Turbulent Kinetic Energy Measurement Using Phase Contrast MRI for Estimating the Post-Stenotic Pressure Drop: In Vitro Validation and Clinical Application

Haemodynamic significance of extrinsic outflow graft stenoses during HeartMate 3™ therapy

Aims

The HeartMate 3 (HM3) implantable left ventricular assist device connects the left ventricle apex to the aorta via an outflow graft. Extrinsic obstruction of the graft (eOGO) is associated with serious morbidity and mortality and recently led to a Food and Drug Administration Class 1 device recall of HM3. This study aimed to provide a better understanding of the haemodynamic impact of extrinsic stenoses.

Methods and results

Computed tomography (CT) images of two retrospectively identified patients with eOGO (29 and 36% decrease in cross-sectional area, respectively, by radiological evaluation) were acquired with a novel photon-counting CT system. Numerical evaluations of haemodynamics were conducted using a high-fidelity 3D computational fluid dynamics approach on both the patient-specific graft geometries and in two virtually augmented stenotic severities and three device flows. Visual analysis identified increased velocity, pressure, and turbulent flow in the outer anterior curvature of the outflow graft; however, changes in graft pressure gradients were slight (1-9 mmHg) across the range of stenosis severities and flow rates tested.

Conclusion

Evidence of eOGO during HM3 support and the recent device recall can provoke clinical apprehension and interventions. The haemodynamic impact of a stenosis detected visually or by quantification of cross-sectional area reduction may be difficult to predict and easily overestimated. This numerical study suggests that, for clinically encountered flow rates and stenosis severities below 61% in cross-sectional area decrease, eOGO may have low haemodynamic impact. This suggests that patients without symptoms or signs consistent with haemodynamically significant obstruction might be managed expectantly.

Measurement of Turbulent Kinetic Energy in Hypertrophic Cardiomyopathy Using Triple-velocity Encoding 4D Flow MR Imaging

PURPOSE

The turbulent kinetic energy (TKE) estimation based on 4D flow MRI has been currently developed and can be used to estimate the pressure gradient. The objective of this study was to validate the clinical value of 4D flow-based TKE measurement in patients with hypertrophic cardiomyopathy (HCM).

METHODS

From April 2018 to March 2019, we recruited 28 patients with HCM. Based on echocardiography, they were divided into obstructed HCM (HOCM) and non-obstructed HCM (HNCM). Triple-velocity encoding 4D flow MRI was performed. The volume-of-interest from the left ventricle to the aortic arch was drawn semi-automatically. We defined peak turbulent kinetic energy (TKEpeak) as the highest TKE phase in all cardiac phases.

RESULTS

TKEpeak was significantly higher in HOCM than in HNCM (14.83 ± 3.91 vs. 7.11 ± 3.60 mJ, P < 0.001). TKEpeak was significantly higher in patients with systolic anterior movement (SAM) than in those without SAM (15.60 ± 3.96 vs. 7.44 ± 3.29 mJ, P < 0.001). Left ventricular (LV) mass increased proportionally with TKEpeak (P = 0.012, r = 0.466). When only the asymptomatic patients were extracted, a stronger correlation was observed (P = 0.001, r = 0.842).

CONCLUSION

TKE measurement based on 4D flow MRI can detect the flow alteration induced by systolic flow jet and LV outflow tract geometry, such as SAM in patients with HOCM. The elevated TKE is correlated with increasing LV mass. This indicates that increasing cardiac load, by pressure loss due to turbulence, induces progression of LV hypertrophy, which leads to a worse prognosis.

4Dflow-VP-Net: A deep convolutional neural network for noninvasive estimation of relative pressures in stenotic flows from 4D flow MRI

PURPOSE

To estimate relative transvalvular pressure gradient (TVPG) noninvasively from 4D flow MRI.

METHODS

A novel deep learning-based approach is proposed to estimate pressure gradient across stenosis from four-dimensional flow MRI (4D flow MRI) velocities. A deep neural network 4D flow Velocity-to-Presure Network (4Dflow-VP-Net) was trained to learn the spatiotemporal relationship between velocities and pressure in stenotic vessels. Training data were simulated by computational fluid dynamics (CFD) for different pulsatile flow conditions under an aortic flow waveform. The network was tested to predict pressure from CFD-simulated velocity data, in vitro 4D flow MRI data, and in vivo 4D flow MRI data of patients with both moderate and severe aortic stenosis. TVPG derived from 4Dflow-VP-Net was compared to catheter-based pressure measurements for available flow rates, in vitro and Doppler echocardiography-based pressure measurement, in vivo.

RESULTS

Relative pressures calculated by 4Dflow-VP-Net and in vitro pressure catheterization revealed strong correlation (r2  = 0.91). Correlations analysis of TVPG from reference CFD and 4Dflow-VP-Net for 450 simulated flow conditions showed strong correlation (r2  = 0.99). TVPG from in vitro MRI had a correlation coefficient of r2  = 0.98 with reference CFD. 4Dflow-VP-Net, applied to 4D flow MRI in 16 patients, showed comparable TVPG measurement with Doppler echocardiography (r2  = 0.85). Bland-Altman analysis of TVPG measurements showed mean bias and limits of agreement of -0.20 ± 2.07 mmHg and 0.19 ± 0.45 mmHg for CFD-simulated velocities and in vitro 4D flow velocities. In patients, overestimation of Doppler echocardiography relative to TVPG from 4Dflow-VP-Net (10.99 ± 6.77 mmHg) was observed.

CONCLUSION

The proposed approach can predict relative pressure in both in vitro and in vivo 4D flow MRI of aortic stenotic patients with high fidelity.

Non-invasive cardiovascular magnetic resonance assessment of pressure recovery distance after aortic valve stenosis

BACKGROUND

Decisions in the management of aortic stenosis are based on the peak pressure drop, captured by Doppler echocardiography, whereas gold standard catheterization measurements assess the net pressure drop but are limited by associated risks. The relationship between these two measurements, peak and net pressure drop, is dictated by the pressure recovery along the ascending aorta which is mainly caused by turbulence energy dissipation. Currently, pressure recovery is considered to occur within the first 40-50 mm distally from the aortic valve, albeit there is inconsistency across interventionist centers on where/how to position the catheter to capture the net pressure drop.

METHODS

We developed a non-invasive method to assess the pressure recovery distance based on blood flow momentum via 4D Flow cardiovascular magnetic resonance (CMR). Multi-center acquisitions included physical flow phantoms with different stenotic valve configurations to validate this method, first against reference measurements and then against turbulent energy dissipation (respectively n = 8 and n = 28 acquisitions) and to investigate the relationship between peak and net pressure drops. Finally, we explored the potential errors of cardiac catheterisation pressure recordings as a result of neglecting the pressure recovery distance in a clinical bicuspid aortic valve (BAV) cohort of n = 32 patients.

RESULTS

In-vitro assessment of pressure recovery distance based on flow momentum achieved an average error of 1.8 ± 8.4 mm when compared to reference pressure sensors in the first phantom workbench. The momentum pressure recovery distance and the turbulent energy dissipation distance showed no statistical difference (mean difference of 2.8 ± 5.4 mm, R2 = 0.93) in the second phantom workbench. A linear correlation was observed between peak and net pressure drops, however, with strong dependences on the valvular morphology. Finally, in the BAV cohort the pressure recovery distance was 78.8 ± 34.3 mm from vena contracta, which is significantly longer than currently accepted in clinical practise (40-50 mm), and 37.5% of patients displayed a pressure recovery distance beyond the end of the ascending aorta.

CONCLUSION

The non-invasive assessment of the distance to pressure recovery is possible by tracking momentum via 4D Flow CMR. Recovery is not always complete at the ascending aorta, and catheterised recordings will overestimate the net pressure drop in those situations. There is a need to re-evaluate the methods that characterise the haemodynamic burden caused by aortic stenosis as currently clinically accepted pressure recovery distance is an underestimation.

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.

The Role of Hemodynamics through the Circle of Willis in the Development of Intracranial Aneurysm: A Systematic Review of Numerical Models

Background: The role of regional hemodynamics in the intracranial aneurysmal formation, growth, and rupture has been widely discussed based on numerical models over the past decades. Variation of the circle of Willis (CoW), which results in hemodynamic changes, is associated with the aneurysmal formation and rupture. However, such correlation has not been further clarified yet. The aim of this systematic review is to investigate whether simulated hemodynamic indices of the CoW are relevant to the formation, growth, or rupture of intracranial aneurysm. Methods: We conducted a review of MEDLINE, Web of Science, and EMBASE for studies on the correlation between hemodynamics indices of the CoW derived from numerical models and intracranial aneurysm up to December 2020 in compliance with PRISMA guidelines. Results: Three case reports out of 1046 publications met our inclusion and exclusion criteria, reporting 13 aneurysms in six patients. Eleven aneurysms were unruptured, and the state of the other two aneurysms was unknown. Wall shear stress, oscillatory shear index, von-Mises tension, flow velocity, and flow rate were reported as hemodynamic indices. Due to limited cases and significant heterogeneity between study settings, meta-analysis could not be performed. Conclusion: Numerical models can provide comprehensive information on the cerebral blood flow as well as local flow characteristics in the intracranial aneurysm. Based on only three case reports, no firm conclusion can be drawn regarding the correlation between hemodynamic parameters in the CoW derived from numerical models and aneurysmal formation or rupture. Due to the inherent nature of numerical models, more sensitive analysis and rigorous validations are required to determine its measurement error and thus extend their application into clinical practice for personalized management. Prospero registration number: CRD42021125169.

Turbulent Intensity of Blood Flow in the Healthy Aorta Increases With Dobutamine Stress and is Related to Cardiac Output

Introduction: The blood flow in the normal cardiovascular system is predominately laminar but operates close to the threshold to turbulence. Morphological distortions such as vascular and valvular stenosis can cause transition into turbulent blood flow, which in turn may cause damage to tissues in the cardiovascular system. A growing number of studies have used magnetic resonance imaging (MRI) to estimate the extent and degree of turbulent flow in different cardiovascular diseases. However, the way in which heart rate and inotropy affect turbulent flow has not been investigated. In this study we hypothesized that dobutamine stress would result in higher turbulence intensity in the healthy thoracic aorta.

Method: 4D flow MRI data were acquired in twelve healthy subjects at rest and with dobutamine, which was infused until the heart rate increased by 60% when compared to rest. A semi-automatic segmentation method was used to segment the thoracic aorta in the 4D flow MR images. Subsequently, flow velocity and several turbulent kinetic energy (TKE) parameters were calculated in the ascending aorta, aortic arch, descending aorta and whole thoracic aorta.

Results: With dobutamine infusion there was an increase in heart rate (66 ± 9 vs. 108 ± 13 bpm, p < 0.001) and stroke volume (88 ± 13 vs. 102 ± 25 ml, p < 0.01). Additionally, there was an increase in Peak Average velocity (0.7 ± 0.1 vs. 1.2 ± 0.2 m/s, p < 0.001, Peak Max velocity (1.3 ± 0.1 vs. 2.0 ± 0.2 m/s, p < 0.001), Peak Total TKE (2.9 ± 0.7 vs. 8.0 ± 2.2 mJ, p < 0.001), Peak Median TKE (36 ± 7 vs. 93 ± 24 J/m3, p = 0.002) and Peak Max TKE (176 ± 33 vs. 334 ± 69 J/m3, p < 0.001). The relation between cardiac output and Peak Total TKE in the whole thoracic aorta was very strong (R² = 0.90, p < 0.001).

Conclusion: TKE of blood flow in the healthy thoracic aorta increases with dobutamine stress and is strongly related to cardiac output. Quantification of such turbulence intensity parameters with cardiac stress may serve as a risk assessment of aortic disease development.

Clinical Application of 4D Flow MR Imaging for the Abdominal Aorta

Blood vessels can be regarded as autonomous organs. The endothelial cells on the vessel surface serve as mechanosensors or mechanoreceptors for the flow velocity and turbulence of the blood flow in terms of wall shear stress (WSS), thereby monitoring changes in the flow velocity. Accordingly, the endothelial cells regulate the flow velocity by releasing numerous mediators. Such regulatory systems also trigger atherosclerosis, where the WSS decreases or fluctuates to maintain the flow velocity or local WSS. As occurrences of abdominal aortic aneurysms and aortic dissection are closely related to atherosclerosis, understanding the hemodynamics of the abdominal aorta is necessary to obtain useful information concerning the pathogenesis, diagnosis, and interventions. 4D flow MRI is beneficial for measuring the hemodynamics through comprehensive retrospective flowmetry of the entire spatio-temporal distributions of the flow vectors. This section focuses on abdominal aortic aneurysms and aortic dissection as representative examples of abdominal aortic diseases. Their hemodynamic characteristics and how hemodynamics is involved in their progression are described, and how 4D flow MRI can contribute to their assessment is also explained.

Scale-Resolving Simulations of Steady and Pulsatile Flow Through Healthy and Stenotic Heart Valves

Blood-flow downstream of stenotic and healthy aortic valves exhibits intermittent random fluctuations in the velocity field which are associated with turbulence. Such flows warrant the use of computationally demanding scale-resolving models. The aim of this work was to compute and quantify this turbulent flow in healthy and stenotic heart valves for steady and pulsatile flow conditions. Large eddy simulations (LESs) and Reynolds-averaged Navier-Stokes (RANS) simulations were used to compute the flow field at inlet Reynolds numbers of 2700 and 5400 for valves with an opening area of 70 mm2 and 175 mm2 and their projected orifice-plate type counterparts. Power spectra and turbulent kinetic energy were quantified on the centerline. Projected geometries exhibited an increased pressure-drop (>90%) and elevated turbulent kinetic energy levels (>147%). Turbulence production was an order of magnitude higher in stenotic heart valves compared to healthy valves. Pulsatile flow stabilizes flow in the acceleration phase, whereas onset of deceleration triggered (healthy valve) or amplified (stenotic valve) turbulence. Simplification of the aortic valve by projecting the orifice area should be avoided in computational fluid dynamics (CFD). RANS simulations may be used to predict the transvalvular pressure-drop, but scale-resolving models are recommended when detailed information of the flow field is required.

Hemodynamic Parameters for Cardiovascular System in 4D Flow MRI: Mathematical Definition and Clinical Applications

Blood flow imaging becomes an emerging trend in cardiology with the recent progress in computer technology. It not only visualizes colorful flow velocity streamlines but also quantifies the mechanical stress on cardiovascular structures; thus, it can provide the detailed inspections of the pathophysiology of diseases and predict the prognosis of cardiovascular functions. Clinical applications include the comprehensive assessment of hemodynamics and cardiac functions in echocardiography vector flow mapping (VFM), 4D flow MRI, and surgical planning as a simulation medicine in computational fluid dynamics (CFD).For evaluation of the hemodynamics, novel mathematically derived parameters obtained using measured velocity distributions are essential. Among them, the traditional and typical parameters are wall shear stress (WSS) and its related parameters. These parameters indicate the mechanical damages to endothelial cells, resulting in degenerative intimal change in vascular diseases. Apart from WSS, there are abundant parameters that describe the strength of the vortical and/or helical flow patterns. For instance, vorticity, enstrophy, and circulation indicate the rotating flow strength or power of 2D vortical flows. In addition, helicity, which is defined as the cross-linking number of the vortex filaments, indicates the 3D helical flow strength and adequately describes the turbulent flow in the aortic root in cases with complicated anatomies. For the description of turbulence caused by the diseased flow, there exist two types of parameters based on completely different concepts, namely: energy loss (EL) and turbulent kinetic energy (TKE). EL is the dissipated energy with blood viscosity and evaluates the cardiac workload related to the prognosis of heart failure. TKE describes the fluctuation in kinetic energy during turbulence, which describes the severity of the diseases that cause jet flow. These parameters are based on intuitive and clear physiological concepts, and are suitable for in vivo flow measurements using inner velocity profiles.

In-vitro and In-Vivo Assessment of 4D Flow MRI Reynolds Stress Mapping for Pulsatile Blood Flow

Imaging hemodynamics play an important role in the diagnosis of abnormal blood flow due to vascular and valvular diseases as well as in monitoring the recovery of normal blood flow after surgical or interventional treatment. Recently, characterization of turbulent blood flow using 4D flow magnetic resonance imaging (MRI) has been demonstrated by utilizing the changes in signal magnitude depending on intravoxel spin distribution. The imaging sequence was extended with a six-directional icosahedral (ICOSA6) flow-encoding to characterize all elements of the Reynolds stress tensor (RST) in turbulent blood flow. In the present study, we aimed to demonstrate the feasibility of full RST analysis using ICOSA6 4D flow MRI under physiological conditions. First, the turbulence analysis was performed through in vitro experiments with a physiological pulsatile flow condition. Second, a total of 12 normal subjects and one patient with severe aortic stenosis were analyzed using the same sequence. The in-vitro study showed that total turbulent kinetic energy (TKE) was less affected by the signal-to-noise ratio (SNR), however, maximum principal turbulence shear stress (MPTSS) and total turbulence production (TP) had a noise-induced bias. Smaller degree of the bias was observed for TP compared to MPTSS. In-vivo study showed that the subject-variability on turbulence quantification was relatively low for the consistent scan protocol. The in vivo demonstration of the stenosis patient showed that the turbulence analysis could clearly distinguish the difference in all turbulence parameters as they were at least an order of magnitude larger than those from the normal subjects.

An improved reduced-order model for pressure drop across arterial stenoses

Quantification of pressure drop across stenotic arteries is a major element in the functional assessment of occlusive arterial disease. Accurate estimation of the pressure drop with a numerical model allows the calculation of Fractional Flow Reserve (FFR), which is a haemodynamic index employed for guiding coronary revascularisation. Its non-invasive evaluation would contribute to safer and cost-effective diseases management. In this work, we propose a new formulation of a reduced-order model of trans-stenotic pressure drop, based on a consistent theoretical analysis of the Navier-Stokes equation. The new formulation features a novel term that characterises the contribution of turbulence effect to pressure loss. Results from three-dimensional computational fluid dynamics (CFD) showed that the proposed model produces predictions that are significantly more accurate than the existing reduced-order models, for large and small symmetric and eccentric stenoses, covering mild to severe area reductions. FFR calculations based on the proposed model produced zero classification error for three classes comprising positive (≤ 0.75), negative (≥ 0.8) and intermediate (0.75 − 0.8) classes.

Comparison of Four-Dimensional Flow Magnetic Resonance Imaging and Particle Image Velocimetry to Quantify Velocity and Turbulence Parameters

Although recent advances of four-dimensional (4D) flow magnetic resonance imaging (MRI) has introduced a new way to measure Reynolds stress tensor (RST) in turbulent flows, its measurement accuracy and possible bias have remained to be revealed. The purpose of this study was to compare the turbulent flow measurement of 4D flow MRI and particle image velocimetry (PIV) in terms of velocity and turbulence quantification. Two difference flow rates of 10 and 20 L/min through a 50% stenosis were measured with both PIV and 4D flow MRI. Not only velocity through the stenosis but also the turbulence parameters such as turbulence kinetic energy and turbulence production were quantitatively compared. Results shows that 4D flow MRI velocity measurement well agreed with the that of PIV, showing the linear regression slopes of two methods are 0.94 and 0.89, respectively. Although turbulence mapping of 4D flow MRI was qualitatively agreed with that of PIV, the quantitative comparison shows that the 4D flow MRI overestimates RST showing the linear regression slopes of 1.44 and 1.66, respectively. In this study, we demonstrate that the 4D flow MRI visualize and quantify not only flow velocity and also turbulence tensor. However, further optimization of 4D flow MRI for better accuracy might be remained.

Self-navigated versus navigator-gated 3D MRI sequence for non-enhanced aortic root measurement in transcatheter aortic valve implantation

OBJECTIVES

To prospectively compare image-quality, reliability and graft sizing of a prototype self-navigated and a navigator-gated non-contrast three dimensional (3D) whole-heart magnetic-resonance-angiography (MRA) sequence with computed-tomography-angiography (CTA) for planning transcatheter-aortic-valve-implantation (TAVI).

METHODS

Self- and navigator-gated 1.5 T MRA were performed in 27 patients (aged 83 ± 5 years, 41 % male) for aortic root sizing and coronary ostia height measurements; 15 (56 %) patients underwent additional CTA. Subjective-image quality was graded on a 4-point Likert scale, objective MRA image-quality was assessed by signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Continuous MRA and CTA measurements were analyzed with regression and Bland-Altman analysis, valve sizing by kappa statistics.

RESULTS

Median image-quality as rated by two observers was 1.5 [interquartile range (IQR) 1-3] for self-navigated MRA and 1 [IQR 1-2] for navigator-gated MRA (p = 0.059). SNR and CNR were comparable between MRA sequences (p = 0.471 and 0.445, respectively). Acquisition time was shorter for self-navigated MRA compared to navigator-gated MRA (5.5 ± 1 min vs, 6.5 ± 2 min, p = 0.029). Inter-observer correlation of aortic root measurements was high to very high for both self- and navigator-gated MRA (r = 0.75 to 0.94 and r = 0.85 to 0.96, respectively, all p < 0.0001). Theoretical prosthetic valve sizing of self-navigated MRA and CTA was equivalent (κ = 1). However, in four patients (15 %) one coronary ostium each (right coronary artery 3, left main artery 1) was not clearly definable on self-navigated MRA.

CONCLUSION

Self-navigated MRA enables aortic annulus TAVI measurements without significant difference to navigator-gated MRA at shortened acquisition time. Prosthesis sizing by self-navigated MRA measurements is equivalent to navigator-gated MRA and CTA-based choice.

Characterization of anisotropic turbulence behavior in pulsatile blood flow

Turbulent-like hemodynamics with prominent cycle-to-cycle flow variations have received increased attention as a potential stimulus for cardiovascular diseases. These turbulent conditions are typically evaluated in a statistical sense from single scalars extracted from ensemble-averaged tensors (such as the Reynolds stress tensor), limiting the amount of information that can be used for physical interpretations and quality assessments of numerical models. In this study, barycentric anisotropy invariant mapping was used to demonstrate an efficient and comprehensive approach to characterize turbulence-related tensor fields in patient-specific cardiovascular flows, obtained from scale-resolving large eddy simulations. These techniques were also used to analyze some common modeling compromises as well as MRI turbulence measurements through an idealized constriction. The proposed method found explicit sites of elevated turbulence anisotropy, including a broad but time-varying spectrum of characteristics over the flow deceleration phase, which was different for both the steady inflow and Reynolds-averaged Navier–Stokes modeling assumptions. Qualitatively, the MRI results showed overall expected post-stenotic turbulence characteristics, however, also with apparent regions of unrealizable or conceivably physically unrealistic conditions, including the highest turbulence intensity ranges. These findings suggest that more detailed studies of MRI-measured turbulence fields are needed, which hopefully can be assisted by more comprehensive evaluation tools such as the once described herein.

Non-invasive determination of pressure recovery by cardiac MRI and echocardiography in patients with severe aortic stenosis: short and long-term outcome prediction

OBJECTIVE

To assess the influence of pressure recovery (PR)-corrected haemodynamic parameters on outcome in patients with aortic stenosis.

METHODS

Aortic stenosis severity parameters were corrected for PR (increase in static pressure due to decreasing dynamic pressure), assessed using transthoracic echocardiography (TTE) or cardiac magnetic resonance imaging (CMR), in patients with aortic stenosis. PR, indexed PR (iPR) and energy loss index (ELI) were determined. Factors that predicted all-cause mortality, and 9-month or 10-year New York Heart Association classification ≥2 were assessed using Cox proportional hazards regression.

RESULTS

A total of 25 patients, aged 68 ± 10 years, were included. PR was 17 ± 6 mmHg using CMR, and CMR correlated with TTE measurements. PR correction using CMR data reduced the AS-severity classification in 12-20% of patients, and correction using TTE data reduced the AS-severity classification in 16% of patients. Age (Wald 4.774) was a statistically significant predictor of all-cause mortality; effective orifice area (Wald 3.753) and ELI (Wald 3.772) almost reached significance.

CONCLUSIONS

PR determination may result in significant reclassification of aortic stenosis severity and may hold value in predicting all-cause mortality.

Usefulness of Cardiac Magnetic Resonance Imaging in Aortic Stenosis

The objective of this review is to provide an overview of the role of cardiac magnetic resonance (CMR) in aortic stenosis (AS). Although CMR is undeniably the gold standard for assessing left ventricular volume, mass, and function, the assessment of the left ventricular repercussions of AS by CMR is not routinely performed in clinical practice, and its role in evaluating and quantifying AS is not yet well established. CMR is an imaging modality integrating myocardial function and disease, which could be particularly useful in a pathology like AS that should be considered as a global myocardial disease rather than an isolated valve disease. In this review, we discuss the emerging potential of CMR for the diagnosis and prognosis of AS. We detail its utility for studying all aspects of AS, including valve anatomy, flow quantification, left ventricular volumes, mass, remodeling, and function, tissue mapping, and 4-dimensional flow magnetic resonance imaging. We also discuss different clinical situations where CMR could be useful in AS, for example, in low-flow low-gradient AS to confirm the low-flow state and to understand the reason for the left ventricular dysfunction or when there is a suspicion of associated cardiac amyloidosis.

Advanced cardiac MRI techniques for evaluation of left-sided valvular heart disease

The most common types of left‐sided valvular heart disease (VHD) in the Western world are aortic valve stenosis, aortic valve regurgitation, and mitral valve regurgitation. Comprehensive clinical evaluation entails both hemodynamic analysis and structural as well as functional characterization of the left ventricle. Cardiac magnetic resonance imaging (MRI) is an established diagnostic modality for assessment of left‐sided VHD and is progressively gaining ground in modern‐day clinical practice. Detailed flow visualization and quantification of flow‐related biomarkers in VHD can be obtained using 4D flow MRI, an imaging technique capable of measuring blood flow in three orthogonal directions over time. In addition, recent MRI sequences enable myocardial tissue characterization and strain analysis. In this review we discuss the emerging potential of state‐of‐the‐art MRI including 4D flow MRI, tissue mapping, and strain quantification for the diagnosis and prognosis of left‐sided VHD.

Level of Evidence: 1

Technical Efficacy Stage: 1

J. Magn. Reson. Imaging 2018. J. MAGN. RESON. IMAGING 2018;48:318–329.

Non-Invasive Assessment of Intravascular Pressure Gradients: A Review of Current and Proposed Novel Methods

Invasive catheterization is associated with a low risk of serious complications. However, although it is the gold standard for measuring pressure gradients, it induces changes to blood flow and requires significant resources. Therefore, non-invasive alternatives are urgently needed. Pressure gradients are routinely estimated non-invasively in clinical settings using ultrasound and calculated with the simplified Bernoulli equation, a method with several limitations. A PubMed literature search on validation of non-invasive techniques was conducted, and studies were included if non-invasively estimated pressure gradients were compared with invasively measured pressure gradients in vivo. Pressure gradients were mainly estimated from velocities obtained with Doppler ultrasound or magnetic resonance imaging. Most studies used the simplified Bernoulli equation, but more recent studies have employed the expanded Bernoulli and Navier⁻Stokes equations. Overall, the studies reported good correlation between non-invasive estimation of pressure gradients and catheterization. Despite having strong correlations, several studies reported the non-invasive techniques to either overestimate or underestimate the invasive measurements, thus questioning the accuracy of the non-invasive methods. In conclusion, more advanced imaging techniques may be needed to overcome the shortcomings of current methods.

Validation of pressure drop assessment using 4D flow MRI-based turbulence production in various shapes of aortic stenoses

PURPOSE

To validate pressure drop measurements using 4D flow MRI-based turbulence production in various shapes of stenotic stenoses.

METHODS

In vitro flow phantoms with seven different 3D-printed aortic valve geometries were constructed and scanned with 4D flow MRI with six-directional flow encoding (ICOSA6). The pressure drop through the valve was non-invasively predicted based on the simplified Bernoulli, the extended Bernoulli, the turbulence production, and the shear-scaling methods. Linear regression and agreement of the predictions with invasively measured pressure drop were analyzed.

RESULTS

All pressure drop predictions using 4D Flow MRI were linearly correlated to the true pressure drop but resulted in different regression slopes. The regression slope and 95% limits of agreement for the simplified Bernoulli method were 1.35 and 11.99 ± 21.72 mm Hg. The regression slope and 95% limits of agreement for the extended Bernoulli method were 1.02 and 0.74 ± 8.48 mm Hg. The regression slope and 95% limits of agreement for the turbulence production method were 0.89 and 0.96 ± 8.01 mm Hg. The shear-scaling method presented good correlation with an invasively measured pressure drop, but the regression slope varied between 0.36 and 1.00 depending on the shear-scaling coefficient.

CONCLUSION

The pressure drop assessment based on the turbulence production method agrees well with the extended Bernoulli method and invasively measured pressure drop in various shapes of the aortic valve. Turbulence-based pressure drop estimation can, as a complement to the conventional Bernoulli method, play a role in the assessment of valve diseases.

Effect of pannus formation on the prosthetic heart valve: In vitro demonstration using particle image velocimetry

Although hemodynamic influence of the subprosthetic tissue, termed as pannus, may contribute to prosthetic aortic valve dysfunction, the relationship between pannus extent and hemodynamics in the prosthetic valve has rarely been reported. We investigated the fluid dynamics of pannus formation using in vitro experiments with particle image velocimetry. Subvalvular pannus formation caused substantial changes in prosthetic valve transvalvular peak velocity, transvalvular pressure gradient (TPG) and opening angle. Maximum flow velocity and corresponding TPG were mostly affected by pannus width. When the pannus width was 25% of the valve diameter, pannus formation elevated TPG to >2.5 times higher than that without pannus formation. Opening dysfunction was observed only for a pannus involvement angle of 360°. Although circumferential pannus with an involvement angle of 360° decreased the opening angle of the valve from approximately 82° to 58°, eccentric pannus with an involvement angle of 180° did not induce valve opening dysfunction. The pannus involvement angle largely influenced the velocity flow field at the aortic sinus and corresponding hemodynamic indices, including wall shear stress, principal shear stress and viscous energy loss distributions. Substantial discrepancy between the velocity-based TPG estimation and direct pressure measurements was observed for prosthetic valve flow with pannus formation.

Age-Related Vascular Changes Affect Turbulence in Aortic Blood Flow

Turbulent blood flow is implicated in the pathogenesis of several aortic diseases but the extent and degree of turbulent blood flow in the normal aorta is unknown. We aimed to quantify the extent and degree of turbulece in the normal aorta and to assess whether age impacts the degree of turbulence. 22 young normal males (23.7 ± 3.0 y.o.) and 20 old normal males (70.9 ± 3.5 y.o.) were examined using four dimensional flow magnetic resonance imaging (4D Flow MRI) to quantify the turbulent kinetic energy (TKE), a measure of the intensity of turbulence, in the aorta. All healthy subjects developed turbulent flow in the aorta, with total TKE of 3–19 mJ. The overall degree of turbulence in the entire aorta was similar between the groups, although the old subjects had about 73% more total TKE in the ascending aorta compared to the young subjects (young = 3.7 ± 1.8 mJ, old = 6.4 ± 2.4 mJ, p < 0.001). This increase in ascending aorta TKE in old subjects was associated with age-related dilation of the ascending aorta which increases the volume available for turbulence development. Conversely, age-related dilation of the descending and abdominal aorta decreased the average flow velocity and suppressed the development of turbulence. In conclusion, turbulent blood flow develops in the aorta of normal subjects and is impacted by age-related geometric changes. Non-invasive assessment enables the determination of normal levels of turbulent flow in the aorta which is a prerequisite for understanding the role of turbulence in the pathophysiology of cardiovascular disease.

Association between flow skewness and aortic dilatation in patients with aortic stenosis

We investigated association between hemodynamic characteristics and aortic dilatation in patients with severe aortic stenosis (AS). Eighty patients with severe AS (mean age, 67.2 ± 12.5 years) who underwent multi-detector computed tomography and phase-contrast magnetic resonance imaging at the ascending aorta were retrospectively analyzed. Patients with an ascending aorta diameter >4 cm had a significantly higher forward flow rate at systole (28.5 ± 6.0 vs. 36.2 ± 8.6 L min, P < 0.001), and retrograde flow rate at systole (11.3 ± 4.2 vs. 18.8 ± 5.8 L min, P < 0.001), fractional reverse ratio (a ratio of retrograde flow rate to forward flow rate; 34.1 ± 11.9% vs. 43.5 ± 18.0%, P = 0.014), flow skewness R_skewness (a ratio of sum of forward and retrograde systole flow to net systole flow rate; 2.4 ± 0.7 vs. 3.2 ± 1.0, P < 0.001). The presence of bicuspid aortic valve (BAV; odds ratio [OR] 72.01, 95% confidence interval [CI] 10.57-490.46, P < 0.001), Left ventricular mass index (LVMI; OR 1.02 /g/m²; CI 1.00-1.04, P = 0.043) and R_skewness (OR 5.6 per 1, 95% CI 1.8-17.1, P = 0.001) were associated with aortic dilatation. BAV, LVMI, and increased R_skewness in the ascending aorta are associated with aortic dilatation in patients with AS.

Estimating the irreversible pressure drop across a stenosis by quantifying turbulence production using 4D Flow MRI

The pressure drop across a stenotic vessel is an important parameter in medicine, providing a commonly used and intuitive metric for evaluating the severity of the stenosis. However, non-invasive estimation of the pressure drop under pathological conditions has remained difficult. This study demonstrates a novel method to quantify the irreversible pressure drop across a stenosis using 4D Flow MRI by calculating the total turbulence production of the flow. Simulation MRI acquisitions showed that the energy lost to turbulence production can be accurately quantified with 4D Flow MRI within a range of practical spatial resolutions (1-3 mm; regression slope = 0.91, R2 = 0.96). The quantification of the turbulence production was not substantially influenced by the signal-to-noise ratio (SNR), resulting in less than 2% mean bias at SNR > 10. Pressure drop estimation based on turbulence production robustly predicted the irreversible pressure drop, regardless of the stenosis severity and post-stenosis dilatation (regression slope = 0.956, R2 = 0.96). In vitro validation of the technique in a 75% stenosis channel confirmed that pressure drop prediction based on the turbulence production agreed with the measured pressure drop (regression slope = 1.15, R2 = 0.999, Bland-Altman agreement = 0.75 ± 3.93 mmHg).

Assessment of turbulent viscous stress using ICOSA 4D Flow MRI for prediction of hemodynamic blood damage

Flow-induced blood damage plays an important role in determining the hemodynamic impact of abnormal blood flow, but quantifying of these effects, which are dominated by shear stresses in highly fluctuating turbulent flow, has not been feasible. This study evaluated the novel application of turbulence tensor measurements using simulated 4D Flow MRI data with six-directional velocity encoding for assessing hemodynamic stresses and corresponding blood damage index (BDI) in stenotic turbulent blood flow. The results showed that 4D Flow MRI underestimates the maximum principal shear stress of laminar viscous stress (PLVS), and overestimates the maximum principal shear stress of Reynolds stress (PRSS) with increasing voxel size. PLVS and PRSS were also overestimated by about 1.2 and 4.6 times at medium signal to noise ratio (SNR) = 20. In contrast, the square sum of the turbulent viscous shear stress (TVSS), which is used for blood damage index (BDI) estimation, was not severely affected by SNR and voxel size. The square sum of TVSS and the BDI at SNR >20 were underestimated by less than 1% and 10%, respectively. In conclusion, this study demonstrated the feasibility of 4D Flow MRI based quantification of TVSS and BDI which are closely linked to blood damage.

The influence of the aortic valve angle on the hemodynamic features of the thoracic aorta

Since the first observation of a helical flow pattern in aortic blood flow, the existence of helical blood flow has been found to be associated with various pathological conditions such as bicuspid aortic valve, aortic stenosis, and aortic dilatation. However, an understanding of the development of helical blood flow and its clinical implications are still lacking. In our present study, we hypothesized that the direction and angle of aortic inflow can influence helical flow patterns and related hemodynamic features in the thoracic aorta. Therefore, we investigated the hemodynamic features in the thoracic aorta and various aortic inflow angles using patient-specific vascular phantoms that were generated using a 3D printer and time-resolved, 3D, phase-contrast magnetic resonance imaging (PC-MRI). The results show that the rotational direction and strength of helical blood flow in the thoracic aorta largely vary according to the inflow direction of the aorta, and a higher helical velocity results in higher wall shear stress distributions. In addition, right-handed rotational flow conditions with higher rotational velocities imply a larger total kinetic energy than left-handed rotational flow conditions with lower rotational velocities.