Predictive Medicine: Computational Techniques in Therapeutic Decision-Making

Blood flow effects in a patient with a thoracic aortic endovascular prosthesis

This work analyzes hemodynamic phenomena within the aorta of two elderly patients and their impact on blood flow behavior, particularly affected by an endovascular prosthesis in one of them (Patient II). Computational Fluid Dynamics (CFD) was utilized for this study, involving measurements of velocity, pressure, and wall shear stress (WSS) at various time points during the third cardiac cycle, at specific positions within two cross sections of the thoracic aorta. The first cross-section (Cross-Section 1, CS1) is located before the initial fluid bifurcation, just before the right subclavian artery. The second cross-section (Cross-Section 2, CS2) is situated immediately after the left subclavian artery. The results reveal that, under regular aortic geometries, velocity and pressure magnitudes follow the principles of fluid dynamics, displaying variations. However, in Patient II, an endoprosthesis near the CS2 and the proximal border of the endoprosthesis significantly disrupts fluid behavior owing to the pulsatile flow. The cross-sectional areas of Patient I are smaller than those of Patient II, leading to higher flow magnitudes. Although in CS1 of Patient I, there is considerable variability in velocity magnitudes, they exhibit a more uniform and predictable transition. In contrast, CS2 of Patient II, where magnitude variation is also high, displays irregular fluid behavior due to the endoprosthesis presence. This cross-section coincides with the border of the fluid bifurcation. Additionally, the irregular geometry caused by endovascular aneurysm repair contributes to flow disruption as the endoprosthesis adjusts to the endothelium, reshaping itself to conform with the vessel wall. In this context, significant alterations in velocity values, pressure differentials fluctuating by up to 10%, and low wall shear stress indicate the pronounced influence of the endovascular prosthesis on blood flow behavior. These flow disturbances, when compounded by the heart rate, can potentially lead to changes in vascular anatomy and displacement, resulting in a disruption of the prosthesis-endothelium continuity and thereby causing clinical complications in the patient.

Computational approaches for mechanobiology in cardiovascular development and diseases

The cardiovascular development in vertebrates evolves in response to genetic and mechanical cues. The dynamic interplay among mechanics, cell biology, and anatomy continually shapes the hydraulic networks, characterized by complex, non-linear changes in anatomical structure and blood flow dynamics. To better understand this interplay, a diverse set of molecular and computational tools has been used to comprehensively study cardiovascular mechanobiology. With the continual advancement of computational capacity and numerical techniques, cardiovascular simulation is increasingly vital in both basic science research for understanding developmental mechanisms and disease etiologies, as well as in clinical studies aimed at enhancing treatment outcomes. This review provides an overview of computational cardiovascular modeling. Beginning with the fundamental concepts of computational cardiovascular modeling, it navigates through the applications of computational modeling in investigating mechanobiology during cardiac development. Second, the article illustrates the utility of computational hemodynamic modeling in the context of treatment planning for congenital heart diseases. It then delves into the predictive potential of computational models for elucidating tissue growth and remodeling processes. In closing, we outline prevailing challenges and future prospects, underscoring the transformative impact of computational cardiovascular modeling in reshaping cardiovascular science and clinical practice.

A time-consistent stabilized finite element method for fluids with applications to hemodynamics

Several finite element methods for simulating incompressible flows rely on the streamline upwind Petrov-Galerkin stabilization (SUPG) term, which is weighted by [Formula: see text]. The conventional formulation of [Formula: see text] includes a constant that depends on the time step size, producing an overall method that becomes exceedingly less accurate as the time step size approaches zero. In practice, such method inconsistency introduces significant error in the solution, especially in cardiovascular simulations, where small time step sizes may be required to resolve multiple scales of the blood flow. To overcome this issue, we propose a consistent method that is based on a new definition of [Formula: see text]. This method, which can be easily implemented on top of an existing streamline upwind Petrov-Galerkin and pressure stabilizing Petrov-Galerkin method, involves the replacement of the time step size in [Formula: see text] with a physical time scale. This time scale is calculated in a simple operation once every time step for the entire computational domain from the ratio of the L2-norm of the acceleration and the velocity. The proposed method is compared against the conventional method using four cases: a steady pipe flow, a blood flow through vascular anatomy, an external flow over a square obstacle, and a fluid-structure interaction case involving an oscillatory flexible beam. These numerical experiments, which are performed using linear interpolation functions, show that the proposed formulation eliminates the inconsistency issue associated with the conventional formulation in all cases. While the proposed method is slightly more costly than the conventional method, it significantly reduces the error, particularly at small time step sizes. For the pipe flow where an exact solution is available, we show the conventional method can over-predict the pressure drop by a factor of three. This large error is almost completely eliminated by the proposed formulation, dropping to approximately 1% for all time step sizes and Reynolds numbers considered.

A novel physics-based model for fast computation of blood flow in coronary arteries

Blood flow and pressure calculated using the currently available methods have shown the potential to predict the progression of pathology, guide treatment strategies and help with postoperative recovery. However, the conspicuous disadvantage of these methods might be the time-consuming nature due to the simulation of virtual interventional treatment. The purpose of this study is to propose a fast novel physics-based model, called FAST, for the prediction of blood flow and pressure. More specifically, blood flow in a vessel is discretized into a number of micro-flow elements along the centerline of the artery, so that when using the equation of viscous fluid motion, the complex blood flow in the artery is simplified into a one-dimensional (1D) steady-state flow. We demonstrate that this method can compute the fractional flow reserve (FFR) derived from coronary computed tomography angiography (CCTA). 345 patients with 402 lesions are used to evaluate the feasibility of the FAST simulation through a comparison with three-dimensional (3D) computational fluid dynamics (CFD) simulation. Invasive FFR is also introduced to validate the diagnostic performance of the FAST method as a reference standard. The performance of the FAST method is comparable with the 3D CFD method. Compared with invasive FFR, the accuracy, sensitivity and specificity of FAST is 88.6%, 83.2% and 91.3%, respectively. The AUC of FFR_FAST is 0.906. This demonstrates that the FAST algorithm and 3D CFD method show high consistency in predicting steady-state blood flow and pressure. Meanwhile, the FAST method also shows the potential in detecting lesion-specific ischemia.

Recasting Current Knowledge of Human Fetal Circulation: The Importance of Computational Models

Computational hemodynamic simulations are becoming increasingly important for cardiovascular research and clinical practice, yet incorporating numerical simulations of human fetal circulation is relatively underutilized and underdeveloped. The fetus possesses unique vascular shunts to appropriately distribute oxygen and nutrients acquired from the placenta, adding complexity and adaptability to blood flow patterns within the fetal vascular network. Perturbations to fetal circulation compromise fetal growth and trigger the abnormal cardiovascular remodeling that underlies congenital heart defects. Computational modeling can be used to elucidate complex blood flow patterns in the fetal circulatory system for normal versus abnormal development. We present an overview of fetal cardiovascular physiology and its evolution from being investigated with invasive experiments and primitive imaging techniques to advanced imaging (4D MRI and ultrasound) and computational modeling. We introduce the theoretical backgrounds of both lumped-parameter networks and three-dimensional computational fluid dynamic simulations of the cardiovascular system. We subsequently summarize existing modeling studies of human fetal circulation along with their limitations and challenges. Finally, we highlight opportunities for improved fetal circulation models.

In-silico investigations of haemodynamic parameters for a blunt thoracic aortic injury case

Accounting for 1.5% of thoracic trauma, blunt thoracic aortic injury (BTAI) is a rare disease with a high mortality rate that nowadays is treated mostly via thoracic endovascular aortic repair (TEVAR). Personalised computational models based on fluid-solid interaction (FSI) principals not only support clinical researchers in studying virtual therapy response, but also are capable of predicting eventual outcomes. The present work studies the variation of key haemodynamic parameters in a clinical case of BTAI after successful TEVAR, using a two-way FSI model. The three-dimensional (3D) patient-specific geometries of the patient were coupled with three-element Windkessel model for both prior and post intervention cases, forcing a correct prediction of blood flow over each section. Results showed significant improvement in velocity and pressure distribution after stenting. High oscillatory, low magnitude shear (HOLMES) regions require careful examination in future follow-ups, since thrombus formation was confirmed in some previously clinically reported cases of BTAI treated with TEVAR. The strength of swirling flows along aorta was also damped after stent deployment. Highlighting the importance of haemodynamic parameters in case-specific therapies. In future studies, compromising motion of aortic wall due to excessive cost of FSI simulations can be considered and should be based on the objectives of studies to achieve a more clinical-friendly patient-specific CFD model.

The Effect of Blood Rheology and Inlet Boundary Conditions on Realistic Abdominal Aortic Aneurysms under Pulsatile Flow Conditions

BACKGROUND

The effects of non-Newtonian rheology and boundary conditions on various pathophysiologies have been studied quite extensively in the literature. The majority of results present qualitative and/or quantitative conclusions that are not thoroughly assessed from a statistical perspective.

METHODS

The finite volume method was employed for the numerical simulation of seven patient-specific abdominal aortic aneurysms. For each case, five rheological models and three inlet velocity boundary conditions were considered. Outlier- and heteroscedasticity-robust ANOVA tests assessed the simultaneous effect of rheological specifications and boundary conditions on fourteen variables that capture important characteristics of vascular flows.

RESULTS

The selection of inlet velocity profiles appears as a more critical factor relative to rheological specifications, especially regarding differences in the oscillatory characteristics of computed flows. Response variables that relate to the average tangential force on the wall over the entire cycle do not differ significantly across alternative factor levels, as long as one focuses on non-Newtonian specifications.

CONCLUSIONS

The two factors, namely blood rheological models and inlet velocity boundary condition, exert additive effects on variables that characterize vascular flows, with negligible interaction effects. Regarding thrombus-prone conditions, the Plug inlet profile offers an advantageous hemodynamic configuration with respect to the other two profiles.

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

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

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

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

Simulation of flow in an artery under pathological hemodynamic conditions: The use of a diagnostic disease descriptor

A numerical model for simulating and predicting blood flow dynamics in diseased arterial vessels has been developed. The time-dependent one-dimensional hyperbolic system of quasilinear partial differential equations which incorporates a diagnostic disease descriptor (k D ) was used to simulate transient flow distribution for idealized healthy and diseased states. Blood flow simulations in the iliac arteries over about 125% of a cardiac cycle were generated and calibrated using thek D values from 0 to 3 representing hypothetical diseased states. Early results indicate that disease conditions induce abnormal flow in the artery, generating disorder and increased amplitude of blood pressure, flow and distensibility with increasing numerical values of the disease factork D . More so, the prospective use of thek D -approach with documentation of in vivo adverse flow visualizations for diagnostic purposes was decisively discussed.

Hemodynamic performance of tissue-engineered vascular grafts in Fontan patients

In the field of congenital heart surgery, tissue-engineered vascular grafts (TEVGs) are a promising alternative to traditionally used synthetic grafts. Our group has pioneered the use of TEVGs as a conduit between the inferior vena cava and the pulmonary arteries in the Fontan operation. The natural history of graft remodeling and its effect on hemodynamic performance has not been well characterized. In this study, we provide a detailed analysis of the first U.S. clinical trial evaluating TEVGs in the treatment of congenital heart disease. We show two distinct phases of graft remodeling: an early phase distinguished by rapid changes in graft geometry and a second phase of sustained growth and decreased graft stiffness. Using clinically informed and patient-specific computational fluid dynamics (CFD) simulations, we demonstrate how changes to TEVG geometry, thickness, and stiffness affect patient hemodynamics. We show that metrics of patient hemodynamics remain within normal ranges despite clinically observed levels of graft narrowing. These insights strengthen the continued clinical evaluation of this technology while supporting recent indications that reversible graft narrowing can be well tolerated, thus suggesting caution before intervening clinically.

Machine learning approaches to surrogate multifidelity Growth and Remodeling models for efficient abdominal aortic aneurysmal applications

Computational Growth and Remodeling (G&R) models have been widely used to capture the pathological development of arterial diseases and have shown promise for aiding clinical diagnosis, prognosis prediction, and staging classification. However, due to the high complexity of the arterial adaptation mechanism, high-fidelity arterial G&R simulation usually takes hours or even days, which hinders its application in clinical practice. To remedy this problem, we develop a computationally efficient arterial G&R simulation framework that comprehensively combines the physics-based G&R simulations and data-driven machine learning approaches. The proposed framework greatly enhances the computational efficiency of arterial G&R simulations, thereby enabling more time-consuming arterial applications, including personalized parameter estimation and arterial disease progression prediction. In particular, we achieve significant computational cost reduction mainly through two methods: (1) constructing a Multifidelity Surrogate (MFS) to approximate multifidelity G&R simulations by using a cokriging approach and (2) developing a novel iterative optimization algorithm for personalized parameter estimation. The proposed framework is demonstrated by estimating G&R model parameters and predicting individual aneurysm growth using follow-up CT images of Abdominal Aortic Aneurysms (AAAs) from 21 patients. Results show that the personalized parameters are satisfactorily estimated and the growth of AAAs is predicted within the clinically relevant time frame, i.e., less than 2 h, without a loss of accuracy.

Flow velocity quantification by exploiting the principles of the Doppler effect and magnetic particle imaging

Changes in blood flow velocity play a crucial role during pathogenesis and progression of cardiovascular diseases. Imaging techniques capable of assessing flow velocities are clinically applied but are often not accurate, quantitative, and reliable enough to assess fine changes indicating the early onset of diseases and their conversion into a symptomatic stage. Magnetic particle imaging (MPI) promises to overcome these limitations. Existing MPI-based techniques perform velocity estimation on the reconstructed images, which restricts the measurable velocity range. Therefore, we developed a novel velocity quantification method by adapting the Doppler principle to MPI. Our method exploits the velocity-dependent frequency shift caused by a tracer motion-induced modulation of the emitted signal. The fundamental theory of our method is deduced and validated by simulations and measurements of moving phantoms. Overall, our method enables robust velocity quantification within milliseconds, with high accuracy, no radiation risk, no depth-dependency, and extended range compared to existing MPI-based velocity quantification techniques, highlighting the potential of our method as future medical application.

Haemodynamic assessment of bicuspid aortic valve aortopathy: a systematic review of the current literature

Both genetic and haemodynamic theories explain the aetiology, progression and optimal management of bicuspid aortic valve aortopathy. In recent years, the haemodynamic theory has been explored with the help of magnetic resonance imaging and computational fluid dynamics. The objective of this review was to summarize the findings of these investigations with focus on the blood flow pattern and associated variables, including flow eccentricity, helicity, flow displacement, cusp opening angle, systolic flow angle, wall shear stress (WSS) and oscillatory shear index. A structured literature review was performed from January 1990 to January 2018 and revealed the following 3 main findings: (i) the bicuspid aortic valve is associated with flow eccentricity and helicity in the ascending aorta compared to healthy and diseased tricuspid aortic valve, (ii) flow displacement is easier to obtain than WSS and has been shown to correlate with valve morphology and type of aortopathy and (iii) the stenotic bicuspid aortic valve is associated with elevated WSS along the greater curvature of the ascending aorta, where aortic dilatation and aortic wall thinning are commonly found. We conclude that new haemodynamic variables should complement ascending aorta diameter as an indicator for disease progression and the type and timing of intervention. WSS describes the force that blood flow exerts on the vessel wall as a function of viscosity and geometry of the vessel, making it a potentially more reliable marker of disease progression.

Numerical investigation of the effects of blood rheology and wall elasticity in abdominal aortic aneurysm under pulsatile flow conditions

BACKGROUND

Previous studies on aneurysm modeling have focused on the blood rheology and vessel elasticity separately. The combined effects of blood shear thinning properties and wall elasticity need to be revealed.

OBJECTIVE

To provide insights on how pulsatile hemodynamics vary with blood rheology and vessel elasticity for a developed abdominal aortic aneurysm (AAA).

METHOD

An Arbitrary Lagrangian-Eulerian fluid-solid interaction method is adopted with the Newtonian and the shear thinning Carreau constitutive models for the fluid with the linearly elastic and the hyperelastic Yeoh models for the vessel. Finite element based numerical solver is used to simulate the blood flow in the AAA.

RESULTS

Newtonian model overestimates the velocity values compared to the Carreau model and the difference in the velocity field increases as the shear rate decreases at the instances of the cardiac cycle. The rigid walled simulations display higher deviations in the velocity and wall shear stress with the fluid rheology. The risk indicators show that Newtonian assumption combined with the linearly elastic model may overlook degeneration risk of arterial tissue.

CONCLUSIONS

Newtonian assumption for the blood as well as modelling the arterial wall as linearly elastic lead to significant differences in oscillatory hemodynamic properties with respect to the use of Carreau fluid together with hyperelastic vessel model, even in large vessel aneurysms.

A Re-Engineered Software Interface and Workflow for the Open-Source SimVascular Cardiovascular Modeling Package

Patient-specific simulation plays an important role in cardiovascular disease research, diagnosis, surgical planning and medical device design, as well as education in cardiovascular biomechanics. simvascular is an open-source software package encompassing an entire cardiovascular modeling and simulation pipeline from image segmentation, three-dimensional (3D) solid modeling, and mesh generation, to patient-specific simulation and analysis. SimVascular is widely used for cardiovascular basic science and clinical research as well as education, following increased adoption by users and development of a GATEWAY web portal to facilitate educational access. Initial efforts of the project focused on replacing commercial packages with open-source alternatives and adding increased functionality for multiscale modeling, fluid-structure interaction (FSI), and solid modeling operations. In this paper, we introduce a major SimVascular (SV) release that includes a new graphical user interface (GUI) designed to improve user experience. Additional improvements include enhanced data/project management, interactive tools to facilitate user interaction, new boundary condition (BC) functionality, plug-in mechanism to increase modularity, a new 3D segmentation tool, and new computer-aided design (CAD)-based solid modeling capabilities. Here, we focus on major changes to the software platform and outline features added in this new release. We also briefly describe our recent experiences using SimVascular in the classroom for bioengineering education.

Image-Based Computational Fluid Dynamic Analysis for Surgical Planning of Sequential Grafts in Coronary Artery Bypass Grafting

Coronary bypass grafting (CABG) is a surgical procedure for anastomosing small grafts to the coronary vessels. The bypass graft bridges the occluded or diseased coronary artery, allowing sufficient blood flow to deliver oxygen and nutrients to the heart muscles. Patient-specific (PS) anatomy obtained from coronary computed tomography angiography (CCTA) was used to generate a 3D aorto-coronary model (pre-surgery). Additionally, three more models with idealized grafts (individual and sequential grafts), were created using Boolean operations to represent post-surgery configuration. Fractional flow reserve (FFR) and wall shear stress (WSS) were estimated from the computational fluid dynamics (CFD). The pre-surgical FFR values for all the three left coronary arteries were significant (FFR<.80). The flow was restored (FFR>0.80) distal to stenosis in all the three post- surgical idealized graft models. Peak WSS values of 468, 336 and 295 dynes/cm² were observed at the toe of the individual end-to-side anastomosis for the three graft models. More importantly, low WSS (< 100 dynes/cm²) prevails at the heel and the walls opposite to the anastomosis in the sequential graft models. The prevailing low WSS at the heel and the wall bed opposite to anastomosis, in a sequential graft model, reduces restenosis rates and promotes a uniform hemodynamic environment for a better long-term patency of the graft. PS- CFD simulations based on CCTA can be helpful in assessing the hemodynamic parameters of graft models for optimal surgical planning.

Morphological and hemodynamical alterations in brachial artery and cephalic vein. An image-based study for preoperative assessment for vascular access creation

The current study aims to computationally evaluate the effect of right upper arm position on the geometric and hemodynamic characteristics of the brachial artery (BA) and cephalic vein (CV) and, furthermore, to present in detail the methodology to characterise morphological and hemodynamical healthy vessels. Ten healthy volunteers were analysed in two configurations, the supine (S) and the prone (P) position. Lumen 3D surface models were constructed from images acquired from a non-contrast MRI sequence. Then, the models were used to numerically compute the physiological range of geometric (n = 10) and hemodynamic (n = 3) parameters in the BA and CV. Geometric parameters such as curvature and tortuosity, and hemodynamic parameters based on wall shear stress (WSS) metrics were calculated with the use of computational fluid dynamics. Our results highlight that changes in arm position had a greater impact on WSS metrics of the BA by altering the mean and maximum blood flow rate of the vessel. Whereas, curvature and tortuosity were found not to be significantly different between positions. Inter-variability was associated with antegrade and retrograde flow in BA, and antegrade flow in CV. Shear stress was low and oscillatory shear forces were negligible. This data suggests that deviations from this state may contribute to the risk of accelerated intimal hyperplasia of the vein in arteriovenous fistulas. Therefore, preoperative conditions coupled with post-operative longitudinal data will aid the identification of such relationships.

Impact of Patient-Specific Inflow Velocity Profile on Hemodynamics of the Thoracic Aorta

Computational fluid dynamics (CFD) provides a noninvasive method to functionally assess aortic hemodynamics. The thoracic aorta has an anatomically complex inlet comprising of the aortic valve and root, which is highly prone to different morphologies and pathologies. We investigated the effect of using patient-specific (PS) inflow velocity profiles compared to idealized profiles based on the patient's flow waveform. A healthy 31 yo with a normally functioning tricuspid aortic valve (subject A), and a 52 yo with a bicuspid aortic valve (BAV), aortic valvular stenosis, and dilated ascending aorta (subject B) were studied. Subjects underwent MR angiography to image and reconstruct three-dimensional (3D) geometric models of the thoracic aorta. Flow-magnetic resonance imaging (MRI) was acquired above the aortic valve and used to extract the patient-specific velocity profiles. Subject B's eccentric asymmetrical inflow profile led to highly complex velocity patterns, which were not replicated by the idealized velocity profiles. Despite having identical flow rates, the idealized inflow profiles displayed significantly different peak and radial velocities. Subject A's results showed some similarity between PS and parabolic inflow profiles; however, other parameters such as Flowasymmetry were significantly different. Idealized inflow velocity profiles significantly alter velocity patterns and produce inaccurate hemodynamic assessments in the thoracic aorta. The complex structure of the aortic valve and its predisposition to pathological change means the inflow into the thoracic aorta can be highly variable. CFD analysis of the thoracic aorta needs to utilize fully PS inflow boundary conditions in order to produce truly meaningful results.

A framework for designing patient-specific bioprosthetic heart valves using immersogeometric fluid-structure interaction analysis

Numerous studies have suggested that medical image derived computational mechanics models could be developed to reduce mortality and morbidity due to cardiovascular diseases by allowing for patient-specific surgical planning and customized medical device design. In this work, we present a novel framework for designing prosthetic heart valves using a parametric design platform and immersogeometric fluid-structure interaction (FSI) analysis. We parameterize the leaflet geometry using several key design parameters. This allows for generating various perturbations of the leaflet design for the patient-specific aortic root reconstructed from the medical image data. Each design is analyzed using our hybrid arbitrary Lagrangian-Eulerian/immersogeometric FSI methodology, which allows us to efficiently simulate the coupling of the deforming aortic root, the parametrically designed prosthetic valves, and the surrounding blood flow under physiological conditions. A parametric study is performed to investigate the influence of the geometry on heart valve performance, indicated by the effective orifice area and the coaptation area. Finally, the FSI simulation result of a design that balances effective orifice area and coaptation area reasonably well is compared with patient-specific phase contrast magnetic resonance imaging data to demonstrate the qualitative similarity of the flow patterns in the ascending aorta.

Cognitive Imaging

This article, an extended version of ICCI*CC-2017 paper, co-authored by biomedical engineers specializing in brain blood circulation modeling and by experts in meaning-based NLP. This article suggests a cognitive computing technology for medical imaging analysis that removes image artifacts resulting in visual deviations from reality, such as discontinuous blood vessels or two vessels shown merged when they are not. It is implemented by supplying the pertinent knowledge that humans have to the computer and letting it initiate the corrective post-processing. The existing OST resource is centered on the ontology that is made to accommodate the domain with a minor adjustment effort; however, any ontology can be used, as demonstrated in this article. The examples from the ontology demonstrate the disparities between what the image shows and what the human knows. The computer detects them autonomously and can initiate the appropriate post-processing. If and when this cognitive imaging prevails, the post-processed images may replace the current ones as legitimate artifact-free MRIs.

AN INTERACTIVE VIRTUAL INTRACORONARY STENTING SYSTEM BASED ON INTRAVASCULAR ULTRASOUND

Percutaneous transluminal coronary angioplasty (PTCA) is a minimally invasive surgery in the clinical treatment of coronary artery diseases. The successful operation highly depends on the size and accurate placement of the stent. In this study, a virtual stenting (VS) system was designed and implemented to facilitate the planning of PTCA. A three-dimensional (3D) vessel model was reconstructed through fusing intravascular ultrasound (IVUS) sequential images and simultaneously recorded X-ray angiograms during cardiac intervention. The user is allowed to intuitively explore the vessel in an endoscopic manner by creating/updating a fly-through trajectory in the lumen. A virtual stent library including a better variety of commercially available bare metal heart stents was built. The user is allowed to select a proper stent according to the morphology of the vessel and lesion and to move it to the lesion. Also, the user can visually observe the stent expansion/apposition and flexibly adjust its position. The system is used to assist visual diagnosis of the vascular diseases, evaluation of interventional treatment and training of the medical personnel.

Applicability Analysis of Validation Evidence for Biomedical Computational Models

Computational modeling has the potential to revolutionize medicine the way it transformed engineering. However, despite decades of work, there has only been limited progress to successfully translate modeling research to patient care. One major difficulty which often occurs with biomedical computational models is an inability to perform validation in a setting that closely resembles how the model will be used. For example, for a biomedical model that makes in vivo clinically relevant predictions, direct validation of predictions may be impossible for ethical, technological, or financial reasons. Unavoidable limitations inherent to the validation process lead to challenges in evaluating the credibility of biomedical model predictions. Therefore, when evaluating biomedical models, it is critical to rigorously assess applicability, that is, the relevance of the computational model, and its validation evidence to the proposed context of use (COU). However, there are no well-established methods for assessing applicability. Here, we present a novel framework for performing applicability analysis and demonstrate its use with a medical device computational model. The framework provides a systematic, step-by-step method for breaking down the broad question of applicability into a series of focused questions, which may be addressed using supporting evidence and subject matter expertise. The framework can be used for model justification, model assessment, and validation planning. While motivated by biomedical models, it is relevant to a broad range of disciplines and underlying physics. The proposed applicability framework could help overcome some of the barriers inherent to validation of, and aid clinical implementation of, biomedical models.

Mathematical Analysis and Physical Profile of Blalock-Taussig Shunt and Sano Modification Procedure in Hypoplastic Left Heart Syndrome: Review of the Literature and Implications for the Anesthesiologist

The first stage of surgical treatment for hypoplastic left heart syndrome (HLHS) includes the creation of artificial systemic-to-pulmonary connections to provide pulmonary blood flow. The modified Blalock-Taussig (mBT) shunt has been the technique of choice for this procedure; however, a right ventricle-pulmonary artery (RV-PA) shunt has been introduced into clinical practice with encouraging but still conflicting outcomes when compared with the mBT shunt. The aim of this study is to explore mathematical modeling as a tool for describing physical profiles that could assist the surgical team in predicting complications related to stenosis and malfunction of grafts in an attempt to find correlations with clinical outcomes from clinical studies that compared both surgical techniques and to assist the anesthesiologist in making decisions to manage patients with this complex cardiac anatomy. Mathematical modeling to display the physical characteristics of the chosen surgical shunt is a valuable tool to predict flow patterns, shear stress, and rate distribution as well as energetic performance at the graft level and relative to ventricular efficiency. Such predictions will enable the surgical team to refine the technique so that hemodynamic complications be anticipated and prevented, and are also important for perioperative management by the anesthesia team.

Gap-free segmentation of vascular networks with automatic image processing pipeline

Current image processing techniques capture large vessels reliably but often fail to preserve connectivity in bifurcations and small vessels. Imaging artifacts and noise can create gaps and discontinuity of intensity that hinders segmentation of vascular trees. However, topological analysis of vascular trees require proper connectivity without gaps, loops or dangling segments. Proper tree connectivity is also important for high quality rendering of surface meshes for scientific visualization or 3D printing. We present a fully automated vessel enhancement pipeline with automated parameter settings for vessel enhancement of tree-like structures from customary imaging sources, including 3D rotational angiography, magnetic resonance angiography, magnetic resonance venography, and computed tomography angiography. The output of the filter pipeline is a vessel-enhanced image which is ideal for generating anatomical consistent network representations of the cerebral angioarchitecture for further topological or statistical analysis. The filter pipeline combined with computational modeling can potentially improve computer-aided diagnosis of cerebrovascular diseases by delivering biometrics and anatomy of the vasculature. It may serve as the first step in fully automatic epidemiological analysis of large clinical datasets. The automatic analysis would enable rigorous statistical comparison of biometrics in subject-specific vascular trees. The robust and accurate image segmentation using a validated filter pipeline would also eliminate operator dependency that has been observed in manual segmentation. Moreover, manual segmentation is time prohibitive given that vascular trees have more than thousands of segments and bifurcations so that interactive segmentation consumes excessive human resources. Subject-specific trees are a first step toward patient-specific hemodynamic simulations for assessing treatment outcomes.

Functional assessment of thoracic aortic aneurysms - the future of risk prediction?

INTRODUCTION

Treatment guidelines for the thoracic aorta concentrate on size, yet acute aortic dissection or rupture can occur when aortic size is below intervention criteria. Functional imaging and computational techniques are a means of assessing haemodynamic parameters involved in aortic pathology.

SOURCES OF DATA

Original articles, reviews, international guidelines.

AREAS OF AGREEMENT

Computational fluid dynamics and 4D flow MRI allow non-invasive assessment of blood flow parameters and aortic wall biomechanics.

AREAS OF CONTROVERSY

Aortic valve morphology (particularly bicuspid aortic valve) is associated with aneurysm of the ascending aorta, although the exact mechanism of aneurysm formation is not yet established.

GROWING POINTS

Haemodynamic assessment of the thoracic aorta has highlighted parameters which are linked with both clinical outcome and protein changes in the aortic wall. Wall shear stress, flow displacement and helicity are elevated in patients with bicuspid aortic valve, particularly at locations of aneurysm formation.

AREAS TIMELY FOR DEVELOPING RESEARCH

With further validation, functional assessment of the aorta may help identify patients at risk of aortic complications, and introduce new haemodynamic indices into management guidelines.

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.

Tissue-scale, personalized modeling and simulation of prostate cancer growth

Recently, mathematical modeling and simulation of diseases and their treatments have enabled the prediction of clinical outcomes and the design of optimal therapies on a personalized (i.e., patient-specific) basis. This new trend in medical research has been termed "predictive medicine." Prostate cancer (PCa) is a major health problem and an ideal candidate to explore tissue-scale, personalized modeling of cancer growth for two main reasons: First, it is a small organ, and, second, tumor growth can be estimated by measuring serum prostate-specific antigen (PSA, a PCa biomarker in blood), which may enable in vivo validation. In this paper, we present a simple continuous model that reproduces the growth patterns of PCa. We use the phase-field method to account for the transformation of healthy cells to cancer cells and use diffusion-reaction equations to compute nutrient consumption and PSA production. To accurately and efficiently compute tumor growth, our simulations leverage isogeometric analysis (IGA). Our model is shown to reproduce a known shape instability from a spheroidal pattern to fingered growth. Results of our computations indicate that such shift is a tumor response to escape starvation, hypoxia, and, eventually, necrosis. Thus, branching enables the tumor to minimize the distance from inner cells to external nutrients, contributing to cancer survival and further development. We have also used our model to perform tissue-scale, personalized simulation of a PCa patient, based on prostatic anatomy extracted from computed tomography images. This simulation shows tumor progression similar to that seen in clinical practice.

Computational Fluid Dynamics modeling of contrast transport in basilar aneurysms following flow-altering surgeries

In vivo measurement of blood velocity fields and flow descriptors remains challenging due to image artifacts and limited resolution of current imaging methods; however, in vivo imaging data can be used to inform and validate patient-specific computational fluid dynamics (CFD) models. Image-based CFD can be particularly useful for planning surgical interventions in complicated cases such as fusiform aneurysms of the basilar artery, where it is crucial to alter pathological hemodynamics while preserving flow to the distal vasculature. In this study, patient-specific CFD modeling was conducted for two basilar aneurysm patients considered for surgical treatment. In addition to velocity fields, transport of contrast agent was simulated for the preoperative and postoperative conditions using two approaches. The transport of a virtual contrast passively following the flow streamlines was simulated to predict post-surgical flow regions prone to thrombus deposition. In addition, the transport of a mixture of blood with an iodine-based contrast agent was modeled to compare and verify the CFD results with X-ray angiograms. The CFD-predicted patterns of contrast flow were qualitatively compared to in vivo X-ray angiograms acquired before and after the intervention. The results suggest that the mixture modeling approach, accounting for the flow rates and properties of the contrast injection, is in better agreement with the X-ray angiography data. The virtual contrast modeling assessed the residence time based on flow patterns unaffected by the injection procedure, which makes the virtual contrast modeling approach better suited for prediction of thrombus deposition, which is not limited to the peri-procedural state.

Three-Dimensional Modeling Analysis of Visceral Arteries and Kidneys during Respiration

BACKGROUND

Visceral arteries are commonly involved in endovascular repair of complex abdominal aortic aneurysms (AAAs). To improve repair techniques and reduce long-term complications involving visceral arteries, it is crucial to understand in vivo arterial geometry and the deformations due to visceral organ movement with respiration. This study quantifies deformation of the celiac, superior mesenteric (SMA), and renal arteries during respiration and correlates the deformations with diaphragmatic excursion.

METHODS

Sixteen patients with small AAAs underwent magnetic resonance angiography during inspiratory and expiratory breathholds. From geometric models of the aorta and visceral arteries, vessel length, branch angle, curvature, and positions were computed, along with degree of diaphragmatic excursion as indicated by kidney translation.

RESULTS

From inspiration to expiration, the celiac artery exhibited axial shortening of 4.8 ± 6.4% (P < 0.001) and a mean curvature increase of 0.03 ± 0.02 mm(-1), greater than other visceral arteries (P < 0.01). With expiration, the SMA, left and right renal arteries (LRA and RRA) angled upward by -9.8 ± 6.4°, -6.4 ± 6.4°, and -5.2 ± 5.0°, respectively (P < 0.005). All vessels translated superiorly (P < 0.0005) and posteriorly (P < 0.01), and the SMA translated rightward additionally (P < 0.005). The left and right kidneys translated by 22 ± 9 mm and 21 ± 9 mm, mostly superiorly (P < 0.001). Translations of all visceral arteries were moderately correlated to the right kidney (R > 0.50). Correlation of the LRA with the left kidney was greater than that of the RRA with the right kidney.

CONCLUSIONS

The celiac artery exhibited less branch angle change, and greater axial and curvature deformations than the other visceral arteries, due to the vicinity to the liver and influence of the median arcuate ligament. Correlation between visceral arteries and kidney translations revealed that diaphragmatic excursion affects vessel mobility. Weaker correlation of the RRA to the right kidney indicates mechanical shielding from the inferior vena cava.

Noninvasive hemodynamic assessment, treatment outcome prediction and follow-up of aortic coarctation from MR imaging

PURPOSE

Coarctation of the aorta (CoA) is a congenital heart disease characterized by an abnormal narrowing of the proximal descending aorta. Severity of this pathology is quantified by the blood pressure drop (△P) across the stenotic coarctation lesion. In order to evaluate the physiological significance of the preoperative coarctation and to assess the postoperative results, the hemodynamic analysis is routinely performed by measuring the △P across the coarctation site via invasive cardiac catheterization. The focus of this work is to present an alternative, noninvasive measurement of blood pressure drop △P through the introduction of a fast, image-based workflow for personalized computational modeling of the CoA hemodynamics.

METHODS

The authors propose an end-to-end system comprised of shape and computational models, their personalization setup using MR imaging, and a fast, noninvasive method based on computational fluid dynamics (CFD) to estimate the pre- and postoperative hemodynamics for coarctation patients. A virtual treatment method is investigated to assess the predictive power of our approach.

RESULTS

Automatic thoracic aorta segmentation was applied on a population of 212 3D MR volumes, with mean symmetric point-to-mesh error of 3.00 ± 1.58 mm and average computation time of 8 s. Through quantitative evaluation of 6 CoA patients, good agreement between computed blood pressure drop and catheter measurements is shown: average differences are 2.38 ± 0.82 mm Hg (pre-), 1.10 ± 0.63 mm Hg (postoperative), and 4.99 ± 3.00 mm Hg (virtual stenting), respectively.

CONCLUSIONS

The complete workflow is realized in a fast, mostly-automated system that is integrable in the clinical setting. To the best of our knowledge, this is the first time that three different settings (preoperative--severity assessment, poststenting--follow-up, and virtual stenting--treatment outcome prediction) of CoA are investigated on multiple subjects. We believe that in future-given wider clinical validation-our noninvasive in-silico method could replace invasive pressure catheterization for CoA.

Coronary Computed Tomography Angiography Derived Fractional Flow Reserve and Plaque Stress

Fractional flow reserve (FFR) measured during invasive coronary angiography is an independent prognosticator in patients with coronary artery disease and the gold standard for decision making in coronary revascularization. The integration of computational fluid dynamics and quantitative anatomic and physiologic modeling now enables simulation of patient-specific hemodynamic parameters including blood velocity, pressure, pressure gradients, and FFR from standard acquired coronary computed tomography (CT) datasets. In this review article, we describe the potential impact on clinical practice and the science behind noninvasive coronary computed tomography (CT) angiography derived fractional flow reserve (FFR_CT) as well as future applications of this technology in treatment planning and quantifying forces on atherosclerotic plaques.

Numerical study of purely viscous non-Newtonian flow in an abdominal aortic aneurysm

It is well known that blood has non-Newtonian properties, but it is generally accepted that blood behaves as a Newtonian fluid at shear rates above 100 s-1. However, in transient conditions, there are times and locations where the shear rate is well below 100 s-1, and it is reasonable to infer that non-Newtonian effects could become important. In this study, purely viscous non-Newtonian (generalized Newtonian) properties of blood are incorporated into the simulation-based framework for cardiovascular surgery planning developed by Taylor et al. (1999, "Predictive Medicine: Computational Techniques in Therapeutic Decision Making," Comput. Aided Surg., 4, pp. 231-247; 1998, "Finite Element Modeling of Blood Flow in Arteries," Comput. Methods Appl. Mech. Eng., 158, pp. 155-196). Equations describing blood flow are solved in a patient-based abdominal aortic aneurysm model under steady and physiological flow conditions. Direct numerical simulation (DNS) is used, and the complex flow is found to be constantly transitioning between laminar and turbulent in both the spatial and temporal sense. It is found for the case simulated that using the non-Newtonian viscosity modifies the solution in subtle ways that yield a mesh-independent solution with fewer degrees of freedom than the Newtonian counterpart. It appears that in regions of separated flow, the lower shear rate produces higher viscosity with the non-Newtonian model, which reduces the associated resolution needs. When considering the real case of pulsatile flow, high shear layers lead to greater unsteadiness in the Newtonian case relative to the non-Newtonian case. This, in turn, results in a tendency for the non-Newtonian model to need fewer computational resources even though it has to perform additional calculations for the viscosity. It is also shown that both viscosity models predict comparable wall shear stress distribution. This work suggests that the use of a non-Newtonian viscosity models may be attractive to solve cardiovascular flows since it can provide simulation results that are presumably physically more realistic with at least comparable computational effort for a given level of accuracy.

4D flow cardiovascular magnetic resonance consensus statement

Pulsatile blood flow through the cavities of the heart and great vessels is time-varying and multidirectional. Access to all regions, phases and directions of cardiovascular flows has formerly been limited. Four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) has enabled more comprehensive access to such flows, with typical spatial resolution of 1.5×1.5×1.5 - 3×3×3 mm(3), typical temporal resolution of 30-40 ms, and acquisition times in the order of 5 to 25 min. This consensus paper is the work of physicists, physicians and biomedical engineers, active in the development and implementation of 4D Flow CMR, who have repeatedly met to share experience and ideas. The paper aims to assist understanding of acquisition and analysis methods, and their potential clinical applications with a focus on the heart and greater vessels. We describe that 4D Flow CMR can be clinically advantageous because placement of a single acquisition volume is straightforward and enables flow through any plane across it to be calculated retrospectively and with good accuracy. We also specify research and development goals that have yet to be satisfactorily achieved. Derived flow parameters, generally needing further development or validation for clinical use, include measurements of wall shear stress, pressure difference, turbulent kinetic energy, and intracardiac flow components. The dependence of measurement accuracy on acquisition parameters is considered, as are the uses of different visualization strategies for appropriate representation of time-varying multidirectional flow fields. Finally, we offer suggestions for more consistent, user-friendly implementation of 4D Flow CMR acquisition and data handling with a view to multicenter studies and more widespread adoption of the approach in routine clinical investigations.

Measurement and modeling of coronary blood flow

Ischemic heart disease that comprises both coronary artery disease and microvascular disease is the single greatest cause of death globally. In this context, enhancing our understanding of the interaction of coronary structure and function is not only fundamental for advancing basic physiology but also crucial for identifying new targets for treating these diseases. A central challenge for understanding coronary blood flow is that coronary structure and function exhibit different behaviors across a range of spatial and temporal scales. While experimental studies have sought to understand this feature by isolating specific mechanisms, in tandem, computational modeling is increasingly also providing a unique framework to integrate mechanistic behaviors across different scales. In addition, clinical methods for assessing coronary disease severity are continuously being informed and updated by findings in basic physiology. Coupling these technologies, computational modeling of the coronary circulation is emerging as a bridge between the experimental and clinical domains, providing a framework to integrate imaging and measurements from multiple sources with mathematical descriptions of governing physical laws. State-of-the-art computational modeling is being used to combine mechanistic models with data to provide new insight into coronary physiology, optimization of medical technologies, and new applications to guide clinical practice.

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.

Computational modeling of flow-altering surgeries in basilar aneurysms

In cases where surgeons consider different interventional options for flow alterations in the setting of pathological basilar artery hemodynamics, a virtual model demonstrating the flow fields resulting from each of these options can assist in making clinical decisions. In this study, image-based computational fluid dynamics (CFD) models were used to simulate the flow in four basilar artery aneurysms in order to evaluate postoperative hemodynamics that would result from flow-altering interventions. Patient-specific geometries were constructed using MR angiography and velocimetry data. CFD simulations carried out for the preoperative flow conditions were compared to in vivo phase-contrast MRI measurements (4D Flow MRI) acquired prior to the interventions. The models were then modified according to the procedures considered for each patient. Numerical simulations of the flow and virtual contrast transport were carried out in each case in order to assess postoperative flow fields and estimate the likelihood of intra-aneurysmal thrombus deposition following the procedures. Postoperative imaging data, when available, were used to validate computational predictions. In two cases, where the aneurysms involved vital pontine perforator arteries branching from the basilar artery, idealized geometries of these vessels were incorporated into the CFD models. The effect of interventions on the flow through the perforators was evaluated by simulating the transport of contrast in these vessels. The computational results were in close agreement with the MR imaging data. In some cases, CFD simulations could help determine which of the surgical options was likely to reduce the flow into the aneurysm while preserving the flow through the basilar trunk. The study demonstrated that image-based computational modeling can provide guidance to clinicians by indicating possible outcome complications and indicating expected success potential for ameliorating pathological aneurysmal flow, prior to a procedure.

Numerical simulation of blood flow and pressure drop in the pulmonary arterial and venous circulation

A novel multiscale mathematical and computational model of the pulmonary circulation is presented and used to analyse both arterial and venous pressure and flow. This work is a major advance over previous studies by Olufsen et al. (Ann Biomed Eng 28:1281-1299, 2012) which only considered the arterial circulation. For the first three generations of vessels within the pulmonary circulation, geometry is specified from patient-specific measurements obtained using magnetic resonance imaging (MRI). Blood flow and pressure in the larger arteries and veins are predicted using a nonlinear, cross-sectional-area-averaged system of equations for a Newtonian fluid in an elastic tube. Inflow into the main pulmonary artery is obtained from MRI measurements, while pressure entering the left atrium from the main pulmonary vein is kept constant at the normal mean value of 2 mmHg. Each terminal vessel in the network of 'large' arteries is connected to its corresponding terminal vein via a network of vessels representing the vascular bed of smaller arteries and veins. We develop and implement an algorithm to calculate the admittance of each vascular bed, using bifurcating structured trees and recursion. The structured-tree models take into account the geometry and material properties of the 'smaller' arteries and veins of radii ≥ 50 μm. We study the effects on flow and pressure associated with three classes of pulmonary hypertension expressed via stiffening of larger and smaller vessels, and vascular rarefaction. The results of simulating these pathological conditions are in agreement with clinical observations, showing that the model has potential for assisting with diagnosis and treatment for circulatory diseases within the lung.

Computational modeling of pathophysiologic responses to exercise in Fontan patients

Reduced exercise capacity is nearly universal among Fontan patients. Although many factors have emerged as possible contributors, the degree to which each impacts the overall hemodynamics is largely unknown. Computational modeling provides a means to test hypotheses of causes of exercise intolerance via precisely controlled virtual experiments and measurements. We quantified the physiological impacts of commonly encountered, clinically relevant dysfunctions introduced to the exercising Fontan system via a previously developed lumped-parameter model of Fontan exercise. Elevated pulmonary arterial pressure was observed in all cases of dysfunction, correlated with lowered cardiac output (CO), and often mediated by elevated atrial pressure. Pulmonary vascular resistance was not the most significant factor affecting exercise performance as measured by CO. In the absence of other dysfunctions, atrioventricular valve insufficiency alone had significant physiological impact, especially under exercise demands. The impact of isolated dysfunctions can be linearly summed to approximate the combined impact of several dysfunctions occurring in the same system. A single dominant cause of exercise intolerance was not identified, though several hypothesized dysfunctions each led to variable decreases in performance. Computational predictions of performance improvement associated with various interventions should be weighed against procedural risks and potential complications, contributing to improvements in routine patient management protocol.

Strategy for modeling flow diverters in cerebral aneurysms as a porous medium

Simulations using the patient-specific geometry of the aneurysm may help in a better planning of the treatment and in a consequent reduction of the associated risks. We propose, evaluate, and implement a methodology for the simulation of flow diverter (FD) devices in intracranial aneurysms by using a porous medium method (PMM), which greatly reduces the computational cost of these simulations compared with immersed method (IMM) approaches used to model complex FDs. The method relies on parameters from an empirical correlation derived from experimental observations in wire screens, consistent with CFD simulations. The verification of our PMM strategy was carried out by comparing the results of simulations in different (patient-specific) geometries and FDs, to those obtained under identical conditions by the IMM. Overall, both quantitative and qualitative results are consistent between IMM and PMM in cases where the local porosity remains roughly uniform throughout the neck, with differences in the reduction of the observables lower than 10%. This PMM strategy is up to 10 times faster than the IMM, which allows for a runtime of hours instead of days, bringing it closer for its application in the clinic.

Continuous stroke volume estimation from aortic pressure using zero dimensional cardiovascular model: proof of concept study from porcine experiments

Introduction

Accurate, continuous, left ventricular stroke volume (SV) measurements can convey large amounts of information about patient hemodynamic status and response to therapy. However, direct measurements are highly invasive in clinical practice, and current procedures for estimating SV require specialized devices and significant approximation.

Method

This study investigates the accuracy of a three element Windkessel model combined with an aortic pressure waveform to estimate SV. Aortic pressure is separated into two components capturing; 1) resistance and compliance, 2) characteristic impedance. This separation provides model-element relationships enabling SV to be estimated while requiring only one of the three element values to be known or estimated. Beat-to-beat SV estimation was performed using population-representative optimal values for each model element. This method was validated using measured SV data from porcine experiments (N = 3 female Pietrain pigs, 29–37 kg) in which both ventricular volume and aortic pressure waveforms were measured simultaneously.

Results

The median difference between measured SV from left ventricle (LV) output and estimated SV was 0.6 ml with a 90% range (5^th–95^th percentile) −12.4 ml–14.3 ml. During periods when changes in SV were induced, cross correlations in between estimated and measured SV were above R = 0.65 for all cases.

Conclusion

The method presented demonstrates that the magnitude and trends of SV can be accurately estimated from pressure waveforms alone, without the need for identification of complex physiological metrics where strength of correlations may vary significantly from patient to patient.