Impact of prosthetic mitral valve orientation on the ventricular flow field: Comparison using patient-specific computational fluid dynamics

Verification Study of In Silico Computed Intracardiac Blood Flow With 4D Flow MRI

OBJECTIVE

Major challenges for clinical applications of in silico medicine are limitations in time and computational resources. Computational approaches should therefore be tailored to specific applications with relatively low complexity and must be verified and validated against clinical gold standards.

METHODS

This study performed computational fluid dynamics simulations of left ventricular hemodynamics of different complexity based on shape reconstruction from steady state gradient echo magnetic resonance imaging (MRI) data. Computed flow results of a rigid wall model (RWM) and a prescribed motion fluid-structure interaction (PM-FSI) model were compared against phase-contrast MRI measurements for three healthy subjects.

RESULTS

Extracted boundary conditions from the steady state MRI sequences as well as computed metrics, such as flow rate, valve velocities, and kinetic energy show good agreement with in vivo flow measurements. Regional flow analysis reveals larger differences.

CONCLUSION

Basic flow structures are well captured with RWM and PM-FSI. For the computation of further biomarkers like washout or flow efficiency, usage of PM-FSI is required. Regarding boundary-near flow, more accurate anatomical models are inevitable.

SIGNIFICANCE

These results delineate areas of application of both methods and lay a foundation for larger validation studies and sensitivity analysis for healthy and diseased cases, being an essential step upon clinical translations.

Structural Challenges in Native Atrioventricular Valves Replacement

Atrioventricular (AV) valve disease is a major burden in our Indian subcontinent, where rheumatic heart disease is still prevalent, when compared to the Western world, where degenerative heart disease is more prevalent. Worldwide, nearly 300,000 valve replacements are done every year but not without complications. These challenges can be multidimensional and multiscalar with the macroscopic and microscopic properties of the native patient tissue interacting with the mechanical and bioprosthetic heart valves and rings. Understanding the complex and variable anatomy of the AV valves is essential to know the exact pathophysiology of the disease and to decide the treatment of choice.

Revisiting echocardiographic features of prosthetic heart valves: the necessity of correct differentiation of mono-leaflet vs. bileaflet mechanical heart valves in a case report

BACKGROUND

Mechanical heart valve replacement is a standard treatment for severe valvular disorders. The use of mono-leaflet valves has decreased recently. Recognizing the echocardiographic features of mono-leaflet and bileaflet valves is crucial for accurate complication diagnosis and proper management.

CASE PRESENTATION

A 65-year-old female with mono-leaflet mitral and bileaflet tricuspid valves underwent an echocardiographic assessment. This simple educational case provides a unique opportunity to compare the echocardiographic features of these valves within a single patient.

CONCLUSION

There is a crucial need for clinicians, particularly those in training, to differentiate between mono-leaflet and bileaflet mechanical heart valves adeptly. With mono-leaflet valves decreasing in prevalence, proficiency in recognizing the echocardiographic nuances of each type is imperative. Failure to do so may result in misdiagnoses and inappropriate management. This underscores the significance of continuous education and vigilance in echocardiographic assessments to ensure optimal patient care.

Impact of Bileaflet Mechanical Mitral Valve Orientation on Pannus Overgrowth

OBJECTIVE

Pannus overgrowth is a chronic inflammatory process that can cause valve dysfunction and threaten the durability of prosthetic valves. Bileaflet mechanical mitral valve can be implanted in either an anatomical (parallel to the anatomical axis) or nonanatomical (perpendicular or oblique to the anatomical axis) orientation. The effect of the rotational orientation of the bileaflet mechanical mitral valve on excessive pannus enlargement is unknown. The present study compared the effect of bileaflet mechanical mitral valve orientation on pannus overgrowth.

METHODS

The study included patients who underwent bileaflet mechanical mitral valve replacement for rheumatic mitral valve stenosis. The pannus formation was confirmed by reexamining all transesophageal echocardiography images in the picture archiving and communication systems between May 2017 and April 2021. The primary aim of this study was the development of pannus overgrowth. Patients were divided into 2 groups based on their implantation orientation of the bileaflet mechanical mitral valve.

RESULTS

Pannus overgrowth was found in 26 patients (56.5%) in the anatomical orientation group and 71 patients (74.7%) in the nonanatomical orientation group (P = 0.03). Anatomical orientation reduced the development of pannus overgrowth (odds ratio [OR] = 0.39, P = 0.04), and double left heart valve replacement increased the development of pannus overgrowth (OR = 2.73, P = 0.04).

CONCLUSIONS

Pannus overgrowth was less common in bileaflet mechanical mitral valves implanted in the anatomical orientation.

Accelerated sequences of 4D flow MRI using GRAPPA and compressed sensing: A comparison against conventional MRI and computational fluid dynamics

PURPOSE

To evaluate hemodynamic markers obtained by accelerated GRAPPA (R = 2, 3, 4) and compressed sensing (R = 7.6) 4D flow MRI sequences under complex flow conditions.

METHODS

The accelerated 4D flow MRI scans were performed on a pulsatile flow phantom, along with a nonaccelerated fully sampled k-space acquisition. Computational fluid dynamics simulations based on the experimentally measured flow fields were conducted for additional comparison. Voxel-wise comparisons (Bland-Altman analysis, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow><mml:msub><mml:mi>L</mml:mi> <mml:mn>2</mml:mn></mml:msub> </mml:mrow> <mml:annotation>$$ {L}_2 $$</mml:annotation></mml:semantics> </mml:math> -norm metric), as well as nonderived quantities (velocity profiles, flow rates, and peak velocities), were used to compare the velocity fields obtained from the different modalities.

RESULTS

4D flow acquisitions and computational fluid dynamics depicted similar hemodynamic patterns. Voxel-wise comparisons between the MRI scans highlighted larger discrepancies at the voxels located near the phantom's boundary walls. A trend for all MR scans to overestimate velocity profiles and peak velocities as compared to computational fluid dynamics was noticed in regions associated with high velocity or acceleration. However, good agreement for the flow rates was observed, and eddy-current correction appeared essential for consistency of the flow rates measurements with respect to the principle of mass conservation.

CONCLUSION

GRAPPA (R = 2, 3) and highly accelerated compressed sensing showed good agreement with the fully sampled acquisition. Yet, all 4D flow MRI scans were hampered by artifacts inherent to the phase-contrast acquisition procedure. Computational fluid dynamics simulations are an interesting tool to assess these differences but are sensitive to modeling parameters.

The impact of 4D-Flow MRI spatial resolution on patient-specific CFD simulations of the thoracic aorta

Magnetic Resonance Imaging (MRI) is considered the gold standard of medical imaging technologies as it allows for accurate imaging of blood vessels. 4-Dimensional Flow Magnetic Resonance Imaging (4D-Flow MRI) is built on conventional MRI, and provides flow data in the three vector directions and a time resolved magnitude data set. As such it can be used to retrospectively calculate haemodynamic parameters of interest, such as Wall Shear Stress (WSS). However, multiple studies have indicated that a significant limitation of the imaging technique is the spatiotemporal resolution that is currently available. Recent advances have proposed and successfully integrated 4D-Flow MRI imaging techniques with Computational Fluid Dynamics (CFD) to produce patient-specific simulations that have the potential to aid in treatments,surgical decision making, and risk stratification. However, the consequences of using insufficient 4D-Flow MRI spatial resolutions on any patient-specific CFD simulations is currently unclear, despite being a recognised limitation. The research presented in this study aims to quantify the inaccuracies in patient-specific 4D-Flow MRI based CFD simulations that can be attributed to insufficient spatial resolutions when acquiring 4D-Flow MRI data. For this research, a patient has undergone four 4D-Flow MRI scans acquired at various isotropic spatial resolutions and patient-specific CFD simulations have subsequently been run using geometry and velocity data produced from each scan. It was found that compared to CFD simulations based on a \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$1.5\,{\text {mm}} \times 1.5\,{\text {mm}} \times 1.5\,{\text {mm}}$$\end{document}1.5mm×1.5mm×1.5mm, using a spatial resolution of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$4\,{\text {mm}} \times 4\,{\text {mm}} \times 4\,{\text {mm}}$$\end{document}4mm×4mm×4mm substantially underestimated the maximum velocity magnitude at peak systole by \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$110.55\%$$\end{document}110.55%. The impacts of 4D-Flow MRI spatial resolution on WSS calculated from CFD simulations have been investigated and it has been shown that WSS is underestimated in CFD simulations that are based on a coarse 4D-Flow MRI spatial resolution. The authors have concluded that a minimum 4D-Flow MRI spatial resolution of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$1.5\,{\text {mm}} \times 1.5\,{\text {mm}} \times 1.5\,{\text {mm}}$$\end{document}1.5mm×1.5mm×1.5mm must be used when acquiring 4D-Flow MRI data to perform patient-specific CFD simulations. A coarser spatial resolution will produce substantial differences within the flow field and geometry.

Blood flow analysis with computational fluid dynamics and 4D-flow MRI for vascular diseases

Both computational fluid dynamics (CFD) and time-resolved, three-dimensional, phase-contrast, magnetic resonance imaging (4D-flow MRI) enable visualization of time-varying blood flow structures and quantification of blood flow in vascular diseases. However, they are totally different. CFD is a method to calculate blood flow by solving the governing equations of fluid mechanics, so the obtained flow field is somewhat virtual. On the other hand, 4D-flow MRI measures blood flow in vivo, thus the flow is real. Recently, with the development and enhancement of computers, medical imaging techniques, and related software, blood flow analysis has become more accessible to clinicians and its usefulness in vascular diseases has been demonstrated. In this review, we have outlined the methods and characteristics of CFD and 4D-flow MRI, respectively. We have discussed the differences in the characteristics between both methods; reviewed the milestones achieved by blood flow analysis in various vascular diseases; and discussed the usefulness, challenges, and limitations of blood flow analysis. We have discussed the difficulties and limitations of current blood flow analysis. We have also discussed our views on future directions.

Clinical Impact of Computational Heart Valve Models

This paper provides a review of engineering applications and computational methods used to analyze the dynamics of heart valve closures in healthy and diseased states. Computational methods are a cost-effective tool that can be used to evaluate the flow parameters of heart valves. Valve repair and replacement have long-term stability and biocompatibility issues, highlighting the need for a more robust method for resolving valvular disease. For example, while fluid-structure interaction analyses are still scarcely utilized to study aortic valves, computational fluid dynamics is used to assess the effect of different aortic valve morphologies on velocity profiles, flow patterns, helicity, wall shear stress, and oscillatory shear index in the thoracic aorta. It has been analyzed that computational flow dynamic analyses can be integrated with other methods to create a superior, more compatible method of understanding risk and compatibility.

Co-simulation of hypertensive left ventricle based on computational fluid dynamics and a closed-loop network model

OBJECTIVE

Hypertension is one of the most common chronic and cardiovascular diseases, with the largest number of deaths. According to clinical experience, long-term hypertension will cause cardiac hypertrophy and other complications, and heart structure remodeling will significantly change the energy characteristics of the heart chambers, and impair heart function. Research shows that, early hypertension can be diagnosed by the blood flow and energy loss in the left ventricle. Therefore, it is important to choose an appropriate method to simulate and predict the flow domain of this ventricle.

METHODS

This study took the left ventricular flow field of patients with hypertensive myocardial hypertrophy as the research object, used MATLAB-SIMULINK to establish a closed-loop network cardiovascular model, provided flow boundary conditions for the computational fluid dynamics (CFD) numerical simulation method, and, finally, completed a co-simulation.

RESULTS

This article compared the degree of agreement between the energy loss in different phases of the heart cavity and clinical experimental data and summarized the characteristics of the flow field in patients with hypertensive myocardial hypertrophy. The analysis of three simulation groups (control group, non-left ventricular hypertrophy group, and left ventricular hypertrophy [LVH] group) showed that the vortices in the LVH group were irregular and not fully developed, accompanied by significant energy loss.

CONCLUSION

The simulation method used in this study is basically consistent with the clinical data. Myocardial hypertrophy has a significant influence on the blood flow of the left ventricle. Changes in the blood flow make the left ventricular vortex distribution abnormal during the rapid systole and rapid ejection periods, leading to a series of dangerous factors, including increased energy loss and a low cardiac ejection fraction.

CT-Based Simulation of Left Ventricular Hemodynamics: A Pilot Study in Mitral Regurgitation and Left Ventricle Aneurysm Patients

Background

Cardiac CT (CCT) is well suited for a detailed analysis of heart structures due to its high spatial resolution, but in contrast to MRI and echocardiography, CCT does not allow an assessment of intracardiac flow. Computational fluid dynamics (CFD) can complement this shortcoming. It enables the computation of hemodynamics at a high spatio-temporal resolution based on medical images. The aim of this proposed study is to establish a CCT-based CFD methodology for the analysis of left ventricle (LV) hemodynamics and to assess the usability of the computational framework for clinical practice.

Materials and Methods

The methodology is demonstrated by means of four cases selected from a cohort of 125 multiphase CCT examinations of heart failure patients. These cases represent subcohorts of patients with and without LV aneurysm and with severe and no mitral regurgitation (MR). All selected LVs are dilated and characterized by a reduced ejection fraction (EF). End-diastolic and end-systolic image data was used to reconstruct LV geometries with 2D valves as well as the ventricular movement. The intraventricular hemodynamics were computed with a prescribed-motion CFD approach and evaluated in terms of large-scale flow patterns, energetic behavior, and intraventricular washout.

Results

In the MR patients, a disrupted E-wave jet, a fragmentary diastolic vortex formation and an increased specific energy dissipation in systole are observed. In all cases, regions with an impaired washout are visible. The results furthermore indicate that considering several cycles might provide a more detailed view of the washout process. The pre-processing times and computational expenses are in reach of clinical feasibility.

Conclusion

The proposed CCT-based CFD method allows to compute patient-specific intraventricular hemodynamics and thus complements the informative value of CCT. The method can be applied to any CCT data of common quality and represents a fair balance between model accuracy and overall expenses. With further model enhancements, the computational framework has the potential to be embedded in clinical routine workflows, to support clinical decision making and treatment planning.

Computational Methods for Fluid-Structure Interaction Simulation of Heart Valves in Patient-Specific Left Heart Anatomies

Given the complexity of human left heart anatomy and valvular structures, the fluid–structure interaction (FSI) simulation of native and prosthetic valves poses a significant challenge for numerical methods. In this review, recent numerical advancements for both fluid and structural solvers for heart valves in patient-specific left hearts are systematically considered, emphasizing the numerical treatments of blood flow and valve surfaces, which are the most critical aspects for accurate simulations. Numerical methods for hemodynamics are considered under both the continuum and discrete (particle) approaches. The numerical treatments for the structural dynamics of aortic/mitral valves and FSI coupling methods between the solid Ωs and fluid domain Ωf are also reviewed. Future work toward more advanced patient-specific simulations is also discussed, including the fusion of high-fidelity simulation within vivo measurements and physics-based digital twining based on data analytics and machine learning techniques.