisms, which drive efficient delivery of oxygen and nutrients to various physiological compartments. Because fluid circulation occurs in a network, the systemic flux and pressure are not simple outcomes of any given component. Rather, they are emergent properties of network elements and network topology. Moreover, consistent pressure and osmolarity gradients across compartments such as the kidney, interstitium, and vessels are known. How these gradients and network properties are established and maintained is an unanswered question in systems physiology. Previous studies have shown that epithelial cells are fluid pumps that actively generate pressure and osmolarity gradients. Polarization and activity of ion exchangers that drive fluid flux in epithelial cells are affected by pressure and osmolarity gradients. Therefore, there is an unexplored coupling between the pressure and osmolarity in the circulating network. Here we develop a mathematical theory that integrates the influence of pressure and osmolarity on solute transport and explores both cell fluid transport and systemic circulation. This model naturally generates pressure and osmolarity gradients across physiological compartments, and demonstrates how systemic transport properties can depend on cell properties, and how the cell state can depend on systemic properties. When epithelial and endothelial pumps are considered together, we predict how pressures at various points in the network depend on the overall osmolarity of the system. The model can be improved by including physiological geometries and expanding solute species, and highlights the interplay of fluid properties with cell function in living organisms.

Computational Fluid Dynamic Assessment of Patients with Congenital Heart Disease from 3D Rotational Angiography

For congenital heart disease patients, multiple imaging modalities are needed to discern anatomy and functional information such as differential blood flow. During cardiac catheterization, 3D rotational angiography (3DRA) can provide CTA-like images, enabling anatomical information and intraprocedural guidance. We seek to establish whether unique aspects of this technique can also generate quantitative functional blood flow information. We propose that systematic integration of 3DRA imaging, catheter hemodynamic information, and computational fluid dynamics (CFD), can provide quantitative information regarding blood flow dynamics and energetics, without additional imaging or procedures. We report a single center retrospective feasibility study comprising four patients with 3DRA imaging and a complete set of hemodynamic data. 3DRA was processed and segmented to reconstruct vascular regions of interest (ROI), and a computational grid for CFD modeling of blood flow through the ROI was generated. Blood flow was simulated by integrating catheter hemodynamic data to devise boundary conditions at vascular ROI inlets and outlets. The 3DRA-based workflow successfully generated key computational outputs commonly used for cardiovascular applications, including flow patterns, distribution fractions, wall shear stress. Computational outputs obtained were as detailed and resolved as those obtained from more commonly used CT or MR angiography. Accuracy was confirmed by comparing computed flow distributions with measurements for 2 cases, showing less than 2.0% error from the measured data. Systematic integration of catheter hemodynamic information, 3DRA imaging, and CFD modeling, provides an effective and feasible alternative to obtain important quantitative blood flow information and visualization, without additional imaging.

A Modular Framework for Implicit 3D-0D Coupling in Cardiac Mechanics

In numerical simulations of cardiac mechanics, coupling the heart to a model of the circulatory system is essential for capturing physiological cardiac behavior. A popular and efficient technique is to use an electrical circuit analogy, known as a lumped parameter network or zero-dimensional (0D) fluid model, to represent blood flow throughout the cardiovascular system. Due to the strong physical interaction between the heart and the blood circulation, developing accurate and efficient numerical coupling methods remains an active area of research. In this work, we present a modular framework for implicitly coupling three-dimensional (3D) finite element simulations of cardiac mechanics to 0D models of blood circulation. The framework is modular in that the circulation model can be modified independently of the 3D finite element solver, and vice versa. The numerical scheme builds upon a previous work that combines 3D blood flow models with 0D circulation models (3D fluid - 0D fluid). Here, we extend it to couple 3D cardiac tissue mechanics models with 0D circulation models (3D structure - 0D fluid), showing that both mathematical problems can be solved within a unified coupling scheme. The effectiveness, temporal convergence, and computational cost of the algorithm are assessed through multiple examples relevant to the cardiovascular modeling community. Importantly, in an idealized left ventricle example, we show that the coupled model yields physiological pressure-volume loops and naturally recapitulates the isovolumic contraction and relaxation phases of the cardiac cycle without any additional numerical techniques. Furthermore, we provide a new derivation of the scheme inspired by the Approximate Newton Method of Chan (1985), explaining how the proposed numerical scheme combines the stability of monolithic approaches with the modularity and flexibility of partitioned approaches.

Learning reduced-order models for cardiovascular simulations with graph neural networks

Reduced-order models based on physics are a popular choice in cardiovascular modeling due to their efficiency, but they may experience loss in accuracy when working with anatomies that contain numerous junctions or pathological conditions. We develop one-dimensional reduced-order models that simulate blood flow dynamics using a graph neural network trained on three-dimensional hemodynamic simulation data. Given the initial condition of the system, the network iteratively predicts the pressure and flow rate at the vessel centerline nodes. Our numerical results demonstrate the accuracy and generalizability of our method in physiological geometries comprising a variety of anatomies and boundary conditions. Our findings demonstrate that our approach can achieve errors below 3% for pressure and flow rate, provided there is adequate training data. As a result, our method exhibits superior performance compared to physics-based one-dimensional models while maintaining high efficiency at inference time.

Hemi-Fontan and bidirectional Glenn operations result in flow-mediated viscous energy loss at the time of stage II palliation

Background

Superior cavopulmonary connection (SCPC) for stage II palliation of hypoplastic left heart syndrome (HLHS) is achieved most frequently by either a bidirectional Glenn (BDG) or hemi-Fontan (HF) operation. The comparison of flow hemodynamic efficiency at the region of surgical reconstruction and in proximal pulmonary arteries has been evaluated primarily using computational modeling techniques with conflicting reports. The purpose of this descriptive study was to compare flow hemodynamics following stage II (BDG vs HF) using 4-dimensional flow magnetic resonance imaging (4D-Flow MRI) with particular focus on flow-mediated viscous energy loss (EL') under matched hemodynamic conditions.

Methods

Patients with hypoplastic left heart syndrome (HLHS) who underwent either HF or BDG as part of stage II palliation underwent pre-Fontan 4D-Flow MRI. Patients were matched by the pulmonary vascular resistance index, net superior vena cava (SVC) flow, right pulmonary artery (RPA) and left pulmonary artery (LPA) size, and age. Maximum EL' throughout the cardiac cycle was calculated along the SVC-RPA and SVC-LPA tracts.

Results

Eight patients who underwent HF as part of their stage II single ventricle palliation were matched with 8 patients who underwent BDG. There were no differences between the 2 groups in median volumetric indices, including end-diastolic volume (P = .278) and end-systolic volume (P = .213). Moreover, no differences were observed in ejection fraction (P = .091) and cardiac index (P = .324). There also were no differences in peak EL' measured along the SVC-RPA tract (median, 0.05 mW for HF vs 0.04 mW for BDG; P = .365) or along the SVC-LPA tract (median, 0.05 mW vs 0.04 mW; P = .741).

Conclusions

The second stage of surgical palliation of HLHS using either HF or BDG results in similar flow-mediated viscous energy loss throughout the SCPC junction. 4D-Flow MRI and computational methods should be applied together to investigate flow hemodynamic patterns throughout the Fontan palliation and overall efficiency of the Fontan circuit.

Beyond CFD: Emerging methodologies for predictive simulation in cardiovascular health and disease

Physics-based computational models of the cardiovascular system are increasingly used to simulate hemodynamics, tissue mechanics, and physiology in evolving healthy and diseased states. While predictive models using computational fluid dynamics (CFD) originated primarily for use in surgical planning, their application now extends well beyond this purpose. In this review, we describe an increasingly wide range of modeling applications aimed at uncovering fundamental mechanisms of disease progression and development, performing model-guided design, and generating testable hypotheses to drive targeted experiments. Increasingly, models are incorporating multiple physical processes spanning a wide range of time and length scales in the heart and vasculature. With these expanded capabilities, clinical adoption of patient-specific modeling in congenital and acquired cardiovascular disease is also increasing, impacting clinical care and treatment decisions in complex congenital heart disease, coronary artery disease, vascular surgery, pulmonary artery disease, and medical device design. In support of these efforts, we discuss recent advances in modeling methodology, which are most impactful when driven by clinical needs. We describe pivotal recent developments in image processing, fluid-structure interaction, modeling under uncertainty, and reduced order modeling to enable simulations in clinically relevant timeframes. In all these areas, we argue that traditional CFD alone is insufficient to tackle increasingly complex clinical and biological problems across scales and systems. Rather, CFD should be coupled with appropriate multiscale biological, physical, and physiological models needed to produce comprehensive, impactful models of mechanobiological systems and complex clinical scenarios. With this perspective, we finally outline open problems and future challenges in the field.

Learning Whole Heart Mesh Generation From Patient Images for Computational Simulations

Patient-specific cardiac modeling combines geometries of the heart derived from medical images and biophysical simulations to predict various aspects of cardiac function. However, generating simulation-suitable models of the heart from patient image data often requires complicated procedures and significant human effort. We present a fast and automated deep-learning method to construct simulation-suitable models of the heart from medical images. The approach constructs meshes from 3D patient images by learning to deform a small set of deformation handles on a whole heart template. For both 3D CT and MR data, this method achieves promising accuracy for whole heart reconstruction, consistently outperforming prior methods in constructing simulation-suitable meshes of the heart. When evaluated on time-series CT data, this method produced more anatomically and temporally consistent geometries than prior methods, and was able to produce geometries that better satisfy modeling requirements for cardiac flow simulations. Our source code and pretrained networks are available at https://github.com/fkong7/HeartDeformNets.

Automated generation of 0D and 1D reduced-order models of patient-specific blood flow

Three-dimensional (3D) cardiovascular fluid dynamics simulations typically require hours to days of computing time on a high-performance computing cluster. One-dimensional (1D) and lumped-parameter zero-dimensional (0D) models show great promise for accurately predicting blood bulk flow and pressure waveforms with only a fraction of the cost. They can also accelerate uncertainty quantification, optimization, and design parameterization studies. Despite several prior studies generating 1D and 0D models and comparing them to 3D solutions, these were typically limited to either 1D or 0D and a singular category of vascular anatomies. This work proposes a fully automated and openly available framework to generate and simulate 1D and 0D models from 3D patient-specific geometries, automatically detecting vessel junctions and stenosis segments. Our only input is the 3D geometry; we do not use any prior knowledge from 3D simulations. All computational tools presented in this work are implemented in the open-source software platform SimVascular. We demonstrate the reduced-order approximation quality against rigid-wall 3D solutions in a comprehensive comparison with N = 72 publicly available models from various anatomies, vessel types, and disease conditions. Relative average approximation errors of flows and pressures typically ranged from 1% to 10% for both 1D and 0D models, measured at the outlets of terminal vessel branches. In general, 0D model errors were only slightly higher than 1D model errors despite requiring only a third of the 1D runtime. Automatically generated ROMs can significantly speed up model development and shift the computational load from high-performance machines to personal computers.

Multiple blood flow surges during intermittent pneumatic compression: The origins and their implications

Intermittent pneumatic compression (IPC) therapy has been used to enhance peripheral blood flow for prevention and rehabilitation of ischemic-related vascular diseases. A novel phenomenon has been reported that multiple blood flow surges appeared in the skin blood flow signal during each compression, but its mechanism has not been fully revealed. This study aimed to gain insights into the origins of these blood flow surges through experiment and biomechanical modeling methods. Foot skin blood flow (SBF) signals of 13 healthy adults (23.8 ± 0.5 yr old, 7 males) and air cuff pressure signals were recorded during IPC. Lumped parameter modeling and wavelet analysis were adopted to investigate the multiple blood flow surges (named as Peak₁, Peak₂ and Peak₃). The results of the simulated Peak₁ and Peak₂ were in good agreements with the experiment results, suggesting that IPC could enhance foot SBF not only by deflation, but also by inflation. Statistical analysis demonstrated that high frequency compression with more frequent occurrence of Peak₁ and Peak₂ lead to significantly higher (Friedman test, p < 0.001) time-averaged SBF enhancement than the traditional mode. In addition, wavelet analysis showed that the major frequency component of the Peak₃ (0.059 Hz) was within the range of the vascular myogenic activity, suggesting a vascular regulation process triggered by intravascular pressure changes. Our study provide new insights into the mechanism of how IPC enhance foot SBF.

Blood Flow Simulation to Determine the Risk of Thrombosis in the Fontan Circulation: Comparison between Atriopulmonary and Total Cavopulmonary Connections

Three-dimensional computational fluid dynamics (CFD) simulations were performed in the anastomotic region of the Fontan route between the venae cava and pulmonary arteries to investigate the risk of thrombosis due to blood stasis in the Fontan circulation. The finite volume method based on the time-averaged continuity and Navier–Stokes equations combined with the k-ω SST turbulent model was used in the CFD simulations. Low shear rate (SR) and SR on the wall (WSR) of <10 s−1 were used as markers to assess blood stasis as a cause of blood coagulation. Simulated blood flow velocity and both SR and WSR were reduced in the right atrium (RA) as the cavity of a flow channel in the atriopulmonary connection (APC) Fontan model, whereas the values increased in the total cavopulmonary connection (TCPC) Fontan model, which has no cavity. The volume of SR <10 s−1 and wall surface area of WSR <10 s−1 were, respectively, 4.6–261.8 cm3 and 1.2–38.3 cm2 in the APC Fontan model, and 0.1–0.3 cm3 and 0.1–0.6 cm2 in the TCPC Fontan model. The SR and WSR increased in the APC model with a normal-sized RA and the TCPC model as the flow rate of blood from the inferior vena cava increased with exercise; however, the SR and WSR in the RA decreased in the APC model with a dilated RA owing to the development of a recirculating flow. These findings suggest that the APC Fontan has a higher risk of thrombosis due to blood stasis than the TCPC Fontan and a higher RA dilation is associated with a higher risk of thrombosis from a fluid mechanics perspective.

Hemodynamic Response to Device Titration in the Shunted Single Ventricle Circulation: A Patient Cohort Modeling Study

Clinical outcomes of ventricular assist device (VAD) support for shunted single ventricle patients trail the larger population due in part to the challenges in optimizing VAD support and balancing systemic and pulmonary circulations. We sought to understand the response to VAD titration in the shunted circulation using a lumped-parameter network modeling six patient-specific clinical cases. Hemodynamic data from six patients (mean body surface area = 0.30 m2) with a systemic-to-pulmonary shunt was used to construct simulated cases of heart failure and hemodynamic response to increasing VAD flow from 5 to 10 L/min/m2. With increasing VAD flow, the pulmonary arterial pressure stayed relatively constant in five patient cases and increased in one patient case. The mean VAD flow needed to attain an arterial-venous O2 saturation difference of 30% was 6.5 ± 1.2 L/min/m2, which is higher than that in the equivalent nonshunted scenario due to the partial diversion of flow to the pulmonary circulation. The hemodynamic responses to VAD support can vary significantly between specific patient cases; therefore hemodynamic modeling may help guide an individualized approach to perioperative VAD management in the shunted single-ventricle circulation and to understand the patients who may benefit the most from VAD support.

Tunable Blood Shunt for Neonates With Complex Congenital Heart Defects

Despite advancements in procedures and patient care, mortality rates for neonatal recipients of the Norwood procedure, a palliation for single ventricle congenital malformations, remain high due to the use of a fixed-diameter blood shunt. In this study, a new geometrically tunable blood shunt was investigated to address limitations of the current treatment paradigm (e.g., Modified Blalock-Taussig Shunt) by allowing for controlled modulation of blood flow through the shunt to accommodate physiological changes due to the patient’s growth. First, mathematical and computational cardiovascular models were established to investigate the hemodynamic requirements of growing neonatal patients with shunts and to inform design criteria for shunt diameter changes. Then, two stages of prototyping were performed to design, build and test responsive hydrogel systems that facilitate tuning of the shunt diameter by adjusting the hydrogel’s degree of crosslinking. We examined two mechanisms to drive crosslinking: infusion of chemical crosslinking agents and near-UV photoinitiation. The growth model showed that 15–18% increases in shunt diameter were required to accommodate growing patients’ increasing blood flow; similarly, the computational models demonstrated that blood flow magnitudes were in agreement with previous reports. These target levels of diameter increases were achieved experimentally with model hydrogel systems. We also verified that the photocrosslinkable hydrogel, composed of methacrylated dextran, was contact-nonhemolytic. These results demonstrate proof-of-concept feasibility and reflect the first steps in the development of this novel blood shunt. A tunable shunt design offers a new methodology to rebalance blood flow in this vulnerable patient population during growth and development.

On the Periodicity of Cardiovascular Fluid Dynamics Simulations

Three-dimensional cardiovascular fluid dynamics simulations typically require computation of several cardiac cycles before they reach a periodic solution, rendering them computationally expensive. Furthermore, there is currently no standardized method to determine whether a simulation has yet reached that periodic state. In this work, we propose the use of an asymptotic error measurement to quantify the difference between simulation results and their ideal periodic state using open-loop lumped-parameter modeling. We further show that initial conditions are crucial in reducing computational time and develop an automated framework to generate appropriate initial conditions from a one-dimensional model of blood flow. We demonstrate the performance of our initialization method using six patient-specific models from the Vascular Model Repository. In our examples, our initialization protocol achieves periodic convergence within one or two cardiac cycles, leading to a significant reduction in computational cost compared to standard methods. All computational tools used in this work are implemented in the open-source software platform SimVascular. Automatically generated initial conditions have the potential to significantly reduce computation time in cardiovascular fluid dynamics simulations.

Predictive Models for Pulmonary Artery Size in Fontan Patients

We developed models of pulmonary artery (PA) size in Fontan patients as a function of age and body surface area (BSA) using linear regression and breakpoint analyses based on data from 43 Fontan patients divided into two groups: the extracardiac conduit (ECC) group (n = 24) and the non-ECC group (n = 19). Model predictions were compared against those of a non-Fontan control group (n = 18) and published literature. We observed strong positive correlations of the mean PA diameter with BSA (r = 0.9, p < 0.05) and age (r = 0.88, p < 0.05) in the ECC group. The absolute percentage differences between our BSA and age model predictions against published literature were less than 16% and 20%, respectively. Predicted PA size for Fontan patients was consistently smaller than the control group. These models may serve as useful references for clinicians and be utilized to construct 3D anatomic models that correspond to patient body size or age.

Engineering Perspective on Cardiovascular Simulations of Fontan Hemodynamics: Where Do We Stand with a Look Towards Clinical Application

BACKGROUND

Cardiovascular simulations for patients with single ventricles undergoing the Fontan procedure can assess patient-specific hemodynamics, explore surgical advances, and develop personalized strategies for surgery and patient care. These simulations have not yet been broadly accepted as a routine clinical tool owing to a number of limitations. Numerous approaches have been explored to seek innovative solutions for improving methodologies and eliminating these limitations.

PURPOSE

This article first reviews the current state of cardiovascular simulations of Fontan hemodynamics. Then, it will discuss the technical progress of Fontan simulations with the emphasis of its clinical impact, noting that substantial improvements have been made in the considerations of patient-specific anatomy, flow, and blood rheology. The article concludes with insights into potential future directions involving clinical validation, uncertainty quantification, and computational efficiency. The advancements in these aspects could promote the clinical usage of Fontan simulations, facilitating its integration into routine clinical practice.

A Tribute to Ajit Yoganathan's Cardiovascular Fluid Mechanics Lab: A Survey of Its Contributions to Our Understanding of the Physiology and Management of Single-Ventricle Patients

INTRODUCTION

Among patients with congenital heart disease, those born with only a single working ventricle represent a particularly complex sub-population, typically requiring multiple surgeries and suffering from high levels of mortality and morbidity. Their cardiac care is complex and has evolved considerably since surgical palliation was first introduced more than 50 years ago. Improvements in treatment have been driven both by growing clinical experience and by knowledge gained through experimental and computational studies of blood flow in these patients. The Cardiovascular Fluid Mechanics Lab at the Georgia Institute of Technology, founded 30 years ago by Dr. Ajit Yoganathan, has pioneered work in this field.

METHODS

In this review, key contributions of Dr. Yoganathan's Cardiovascular Fluid Dynamics Lab are surveyed, including experimental flow loop studies as well as computational fluid dynamics analyses that address many of the critical challenges that cardiologists and surgeons face in treating these patients, including how to reconstruct cardiovascular anatomy to minimize power loss, balance blood flow distribution at key bifurcation points, and avoid other unfavorable hemodynamic conditions.

CONCLUSIONS

Among many contributions in this field, work from the Cardiovascular Fluid Mechanics Lab has led to novel medical devices and patient-specific computational modeling workflows and software tools. These key contributions from this group have enhanced our understanding of the physiology and management of single-ventricle patients.

Uncertainty quantification implementations in human hemodynamic flows

BACKGROUND AND OBJECTIVE

Human hemodynamic modeling is usually influenced by uncertainties occurring from a considerable unavailability of information linked to the boundary conditions and the physical properties used in the numerical models. Calculating the effect of these uncertainties on the numerical findings along the cardiovascular system is a demanding process due to the complexity of the morphology of the body and the area dynamics. To cope with all these difficulties, Uncertainty Quantification (UQ) methods seem to be an ideal tool.

RESULTS

This study focuses on analyzing and summarizing some of the recent research efforts and directions of implementing UQ in human hemodynamic flows by analyzing 139 research papers. Initially, the suitability of applying this approach is analyzed and demonstrated. Then, an overview of the most significant research work in various fields of biomedical hemodynamic engineering is presented. Finally, it is attempted to identify any possible forthcoming directions for research and methodological progress of UQ in biomedical sciences.

CONCLUSION

This review concludes that by finding the best statistical methods and parameters to represent the propagated uncertainties, while achieving a good interpretation of the interaction between input-output, is crucial for implementing UQ in biomedical sciences.

Fluid-Structure Interaction Simulation of an Intra-Atrial Fontan Connection

Simple Summary

A fluid-structure interaction (FSI) simulation of an intra-atrial Fontan connection was performed. Power loss and pressure drop results fluctuated less during the FSI simulation than during the simulation run with rigid walls, but there were no observable differences in time-averaged pressure drop, connection power loss or hepatic flow distribution. These results suggested that employing a rigid wall is a reasonable assumption when evaluating time-averaged hemodynamic quantities of the Fontan connection under resting breath-held flow conditions.

Abstract

Total cavopulmonary connection (TCPC) hemodynamics has been hypothesized to be associated with long-term complications in single ventricle heart defect patients. Rigid wall assumption has been commonly used when evaluating TCPC hemodynamics using computational fluid dynamics (CFD) simulation. Previous study has evaluated impact of wall compliance on extra-cardiac TCPC hemodynamics using fluid-structure interaction (FSI) simulation. However, the impact of ignoring wall compliance on the presumably more compliant intra-atrial TCPC hemodynamics is not fully understood. To narrow this knowledge gap, this study aims to investigate impact of wall compliance on an intra-atrial TCPC hemodynamics. A patient-specific model of an intra-atrial TCPC is simulated with an FSI model. Patient-specific 3D TCPC anatomies were reconstructed from transverse cardiovascular magnetic resonance images. Patient-specific vessel flow rate from phase-contrast magnetic resonance imaging (MRI) at the Fontan pathway and the superior vena cava under resting condition were prescribed at the inlets. From the FSI simulation, the degree of wall deformation was compared with in vivo wall deformation from phase-contrast MRI data as validation of the FSI model. Then, TCPC flow structure, power loss and hepatic flow distribution (HFD) were compared between rigid wall and FSI simulation. There were differences in instantaneous pressure drop, power loss and HFD between rigid wall and FSI simulations, but no difference in the time-averaged quantities. The findings of this study support the use of a rigid wall assumption on evaluation of time-averaged intra-atrial TCPC hemodynamic metric under resting breath-held condition.

A patient-specific modelling method of blood circulatory system for the numerical simulation of enhanced external counterpulsation

Lumped parameter model (LPM) is a common numerical model for hemodynamic simulation of human's blood circulatory system. The numerical simulation of enhanced external counterpulsation (EECP) is a typical biomechanical simulation process based on the LPM of blood circulatory system. In order to simulate patient-specific hemodynamic effects of EECP and develop best treatment strategy for each individual, this study developed an optimization algorithm to individualize LPM elements. Physiological data from 30 volunteers including approximate aortic pressure, cardiac output, ankle pressure and carotid artery flow were clinically collected as optimization objectives. A closed-loop LPM was established for the simulation of blood circulatory system. Aiming at clinical data, a sensitivity analysis for each element was conducted to identify the significant ones. We improved the traditional simulated annealing algorithm to iteratively optimize the sensitive elements. To verify the accuracy of the patient-specific model, 30 samples of simulated data were compared with clinical measurements. In addition, an EECP experiment was conducted on a volunteer to verify the applicability of the optimized model for the simulation of EECP. For these 30 samples, the optimization results show a slight difference between clinical data and simulated data. The average relative root mean square error is lower than 5%. For the subject of EECP experiment, the relative error of hemodynamic responses during EECP is lower than 10%. This slight error demonstrated a good state of optimization. The optimized modeling algorithm can effectively individualize the LPM for blood circulatory system, which is significant to the numerical simulation of patient-specific hemodynamics.

Assessment of surface roughness and blood rheology on local coronary haemodynamics: a multi-scale computational fluid dynamics study

The surface roughness of the coronary artery is associated with the onset of atherosclerosis. The study applies, for the first time, the micro-scale variation of the artery surface to a 3D coronary model, investigating the impact on haemodynamic parameters which are indicators for atherosclerosis. The surface roughness of porcine coronary arteries have been detailed based on optical microscopy and implemented into a cylindrical section of coronary artery. Several approaches to rheology are compared to determine the benefits/limitations of both single and multiphase models for multi-scale geometry. Haemodynamic parameters averaged over the rough/smooth sections are similar; however, the rough surface experiences a much wider range, with maximum wall shear stress greater than 6 Pa compared to the approximately 3 Pa on the smooth segment. This suggests the smooth-walled assumption may neglect important near-wall haemodynamics. While rheological models lack sufficient definition to truly encompass the micro-scale effects occurring over the rough surface, single-phase models (Newtonian and non-Newtonian) provide numerically stable and comparable results to other coronary simulations. Multiphase models allow for phase interactions between plasma and red blood cells which is more suited to such multi-scale models. These models require additional physical laws to govern advection/aggregation of particulates in the near-wall region.

Multilevel and multifidelity uncertainty quantification for cardiovascular hemodynamics

Standard approaches for uncertainty quantification in cardiovascular modeling pose challenges due to the large number of uncertain inputs and the significant computational cost of realistic three-dimensional simulations. We propose an efficient uncertainty quantification framework utilizing a multilevel multifidelity Monte Carlo (MLMF) estimator to improve the accuracy of hemodynamic quantities of interest while maintaining reasonable computational cost. This is achieved by leveraging three cardiovascular model fidelities, each with varying spatial resolution to rigorously quantify the variability in hemodynamic outputs. We employ two low-fidelity models (zero- and one-dimensional) to construct several different estimators. Our goal is to investigate and compare the efficiency of estimators built from combinations of these two low-fidelity model alternatives and our high-fidelity three-dimensional models. We demonstrate this framework on healthy and diseased models of aortic and coronary anatomy, including uncertainties in material property and boundary condition parameters. Our goal is to demonstrate that for this application it is possible to accelerate the convergence of the estimators by utilizing a MLMF paradigm. Therefore, we compare our approach to single fidelity Monte Carlo estimators and to a multilevel Monte Carlo approach based only on three-dimensional simulations, but leveraging multiple spatial resolutions. We demonstrate significant, on the order of 10 to 100 times, reduction in total computational cost with the MLMF estimators. We also examine the differing properties of the MLMF estimators in healthy versus diseased models, as well as global versus local quantities of interest. As expected, global quantities such as outlet pressure and flow show larger reductions than local quantities, such as those relating to wall shear stress, as the latter rely more heavily on the highest fidelity model evaluations. Similarly, healthy models show larger reductions than diseased models. In all cases, our workflow coupling Dakota's MLMF estimators with the SimVascular cardiovascular modeling framework makes uncertainty quantification feasible for constrained computational budgets.

Cardiovascular models for personalised medicine: Where now and where next?

The aim of this position paper is to provide a brief overview of the current status of cardiovascular modelling and of the processes required and some of the challenges to be addressed to see wider exploitation in both personal health management and clinical practice. In most branches of engineering the concept of the digital twin, informed by extensive and continuous monitoring and coupled with robust data assimilation and simulation techniques, is gaining traction: the Gartner Group listed it as one of the top ten digital trends in 2018. The cardiovascular modelling community is starting to develop a much more systematic approach to the combination of physics, mathematics, control theory, artificial intelligence, machine learning, computer science and advanced engineering methodology, as well as working more closely with the clinical community to better understand and exploit physiological measurements, and indeed to develop jointly better measurement protocols informed by model-based understanding. Developments in physiological modelling, model personalisation, model outcome uncertainty, and the role of models in clinical decision support are addressed and 'where-next' steps and challenges discussed.

Verification of the coupled-momentum method with Womersley's Deformable Wall analytical solution

In this paper, we perform a verification study of the Coupled-Momentum Method (CMM), a 3D fluid-structure interaction (FSI) model which uses a thin linear elastic membrane and linear kinematics to describe the mechanical behavior of the vessel wall. The verification of this model is done using Womersley's deformable wall analytical solution for pulsatile flow in a semi-infinite cylindrical vessel. This solution is, under certain premises, the analytical solution of the CMM and can thus be used for model verification. For the numerical solution, we employ an impedance boundary condition to define a reflection-free outflow boundary condition and thus mimic the physics of the analytical solution, which is defined on a semi-infinite domain. We first provide a rigorous derivation of Womersley's deformable wall theory via scale analysis. We then illustrate different characteristics of the analytical solution such as space-time wave periodicity and attenuation. Finally, we present the verification tests comparing the CMM with Womersley's theory.

Multiscale Modeling of Superior Cavopulmonary Circulation: Hemi-Fontan and Bidirectional Glenn Are Equivalent

Superior cavopulmonary circulation (SCPC) can be achieved by either the Hemi-Fontan (hF) or Bidirectional Glenn (bG) connection. Debate remains as to which results in best hemodynamic results. Adopting patient-specific multiscale computational modeling, we examined both the local dynamics and global physiology to determine if surgical choice can lead to different hemodynamic outcomes. Six patients (age: 3-6 months) underwent cardiac magnetic resonance imaging and catheterization prior to SCPC surgery. For each patient: (1) a finite 3-dimensional (3D) volume model of the preoperative anatomy was constructed to include detailed definition of the distal branch pulmonary arteries, (2) virtual hF and bG operations were performed to create 2 SCPC 3D models, and (3) a specific lumped network representing each patient's entire cardiovascular circulation was developed from clinical data. Using a previously validated multiscale algorithm that couples the 3D models with lumped network, both local flow dynamics, that is, power loss, and global systemic physiology can be quantified. In 2 patients whose preoperative imaging demonstrated significant left pulmonary artery (LPA) stenosis, we performed virtual pulmonary arterioplasty to assess its effect. In one patient, the hF model showed higher power loss (107%) than the bG, while in 3, the power losses were higher in the bG models (18-35%). In the remaining 2 patients, the power loss differences were minor. Despite these variations, for all patients, there were no significant differences between the hF and bG models in hemodynamic or physiological outcomes, including cardiac output, superior vena cava pressure, right-left pulmonary flow distribution, and systemic oxygen delivery. In the 2 patients with LPA stenosis, arterioplasty led to better LPA flow (5-8%) while halving the power loss, but without important improvements in SVC pressure or cardiac output. Despite power loss differences, both hF and bG result in similar SCPC hemodynamics and physiology outcome. This suggests that for SCPC, the pre-existing patient-specific physiology and condition, such as pulmonary vascular resistance, are more deterministic in the hemodynamic performance than the type of surgical palliation. Multiscale modeling can be a decision-assist tool to assess whether an extensive LPA reconstruction is needed at the time of SCPC for LPA stenosis.

Mixed impact of torsion on LV hemodynamics: A CFD study based on the Chimera technique

Image-based patient-specific Computational Fluid Dynamics (CFD) models of the Left Ventricle (LV) can be used to quantify hemodynamics-based biomarkers that can support the clinicians in the early diagnosis, follow-up and treatment planning of patients, beyond the capabilities of the current imaging modalities. We propose a workflow to build patient-specific CFD models of the LV with moving boundaries based on the Chimera technique to overcome the convergence issues previously encountered by means of the Arbitrarian Lagrangian Eulerian approach. The workflow was tested while investigating whether the torsional motion has an impact on LV fluid dynamics. Starting from 3D cine MRI scans of a healthy volunteer, six cardiac cycles were simulated in three CFD LV models: with no, physiological, and exaggerated torsion. The Chimera technique was robust in handling the impulsive motion of the LV endocardium, allowing to notice cycle-to-cycle variations in every simulated case. Torsion affected slightly velocity, vorticity, WSS. It did not affect energy loss and induced a double-sided effect in terms of residence time: the particles ejected in one beat decreased, whereas the motility of the particles remaining in the LV was affected only in the exaggerated torsion case, indicating that implementation of torsion can be discarded in case of physiological levels. Nonetheless, caution is warranted when interpreting these results given the absence of the mitral valve, the papillary muscles, and the trabeculae. The effects of the mitral valve will be evaluated within an Fluid Structure Interaction simulation framework as further development of the current model.

A Hybrid Experimental-Computational Modeling Framework for Cardiovascular Device Testing

Significant advances in biomedical science often leverage powerful computational and experimental modeling platforms. We present a framework named physiology simulation coupled experiment ("PSCOPE") that can capitalize on the strengths of both types of platforms in a single hybrid model. PSCOPE uses an iterative method to couple an in vitro mock circuit to a lumped-parameter numerical simulation of physiology, obtaining closed-loop feedback between the two. We first compared the results of Fontan graft obstruction scenarios modeled using both PSCOPE and an established multiscale computational fluid dynamics method; the normalized root-mean-square error values of important physiologic parameters were between 0.1% and 2.1%, confirming the fidelity of the PSCOPE framework. Next, we demonstrate an example application of PSCOPE to model a scenario beyond the current capabilities of multiscale computational methods-the implantation of a Jarvik 2000 blood pump for cavopulmonary support in the single-ventricle circulation; we found that the commercial Jarvik 2000 controller can be modified to produce a suitable rotor speed for augmenting cardiac output by approximately 20% while maintaining blood pressures within safe ranges. The unified modeling framework enables a testing environment which simultaneously operates a medical device and performs computational simulations of the resulting physiology, providing a tool for physically testing medical devices with simulated physiologic feedback.

Fontan Surgical Planning: Previous Accomplishments, Current Challenges, and Future Directions

The ultimate goal of Fontan surgical planning is to provide additional insights into the clinical decision-making process. In its current state, surgical planning offers an accurate hemodynamic assessment of the pre-operative condition, provides anatomical constraints for potential surgical options, and produces decent post-operative predictions if boundary conditions are similar enough between the pre-operative and post-operative states. Moving forward, validation with post-operative data is a necessary step in order to assess the accuracy of surgical planning and determine which methodological improvements are needed. Future efforts to automate the surgical planning process will reduce the individual expertise needed and encourage use in the clinic by clinicians. As post-operative physiologic predictions improve, Fontan surgical planning will become an more effective tool to accurately model patient-specific hemodynamics.

Computational Investigation of a Self-Powered Fontan Circulation

Children born with anatomic or functional "single ventricle" must progress through two or more major operations to sustain life. This management sequence culminates in the total cavopulmonary connection, or "Fontan" operation. A consequence of the "Fontan circulation", however, is elevated central venous pressure and inadequate ventricular preload, which contribute to continued morbidity. We propose a solution to these problems by increasing pulmonary blood flow using an "injection jet" (IJS) in which the source of blood flow and energy is the ventricle itself. The IJS has the unique property of lowering venous pressure while enhancing pulmonary blood flow and ventricular preload. We report preliminary results of an analysis of this circulation using a tightly-coupled, multi-scale computational fluid dynamics model. Our calculations show that, constraining the excess volume load to the ventricle at 50% (pulmonary to systemic flow ratio of 1.5), an optimally configured IJS can lower venous pressure by 3 mmHg while increasing systemic oxygen delivery. Even this small decrease in venous pressure may have substantial clinical impact on the Fontan patient. These findings support the potential for a straightforward surgical modification to decrease venous pressure, and perhaps improve clinical outcome in selected patients.

Evaluation of the anatomic and hemodynamic abnormalities in tricuspid atresia before and after surgery using computational fluid dynamics

Analysis of hemodynamics inside tricuspid atresia (TA) chamber is essential to the understanding of TA for optimal treatment. In this study, we introduced a combined computational fluid dynamics (CFD) to simulate blood flow in the left ventricle (LV) to study the diastolic flow changes in TA.Real-time 3-dimentional echocardiography loops (ECHO) were acquired in normal control group, in TA patients before surgery (pre-op group) and after surgery (post-op group). ECHO loops were reconstructed and simulated by CFD, the geometric, volumetric changes, and vortices in the LV were studies and compare among 3 groups.Compared with the control group, pre-op TA patients demonstrated significant LV remodeling, manifesting with smaller LV length, larger diameter, width and spherical index, as well as lager volumes; post-op TA group showed revisions in values of both geometric and volumetric measurements. CDF also demonstrated the abnormality of vortices in the pre-op TA patients and the alteration of existence and measurements of vortex in postoperation group.Echo-based CFD modeling can show the abnormality of TA in both LV geometric, volumetric measurements and intracardiac vortices; and CFD is capable to demonstrate the alterations of LV after Fontan and Glenn surgical procedure.

Virtual medicine: Utilization of the advanced cardiac imaging patient avatar for procedural planning and facilitation

Advances in imaging technology have led to a paradigm shift from planning of cardiovascular procedures and surgeries requiring the actual patient in a "brick and mortar" hospital to utilization of the digitalized patient in the virtual hospital. Cardiovascular computed tomographic angiography (CCTA) and cardiovascular magnetic resonance (CMR) digitalized 3-D patient representation of individual patient anatomy and physiology serves as an avatar allowing for virtual delineation of the most optimal approaches to cardiovascular procedures and surgeries prior to actual hospitalization. Pre-hospitalization reconstruction and analysis of anatomy and pathophysiology previously only accessible during the actual procedure could potentially limit the intrinsic risks related to time in the operating room, cardiac procedural laboratory and overall hospital environment. Although applications are specific to areas of cardiovascular specialty focus, there are unifying themes related to the utilization of technologies. The virtual patient avatar computer can also be used for procedural planning, computational modeling of anatomy, simulation of predicted therapeutic result, printing of 3-D models, and augmentation of real time procedural performance. Examples of the above techniques are at various stages of development for application to the spectrum of cardiovascular disease processes, including percutaneous, surgical and hybrid minimally invasive interventions. A multidisciplinary approach within medicine and engineering is necessary for creation of robust algorithms for maximal utilization of the virtual patient avatar in the digital medical center. Utilization of the virtual advanced cardiac imaging patient avatar will play an important role in the virtual health care system. Although there has been a rapid proliferation of early data, advanced imaging applications require further assessment and validation of accuracy, reproducibility, standardization, safety, efficacy, quality, cost effectiveness, and overall value to medical care.

Computational Fluid Dynamics and Additive Manufacturing to Diagnose and Treat Cardiovascular Disease

Noninvasive engineering models are now being used for diagnosing and planning the treatment of cardiovascular disease. Techniques in computational modeling and additive manufacturing have matured concurrently, and results from simulations can inform and enable the design and optimization of therapeutic devices and treatment strategies. The emerging synergy between large-scale simulations and 3D printing is having a two-fold benefit: first, 3D printing can be used to validate the complex simulations, and second, the flow models can be used to improve treatment planning for cardiovascular disease. In this review, we summarize and discuss recent methods and findings for leveraging advances in both additive manufacturing and patient-specific computational modeling, with an emphasis on new directions in these fields and remaining open questions.

On the choice of outlet boundary conditions for patient-specific analysis of aortic flow using computational fluid dynamics

Boundary conditions (BCs) are an essential part in computational fluid dynamics (CFD) simulations of blood flow in large arteries. Although several studies have investigated the influence of BCs on predicted flow patterns and hemodynamic wall parameters in various arterial models, there is a lack of comprehensive assessment of outlet BCs for patient-specific analysis of aortic flow. In this study, five different sets of outlet BCs were tested and compared using a subject-specific model of a normal aorta. Phase-contrast magnetic resonance imaging (PC-MRI) was performed on the same subject and velocity profiles extracted from the in vivo measurements were used as the inlet boundary condition. Computational results obtained with different outlet BCs were assessed in terms of their agreement with the PC-MRI velocity data and key hemodynamic parameters, such as pressure and flow waveforms and wall shear stress related indices. Our results showed that the best overall performance was achieved by using a well-tuned three-element Windkessel model at all model outlets, which not only gave a good agreement with in vivo flow data, but also produced physiological pressure waveforms and values. On the other hand, opening outlet BCs with zero pressure at multiple outlets failed to reproduce any physiologically relevant flow and pressure features.

Tetralogy of Fallot Surgical Repair: Shunt Configurations, Ductus Arteriosus and the Circle of Willis

In this study, hemodynamic performance of three novel shunt configurations that are considered for the surgical repair of tetralogy of Fallot (TOF) disease are investigated in detail. Clinical experience suggests that the shunt location, connecting angle, and its diameter can influence the post-operative physiology and the neurodevelopment of the neonatal patient. An experimentally validated second order computational fluid dynamics (CFD) solver and a parametric neonatal diseased great artery model that incorporates the ductus arteriosus (DA) and the full patient-specific circle of Willis (CoW) are employed. Standard truncated resistance CFD boundary conditions are compared with the full cerebral arterial system, which resulted 21, -13, and 37% difference in flow rate at the brachiocephalic, left carotid, and subclavian arteries, respectively. Flow splits at the aortic arch and cerebral arteries are calculated and found to change with shunt configuration significantly for TOF disease. The central direct shunt (direct shunt) has pulmonary flow 5% higher than central oblique shunt (oblique shunt) and 23% higher than modified Blalock Taussig shunt (RPA shunt) while the DA is closed. Maximum wall shear stress (WSS) in the direct shunt configuration is 9 and 60% higher than that of the oblique and RPA shunts, respectively. Patent DA, significantly eliminated the pulmonary flow control function of the shunt repair. These results suggests that, due to the higher flow rates at the pulmonary arteries, the direct shunt, rather than the central oblique, or right pulmonary artery shunts could be preferred by the surgeon. This extended model introduced new hemodynamic performance indices for the cerebral circulation that can correlate with the post-operative neurodevelopment quality of the patient.

Patient-specific parameter estimation in single-ventricle lumped circulation models under uncertainty

Computational models of cardiovascular physiology can inform clinical decision-making, providing a physically consistent framework to assess vascular pressures and flow distributions, and aiding in treatment planning. In particular, lumped parameter network (LPN) models that make an analogy to electrical circuits offer a fast and surprisingly realistic method to reproduce the circulatory physiology. The complexity of LPN models can vary significantly to account, for example, for cardiac and valve function, respiration, autoregulation, and time-dependent hemodynamics. More complex models provide insight into detailed physiological mechanisms, but their utility is maximized if one can quickly identify patient specific parameters. The clinical utility of LPN models with many parameters will be greatly enhanced by automated parameter identification, particularly if parameter tuning can match non-invasively obtained clinical data. We present a framework for automated tuning of 0D lumped model parameters to match clinical data. We demonstrate the utility of this framework through application to single ventricle pediatric patients with Norwood physiology. Through a combination of local identifiability, Bayesian estimation and maximum a posteriori simplex optimization, we show the ability to automatically determine physiologically consistent point estimates of the parameters and to quantify uncertainty induced by errors and assumptions in the collected clinical data. We show that multi-level estimation, that is, updating the parameter prior information through sub-model analysis, can lead to a significant reduction in the parameter marginal posterior variance. We first consider virtual patient conditions, with clinical targets generated through model solutions, and second application to a cohort of four single-ventricle patients with Norwood physiology. Copyright © 2016 John Wiley & Sons, Ltd.

SimVascular: An Open Source Pipeline for Cardiovascular Simulation

Patient-specific cardiovascular simulation has become a paradigm in cardiovascular research and is emerging as a powerful tool in basic, translational and clinical research. In this paper we discuss the recent development of a fully open-source SimVascular software package, which provides a complete pipeline from medical image data segmentation to patient-specific blood flow simulation and analysis. This package serves as a research tool for cardiovascular modeling and simulation, and has contributed to numerous advances in personalized medicine, surgical planning and medical device design. The SimVascular software has recently been refactored and expanded to enhance functionality, usability, efficiency and accuracy of image-based patient-specific modeling tools. Moreover, SimVascular previously required several licensed components that hindered new user adoption and code management and our recent developments have replaced these commercial components to create a fully open source pipeline. These developments foster advances in cardiovascular modeling research, increased collaboration, standardization of methods, and a growing developer community.

Hemodynamics of patient-specific aorta-pulmonary shunt configurations

Optimal hemodynamics in aorta-pulmonary shunt reconstruction is essential for improved post-operative recovery of the newborn congenital heart disease patient. However, prior to in vivo execution, the prediction of post-operative hemodynamics is extremely challenging due to the interplay of multiple confounding physiological factors. It is hypothesized that the post-operative performance of the surgical shunt can be predicted through computational blood flow simulations that consider patient size, shunt configuration, cardiac output and the complex three-dimensional disease anatomy. Utilizing only the routine patient-specific pre-surgery clinical data sets, we demonstrated an intelligent decision-making process for a real patient having pulmonary artery atresia and ventricular septal defect. For this patient, a total of 12 customized candidate shunt configurations are contemplated and reconstructed virtually using a sketch-based computer-aided anatomical editing tool. Candidate shunt configurations are evaluated based on the parameters that are computed from the flow simulations, which include 3D flow complexity, outlet flow splits, shunt patency, coronary perfusion and energy loss. Our results showed that the modified Blalock-Taussig (mBT) shunt has 12% higher right pulmonary artery (RPA) and 40% lower left pulmonary artery (LPA) flow compared to the central shunt configuration. Also, the RPA flow regime is distinct from the LPA, creating an uneven flow split at the pulmonary arteries. For all three shunt sizes, right mBT innominate and central configurations cause higher pulmonary artery (PA) flow and lower coronary artery pressure than right and left mBT subclavian configurations. While there is a trade-off between energy loss, flow split and coronary artery pressure, overall, the mBT shunts provide sufficient PA perfusion with higher coronary artery pressures and could be preferred for similar patients having PA overflow risk. Central shunts would be preferred otherwise particularly for cases with very low PA overflow risk.

Can time-averaged flow boundary conditions be used to meet the clinical timeline for Fontan surgical planning?

Cardiovascular simulations have great potential as a clinical tool for planning and evaluating patient-specific treatment strategies for those suffering from congenital heart diseases, specifically Fontan patients. However, several bottlenecks have delayed wider deployment of the simulations for clinical use; the main obstacle is simulation cost. Currently, time-averaged clinical flow measurements are utilized as numerical boundary conditions (BCs) in order to reduce the computational power and time needed to offer surgical planning within a clinical time frame. Nevertheless, pulsatile blood flow is observed in vivo, and its significant impact on numerical simulations has been demonstrated. Therefore, it is imperative to carry out a comprehensive study analyzing the sensitivity of using time-averaged BCs. In this study, sensitivity is evaluated based on the discrepancies between hemodynamic metrics calculated using time-averaged and pulsatile BCs; smaller discrepancies indicate less sensitivity. The current study incorporates a comparison between 3D patient-specific CFD simulations using both the time-averaged and pulsatile BCs for 101 Fontan patients. The sensitivity analysis involves two clinically important hemodynamic metrics: hepatic flow distribution (HFD) and indexed power loss (iPL). Paired demographic group comparisons revealed that HFD sensitivity is significantly different between single and bilateral superior vena cava cohorts but no other demographic discrepancies were observed for HFD or iPL. Multivariate regression analyses show that the best predictors for sensitivity involve flow pulsatilities, time-averaged flow rates, and geometric characteristics of the Fontan connection. These predictors provide patient-specific guidelines to determine the effectiveness of analyzing patient-specific surgical options with time-averaged BCs within a clinical time frame.

Hemodynamic analysis of outflow grafting positions of a ventricular assist device using closed-loop multiscale CFD simulations: Preliminary results

Subclavian arteries are a possible alternate location for left ventricular assist device (LVAD) outflow grafts due to easier surgical access and application in high risk patients. As vascular blood flow mechanics strongly influence the clinical outcome, insights into the hemodynamics during LVAD support can be used to evaluate different grafting locations. In this study, the feasibility of left and right subclavian artery (SA) grafting was investigated for the HeartWare HVAD with a numerical multiscale model. A 3-D CFD model of the aortic arch was coupled to a lumped parameter model of the cardiovascular system under LVAD support. Grafts in the left and right SA were placed at three different anastomoses angles (90°, 60° and 30°). Additionally, standard grafting of the ascending and descending aorta was modelled. Full support LVAD (5l/min) and partial support LVAD (3l/min) in co-pulsation and counter-pulsation mode were analysed. The grafting positions were investigated regarding coronary and cerebral perfusion. Furthermore, the influence of the anastomosis angle on wall shear stress (WSS) was evaluated. Grafting of left or right subclavian arteries has similar hemodynamic performance in comparison to standard cannula positions. Angularity change of the graft anastomosis from 90° to 30° slightly increases the coronary and cerebral blood flow by 6-9% while significantly reduces the WSS by 35%. Cannulation of the SA is a feasible anastomosis location for the HVAD in the investigated vessel geometry.

Computational modeling and engineering in pediatric and congenital heart disease

PURPOSE OF REVIEW

Recent methodological advances in computational simulations are enabling increasingly realistic simulations of hemodynamics and physiology, driving increased clinical utility. We review recent developments in the use of computational simulations in pediatric and congenital heart disease, describe the clinical impact in modeling in single-ventricle patients, and provide an overview of emerging areas.

RECENT FINDINGS

Multiscale modeling combining patient-specific hemodynamics with reduced order (i.e., mathematically and computationally simplified) circulatory models has become the de-facto standard for modeling local hemodynamics and 'global' circulatory physiology. We review recent advances that have enabled faster solutions, discuss new methods (e.g., fluid structure interaction and uncertainty quantification), which lend realism both computationally and clinically to results, highlight novel computationally derived surgical methods for single-ventricle patients, and discuss areas in which modeling has begun to exert its influence including Kawasaki disease, fetal circulation, tetralogy of Fallot (and pulmonary tree), and circulatory support.

SUMMARY

Computational modeling is emerging as a crucial tool for clinical decision-making and evaluation of novel surgical methods and interventions in pediatric cardiology and beyond. Continued development of modeling methods, with an eye towards clinical needs, will enable clinical adoption in a wide range of pediatric and congenital heart diseases.

Patient-Specific Surgical Planning, Where Do We Stand? The Example of the Fontan Procedure

The Fontan surgery for single ventricle heart defects is a typical example of a clinical intervention in which patient-specific computational modeling can improve patient outcome: with the functional heterogeneity of the presenting patients, which precludes generic solutions, and the clear influence of the surgically-created Fontan connection on hemodynamics, it is acknowledged that individualized computational optimization of the post-operative hemodynamics can be of clinical value. A large body of literature has thus emerged seeking to provide clinically relevant answers and innovative solutions, with an increasing emphasis on patient-specific approaches. In this review we discuss the benefits and challenges of patient-specific simulations for the Fontan surgery, reviewing state of the art solutions and avenues for future development. We first discuss the clinical impact of patient-specific simulations, notably how they have contributed to our understanding of the link between Fontan hemodynamics and patient outcome. This is followed by a survey of methodologies for capturing patient-specific hemodynamics, with an emphasis on the challenges of defining patient-specific boundary conditions and their extension for prediction of post-operative outcome. We conclude with insights into potential future directions, noting that one of the most pressing issues might be the validation of the predictive capabilities of the developed framework.

In Vitro Assessment of the Assisted Bidirectional Glenn Procedure for Stage One Single Ventricle Repair

This in vitro study compares the hemodynamic performance of the Norwood and the Glenn circulations to assess the performance of a novel assisted bidirectional Glenn (ABG) procedure for stage one single ventricle surgery. In the ABG, the flow in a bidirectional Glenn procedure is assisted by injection of a high-energy flow stream from the systemic circulation using an aorta-caval shunt with nozzle. The aim is to explore experimentally the potential of the ABG as a surgical alternative to current surgical practice. The experiments are directly compared against previously published numerical simulations. A multiscale mock circulatory system was used to measure the hemodynamic performance of the three circulations. For each circulation, the system was tested using both low and high values of pulmonary vascular resistance. Resulting parameters measured were: pressure and flow rate at left/right pulmonary artery and superior vena cava (SVC). Systemic oxygen delivery (OD) was calculated. A parametric study of the ratio of ABG nozzle to shunt diameter was done. We report time-based comparisons with numerical simulations for the three surgical variants tested. The ABG circulation demonstrated an increase of 30-38% in pulmonary flow with a 2-3.7 mmHg increase in SVC pressure compared to the Glenn and a 4-14% higher systemic OD than either the Norwood or the Glenn. The nozzle/shunt diameter ratio affected the local hemodynamics. These experimental results agreed with those of the numerical model: mean flow values were not significantly different (p > 0.05) while mean pressures were comparable within 1.2 mmHg. The results verify the approaches providing two tools to study this complicated circulation. Using a realistic experimental model we demonstrate the performance of a novel surgical procedure with potential to improve patient hemodynamics in early palliation of the univentricular circulation.

A multiscale model for the study of cardiac biomechanics in single-ventricle surgeries: a clinical case

Complex congenital heart disease characterized by the underdevelopment of one ventricular chamber (single ventricle (SV) circulation) is normally treated with a three-stage surgical repair. This study aims at developing a multiscale computational framework able to couple a patient-specific three-dimensional finite-element model of the SV to a patient-specific lumped parameter (LP) model of the whole circulation, in a closed-loop fashion. A sequential approach was carried out: (i) cardiocirculatory parameters were estimated by using a fully LP model; (ii) ventricular material parameters and unloaded geometry were identified by means of the stand-alone, three-dimensional model of the SV; and (iii) the three-dimensional model of SV was coupled to the LP model of the circulation, thus closing the loop and creating a multiscale model. Once the patient-specific multiscale model was set using pre-operative clinical data, the virtual surgery was performed, and the post-operative conditions were simulated. This approach allows the analysis of local information on ventricular function as well as global parameters of the cardiovascular system. This methodology is generally applicable to patients suffering from SV disease for surgical planning at different stages of treatment. As an example, a clinical case from stage 1 to stage 2 is considered here.

A simulation protocol for exercise physiology in Fontan patients using a closed loop lumped-parameter model

BACKGROUND

Reduced exercise capacity is nearly universal among Fontan patients, though its etiology is not yet fully understood. While previous computational studies have attempted to model Fontan exercise, they did not fully account for global physiologic mechanisms nor directly compare results against clinical and physiologic data.

METHODS

In this study, we developed a protocol to simulate Fontan lower-body exercise using a closed-loop lumped-parameter model describing the entire circulation. We analyzed clinical exercise data from a cohort of Fontan patients, incorporated previous clinical findings from literature, quantified a comprehensive list of physiological changes during exercise, translated them into a computational model of the Fontan circulation, and designed a general protocol to model Fontan exercise behavior. Using inputs of patient weight, height, and if available, patient-specific reference heart rate (HR) and oxygen consumption, this protocol enables the derivation of a full set of parameters necessary to model a typical Fontan patient of a given body-size over a range of physiologic exercise levels.

RESULTS

In light of previous literature data and clinical knowledge, the model successfully produced realistic trends in physiological parameters with exercise level. Applying this method retrospectively to a set of clinical Fontan exercise data, direct comparison between simulation results and clinical data demonstrated that the model successfully reproduced the average exercise response of a cohort of typical Fontan patients.

CONCLUSION

This work is intended to offer a foundation for future advances in modeling Fontan exercise, highlight the needs in clinical data collection, and provide clinicians with quantitative reference exercise physiologies for Fontan patients.

Using 4D Cardiovascular Magnetic Resonance Imaging to Validate Computational Fluid Dynamics: A Case Study

Computational fluid dynamics (CFD) can have a complementary predictive role alongside the exquisite visualization capabilities of 4D cardiovascular magnetic resonance (CMR) imaging. In order to exploit these capabilities (e.g., for decision-making), it is necessary to validate computational models against real world data. In this study, we sought to acquire 4D CMR flow data in a controllable, experimental setup and use these data to validate a corresponding computational model. We applied this paradigm to a case of congenital heart disease, namely, transposition of the great arteries (TGA) repaired with arterial switch operation. For this purpose, a mock circulatory loop compatible with the CMR environment was constructed and two detailed aortic 3D models (i.e., one TGA case and one normal aortic anatomy) were tested under realistic hemodynamic conditions, acquiring 4D CMR flow. The same 3D domains were used for multi-scale CFD simulations, whereby the remainder of the mock circulatory system was appropriately summarized with a lumped parameter network. Boundary conditions of the simulations mirrored those measured in vitro. Results showed a very good quantitative agreement between experimental and computational models in terms of pressure (overall maximum % error = 4.4% aortic pressure in the control anatomy) and flow distribution data (overall maximum % error = 3.6% at the subclavian artery outlet of the TGA model). Very good qualitative agreement could also be appreciated in terms of streamlines, throughout the cardiac cycle. Additionally, velocity vectors in the ascending aorta revealed less symmetrical flow in the TGA model, which also exhibited higher wall shear stress in the anterior ascending aorta.