4D Flow MRI quantification of blood flow patterns, turbulence and pressure drop in normal and stenotic prosthetic heart valves

Aortic valve neocuspidization and bioprosthetic valves: Evaluating turbulence haemodynamics

Aortic valve disease is often treated with bioprosthetic valves. An alternative treatment is aortic valve neocuspidization which is a relatively new reparative procedure whereby the three aortic cusps are replaced with patient pericardium or bovine tissues. Recent research indicates that aortic blood flow is disturbed, and turbulence effects have yet to be evaluated in either bioprosthetic or aortic valve neocuspidization valve types in patient-specific settings. The aim of this study is to better understand turbulence production in the aorta and evaluate its effects on laminar and turbulent wall shear stress. Four patients with aortic valve disease were treated with either bioprosthetic valves (n=2) or aortic valve neocuspidization valvular repair (n=2). Aortic geometries were segmented from magnetic resonance images (MRI), and 4D flow MRI was used to derive physiological inlet and outlet boundary conditions. Pulsatile large-eddy simulations were performed to capture the full range of laminar, transitional and turbulence characteristics in the aorta. Turbulence was produced in all aortas with highest levels occurring during systolic deceleration. In the ascending aorta, turbulence production is attributed to a combination of valvular skew, valvular eccentricity, and ascending aortic dilation. In the proximal descending thoracic aorta, turbulence production is dependent on the type of arch-descending aorta connection (e.g., a narrowing or sharp bend) which induces flow separation. Laminar and turbulent wall shear stresses are of similar magnitude throughout late systolic deceleration and diastole, although turbulent wall shear stress magnitudes exceed laminar wall shear stresses between 27.3% and 61.1% of the cardiac cycle. This emphasises the significance of including turbulent wall shear stress to improve our comprehension of progressive arterial wall diseases. The findings of this study recommend that aortic valve treatments should prioritise minimising valvular eccentricity and skew in order to mitigate turbulence generation.

Guidelines for the Evaluation of Prosthetic Valve Function With Cardiovascular Imaging: A Report From the American Society of Echocardiography Developed in Collaboration With the Society for Cardiovascular Magnetic Resonance and the Society of Cardiovascular Computed Tomography

In patients with significant cardiac valvular disease, intervention with either valve repair or valve replacement may be inevitable. Although valve repair is frequently performed, especially for mitral and tricuspid regurgitation, valve replacement remains common, particularly in adults. Diagnostic methods are often needed to assess the function of the prosthesis. Echocardiography is the first-line method for noninvasive evaluation of prosthetic valve function. The transthoracic approach is complemented with two-dimensional and three-dimensional transesophageal echocardiography for further refinement of valve morphology and function when needed. More recently, advances in computed tomography and cardiac magnetic resonance have enhanced their roles in evaluating valvular heart disease. This document offers a review of the echocardiographic techniques used and provides recommendations and general guidelines for evaluation of prosthetic valve function on the basis of the scientific literature and consensus of a panel of experts. This guideline discusses the role of advanced imaging with transesophageal echocardiography, cardiac computed tomography, and cardiac magnetic resonance in evaluating prosthetic valve structure, function, and regurgitation. It replaces the 2009 American Society of Echocardiography guideline on prosthetic valves and complements the 2019 guideline on the evaluation of valvular regurgitation after percutaneous valve repair or replacement.

Clinical Use of Blood Flow Analysis through 4D-Flow Imaging in Aortic Valve Disease

Bicuspid aortic valve (BAV), which affects 1% of the general population, results from the abnormal fusion of the cusps of the aortic valve. BAV can lead to the dilatation of the aorta, aortic coarctation, development of aortic stenosis (AS), and aortic regurgitation. Surgical intervention is usually recommended for patients with BAV and bicuspid aortopathy. This review aims to examine 4D-flow imaging as a tool in cardiac magnetic resonance imaging for assessing abnormal blood flow and its clinical application in BAV and AS. We present a historical clinical approach summarizing evidence of abnormal blood flow in aortic valve disease. We highlight how abnormal flow patterns can contribute to the development of aortic dilatation and novel flow-based biomarkers that can be used for a better understanding of the disease progression.

Multiscale model for blood flow after a bileaflet artificial aortic valve implantation

Cardiovascular diseases are the leading cause of mortality in the world, mainly due to atherosclerosis and its consequences. The article presents the numerical model of the blood flow through artificial aortic valve. The overset mesh approach was applied to simulate the valve leaflets motion and to realize the moving mesh, in the aortic arch and the main branches of cardiovascular system. To capture the cardiac system's response and the effect of vessel compliance on the outlet pressure, the lumped parameter model has been also included within the solution procedure. Three different turbulence modeling approaches were used and compared - the laminar, k-ϵ and k-ω model. The simulation results were also compared with the model excluding the moving valve geometry and the importance of the lumped parameter model for the outlet boundary condition was analyzed. Proposed numerical model and protocol was found as suitable for performing the virtual operations on the real patient vasculature geometry. The time-efficient turbulence model and overall solving procedure allows to support the clinicians in making decisions about the patient treatment and to predict the results of the future surgery.

Relative pressure estimation from 4D flow MRI using generalized Bernoulli equation in a phantom model of arterial stenosis

OBJECTIVE

Arterial stenosis is a significant cardiovascular disease requiring accurate estimation of the pressure gradients for determining hemodynamic significance. In this paper, we propose Generalized Bernoulli Equation (GBE) utilizing interpolated-based method to estimate relative pressures using streamlines and pathlines from 4D Flow MRI.

METHODS

4D Flow MRI data in a stenotic phantom model and computational fluid dynamics simulated velocities generated under identical flow conditions were processed by Generalized Bernoulli Equation (GBE), Reduced Bernoulli Equations (RBE), as well as the Simple Bernoulli Equation (SBE) which is clinically prevalent. Pressures derived from 4D flow MRI and noise corrupted CFD velocities were compared with pressures generated directly with CFD as well as pressures obtained using Millar catheters under identical flow conditions.

RESULTS

It was found that SBE and RBE methods underestimated the relative pressure for lower flow rates while overestimating the relative pressure at higher flow rates. Specifically, compared to the reference pressure, SBE underestimated the maximum relative pressure by 22[Formula: see text] for a pulsatile flow data with peak flow rate [Formula: see text] and overestimated by around 40[Formula: see text] when [Formula: see text]. In contrast, for GBE method the relative pressure values were overestimated by 15[Formula: see text] with [Formula: see text]and around 10[Formula: see text] with [Formula: see text].

CONCLUSION

GBE methods showed robust performance to additive image noise compared to other methods. Our findings indicate that GBE pressure estimation over pathlines attains the highest level of accuracy compared to GBE over streamlines, and the SBE and RBE methods.

Inverse problems in blood flow modeling: A review

Mathematical and computational modeling of the cardiovascular system is increasingly providing non-invasive alternatives to traditional invasive clinical procedures. Moreover, it has the potential for generating additional diagnostic markers. In blood flow computations, the personalization of spatially distributed (i.e., 3D) models is a key step which relies on the formulation and numerical solution of inverse problems using clinical data, typically medical images for measuring both anatomy and function of the vasculature. In the last years, the development and application of inverse methods has rapidly expanded most likely due to the increased availability of data in clinical centers and the growing interest of modelers and clinicians in collaborating. Therefore, this work aims to provide a wide and comparative overview of literature within the last decade. We review the current state of the art of inverse problems in blood flows, focusing on studies considering fully dimensional fluid and fluid-solid models. The relevant physical models and hemodynamic measurement techniques are introduced, followed by a survey of mathematical data assimilation approaches used to solve different kinds of inverse problems, namely state and parameter estimation. An exhaustive discussion of the literature of the last decade is presented, structured by types of problems, models and available data.

Hemodynamic Assessment in Bicuspid Aortic Valve Disease and Aortic Dilation: New Insights From Voxel-By-Voxel Analysis of Reverse Flow, Stasis, and Energetics

Objectives: Clinical management decisions surrounding ascending aorta (AAo) dilation in bicuspid aortic valve (BAV) disease benefit from personalized predictive tools. 4D-flow MRI may provide patient-specific markers reflective of BAV-associated aortopathy. This study aims to explore novel 4D-flow MRI parametric voxel-by-voxel forward flow, reverse flow, kinetic energy and stasis in BAV disease. We hypothesize that novel parametric voxel-by-voxel markers will be associated with aortic dilation and referral for surgery and can enhance our understanding of BAV hemodynamics beyond standard metrics.

Methods: A total of 96 subjects (73 BAV patients, 23 healthy controls) underwent MRI scan. Healthy controls had no known cardiovascular disease. Patients were clinically referred for AAo dilation assessment. Indexed diameters were obtained by dividing the aortic diameter by the patient’s body surface area. Patients were followed for the occurrence of aortic surgery. 4D-flow analysis was performed by a single observer in five regions: left ventricular outflow tract (LVOT), AAo, arch, proximal descending aorta (PDAo), and distal descending aorta (DDAo). In each region peak velocity, kinetic energy (KE), forward flow (FF), reverse flow (RF), and stasis were measured on a voxel-by-voxel basis. T-tests (or non-parametric equivalent) compared flow parameters between cohorts. Univariate and multivariate analyses explored associations between diameter and parametric voxel-by-voxel parameters.

Results: Compared to controls, BAV patients showed reduced stasis (p < 0.01) and increased RF and FF (p < 0.01) throughout the aorta, and KE remained similar. In the AAo, indexed diameter correlated with age (R = 0.326, p = 0.01), FF (R = −0.648, p < 0.001), RF (R = −0.441, p < 0.001), and stasis (R = −0.288, p < 0.05). In multivariate analysis, FF showed a significant inverse association with AAo indexed diameter, independent of age. During a median 179 ± 180 days of follow-up, 23 patients (32%) required aortic surgery. Compared to patients not requiring surgery, they showed increased KE and peak velocity in the proximal aorta (p < 0.01), accompanied by increased RF and reduced stasis throughout the entire aorta (p < 0.01).

Conclusion: Novel voxel-by-voxel reverse flow and stasis were altered in BAV patients and are associated with aortic dilation and surgical treatment.

Data Assimilation by Stochastic Ensemble Kalman Filtering to Enhance Turbulent Cardiovascular Flow Data From Under-Resolved Observations

We propose a data assimilation methodology that can be used to enhance the spatial and temporal resolution of voxel-based data as it may be obtained from biomedical imaging modalities. It can be used to improve the assessment of turbulent blood flow in large vessels by combining observed data with a computational fluid dynamics solver. The methodology is based on a Stochastic Ensemble Kalman Filter (SEnKF) approach and geared toward pulsatile and turbulent flow configurations. We describe the observed flow fields by a mean value and its covariance. These flow fields are combined with forecasts obtained from a direct numerical simulation of the flow field. The method is validated against canonical pulsatile and turbulent flows. Finally, it is applied to a clinically relevant configuration, namely the flow downstream of a bioprosthetic valve in an aorta phantom. It is demonstrated how the 4D flow field obtained from experimental observations can be enhanced by the data assimilation algorithm. Results show that the presented method is promising for future use with in vivo data from 4D Flow Magnetic Resonance Imaging (4D Flow MRI). 4D Flow MRI returns spatially and temporally averaged flow fields that are limited by the spatial and the temporal resolution of the tool. These averaged flow fields and the associated uncertainty might be used as observation data in the context of the proposed methodology.

Bicuspid aortic valve disease is associated with abnormal wall shear stress, viscous energy loss, and pressure drop within the ascending thoracic aorta: A cross-sectional study

Bicuspid aortic valve (BAV) disease has significant gaps in its clinical management practices. To highlight the potential utility of advanced hemodynamic biomarkers in strengthening BAV assessment, we used 4-dimentional flow magnetic resonance imaging to investigate altered hemodynamics in the ascending aorta (AAo).A total of 32 healthy controls and 53 age-matched BAV patients underwent cardiac magnetic resonance imaging at 3T, with cine imaging and 4D-flow. Analysis planes were placed along 3D-segmented aortas at the left ventricular outflow tract (LVOT), sinuses of Valsalva, mid-ascending aorta (MAA), and proximal to the first aortic branch. Locations were analyzed for aortic diameter (normalized to body surface area), pressure drop (PD), viscous energy loss (EL), and wall shear stress (WSS) sub-vectors (axial wall shear stress, circumferential wall shear stress [WSSC], magnitude wall shear stress). Student's t tests, or non-parametric equivalents, compared parameters between cohorts. Univariable and multivariable analyses explored the associations of AAo diameter with hemodynamics within the BAV cohort.Compared to control cohort, BAV patients showed significantly greater PD (MAA: 9.5 ± 8.0 vs 2.8 ± 2.4 mm Hg; P < .01), EL (from LVOT-AA1: 7.39 ± 4.57 mW vs 2.90 ± 1.07 mW; P < .01), and WSSC (MAA: 0.3 ± 0.1 vs 0.2 ± 0.06 Pa; P ≤ .01) throughout the AAo. Correlational analyses revealed an inverse association between AAo diameter and both magnitude wall shear stress and axial wall shear stress.BAV patients exhibited increased PD, EL, and WSSC in the AAo, and an inverse association between AAo diameter and WSS sub-vectors. This demonstrated the impact of PD, EL, and WSS in BAV disease and the importance of altered hemodynamics in aortic remodelling.

Bicuspid aortic valve morphology and aortic valvular outflow jets: an experimental analysis using an MRI-compatible pulsatile flow circulation system

The characteristics of aortic valvular outflow jet affect aortopathy in the bicuspid aortic valve (BAV). This study aimed to elucidate the effects of BAV morphology on the aortic valvular outflow jets. Morphotype-specific valve-devising apparatuses were developed to create aortic valve models. A magnetic resonance imaging-compatible pulsatile flow circulation system was developed to quantify the outflow jet. The eccentricity and circulation values of the peak systolic jet were compared among tricuspid aortic valve (TAV), three asymmetric BAVs, and two symmetric BAVs. The results showed mean aortic flow and leakage did not differ among the five BAVs (six samples, each). Asymmetric BAVs demonstrated the eccentric outflow jets directed to the aortic wall facing the smaller leaflets. In the asymmetric BAV with the smaller leaflet facing the right-anterior, left-posterior, and left-anterior quadrants of the aorta, the outflow jets exclusively impinged on the outer curvature of the ascending aorta, proximal arch, and the supra-valvular aortic wall, respectively. Symmetric BAVs demonstrated mildly eccentric outflow jets that did not impinge on the aortic wall. The circulation values at peak systole increased in asymmetric BAVs. The bicuspid symmetry and the position of smaller leaflet were determinant factors of the characteristics of aortic valvular outflow jet.

On the limitations of echo planar 4D flow MRI

PURPOSE

To compare EPI and GRE readout in high-flow velocity regimes and evaluate their impact on measurement accuracy in silico and in vitro.

THEORY AND METHODS

Phase-contrast sequences for EPI and GRE were simulated using CFD velocity data to assess displacement artifacts as well as effective spatial resolution. In silico findings were validated experimentally using a steady flow phantom.

RESULTS

For EPI factor 5 and simulated stenotic flow with peak velocity of 2.2 m s - 1 , displacement artifacts resulted in misregistration of 7.3 mm at echo time and the effective resolution was locally reduced by factors 5 and 8 compared to GRE for flow along phase and frequency encoding directions, respectively. In vitro, a maximum velocity difference between EPI factor 5 and GRE of 0.97 m s - 1 was found.

CONCLUSIONS

Four-dimensional flow MRI using EPI readout results not only in considerable velocity misregistration but also in spatially varying degradation of resolution. The proposed work indicates that EPI is inferior to standard GRE for 4D flow MRI.

Multipoint 5D flow cardiovascular magnetic resonance - accelerated cardiac- and respiratory-motion resolved mapping of mean and turbulent velocities

BACKGROUND

Volumetric quantification of mean and fluctuating velocity components of transient and turbulent flows promises a comprehensive characterization of valvular and aortic flow characteristics. Data acquisition using standard navigator-gated 4D Flow cardiovascular magnetic resonance (CMR) is time-consuming and actual scan times depend on the breathing pattern of the subject, limiting the applicability of the method in a clinical setting. We sought to develop a 5D Flow CMR framework which combines undersampled data acquisition including multipoint velocity encoding with low-rank image reconstruction to provide cardiac- and respiratory-motion resolved assessment of velocity maps and turbulent kinetic energy in fixed scan times.

METHODS

Data acquisition and data-driven motion state detection was performed using an undersampled Cartesian tiny Golden angle approach. Locally low-rank (LLR) reconstruction was implemented to exploit correlations among heart phases and respiratory motion states. To ensure accurate quantification of mean and turbulent velocities, a multipoint encoding scheme with two velocity encodings per direction was incorporated. Velocity-vector fields and turbulent kinetic energy (TKE) were obtained using a Bayesian approach maximizing the posterior probability given the measured data. The scan time of 5D Flow CMR was set to 4 min. 5D Flow CMR with acceleration factors of 19 .0 ± 0.21 (mean ± std) and velocity encodings (VENC) of 0.5 m/s and 1.5 m/s per axis was compared to navigator-gated 2x SENSE accelerated 4D Flow CMR with VENC = 1.5 m/s in 9 subjects. Peak velocities and peak flow were compared and magnitude images, velocity and TKE maps were assessed.

RESULTS

While net scan time of 5D Flow CMR was 4 min independent of individual breathing patterns, the scan times of the standard 4D Flow CMR protocol varied depending on the actual navigator gating efficiency and were 17.8 ± 3.9 min on average. Velocity vector fields derived from 5D Flow CMR in the end-expiratory state agreed well with data obtained from the navigated 4D protocol (normalized root-mean-square error 8.9 ± 2.1%). On average, peak velocities assessed with 5D Flow CMR were higher than for the 4D protocol (3.1 ± 4.4%).

CONCLUSIONS

Respiratory-motion resolved multipoint 5D Flow CMR allows mapping of mean and turbulent velocities in the aorta in 4 min.