Modeling the impact of concomitant aortic stenosis and coarctation of the aorta on left ventricular workload

Review of cardiac-coronary interaction and insights from mathematical modeling

Cardiac-coronary interaction is fundamental to the function of the heart. As one of the highest metabolic organs in the body, the cardiac oxygen demand is met by blood perfusion through the coronary vasculature. The coronary vasculature is largely embedded within the myocardial tissue which is continually contracting and hence squeezing the blood vessels. The myocardium-coronary vessel interaction is two-ways and complex. Here, we review the different types of cardiac-coronary interactions with a focus on insights gained from mathematical models. Specifically, we will consider the following: (1) myocardial-vessel mechanical interaction; (2) metabolic-flow interaction and regulation; (3) perfusion-contraction matching, and (4) chronic interactions between the myocardium and coronary vasculature. We also provide a discussion of the relevant experimental and clinical studies of different types of cardiac-coronary interactions. Finally, we highlight knowledge gaps, key challenges, and limitations of existing mathematical models along with future research directions to understand the unique myocardium-coronary coupling in the heart. This article is categorized under: Cardiovascular Diseases > Computational Models Cardiovascular Diseases > Biomedical Engineering Cardiovascular Diseases > Molecular and Cellular Physiology.

Numerical study of hemodynamic flow in the aortic vessel of Williams syndrome patient with congenital heart disease

Congenital arterial stenosis such as supravalvar aortic stenosis (SVAS) are highly prevalent in Williams syndrome (WS) and other arteriopathies pose a substantial health risk. Conventional tools for severity assessment, including clinical findings and pressure gradient estimations, often fall short due to their susceptibility to transient physiological changes and disease stage influences. Moreover, in the pediatric population, the severity of these and other congenital heart defects (CHDs) often restricts the applicability of invasive techniques for obtaining crucial physiological data. Conversely, evaluating CHDs and their progression requires a comprehensive understanding of intracardiac blood flow. Current imaging modalities, such as blood speckle imaging (BSI) and four-dimensional magnetic resonance imaging (4D MRI) face limitations in resolving flow data, especially in cases of elevated flow velocities. To address these challenges, we devised a computational framework employing zero-dimensional (0D) lumped parameter models coupled with patient-specific reconstructed geometries pre- and post-surgical intervention to execute computational fluid dynamic (CFD) simulations. This framework facilitates the analysis and visualization of intricate blood flow patterns, offering insights into geometry and flow dynamics alterations impacting cardiac function. In this study, we aim to assess the efficacy of surgical intervention in correcting an extreme aortic defect in a patient with WS, leading to reductions in wall shear stress (WSS), maximum velocity magnitude, pressure drop, and ultimately a decrease in cardiac workload.

Simulating impaired left ventricular-arterial coupling in aging and disease: a systematic review

Aortic stenosis, hypertension, and left ventricular hypertrophy often coexist in the elderly, causing a detrimental mismatch in coupling between the heart and vasculature known as ventricular-vascular (VA) coupling. Impaired left VA coupling, a critical aspect of cardiovascular dysfunction in aging and disease, poses significant challenges for optimal cardiovascular performance. This systematic review aims to assess the impact of simulating and studying this coupling through computational models. By conducting a comprehensive analysis of 34 relevant articles obtained from esteemed databases such as Web of Science, Scopus, and PubMed until July 14, 2022, we explore various modeling techniques and simulation approaches employed to unravel the complex mechanisms underlying this impairment. Our review highlights the essential role of computational models in providing detailed insights beyond clinical observations, enabling a deeper understanding of the cardiovascular system. By elucidating the existing models of the heart (3D, 2D, and 0D), cardiac valves, and blood vessels (3D, 1D, and 0D), as well as discussing mechanical boundary conditions, model parameterization and validation, coupling approaches, computer resources and diverse applications, we establish a comprehensive overview of the field. The descriptions as well as the pros and cons on the choices of different dimensionality in heart, valve, and circulation are provided. Crucially, we emphasize the significance of evaluating heart-vessel interaction in pathological conditions and propose future research directions, such as the development of fully coupled personalized multidimensional models, integration of deep learning techniques, and comprehensive assessment of confounding effects on biomarkers.

Simulation of coronary capillary transit time based on full vascular model of the heart

Capillary transit time (CTT) is a fundamental determinant of gas exchange between blood and tissues in the heart and other organs. Despite advances in experimental techniques, it remains difficult to measure coronary CTT in vivo. Here, we developed a novel computational framework that couples coronary microcirculation with cardiac mechanics in a closed-loop system that enables prediction of hemodynamics in the entire coronary network, including arteries, veins, and capillaries. We also developed a novel "particle-tracking" approach for computing CTT where "virtual tracers" are individually tracked as they traverse the capillary network. Model predictions compare well with blood pressure and flow rate distributions in the arterial network reported in previous studies. Model predictions of transit times in the capillaries (1.21 ± 1.5 s) and entire coronary network (11.8 ± 1.8 s) also agree with measurements. We show that, with increasing coronary artery stenosis (as quantified by fractional flow reserve, FFR), intravascular pressure and flow rate downstream are reduced but remain non-stationary even at 100 % stenosis because some flow (∼3 %) is redistributed from the non-occluded to the occluded territories. Importantly, the model predicts that occlusion of a large artery results in higher CTT. For moderate stenosis (FFR > 0.6), the increase in CTT (from 1.21 s without stenosis to 2.23 s at FFR=0.6) is caused by a decrease in capillary flow rate. In severe stenosis (FFR = 0.1), the increase in CTT to 14.2 s is due to both a decrease in flow rate and an increase in path length taken by "virtual tracers" in the capillary network.

Unveiling the gothic aortic arch and cardiac mechanics: insights from young patients after arterial switch operation for d-transposition of the great arteries

The arterial switch operation (ASO) has become the standard surgical treatment for patients with d-transposition of the great arteries. While ASO has significantly improved survival rates, a subset of patients develop a unique anatomical anomaly known as the gothic aortic arch (GAA). Understanding cardiac mechanics in this population is crucial, as altered mechanics can have profound consequences for cardiac function and exercise capacity. The GAA has been associated with changes in ventricular function, hemodynamics, and exercise capacity. Studies have shown a correlation between the GAA and decreased ascending aorta distensibility, loss of systolic wave amplitude across the aortic arch, and adverse cardiovascular outcomes. Various imaging techniques, including echocardiography, cardiac magnetic resonance imaging, and cardiac computed tomography, play a crucial role in assessing cardiac mechanics and evaluating the GAA anomaly. Despite significant advancements, gaps in knowledge regarding the prognostic implications and underlying mechanisms of the GAA anomaly remain. This review aims to explore the implications of the GAA anomaly on cardiac mechanics and its impact on clinical outcomes in young patients after ASO. Advancements in imaging techniques, such as computational modeling, offer promising avenues to enhance our understanding of cardiac mechanics and improve clinical management.

Impact of TAVR on coronary artery hemodynamics using clinical measurements and image-based patient-specific in silico modeling

In recent years, transcatheter aortic valve replacement (TAVR) has become the leading method for treating aortic stenosis. While the procedure has improved dramatically in the past decade, there are still uncertainties about the impact of TAVR on coronary blood flow. Recent research has indicated that negative coronary events after TAVR may be partially driven by impaired coronary blood flow dynamics. Furthermore, the current technologies to rapidly obtain non-invasive coronary blood flow data are relatively limited. Herein, we present a lumped parameter computational model to simulate coronary blood flow in the main arteries as well as a series of cardiovascular hemodynamic metrics. The model was designed to only use a few inputs parameters from echocardiography, computed tomography and a sphygmomanometer. The novel computational model was then validated and applied to 19 patients undergoing TAVR to examine the impact of the procedure on coronary blood flow in the left anterior descending (LAD) artery, left circumflex (LCX) artery and right coronary artery (RCA) and various global hemodynamics metrics. Based on our findings, the changes in coronary blood flow after TAVR varied and were subject specific (37% had increased flow in all three coronary arteries, 32% had decreased flow in all coronary arteries, and 31% had both increased and decreased flow in different coronary arteries). Additionally, valvular pressure gradient, left ventricle (LV) workload and maximum LV pressure decreased by 61.5%, 4.5% and 13.0% respectively, while mean arterial pressure and cardiac output increased by 6.9% and 9.9% after TAVR. By applying this proof-of-concept computational model, a series of hemodynamic metrics were generated non-invasively which can help to better understand the individual relationships between TAVR and mean and peak coronary flow rates. In the future, tools such as these may play a vital role by providing clinicians with rapid insight into various cardiac and coronary metrics, rendering the planning for TAVR and other cardiovascular procedures more personalized.

A Doppler-exclusive non-invasive computational diagnostic framework for personalized transcatheter aortic valve replacement

Given the associated risks with transcatheter aortic valve replacement (TAVR), it is crucial to determine how the implant will affect the valve dynamics and cardiac function, and if TAVR will improve or worsen the outcome of the patient. Effective treatment strategies, indeed, rely heavily on the complete understanding of the valve dynamics. We developed an innovative Doppler-exclusive non-invasive computational framework that can function as a diagnostic tool to assess valve dynamics in patients with aortic stenosis in both pre- and post-TAVR status. Clinical Doppler pressure was reduced by TAVR (52.2 ± 20.4 vs. 17.3 ± 13.8 [mmHg], p < 0.001), but it was not always accompanied by improvements in valve dynamics and left ventricle (LV) hemodynamics metrics. TAVR had no effect on LV workload in 4 patients, and LV workload post-TAVR significantly rose in 4 other patients. Despite the group level improvements in maximum LV pressure (166.4 ± 32.2 vs 131.4 ± 16.9 [mmHg], p < 0.05), only 5 of the 12 patients (41%) had a decrease in LV pressure. Moreover, TAVR did not always improve valve dynamics. TAVR did not necessarily result in a decrease (in 9 out of 12 patients investigated in this study) in major principal stress on the aortic valve leaflets which is one of the main contributors in valve degeneration and, consequently, failure of heart valves. Diastolic stresses increased significantly post-TAVR (34%, 109% and 81%, p < 0.001) for each left, right and non-coronary leaflets respectively. Moreover, we quantified the stiffness and material properties of aortic valve leaflets which correspond with the reduced calcified region average stiffness among leaflets (66%, 74% and 62%; p < 0.001; N = 12). Valve dynamics post-intervention should be quantified and monitored to ensure the improvement of patient conditions and prevent any further complications. Improper evaluation of biomechanical valve features pre-intervention as well as post-intervention may result in harmful effects post-TAVR in patients including paravalvular leaks, valve degeneration, failure of TAVR and heart failure.

An ultrasound-exclusive non-invasive computational diagnostic framework for personalized cardiology of aortic valve stenosis

Aortic stenosis (AS) is an acute and chronic cardiovascular disease and If left untreated, 50% of these patients will die within two years of developing symptoms. AS is characterized as the stiffening of the aortic valve leaflets which restricts their motion and prevents the proper opening under transvalvular pressure. Assessments of the valve dynamics, if available, would provide valuable information about the patient's state of cardiac deterioration as well as heart recovery and can have incredible impacts on patient care, planning interventions and making critical clinical decisions with life-threatening risks. Despite remarkable advancements in medical imaging, there are no clinical tools available to quantify valve dynamics invasively or noninvasively. In this study, we developed a highly innovative ultrasound-based non-invasive computational framework that can function as a diagnostic tool to assess valve dynamics (e.g. transient 3-D distribution of stress and displacement, 3-D deformed shape of leaflets, geometric orifice area and angular positions of leaflets) for patients with AS at no risk to the patients. Such a diagnostic tool considers the local valve dynamics and the global circulatory system to provide a platform for testing the intervention scenarios and evaluating their effects. We used clinical data of 12 patients with AS not only to validate the proposed framework but also to demonstrate its diagnostic abilities by providing novel analyses and interpretations of clinical data in both pre and post intervention states. We used transthoracic echocardiogram (TTE) data for the developments and transesophageal echocardiography (TEE) data for validation.

Long-term prognostic impact of paravalvular leakage on coronary artery disease requires patient-specific quantification of hemodynamics

Transcatheter aortic valve replacement (TAVR) is a frequently used minimally invasive intervention for patient with aortic stenosis across a broad risk spectrum. While coronary artery disease (CAD) is present in approximately half of TAVR candidates, correlation of post-TAVR complications such as paravalvular leakage (PVL) or misalignment with CAD are not fully understood. For this purpose, we developed a multiscale computational framework based on a patient-specific lumped-parameter algorithm and a 3-D strongly-coupled fluid-structure interaction model to quantify metrics of global circulatory function, metrics of global cardiac function and local cardiac fluid dynamics in 6 patients. Based on our findings, PVL limits the benefits of TAVR and restricts coronary perfusion due to the lack of sufficient coronary blood flow during diastole phase (e.g., maximum coronary flow rate reduced by 21.73%, 21.43% and 21.43% in the left anterior descending (LAD), left circumflex (LCX) and right coronary artery (RCA) respectively (N = 6)). Moreover, PVL may increase the LV load (e.g., LV load increased by 17.57% (N = 6)) and decrease the coronary wall shear stress (e.g., maximum wall shear stress reduced by 20.62%, 21.92%, 22.28% and 25.66% in the left main coronary artery (LMCA), left anterior descending (LAD), left circumflex (LCX) and right coronary artery (RCA) respectively (N = 6)), which could promote atherosclerosis development through loss of the physiological flow-oriented alignment of endothelial cells. This study demonstrated that a rigorously developed personalized image-based computational framework can provide vital insights into underlying mechanics of TAVR and CAD interactions and assist in treatment planning and patient risk stratification in patients.

Impact of extra-anatomical bypass on coarctation fluid dynamics using patient-specific lumped parameter and Lattice Boltzmann modeling

Accurate hemodynamic analysis is not only crucial for successful diagnosis of coarctation of the aorta (COA), but intervention decisions also rely on the hemodynamics assessment in both pre and post intervention states to minimize patient risks. Despite ongoing advances in surgical techniques for COA treatments, the impacts of extra-anatomic bypass grafting, a surgical technique to treat COA, on the aorta are not always benign. Our objective was to investigate the impact of bypass grafting on aortic hemodynamics. We investigated the impact of bypass grafting on aortic hemodynamics using a patient-specific computational-mechanics framework in three patients with COA who underwent bypass grafting. Our results describe that bypass grafting improved some hemodynamic metrics while worsened the others: (1) Doppler pressure gradient improved (decreased) in all patients; (2) Bypass graft did not reduce the flow rate substantially through the COA; (3) Systemic arterial compliance increased in patients #1 and 3 and didn't change (improve) in patient 3; (4) Hypertension got worse in all patients; (5) The flow velocity magnitude improved (reduced) in patient 2 and 3 but did not improve significantly in patient 1; (6) There were elevated velocity magnitude, persistence of vortical flow structure, elevated turbulence characteristics, and elevated wall shear stress at the bypass graft junctions in all patients. We concluded that bypass graft may lead to pseudoaneurysm formation and potential aortic rupture as well as intimal hyperplasia due to the persistent abnormal and irregular aortic hemodynamics in some patients. Moreover, post-intervention, exposures of endothelial cells to high shear stress may lead to arterial remodeling, aneurysm, and rupture.

Reducing Morbidity and Mortality in Patients With Coarctation Requires Systematic Differentiation of Impacts of Mixed Valvular Disease on Coarctation Hemodynamics

Background Despite ongoing advances in surgical techniques for coarctation of the aorta (COA) repair, the long-term results are not always benign. Associated mixed valvular diseases (various combinations of aortic and mitral valvular pathologies) are responsible for considerable postoperative morbidity and mortality. We investigated the impact of COA and mixed valvular diseases on hemodynamics. Methods and Results We developed a patient-specific computational framework. Our results demonstrate that mixed valvular diseases interact with COA fluid dynamics and contribute to speed up the progression of the disease by amplifying the irregular flow patterns downstream of COA (local) and exacerbating the left ventricular function (global) (N=26). Velocity downstream of COA with aortic regurgitation alone was increased, and the situation got worse when COA and aortic regurgitation coexisted with mitral regurgitation (COA with normal valves: 5.27 m/s, COA with only aortic regurgitation: 8.8 m/s, COA with aortic and mitral regurgitation: 9.36 m/s; patient 2). Workload in these patients was increased because of the presence of aortic stenosis alone, aortic regurgitation alone, mitral regurgitation alone, and when they coexisted (COA with normal valves: 1.0617 J; COA with only aortic stenosis: 1.225 J; COA with only aortic regurgitation: 1.6512 J; COA with only mitral regurgitation: 1.3599 J; patient 1). Conclusions Not only the severity of COA, but also the presence and the severity of mixed valvular disease should be considered in the evaluation of risks in patients. The results suggest that more aggressive surgical approaches may be required, because regularly chosen current surgical techniques may not be optimal for such patients.

On Left Ventricle Stroke Work Efficiency in Children with Moderate Aortic Valve Regurgitation or Moderate Aortic Valve Stenosis

The optimal timing for management of pediatric patients with moderate aortic valve disease [moderate aortic stenosis (modAS) or moderate aortic regurgitation (modAR)] remains unknown and largely unexplored. Although usually asymptomatic, the risk of increased left ventricular (LV) wall stress, irreversible myocardial fibrosis and sudden death in untreated moderate conditions warrants clearer risk stratification for appropriate timely intervention. In this study, we explore the use of a patient-specific mathematical model to introduce a new evaluative parameter of LV performance in patients with moderate aortic valve disease. Synthetic patient data (N = 520) representing healthy patients, and patients with modAS or modAR were first generated. Then, data from twenty-five pediatric patients were included in this study (healthy = 9; moderate AS = 8; modAR = 8). The effect of modAS or modAR on LV performance was evaluated by LV stroke work (LVSW) efficiency, a new non-invasive parameter. The results demonstrate that healthy patients possess a very high LVSW efficiency (synthetic data: 91 ± 2%, in vivo data: 92 ± 3%). However, modAS patients have a significant reduction in LVSW efficiency (synthetic data: 78 ± 2%, in vivo data: 76 ± 5%, p < 0.05), whereas modAR patients had the lowest LVSW efficiency (synthetic data: 58 ± 3%, in vivo data: 66 ± 7%; p < 0.05). This highlights that patients with moderate aortic valve disease require careful myocardial assessment, regardless of onset of clinical symptoms as their LV performance is significantly reduced. The evaluation of LVSW efficiency offers a promising avenue for future stratification of mixed aortic valve disease for optimal timing of management and intervention.

Ventricular outflow tract obstruction: An in-silico model to relate the obstruction to hemodynamic quantities in cardiac paediatric patients

BACKGROUND

Right (R) or left (L) ventricular outflow tract (VOT) obstruction can be either a dynamic phenomenon or a congenital anatomic lesion, which requires a prompt and optimal timing of treatment to avoid a pathological ventricular remodelling.

OBJECTIVE

To develop a simple and reliable numerical tool able to relate the R/L obstruction size with the pressure gradient and the cardiac output. To provide indication of the obstruction severity and be of help in the clinical management of patients and designing the surgical treatment for obstruction mitigation.

METHODS

Blood flow across the obstruction is described according to the classical theory of one-dimensional flow, with the obstruction uniquely characterized by its size. Hemodynamics of complete circulation is simulated according to the lumped parameter approach. The case of a 2 years-old baby is reproduced, with the occlusion placed in either the R/ or the L/VOT. Conditions from wide open to almost complete obstruction are reproduced.

RESULTS

Both R/LVOT obstruction in the in-silico model resulted in an increased pressure gradient and a decreased cardiac output, proportional to the severity of the VOT obstruction and dependent on the R/L location of the obstruction itself, as it is clinically observed.

CONCLUSION

The in-silico model of ventricular obstruction which simulates pressure gradient and/or cardiac output agrees with clinical data, and is a first step towards the creation of a tool that can support the clinical management of patients from diagnosis to surgical treatments.

Effects of Choice of Medical Imaging Modalities on a Non-invasive Diagnostic and Monitoring Computational Framework for Patients With Complex Valvular, Vascular, and Ventricular Diseases Who Undergo Transcatheter Aortic Valve Replacement

Due to the high individual differences in the anatomy and pathophysiology of patients, planning individualized treatment requires patient-specific diagnosis. Indeed, hemodynamic quantification can be immensely valuable for accurate diagnosis, however, we still lack precise diagnostic methods for numerous cardiovascular diseases including complex (and mixed) valvular, vascular, and ventricular interactions (C3VI) which is a complicated situation made even more challenging in the face of other cardiovascular pathologies. Transcatheter aortic valve replacement (TAVR) is a new less invasive intervention and is a growing alternative for patients with aortic stenosis. In a recent paper, we developed a non-invasive and Doppler-based diagnostic and monitoring computational mechanics framework for C3VI, called C3VI-DE that uses input parameters measured reliably using Doppler echocardiography. In the present work, we have developed another computational-mechanics framework for C3VI (called C3VI-CT). C3VI-CT uses the same lumped-parameter model core as C3VI-DE but its input parameters are measured using computed tomography and a sphygmomanometer. Both frameworks can quantify: (1) global hemodynamics (metrics of cardiac function); (2) local hemodynamics (metrics of circulatory function). We compared accuracy of the results obtained using C3VI-DE and C3VI-CT against catheterization data (gold standard) using a C3VI dataset (N = 49) for patients with C3VI who undergo TAVR in both pre and post-TAVR with a high variability. Because of the dataset variability and the broad range of diseases that it covers, it enables determining which framework can yield the most accurate results. In contrast with C3VI-CT, C3VI-DE tracks both the cardiac and vascular status and is in great agreement with cardiac catheter data.

Personalized intervention cardiology with transcatheter aortic valve replacement made possible with a non-invasive monitoring and diagnostic framework

One of the most common acute and chronic cardiovascular disease conditions is aortic stenosis, a disease in which the aortic valve is damaged and can no longer function properly. Moreover, aortic stenosis commonly exists in combination with other conditions causing so many patients suffer from the most general and fundamentally challenging condition: complex valvular, ventricular and vascular disease (C3VD). Transcatheter aortic valve replacement (TAVR) is a new less invasive intervention and is a growing alternative for patients with aortic stenosis. Although blood flow quantification is critical for accurate and early diagnosis of C3VD in both pre and post-TAVR, proper diagnostic methods are still lacking because the fluid-dynamics methods that can be used as engines of new diagnostic tools are not well developed yet. Despite remarkable advances in medical imaging, imaging on its own is not enough to quantify the blood flow effectively. Moreover, understanding of C3VD in both pre and post-TAVR and its progression has been hindered by the absence of a proper non-invasive tool for the assessment of the cardiovascular function. To enable the development of new non-invasive diagnostic methods, we developed an innovative image-based patient-specific computational fluid dynamics framework for patients with C3VD who undergo TAVR to quantify metrics of: (1) global circulatory function; (2) global cardiac function as well as (3) local cardiac fluid dynamics. This framework is based on an innovative non-invasive Doppler-based patient-specific lumped-parameter algorithm and a 3-D strongly-coupled fluid-solid interaction. We validated the framework against clinical cardiac catheterization and Doppler echocardiographic measurements and demonstrated its diagnostic utility by providing novel analyses and interpretations of clinical data in eleven C3VD patients in pre and post-TAVR status. Our findings position this framework as a promising new non-invasive diagnostic tool that can provide blood flow metrics while posing no risk to the patient. The diagnostic information, that the framework can provide, is vitally needed to improve clinical outcomes, to assess patient risk and to plan treatment.

Towards non-invasive computational-mechanics and imaging-based diagnostic framework for personalized cardiology for coarctation

Coarctation of the aorta (COA) is a congenital narrowing of the proximal descending aorta. Although accurate and early diagnosis of COA hinges on blood flow quantification, proper diagnostic methods for COA are still lacking because fluid-dynamics methods that can be used for accurate flow quantification are not well developed yet. Most importantly, COA and the heart interact with each other and because the heart resides in a complex vascular network that imposes boundary conditions on its function, accurate diagnosis relies on quantifications of the global hemodynamics (heart-function metrics) as well as the local hemodynamics (detailed information of the blood flow dynamics in COA). In this study, to enable the development of new non-invasive methods that can quantify local and global hemodynamics for COA diagnosis, we developed an innovative fast computational-mechanics and imaging-based framework that uses Lattice Boltzmann method and lumped-parameter modeling that only need routine non-invasive clinical patient data. We used clinical data of patients with COA to validate the proposed framework and to demonstrate its abilities to provide new diagnostic analyses not possible with conventional diagnostic methods. We validated this framework against clinical cardiac catheterization data, calculations using the conventional finite-volume method and clinical Doppler echocardiographic measurements. The diagnostic information, that the framework can provide, is vitally needed to improve clinical outcomes, to assess patient risk and to plan treatment.

Fluid Structure Interaction on Paravalvular Leakage of Transcatheter Aortic Valve Implantation Related to Aortic Stenosis: A Patient-Specific Case

This study investigated the impact of paravalvular leakage (PVL) in relation to the different valve openings of the transcatheter aortic valve implantation (TAVI) valve using the fluid structure interaction (FSI) approach. Limited studies were found on the subject of FSI with regards to TAVI-PVL condition, which involves both fluid and structural responses in coupling interaction. Hence, further FSI simulation with the two-way coupling method is implemented to investigate the effects of hemodynamics blood flow along the patient-specific aorta model subjected to the interrelationship between PVL and the different valve openings using the established FSI software ANSYS 16.1. A 3D patient-specific aorta model is constructed using MIMICS software. The TAVI valve identical to Edward SAPIEN XT 26 (Edwards Lifesciences, Irvine, California), at different Geometrical Orifice Areas (GOAs), is implanted into the patient's aortic annulus. The leaflet opening of the TAVI valve is drawn according to severity of GOA opening represented in terms of 100%, 80%, 60%, and 40% opening, respectively. The result proved that the smallest percentage of GOA opening produced the highest possibility of PVL, increased the recirculatory flow proximally to the inner wall of the ascending aorta, and produced lower backflow velocity streamlines through the side area of PVL region. Overall, 40% GOA produced 89.17% increment of maximum velocity magnitude, 19.97% of pressure drop, 65.70% of maximum WSS magnitude, and a decrement of 33.62% total displacement magnitude with respect to the 100% GOA.

A diagnostic, monitoring, and predictive tool for patients with complex valvular, vascular and ventricular diseases

Hemodynamics quantification is critically useful for accurate and early diagnosis, but we still lack proper diagnosticmethods for many cardiovascular diseases. Furthermore, as most interventions intend to recover the healthy condition, the ability to monitor and predict hemodynamics following interventions can have significant impacts on saving lives. Predictive methods are rare, enabling prediction of effects of interventions, allowing timely and personalized interventions and helping critical clinical decision making about life-threatening risks based on quantitative data. In this study, an innovative non-invasive imaged-based patient-specific diagnostic, monitoring and predictive tool (called C3VI-CMF) was developed, enabling quantifying (1) details of physiological flow and pressures through the heart and circulatory system; (2) heart function metrics. C3VI-CMF also predicts the breakdown of the effects of each disease constituents on the heart function. Presently, neither of these can be obtained noninvasively in patients and when invasive procedures are undertaken, the collected metrics cannot be by any means as complete as the ones C3VI-CMF provides. C3VI-CMF purposefully uses a limited number of noninvasive input parameters all of which can be measured using Doppler echocardiography and sphygmomanometer. Validation of C3VI-CMF, against cardiac catheterization in forty-nine patients with complex cardiovascular diseases, showed very good agreement with the measurements.

Mixed Valvular Disease Following Transcatheter Aortic Valve Replacement: Quantification and Systematic Differentiation Using Clinical Measurements and Image-Based Patient-Specific In Silico Modeling

Background

Mixed valvular disease (MVD), mitral regurgitation (MR) from pre‐existing disease in conjunction with paravalvular leak (PVL) following transcatheter aortic valve replacement (TAVR), is one of the most important stimuli for left ventricle (LV) dysfunction, associated with cardiac mortality. Despite the prevalence of MVD, the quantitative understanding of the interplay between pre‐existing MVD, PVL, LV, and post‐TAVR recovery is meager.

Methods and Results

We quantified the effects of MVD on valvular‐ventricular hemodynamics using an image‐based patient‐specific computational framework in 72 MVD patients. Doppler pressure was reduced by TAVR (mean, 77%; N=72; P<0.05), but it was not always accompanied by improvements in LV workload. TAVR had no effect on LV workload in 22 patients, and LV workload post‐TAVR significantly rose in 32 other patients. TAVR reduced LV workload in only 18 patients (25%). PVL significantly alters LV flow and increases shear stress on transcatheter aortic valve leaflets. It interacts with mitral inflow and elevates shear stresses on mitral valve and is one of the main contributors in worsening of MR post‐TAVR. MR worsened in 32 patients post‐TAVR and did not improve in 18 other patients.

Conclusions

PVL limits the benefit of TAVR by increasing LV load and worsening of MR and heart failure. Post‐TAVR, most MVD patients (75% of N=72; P<0.05) showed no improvements or even worsening of LV workload, whereas the majority of patients with PVL, but without that pre‐existing MR condition (60% of N=48; P<0.05), showed improvements in LV workload. MR and its exacerbation by PVL may hinder the success of TAVR.

Elimination of Transcoarctation Pressure Gradients Has No Impact on Left Ventricular Function or Aortic Shear Stress After Intervention in Patients With Mild Coarctation

OBJECTIVES

This study sought to investigate the impact of transcatheter intervention on left ventricular function and aortic hemodynamics in patients with mild coarctation of the aorta (COA).

BACKGROUND

The optimal method and timing of transcatheter intervention for COA remains unclear, especially when the severity of COA is mild (peak-to-peak transcoarctation pressure gradient <20 mm Hg). Debate rages regarding the risk/benefit ratio of intervention versus long-term effects of persistent minimal gradient in this heterogeneous population with differing blood pressures, ventricular function, and peripheral perfusion.

METHODS

We developed a unique computational fluid dynamics and lumped parameter modeling framework based on patient-specific hemodynamic input parameters and validated it against patient-specific clinical outcomes (before and after intervention). We used clinically measured hemodynamic metrics and imaging of the aorta and the left ventricle in 34 patients with mild COA to make these correlations.

RESULTS

Despite dramatic reduction in the transcoarctation pressure gradient (catheter and Doppler echocardiography pressure gradients reduced by 75% and 47.3%, respectively), there was only modest effect on aortic flow and no significant impact on aortic shear stress (the maximum time-averaged wall shear stress in descending aorta was reduced 5.1%). In no patient did transcatheter intervention improve left ventricular function (e.g., stroke work and normalized stroke work were reduced by only 4.48% and 3.9%, respectively).

CONCLUSIONS

Transcatheter intervention that successfully relieves mild COA pressure gradients does not translate to decreased myocardial strain. The effects of the intervention were determined to the greatest degree by ventricular-vascular coupling hemodynamics and provide a novel valuable mechanism to evaluate patients with COA that may influence clinical practice.

The role of aortic compliance in determination of coarctation severity: Lumped parameter modeling, in vitro study and clinical evaluation

Early detection and accurate estimation of the extent of coarctation of the aorta (COA) is critical to long-term outcome. Peak-to-peak trans-coarctation pressure gradient (PKdP) higher than 20mmHg is an indication for interventional/surgical repair. Patients with COA have reduced proximal and distal aortic compliances. A comprehensive study investigating the effects of variations of proximal COA and systemic compliances on PKdP, and consequently on the COA severity evaluation has never been done. This study evaluates the effect of aortic compliance on diagnostic accuracy of PKdP. Lumped parameter modeling and in vitro experiments were performed for COA severities of 50%, 75% and 90% by area. Modeling and in vitro results were validated against retrospective clinical data of PKdP, measured in 54 patients with COA. Modeling and in vitro. PKdP increases with reduced proximal COA compliance (+36%, +38% and +53% for COA severities of 50%, 75% and 90%, respectively; p<0.05), but decreases with reduced systemic compliance (-62%, -41% and -36% for COA severities of 50%, 75% and 90%, respectively; p<0.01). Clinical study. PKdP has a modest correlation with COA severity (R=0.29). The main determinants of PKdP are COA severity, stroke volume index and systemic compliance. Systemic compliance was found to be as influential as COA severity in PKdP determination (R=0.30 vs. R =0.34). In conclusion, PKdP is highly influenced by both stroke volume index and arterial compliance. Low values of PKdP cannot be used to exclude the severe COA presence since COA severity may be masked by reduced systemic compliance and/or low flow conditions.

Hemodynamic changes following aortic valve bypass: a mathematical approach

Aortic valve bypass (AVB) has been shown to be a viable solution for patients with severe aortic stenosis (AS). Under this circumstance, the left ventricle (LV) has a double outlet. The objective was to develop a mathematical model capable of evaluating the hemodynamic performance following the AVB surgery. A mathematical model that captures the interaction between LV, AS, arterial system, and AVB was developed. This model uses a limited number of parameters that all can be non-invasively measured using patient data. The model was validated using in vivo data from the literature. The model was used to determine the effect of different AVB and AS configurations on flow proportion and pressure of the aortic valve and the AVB. Results showed that the AVB leads to a significant reduction in transvalvular pressure gradient. The percentage of flow through the AVB can range from 55.47% to 69.43% following AVB with a severe AS. LV stroke work was also significantly reduced following the AVB surgery and reached a value of around 1.2 J for several AS severities. Findings of this study suggest: 1) the AVB leads to a significant reduction in transvalvular pressure gradients; 2) flow distribution between the AS and the AVB is significantly affected by the conduit valve size; 3) the AVB leads to a significant reduction in LV stroke work; and 4) hemodynamic performance variations can be estimated using the model.

Normalized left ventricular workload using phase-contrast magnetic resonance imaging in patients with aortic stenosis

Aortic stenosis (AS) severity contributes to the left ventricle (LV) deterioration due to the aortic valve narrowing and the alteration of systemic hemodynamic load. This load increment may also increase the LV stroke work (SW) which represent the required energy to deliver the blood at ejection. In this study, SW was derived from in-vivo cardiovascular magnetic resonance (CMR) velocity measurements (n=57) using a lumped-parametric model. Furthermore, normalized SW (N-SW) was evaluated as AS severity parameter. SW differentiated from normal flow (>35 mL/m(2)) and low flow (<35 mL/m(2)) states (p<0.05). N-SW showed a good association with valve effective orifice area (EOA, r=-0.5, p<0.001) and valvulo-arterial impedance (ZVA, r=0.65, p<0.001). A severity threshold for N-SW (1.5 cJ/mL) was found using an EOA=1 cm(2) as AS severity marker. CMR-derived SW and N-SW may be useful to the assessment and grading of AS patients.

Non-invasive determination of left ventricular workload in patients with aortic stenosis using magnetic resonance imaging and Doppler echocardiography

Early detection and accurate estimation of aortic stenosis (AS) severity are the most important predictors of successful long-term outcomes in patients. Current clinical parameters used for evaluation of the AS severity have several limitations including flow dependency. Estimation of AS severity is specifically challenging in patients with low-flow and low transvalvular pressure gradient conditions. A proper diagnosis in these patients needs a comprehensive evaluation of the left ventricle (LV) hemodynamic loads. This study has two objectives: (1) developing a lumped-parameter model to describe the ventricular-valvular-arterial interaction and to estimate the LV stroke work (SW); (2) introducing and validating a new index, the normalized stroke work (N-SW), to assess the global hemodynamic load imposed on the LV. N-SW represents the global hemodynamic load that the LV faces for each unit volume of blood ejected. The model uses a limited number of parameters which all can be measured non-invasively using current clinical imaging modalities. The model was first validated by comparing its calculated flow waveforms with the ones measured using Cardiovascular Magnetic Resonance (CMR) in 49 patients and 8 controls. A very good correlation and concordance were found throughout the cycle (median root mean square: 12.21 mL/s) and between the peak values (r = 0.98; SEE = 0.001, p<0.001). The model was then used to determine SW using the parameters measured with transthoracic Doppler-echocardiography (TTE) and CMR. N-SW showed very good correlations with a previously-validated index of global hemodynamic load, the valvular arterial impedance (), using data from both imaging modalities (TTE: r = 0.82, SEE = 0.01, p<0.001; CMR: r = 0.74, SEE = 0.01, p<0.001). Furthermore, unlike , N-SW was almost independent from variations in the flow rate. This study suggests that considering N-SW may provide incremental diagnostic and prognostic information, beyond what standard indices of stenosis severity and provide, particularly in patients with low LV outflow.

Fluid dynamics of coarctation of the aorta and effect of bicuspid aortic valve

Up to 80% of patients with coarctation of the aorta (COA) have a bicuspid aortic valve (BAV). Patients with COA and BAV have elevated risks of aortic complications despite successful surgical repair. The development of such complications involves the interplay between the mechanical forces applied on the artery and the biological processes occurring at the cellular level. The focus of this study is on hemodynamic modifications induced in the aorta in the presence of a COA and a BAV. For this purpose, numerical investigations and magnetic resonance imaging measurements were conducted with different configurations: (1) normal: normal aorta and normal aortic valve; (2) isolated COA: aorta with COA (75% reduction by area) and normal aortic valve; (3) complex COA: aorta with the same severity of COA (75% reduction by area) and BAV. The results show that the coexistence of COA and BAV significantly alters blood flow in the aorta with a significant increase in the maximal velocity, secondary flow, pressure loss, time-averaged wall shear stress and oscillatory shear index downstream of the COA. These findings can contribute to a better understanding of why patients with complex COA have adverse outcome even following a successful surgery.

Blood flow vectoring control in aortic arch using full and partial clamps

BACKGROUND

Early diagnosis and treatment of aneurysm plays an important role in reducing the mortality risk of rupture. The aneurysm is a complex phenomenon and caused by different reasons, such as arteriosclerosis and heredity. In addition, pressure and Wall Shear Stress are two known factors influencing the establishment of an aneurysm. The aim of this study is to investigate the effect of using a full or partial clamp to control the blood flow streamlines and hence the location of stress concentration in a clean configuration of aorta. The main question is how to control the stresses distribution in order to reduce the possibility of aneurysm growth with less negative effects on the other sides.

METHODS AND RESULTS

A simple form of aortic arch with three branches is considered to simulate the effect of changing blood flow streamlines directions. A parameter study has been performed on the main characteristics of clamp, i.e. size, location, and the percentage of coverage. The Shear Stress Transport model is employed to simulate steady-state Newtonian blood flow when the Reynolds number is about 6500. Simulations are conducted using the commercial CFD solver ANSYS Fluent. The obtained results show that the location of clamp is more effective than the size. It is also found that increasing the depth of clamp has a negative impact on mean velocity field and hence on stress concentration.

CONCLUSION

The present results demonstrate that the Blood Flow Vectoring Control (BFVC) can change the main form of flow streamlines and consequently the distributions of pressure and Wall Shear Stress. A partial clamp leads to better results.