The Role of Imaging of Flow Patterns by 4D Flow MRI in Aortic Stenosis

Fluid-structure interaction analysis of a healthy aortic valve and its surrounding haemodynamics

The opening and closing dynamics of the aortic valve (AV) has a strong influence on haemodynamics in the aortic root, and both play a pivotal role in maintaining normal physiological functions of the valve. The aim of this study was to establish a subject-specific fluid-structure interaction (FSI) workflow capable of simulating the motion of a tricuspid healthy valve and the surrounding haemodynamics under physiologically realistic conditions. A subject-specific aortic root was reconstructed from magnetic resonance (MR) images acquired from a healthy volunteer, whilst the valve leaflets were built using a parametric model fitted to the subject-specific aortic root geometry. The material behaviour of the leaflets was described using the isotropic hyperelastic Ogden model, and subject-specific boundary conditions were derived from 4D-flow MR imaging (4D-MRI). Strongly coupled FSI simulations were performed using a finite volume-based boundary conforming method implemented in FlowVision. Our FSI model was able to simulate the opening and closing of the AV throughout the entire cardiac cycle. Comparisons of simulation results with 4D-MRI showed a good agreement in key haemodynamic parameters, with stroke volume differing by 7.5% and the maximum jet velocity differing by less than 1%. Detailed analysis of wall shear stress (WSS) on the leaflets revealed much higher WSS on the ventricular side than the aortic side and different spatial patterns amongst the three leaflets.

Advance in the application of 4-dimensional flow MRI in atrial fibrillation

Atrial fibrillation (AF) is the most prevalent arrhythmia in world-wild places and is associated with the development of severe secondary complications such as heart failure and stroke. Emerging evidence shows that the modified hemodynamic environment associated with AF can cause altered flow patterns in left atrial and even systemic blood associated with left atrial appendage thrombosis. Recent advances in magnetic resonance imaging (MRI) allow for the comprehensive visualization and quantification of in vivo aortic flow pattern dynamics. In particular, the technique of 4- dimensional flow MRI (4D flow MRI) offers the opportunity to derive advanced hemodynamic measures such as velocity, vortex, endothelial cell activation potential, and kinetic energy. This review introduces 4D flow MRI for blood flow visualization and quantification of hemodynamic metrics in the setting of AF, with a focus on AF and associated secondary complications.

Multiscale structure and function of the aortic valve apparatus

Whereas studying the aortic valve in isolation has facilitated the development of life-saving procedures and technologies, the dynamic interplay of the aortic valve and its surrounding structures is vital to preserving their function across the wide range of conditions encountered in an active lifestyle. Our view is that these structures should be viewed as an integrated functional unit, here referred to as the aortic valve apparatus (AVA). The coupling of the aortic valve and root, left ventricular outflow tract, and blood circulation is crucial for AVA's functions: unidirectional flow out of the left ventricle, coronary perfusion, reservoir function, and support of left ventricular function. In this review, we explore the multiscale biological and physical phenomena that underlie the simultaneous fulfillment of these functions. A brief overview of the tools used to investigate the AVA, such as medical imaging modalities, experimental methods, and computational modeling, specifically fluid-structure interaction (FSI) simulations, is included. Some pathologies affecting the AVA are explored, and insights are provided on treatments and interventions that aim to maintain quality of life. The concepts explained in this article support the idea of AVA being an integrated functional unit and help identify unanswered research questions. Incorporating phenomena through the molecular, micro, meso, and whole tissue scales is crucial for understanding the sophisticated normal functions and diseases of the AVA.

Unmet needs and knowledge gaps in aortic stenosis: A position paper from the Heart Valve Council of the French Society of Cardiology

Nowadays, valvular heart disease remains a significant challenge among cardiovascular diseases, affecting millions of people worldwide and exerting substantial pressure on healthcare systems. Within the spectrum of valvular heart disease, aortic stenosis is the most common valvular lesion in developed countries. Despite notable advances in understanding its pathophysiological processes, improved cardiovascular imaging techniques and expanding therapeutic options in recent years, there are still unmet needs and knowledge gaps regarding aortic stenosis pathophysiology, severity assessment, management and decision-making strategy. This review, prepared on behalf of the Heart Valve Council of the French Society of Cardiology, describes these gaps and future research perspectives to improve the outcome of patients with aortic stenosis.

Optimizing encoding strategies for 4D Flow MRI of mean and turbulent flow

For 4D Flow MRI of mean and turbulent flow a compromise between spatiotemporal undersampling and velocity encodings needs to be found. Assuming a fixed scan time budget, the impact of trading off spatiotemporal undersampling versus velocity encodings on quantification of velocity and turbulence for aortic 4D Flow MRI was investigated. For this purpose, patient-specific mean and turbulent aortic flow data were generated using computational fluid dynamics which were embedded into the patient-specific background image data to generate synthetic MRI data with corresponding ground truth flow. Cardiac and respiratory motion were included. Using the synthetic MRI data as input, 4D Flow MRI was subsequently simulated with undersampling along pseudo-spiral Golden angle Cartesian trajectories for various velocity encoding schemes. Data were reconstructed using a locally low rank approach to obtain mean and turbulent flow fields to be compared to ground truth. Results show that, for a 15-min scan, velocity magnitudes can be reconstructed with good accuracy relatively independent of the velocity encoding scheme ( S S I M U = 0.938 ± 0.003 ) , good accuracy ( S S I M U ≥ 0.933 ) and with peak velocity errors limited to 10%. Turbulence maps on the other hand suffer from both lower reconstruction quality ( S S I M TKE ≥ 0.323 ) and larger sensitivity to undersampling, motion and velocity encoding strengths ( S S I M TKE = 0.570 ± 0.110 ) when compared to velocity maps. The best compromise to measure unwrapped velocity maps and turbulent kinetic energy given a fixed 15-min scan budget was found to be a 7-point multi- V enc acquisition with a low V enc tuned for best sensitivity to the range of expected intra-voxel standard deviations and a high V enc larger than the expected peak velocity.

4D flow MRI-derived energy loss and RV workload in adults with tetralogy of Fallot

PURPOSE

To assess flow energy loss (EL) pattern inside the pulmonary circulation in adult patients with repaired tetralogy of Fallot (TOF), particularly in TOF with pulmonary stenosis (PS) and pulmonary regurgitation (PR), as a cardiac workload parameter and its relationship to symptoms and major adverse cardiovascular events (MACE).

METHODS

Prospectively, 51 consecutive TOF adults after intracardiac repair, who underwent four-dimensional flow magnetic resonance imaging, were enrolled. All of them had significant PR (PR regurgitant fraction >25 %). TOF patients who had already reached the conventional criteria were excluded. We defined MACE as the following: 1) fatal arrhythmias, 2) sudden cardiac death, 3) surgical pulmonary valvular repair (PVR), 4) right heart failure (HF) needing diuretics and/or hospitalization within 2 years.

RESULTS

A total of 15 patients had MACE; 1) 10 patients underwent PVR within 2 years, 2) 2 patients had ventricular tachycardia, and 3) 6 patients developed right HF (overlapped). Right ventricular (RV) end diastolic volume index (EDVI), RV end systolic volume index (ESVI), average EL/cardiac output (CO), and diastolic EL/CO in patients with MACE were greater than ones without MACE. On a multivariate logistic analysis, the diastolic EL/CO ratio and RVEDVI had the highest odds with MACE in all TOF (odds ratio, 40.7 and 1.15. 95%CI, 1.83-905 and 1.02-13.0; p-value, 0.02 and 0.03). In sub-analysis within 29 patients with moderate PS with PR, and 10 patients with MACE showed higher diastolic EL/CO. Average and diastolic EL/CO negatively correlated with RV ejection fraction (EF) in this sub-analysis.

CONCLUSIONS

High EL, particularly, high diastolic EL/CO, were the important factors for MACE in adult TOF. Higher diastolic EL/CO was also related to lower RV EF and deteriorated RV function in adult TOF with PS and PR. Right-sided EL can be a sensitive marker of excessive cardiac workload which integrates both afterload and preload in adult patients with TOF, beyond the RV size.

Moderate aortic stenosis: Navigating the uncharted

Aortic stenosis (AS) stands as the most common valvular heart disease in developed countries and is characterized by progressive narrowing of the aortic valve orifice resulting in elevated transvalvular flow resistance, left ventricular hypertrophy, and progressive increased risk of heart failure and sudden death. This narrative review explores clinical challenges and evolving perspectives in moderate AS, where discrepancies between aortic valve area and pressure gradient measurements may pose diagnostic and therapeutic quandaries. Transthoracic echocardiography is the first-line imaging modality for AS evaluation, yet cases of discordance may require the application of ancillary noninvasive diagnostic modalities. This review underscores the importance of accurate grading of AS severity, especially in low-gradient phenotypes, emphasizing the need for vigilant follow-up. Current clinical guidelines primarily recommend aortic valve replacement for severe AS, potentially overlooking latent risks in moderate disease stages. The noninvasive multimodality imaging approach-including echocardiography, cardiac magnetic resonance, computed tomography, and nuclear techniques-provides unique insights into adaptive and maladaptive cardiac remodeling in AS and offers a promising avenue to deliver precise indications and exact timing for intervention in moderate AS phenotypes and asymptomatic patients, potentially improving long-term outcomes. Nevertheless, what we may have gleaned from a large amount of observational data is still insufficient to build a robust framework for clinical decision-making in moderate AS. Future research will prioritize randomized clinical trials designed to weigh the benefits and risks of preemptive aortic valve replacement in the management of moderate AS, as directed by specific imaging and nonimaging biomarkers.

Thoracic aorta injury detected by 4D flow MRI predicts subsequent main adverse cardiovascular events in breast cancer patients receiving anthracyclines: A longitudinal study

PURPOSE

To investigate longitudinal thoracic aorta injury using 3-dimensional phase-contrast magnetic resonance imaging (4D flow MRI) parameters and to evaluate their value for predicting the subsequent main adverse cardiovascular events (MACEs) in breast cancer patients receiving anthracyclines.

METHODS

Between July 2020 and July 2021, eighty-eight female participants with breast cancer scheduled to receive anthracyclines with or without trastuzumab prospectively enrolled. Each subjects underwent 4D flow MRI at baseline, 3 and 6 months in relation to baseline. The diameter, peak velocity (Vpeak), wall shear stress (WSS), pulse wave velocity (PWV), energy loss (EL) and pressure gradient (PG) of thoracic aorta were measured. The association between these parameters and subsequent MACEs was performed by Cox proportional hazard models.

RESULTS

Ten participants had subsequently MACEs. The Vpeak and PG gradually decreased and the WSS, PWV and EL progressively increased at 3 and 6 months compared with baseline. Adjusted multivariable analysis showed that the WSS of the proximal, mid- and distal ascending aorta [HR, 1.314 (95% confidence interval (CI): 1.003, 1.898)], [HR, 1.320 (95% CI: 1.002, 1.801)] and [HR, 1.322 (95% CI: 1.001, 1.805)] and PWV of ascending aorta [HR, 2.223 (95% CI: 1.010, 4.653)] at 3 months were associated with subsequent MACEs. Combined WSS and PWV of ascending aorta at 3 months yielded the highest AUC (0.912) for predicting subsequent MACEs.

CONCLUSION

Combined WSS and PWV of ascending aorta at 3 months is helpful for predicting the subsequent MACEs in breast cancer patients treated by anthracyclines.

Multimodality imaging for the global evaluation of aortic stenosis: The valve, the ventricle, the afterload

Aortic stenosis (AS) is the most common valvular heart disease growing in parallel to the increment of life expectancy. Besides the valve, the degenerative process affects the aorta, impairing its elastic properties and leading to increased systemic resistance. The composite of valvular and systemic afterload mediates ventricular damage. The first step of a thorough evaluation of AS should include a detailed assessment of valvular anatomy and hemodynamics. Subsequently, the ventricle, and the global afterload should be assessed to define disease stage and prognosis. Multimodality imaging is of paramount importance for the comprehensive evaluation of these three elements. Echocardiography is the cornerstone modality whereas Multi-Detector Computed Tomography and Cardiac Magnetic Resonance provide useful complementary information. This review comprehensively examines the merits of these imaging modalities in AS for the evaluation of the valve, the ventricle, and the afterload and ultimately endeavors to integrate them in a holistic assessment of AS.

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.

A Deep Learning Approach to Using Wearable Seismocardiography (SCG) for Diagnosing Aortic Valve Stenosis and Predicting Aortic Hemodynamics Obtained by 4D Flow MRI

In this paper, we explored the use of deep learning for the prediction of aortic flow metrics obtained using 4-dimensional (4D) flow magnetic resonance imaging (MRI) using wearable seismocardiography (SCG) devices. 4D flow MRI provides a comprehensive assessment of cardiovascular hemodynamics, but it is costly and time-consuming. We hypothesized that deep learning could be used to identify pathological changes in blood flow, such as elevated peak systolic velocity ([Formula: see text]) in patients with heart valve diseases, from SCG signals. We also investigated the ability of this deep learning technique to differentiate between patients diagnosed with aortic valve stenosis (AS), non-AS patients with a bicuspid aortic valve (BAV), non-AS patients with a mechanical aortic valve (MAV), and healthy subjects with a normal tricuspid aortic valve (TAV). In a study of 77 subjects who underwent same-day 4D flow MRI and SCG, we found that the [Formula: see text] values obtained using deep learning and SCGs were in good agreement with those obtained by 4D flow MRI. Additionally, subjects with non-AS TAV, non-AS BAV, non-AS MAV, and AS could be classified with ROC-AUC (area under the receiver operating characteristic curves) values of 92%, 95%, 81%, and 83%, respectively. This suggests that SCG obtained using low-cost wearable electronics may be used as a supplement to 4D flow MRI exams or as a screening tool for aortic valve disease.

Diastolic Left Main Coronary Artery Flow Reversal

In patients undergoing percutaneous cardiac interventions, perioperative transesophageal echocardiography is used routinely, often revealing an unusual pathology that was not previously detected with transthoracic echocardiography. In this e-challenge, the authors present a patient undergoing percutaneous transcatheter aortic valve replacement, with preprocedural transesophageal echocardiography revealing an abnormal color Doppler signal near the left main coronary artery during diastole.

Automatic 4D Flow MRI Segmentation Using the Standardized Difference of Means Velocity

We present a method to automatically segment 4D flow magnetic resonance imaging (MRI) by identifying net flow effects using the standardized difference of means (SDM) velocity. The SDM velocity quantifies the ratio between the net flow and observed flow pulsatility in each voxel. Vessel segmentation is performed using an F-test, identifying voxels with significantly higher SDM velocity values than background voxels. We compare the SDM segmentation algorithm against pseudo-complex difference (PCD) intensity segmentation of 4D flow measurements in in vitro cerebral aneurysm models and 10 in vitro Circle of Willis (CoW) datasets. We also compared the SDM algorithm to convolutional neural network (CNN) segmentation in 5 thoracic vasculature datasets. The in vitro flow phantom geometry is known, while the ground truth geometries for the CoW and thoracic aortas are derived from high-resolution time-of-flight (TOF) magnetic resonance angiography and manual segmentation, respectively. The SDM algorithm demonstrates greater robustness than PCD and CNN approaches and can be applied to 4D flow data from other vascular territories. The SDM to PCD comparison demonstrated an approximate 48% increase in sensitivity in vitro and 70% increase in the CoW, respectively; the SDM and CNN sensitivities were similar. The vessel surface derived from the SDM method was 46% closer to the in vitro surfaces and 72% closer to the in vitro TOF surfaces than the PCD approach. The SDM and CNN approaches both accurately identify vessel surfaces. The SDM algorithm is a repeatable segmentation method, enabling reliable computation of hemodynamic metrics associated with cardiovascular disease.

Clinical Applications of Four-Dimensional Flow MRI

Four-dimensional flow MRI is a powerful phase contrast technique used for assessing three-dimensional (3D) blood flow dynamics. By acquiring a time-resolved velocity field, it enables flexible retrospective analysis of blood flow that can include qualitative 3D visualization of complex flow patterns, comprehensive assessment of multiple vessels, reliable placement of analysis planes, and calculation of advanced hemodynamic parameters. This technique provides several advantages over routine two-dimensional flow imaging techniques, allowing it to become part of clinical practice at major academic medical centers. In this review, we present the current state-of-the-art cardiovascular, neurovascular, and abdominal applications.

MR Angiography for Aortic Diseases

Aortic pathologic conditions represent diverse disorders, including aortic aneurysm, acute aortic syndrome, traumatic aortic injury, and atherosclerosis. Given the nonspecific clinical features, noninvasive imaging is critical in screening, diagnosis, management, and posttherapeutic surveillance. Of the commonly used imaging modalities, including ultrasound, computed tomography, and MR imaging, the final choice often depends on a combination of factors: acuity of clinical presentation, suspected underlying diagnosis, and institutional practice. Further research is needed to identify the potential clinical role and define appropriate use criteria for advanced MR applications such as four-dimenional flow to manage patients with aortic pathologic conditions.

4D Flow cardiovascular magnetic resonance consensus statement: 2023 update

Hemodynamic assessment is an integral part of the diagnosis and management of cardiovascular disease. Four-dimensional cardiovascular magnetic resonance flow imaging (4D Flow CMR) allows comprehensive and accurate assessment of flow in a single acquisition. This consensus paper is an update from the 2015 '4D Flow CMR Consensus Statement'. We elaborate on 4D Flow CMR sequence options and imaging considerations. The document aims to assist centers starting out with 4D Flow CMR of the heart and great vessels with advice on acquisition parameters, post-processing workflows and integration into clinical practice. Furthermore, we define minimum quality assurance and validation standards for clinical centers. We also address the challenges faced in quality assurance and validation in the research setting. We also include a checklist for recommended publication standards, specifically for 4D Flow CMR. Finally, we discuss the current limitations and the future of 4D Flow CMR. This updated consensus paper will further facilitate widespread adoption of 4D Flow CMR in the clinical workflow across the globe and aid consistently high-quality publication standards.

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.

Optimization of 4D Flow MRI Spatial and Temporal Resolution for Examining Complex Hemodynamics in the Carotid Artery Bifurcation

BACKGROUND

Three-dimensional, ECG-gated, time-resolved, three-directional, velocity-encoded phase-contrast MRI (4D flow MRI) has been applied extensively to measure blood velocity in great vessels but has been much less used in diseased carotid arteries. Carotid artery webs (CaW) are non-inflammatory intraluminal shelf-like projections into the internal carotid artery (ICA) bulb that are associated with complex flow and cryptogenic stroke.

PURPOSE

Optimize 4D flow MRI for measuring the velocity field of complex flow in the carotid artery bifurcation model that contains a CaW.

METHODS

A 3D printed phantom model created from computed tomography angiography (CTA) of a subject with CaW was placed in a pulsatile flow loop within the MRI scanner. 4D Flow MRI images of the phantom were acquired with five different spatial resolutions (0.50-2.00  mm3) and four different temporal resolutions (23-96 ms) and compared to a computational fluid dynamics (CFD) solution of the flow field as a reference. We examined four planes perpendicular to the vessel centerline, one in the common carotid artery (CCA) and three in the internal carotid artery (ICA) where complex flow was expected. At these four planes pixel-by-pixel velocity values, flow, and time average wall shear stress (TAWSS) were compared between 4D flow MRI and CFD.

HYPOTHESIS

An optimized 4D flow MRI protocol will provide a good correlation with CFD velocity and TAWSS values in areas of complex flow within a clinically feasible scan time (~ 10 min).

RESULTS

Spatial resolution affected the velocity values, time average flow, and TAWSS measurements. Qualitatively, a spatial resolution of 0.50  mm3 resulted in higher noise, while a lower spatial resolution of 1.50-2.00  mm3 did not adequately resolve the velocity profile. Isotropic spatial resolutions of 0.50-1.00  mm3 showed no significant difference in total flow compared to CFD. Pixel-by-pixel velocity correlation coefficients between 4D flow MRI and CFD were > 0.75 for 0.50-1.00  mm3 but were < 0.5 for 1.50 and 2.00  mm3. Regional TAWSS values determined from 4D flow MRI were generally lower than CFD and decreased at lower spatial resolutions (larger pixel sizes). TAWSS differences between 4D flow and CFD were not statistically significant at spatial resolutions of 0.50-1.00  mm3 but were different at 1.50 and 2.00 mm3. Differences in temporal resolution only affected the flow values when temporal resolution was > 48.4 ms; temporal resolution did not affect TAWSS values.

CONCLUSION

A spatial resolution of 0.74-1.00  mm3 and a temporal resolution of 23-48 ms (1-2 k-space segments) provides a 4D flow MRI protocol capable of imaging velocity and TAWSS in regions of complex flow within the carotid bifurcation at a clinically acceptable scan time.

Hemodynamic Evaluation of Type B Aortic Dissection Using Compressed Sensing Accelerated 4D Flow MRI

BACKGROUND

4D Flow MRI is a quantitative imaging technique to evaluate blood flow patterns; however, it is unclear how compressed sensing (CS) acceleration would impact aortic hemodynamic quantification in type B aortic dissection (TBAD).

PURPOSE

To investigate CS-accelerated 4D Flow MRI performance compared to GRAPP-accelerated 4D Flow MRI (GRAPPA) to evaluate aortic hemodynamics in TBAD.

STUDY TYPE

Prospective.

POPULATION

Twelve TBAD patients, two volunteers.

FIELD STRENGTH/SEQUENCE

1.5T, 3D time-resolved cine phase-contrast gradient echo sequence.

ASSESSMENT

GRAPPA (acceleration factor [R] = 2) and two CS-accelerated (R = 7.7 [CS7.7] and 10.2 [CS10.2]) 4D Flow MRI scans were acquired twice for interscan reproducibility assessment. Voxelwise kinetic energy (KE), peak velocity (PV), forward flow (FF), reverse flow (RF), and stasis were calculated. Plane-based mid-lumen flows were quantified. Imaging times were recorded.

TESTS

Repeated measures analysis of variance, Pearson correlation coefficients (r), intraclass correlation coefficients (ICC). P < 0.05 indicated statistical significance.

RESULTS

The KE and FF in true lumen (TL) and PV in false lumen (FL) did not show difference among three acquisition types (P = 0.818, 0.065, 0.284 respectively). The PV and stasis in TL were higher, KE, FF, and RF in FL were lower, and stasis was higher in GRAPPA compared to CS7.7 and CS10.2. The RF was lower in GRAPPA compared to CS10.2. The correlation coefficients were strong in TL (r = [0.781-0.986]), and low to strong in FL (r = [0.347-0.948]). The ICC levels demonstrated moderate to excellent interscan reproducibility (0.732-0.989). The FF and net flow in mid-descending aorta TL were significantly different between CS7.7 and CS10.2.

CONCLUSION

CS-accelerated 4D Flow MRI has potential for clinical utilization with shorter scan times in TBAD. Our results suggest similar hemodynamic trends between acceleration types, but CS-acceleration impacts KE, FF, RF, and stasis more in FL.

EVIDENCE LEVEL

1 Technical Efficacy: Stage 2.

Machine learning prediction of progressive subclinical myocardial dysfunction in moderate aortic stenosis

Background

Moderate severity aortic stenosis (AS) is poorly understood, is associated with subclinical myocardial dysfunction, and can lead to adverse outcome rates that are comparable to severe AS. Factors associated with progressive myocardial dysfunction in moderate AS are not well described. Artificial neural networks (ANNs) can identify patterns, inform clinical risk, and identify features of importance in clinical datasets.

Methods

We conducted ANN analyses on longitudinal echocardiographic data collected from 66 individuals with moderate AS who underwent serial echocardiography at our institution. Image phenotyping involved left ventricular global longitudinal strain (GLS) and valve stenosis severity (including energetics) analysis. ANNs were constructed using two multilayer perceptron models. The first model was developed to predict change in GLS from baseline echocardiography alone and the second to predict change in GLS using data from baseline and serial echocardiography. ANNs used a single hidden layer architecture and a 70%:30% training/testing split.

Results

Over a median follow-up interval of 1.3 years, change in GLS (≤ or >median change) could be predicted with accuracy rates of 95% in training and 93% in testing using ANN with inputs from baseline echocardiogram data alone (AUC: 0.997). The four most important predictive baseline features (reported as normalized % importance relative to most important feature) were peak gradient (100%), energy loss (93%), GLS (80%), and DI < 0.25 (50%). When a further model was run including inputs from both baseline and serial echocardiography (AUC 0.844), the top four features of importance were change in dimensionless index between index and follow-up studies (100%), baseline peak gradient (79%), baseline energy loss (72%), and baseline GLS (63%).

Conclusions

Artificial neural networks can predict progressive subclinical myocardial dysfunction with high accuracy in moderate AS and identify features of importance. Key features associated with classifying progression in subclinical myocardial dysfunction included peak gradient, dimensionless index, GLS, and hydraulic load (energy loss), suggesting that these features should be closely evaluated and monitored in AS.

Experimental investigation on flow boiling bubble motion under ultrasonic field in vertical minichannel by using bubble tracking algorithm

Bubble dynamics is important in flow boiling of minichannel, and ultrasonic field effects bubble behaviors. However, flow boiling bubble movements in minichannels under ultrasonic field have received little research attention and are still poorly understood. In this paper, the effects of ultrasonic field on bubble dynamics are experimentally studied by capturing the bubble motion behaviors of the flow boiling bubbles. The ultrasonic frequencies are set to 23, 28, 32, and 40 kHz. Bubble tracking algorithm, which studies the growth, trajectories, velocities, and traveled distances for bubbles, is created to qualitatively describe bubble motion behavior of flow boiling in minichannel. It is found that after the application of ultrasound, the detachment frequency, velocity, and travel distance of the bubbles significantly increases, and the growth behavior and trajectory are extremely complex, the two-phase gas-liquid flow is extremely unstable. The bubbles gain kinetic energy as the ultrasound frequency increases. Finally, numerical simulations are used to quantitatively investigate the mechanism of bubble motion in microchannels under ultrasonic fields.

Characterization of aortic aging using 3D multi-parametric MRI-long-term follow-up in a population study

We comprehensively studied morphological and functional aortic aging in a population study using modern three-dimensional MR imaging to allow future comparison in patients with diseases of the aortic valve or aorta. We followed 80 of 126 subjects of a population study (20 to 80 years of age at baseline) using the identical methodology 6.0 ± 0.5 years later. All underwent 3 T MRI of the thoracic aorta including 3D T1 weighted MRI (spatial resolution 1 mm³) for measuring aortic diameter and plaque thickness and 4D flow MRI (spatial/temporal resolution = 2 mm³/20 ms) for calculating global and regional aortic pulse wave velocity (PWV) and helicity of aortic blood flow. Mean diameter of the ascending aorta (AAo) decreased and plaque thickness increased significantly in the aortic arch (AA) and descending aorta (DAo) in females. PWV of the thoracic aorta increased (6.4 ± 1.5 to 7.0 ± 1.7 m/s and 6.8 ± 1.5 to 7.3 ± 1.8 m/s in females and males, respectively) over time. Local normalized helicity volumes (LNHV) decreased significantly in the AAo and AA (0.33 to 0.31 and 0.34 to 0.32 in females and 0.34 to 0.32 and 0.32 to 0.28 in males). By contrast, helicity increased significantly in the DAo in both genders (0.28 to 0.29 and 0.29 to 0.30, respectively). 3D MRI was able to characterize changes in aortic diameter, plaque thickness, PWV and helicity during six years in our population. Aortic aging determined by 3D multi-parametric MRI is now available for future comparisons in patients with diseases of the aortic valve or aorta.

Postendovascular Aneurysmal Repair Increase in Local Energy Loss for Fusiform Abdominal Aortic Aneurysm: Assessments With 4D flow MRI

BACKGROUND

Although endovascular aneurysmal repair (EVAR) is a preferred treatment for abdominal aortic aneurysm (AAA) owing to its low invasiveness, its impact on the local hemodynamics has not been fully assessed.

PURPOSE

To elucidate how EVAR affects the local hemodynamics in terms of energy loss (EL).

STUDY TYPE

Prospective single-arm study.

FIELD STRENGTH/SEQUENCE

A 3.0 T/4D flow MRI using a phase-contrast three-dimensional cine-gradient-echo sequence.

POPULATION

A total of 13 consecutive patients (median [interquartile range] age: 77.0 [73.0, 78.8] years, 11 male) scheduled for EVAR as an initial treatment for fusiform AAA.

ASSESSMENT

4D flow MRI covering the abdominal aorta and bilateral common iliac arteries and the corresponding stent-graft (SG) lumen was performed before and after EVAR. Plasma brain natriuretic peptide (BNP) was measured within 1 week before and 1 month after EVAR. The hemodynamic data, including mean velocity and the local EL, were compared pre-/post-EVAR. EL was correlated with AAA neck angle and with BNP. Patients were subdivided into deformed (N = 5) and undeformed SG subgroups (N = 8) and pre-/post-EVAR BNP compared in each.

STATISTICS

Parametric or nonparametric methods. Spearman's rank correlation coefficients (r). The interobserver/intraobserver variabilities with Bland-Altman plots. A P value < 0.05 is considered significant.

RESULTS

The mean velocity (cm/sec) at the AAA was five times greater after EVAR: 4.79 ± 0.32 vs. 0.91 ± 0.02. The total EL (mW) increased by 1.7 times after EVAR: 0.487 (0.420, 0.706) vs. 0.292 (0.192, 0.420). The total EL was proportional to the AAA neck angle pre-EVAR (r = 0.691) and post-EVAR (r = 0.718). BNP (pg/mL) was proportional to the total EL post-EVAR (r = 0.773). In the deformed SG group, EL (0.349 [0.261, 0.416]) increased 2.4-fold to 0.848 (0.597, 1.13), and the BNP 90.3 (53.6, 105) to 100 (67.2, 123) post-EVAR.

CONCLUSION

The local EL showed a 1.7-fold increase after EVAR. The larger increase in the EL in the deformed SG group might be a potential concern for frail patients.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

Population-based reference values for 4D flow MRI derived aortic blood flow parameters

Objective. This study assesses age-related differences of thoracic aorta blood flow profiles and provides age- and sex-specific reference values using 4D flow cardiovascular magnetic resonance (CMR) data.Approach. 126 volunteers (age 20-80 years, female 51%) underwent 4D flow CMR and 12 perpendicular analysis planes in the thoracic aorta were specified. For these planes the following parameters were evaluated: body surface area-adjusted aortic area (A'), normalized flow displacement (NFD), the degree of wall parallelism (WPD), the minimal relative cross-sectional area through which 80% of the volume flow passes (A80) and the angle between flow direction and centerline (α).Main results. Age-related differences in blood flow parameters were seen in the ascending aorta with higher values for NFD and angle and lower values for WPD and A80 in older subjects. All parameters describing blood flow patterns correlated with the cross-sectional area in the ascending aorta. No relevant sex-differences regarding blood flow profiles were found.Significance. These age- and sex-specific reference values for quantitative parameters describing blood flow within the aorta might help to study the clinical relevance of flow profiles in the future.

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.

Spontaneous Echo Contrast in the Left Atrium and Aortic-Arch Atheroma, Detected by Transesophageal Echocardiography, Was Negatively Correlated with Cognitive Function

BACKGROUND

The relationship between transesophageal echocardiography findings and cognitive function.

OBJECTIVE

This study aimed to establish an association between transesophageal echocardiography findings and cognitive function in stroke survivors.

METHODS

A single-center study was conducted between April 1, 2017 and March 31, 2022. All subjects that were included had a past history of ischemic stroke and were admitted after >21 days from onset. The participants underwent cognitive function tests including a Mini-Mental State Examination, Revised Hasegawa Dementia Scale, Frontal Assessment Battery, and transesophageal echocardiography.

RESULTS

The results of 126 participants were analyzed. The cognitive function of participants with a spontaneous echo contrast (+) in the left atrium including appendage or of those with an aorta-arch plaque with a maximum thickness ≥4 mm significantly worse while neither the patent foramen ovale nor the branch extending plaque influenced cognitive function (The median cognitive scores of the spontaneous echo contrast (-) versus (+) were 26 versus 22, p < 0.01**, 26 versus 21, p < 0.001***, and 14 versus 11, p < 0.01**. Those of the aortic-arch plaque max thickness (<4 mm) versus (≥4 mm) were 26 versus 25, p < 0.05*, 27 versus 24, p < 0.05*, and 15 versus 13, p < 0.05*).

CONCLUSION

Our findings show that spontaneous echo contrast in the left atrium and aortic-arch atheroma detected by transesophageal echocardiography, were negatively associated with cognitive function.

Automatic Time-Resolved Cardiovascular Segmentation of 4D Flow MRI Using Deep Learning

BACKGROUND

Segmenting the whole heart over the cardiac cycle in 4D flow MRI is a challenging and time-consuming process, as there is considerable motion and limited contrast between blood and tissue.

PURPOSE

To develop and evaluate a deep learning-based segmentation method to automatically segment the cardiac chambers and great thoracic vessels from 4D flow MRI.

STUDY TYPE

Retrospective.

SUBJECTS

A total of 205 subjects, including 40 healthy volunteers and 165 patients with a variety of cardiac disorders were included. Data were randomly divided into training (n = 144), validation (n = 20), and testing (n = 41) sets.

FIELD STRENGTH/SEQUENCE

A 3 T/time-resolved velocity encoded 3D gradient echo sequence (4D flow MRI).

ASSESSMENT

A 3D neural network based on the U-net architecture was trained to segment the four cardiac chambers, aorta, and pulmonary artery. The segmentations generated were compared to manually corrected atlas-based segmentations. End-diastolic (ED) and end-systolic (ES) volumes of the four cardiac chambers were calculated for both segmentations.

STATISTICAL TESTS

Dice score, Hausdorff distance, average surface distance, sensitivity, precision, and miss rate were used to measure segmentation accuracy. Bland-Altman analysis was used to evaluate agreement between volumetric parameters.

RESULTS

The following evaluation metrics were computed: mean Dice score (0.908 ± 0.023) (mean ± SD), Hausdorff distance (1.253 ± 0.293 mm), average surface distance (0.466 ± 0.136 mm), sensitivity (0.907 ± 0.032), precision (0.913 ± 0.028), and miss rate (0.093 ± 0.032). Bland-Altman analyses showed good agreement between volumetric parameters for all chambers. Limits of agreement as percentage of mean chamber volume (LoA%), left ventricular: 9.3%, 13.5%, left atrial: 12.4%, 16.9%, right ventricular: 9.9%, 15.6%, and right atrial: 18.7%, 14.4%; for ED and ES, respectively.

DATA CONCLUSION

The addition of this technique to the 4D flow MRI assessment pipeline could expedite and improve the utility of this type of acquisition in the clinical setting.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 1.

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 role of 4-dimensional flow in the assessment of bicuspid aortic valve and its valvulo-aortopathies

Bicuspid aortic valve is the most common congenital cardiac malformation and the leading cause of aortopathy and aortic stenosis in younger patients. Aortic wall remodelling secondary to altered haemodynamic flow patterns, changes in peak velocity, and wall shear stress may be implicated in the development of aortopathy in the presence of bicuspid aortic valve and dysfunction. Assessment of these parameters as potential predictors of disease severity and progression is thus desirable. The anatomic and functional information acquired from 4D flow MRI can allow simultaneous visualisation and quantification of the pathological geometric and haemodynamic changes of the aorta. We review the current clinical utility of haemodynamic quantities including velocity, wall sheer stress and energy losses, as well as visual descriptors such as vorticity and helicity, and flow direction in assessing the aortic valve and associated aortopathies.

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.

Quantitative evaluation of aortic valve regurgitation in 4D flow cardiac magnetic resonance: at which level should we measure?

PURPOSE

To find the best level to measure aortic flow for quantification of aortic regurgitation (AR) in 4D flow CMR.

METHODS

In 27 congenital heart disease patients with AR (67% male, 31 ± 16 years) two blinded observers measured antegrade, retrograde, net aortic flow volumes and regurgitant fractions at 6 levels in 4D flow: (1) below the aortic valve (AV), (2) at the AV, (3) at the aortic sinus, (4) at the sinotubular junction, (5) at the level of the pulmonary arteries (PA) and (6) below the brachiocephalic trunk. 2D phase contrast (2DPC) sequences were acquired at the level of PA. All patients received prior transthoracic echocardiography (TTE) with AR severity grading according to a recommended multiparametric approach.

RESULTS

After assigning 2DPC measurements into AR grading, agreement between TTE AR grading and 2DPC was good (κ = 0.88). In 4D flow, antegrade flow was similar between the six levels (p = 0.87). Net flow was higher at level 1-2 than at levels 3-6 (p < 0.05). Retrograde flow and regurgitant fraction at level 1-2 were lower compared to levels 3-6 (p < 0.05). Reproducibility (inter-reader agreement: ICC 0.993, 95% CI 0.986-0.99; intra-reader agreement: ICC 0.982, 95%CI 0.943-0.994) as well as measurement agreement between 4D flow and 2DPC (ICC 0.994; 95%CI 0.989 - 0.998) was best at the level of PA.

CONCLUSION

For estimating severity of AR in 4D flow, best reproducibility along with best agreement with 2DPC measurements can be expected at the level of PA. Measurements at AV or below AV might underestimate AR.

Synthesis of patient-specific multipoint 4D flow MRI data of turbulent aortic flow downstream of stenotic valves

We propose to synthesize patient-specific 4D flow MRI datasets of turbulent flow paired with ground truth flow data to support training of inference methods. Turbulent blood flow is computed based on the Navier-Stokes equations with moving domains using realistic boundary conditions for aortic shapes, wall displacements and inlet velocities obtained from patient data. From the simulated flow, synthetic multipoint 4D flow MRI data is generated with user-defined spatiotemporal resolutions and reconstructed with a Bayesian approach to compute time-varying velocity and turbulence maps. For MRI data synthesis, a fixed hypothetical scan time budget is assumed and accordingly, changes to spatial resolution and time averaging result in corresponding scaling of signal-to-noise ratios (SNR). In this work, we focused on aortic stenotic flow and quantification of turbulent kinetic energy (TKE). Our results show that for spatial resolutions of 1.5 and 2.5 mm and time averaging of 5 ms as encountered in 4D flow MRI in practice, peak total turbulent kinetic energy downstream of a 50, 75 and 90% stenosis is overestimated by as much as 23, 15 and 14% (1.5 mm) and 38, 24 and 23% (2.5 mm), demonstrating the importance of paired ground truth and 4D flow MRI data for assessing accuracy and precision of turbulent flow inference using 4D flow MRI exams.

4D flow MRI derived aortic hemodynamics multi-year follow-up in repaired coarctation with bicuspid aortic valve

PURPOSE

The purpose of this study was to investigate the relationships between hemodynamic parameters and longitudinal changes in aortic dimensions on four-dimensional (4D) flow magnetic resonance imaging (MRI) in patients with bicuspid aortic valve (BAV) and repaired coarctation.

MATERIALS AND METHODS

The study retrospectively included patients with BAV and childhood coarctation repair who had at least two cardiothoracic MRI examinations including 4D flow MRI at baseline and follow-up. Analysis included the calculation of aortic peak velocities, wall shear stress (WSS), pulse wave velocity (PWV), aortic dimensions and annual growth rates. Differences between examinations were assessed using paired t-test or Wilcoxon signed rank test. Relationships between growth rate and 4D flow metrics were assessed using Pearson or Spearman correlation tests.

RESULTS

The cohort included 15 patients (mean age 35 ± 8 [SD] years, 9 men) with a median follow-up time of 3.98 years (Q1: 2.10; Q3: 4.96). There were no significant differences in aortic mean WSS, peak velocities, and PWV between baseline and follow-up values. Greater baseline peak velocities at the site of the coarctation were strongly associated with aortic narrowing (follow-up vs. baseline diameter) at coarctation zone (r = -0.64; P = 0.010) and moderately in descending aorta (r = -0.53; P = 0.042). In addition, increased baseline WSS in the aortic arch was strongly related with narrowing of the coarctation zone at follow-up (r = -0.64, P = 0.011).

CONCLUSION

Measures of aortic hemodynamics and aortic WSS are stable over time in patients with BAV with coarctation repair. Increased peak velocity was associated with a progressive narrowing at the site of the coarctation repair.

Aortic Viscous Energy Loss for Assessment of Valve-related Hemodynamics in Asymptomatic Severe Aortic Stenosis

Purpose

To investigate whether functional assessment of aberrant flow patterns by viscous energy loss (E′L ) using four-dimensional (4D) flow MRI could determine aortic stenosis (AS) severity in accordance with transvalvular energy loss and aid in surgical decision-making in asymptomatic patients with severe AS.

Materials and Methods

In this prospective, single-center study, E′L was measured in the thoracic aorta of 74 consecutive asymptomatic patients with severe AS and preserved left ventricular ejection fraction who presented between January 2015 and December 2017, and 23 healthy volunteers using 4D flow MRI. Transvalvular energy loss was assessed based on the energy loss index (ELI) measured using Doppler echocardiography. The association between E′L and AS-related events including aortic valve replacement was evaluated by receiver operating characteristic curve analysis, Kaplan-Meier analysis, and multivariable Cox regression analysis.

Results

Among 74 asymptomatic patients with severe AS (mean age, 60 years ± 9 [SD]; 43 men; 56 with bicuspid aortic valve), 33 experienced AS-related events during a median follow-up of 42 months (IQR, 30–53 months). Altered flow patterns in severe AS resulted in a sevenfold increase in peak systolic E′L in the ascending aorta compared with controls (13.9 mW ± 3.4 vs 1.80 mW ± 0.44; P < .001). Peak systolic E′L in the ascending aorta was independently associated with the ELI (standardized β, −0.52; P < .001) and showed better discrimination for AS-related events (area under the curve, 0.83; 95% CI: 0.74, 0.93; P < .001) than conventional echocardiographic parameters. After adjustment for confounding variables, peak systolic E′L in the ascending aorta was associated with a significant increase in AS-related events (P < .001 for adjusted hazard ratio).

Conclusion

Changes in AS-mediated poststenotic three-dimensional outflow patterns can be quantified by 4D flow MRI-derived energetic markers to aid in the risk stratification and clinical management of asymptomatic patients with severe AS.

Keywords: Aortic Stenosis, 4D Flow MRI, Flow Energetics, Vascular, Aorta, Aortic Valve, MR Angiography

Supplemental material is available for this article.

© RSNA, 2022

Intra-cardiac pressure drop and flow distribution of bicuspid aortic valve disease in preserved ejection fraction

Background

Bicuspid aortic valve (BAV) is more than a congenital defect since it is accompanied by several secondary complications that intensify induced impairments. Hence, BAV patients need lifelong evaluations to prevent severe clinical sequelae. We applied 4D-flow magnetic resonance imaging (MRI) for in detail visualization and quantification of in vivo blood flow to verify the reliability of the left ventricular (LV) flow components and pressure drops in the silent BAV subjects with mild regurgitation and preserved ejection fraction (pEF).

Materials and methods

A total of 51 BAV patients with mild regurgitation and 24 healthy controls were recruited to undergo routine cardiac MRI followed by 4D-flow MRI using 3T MRI scanners. A dedicated 4D-flow module was utilized to pre-process and then analyze the LV flow components (direct flow, retained inflow, delayed ejection, and residual volume) and left-sided [left atrium (LA) and LV] local pressure drop. To elucidate significant diastolic dysfunction in our population, transmitral early and late diastolic 4D flow peak velocity (E-wave and A-wave, respectively), as well as E/A ratio variable, were acquired.

Results

The significant means differences of each LV flow component (global measurement) were not observed between the two groups (p > 0.05). In terms of pressure analysis (local measurement), maximum and mean as well as pressure at E-wave and A-wave timepoints at the mitral valve (MV) plane were significantly different between BAV and control groups (p: 0.005, p: 0.02, and p: 0.04 and p: <0.001; respectively). Furthermore, maximum pressure and pressure difference at the A-wave timepoint at left ventricle mid and left ventricle apex planes were significant. Although we could not find any correlation between LV diastolic function and flow components, Low but statistically significant correlations were observed with local pressure at LA mid, MV and LV apex planes at E-wave timepoint (R: −0.324, p: 0.005, R: −0.327, p: 0.004, and R: −0.306, p: 0.008, respectively).

Conclusion

In BAV patients with pEF, flow components analysis is not sensitive to differentiate BAV patients with mild regurgitation and healthy control because flow components and EF are global parameters. Inversely, pressure (local measurement) can be a more reliable biomarker to reveal the early stage of diastolic dysfunction.

Rationale and clinical applications of 4D flow cardiovascular magnetic resonance in assessment of valvular heart disease: a comprehensive review

BACKGROUND

Accurate evaluation of valvular pathology is crucial in the timing of surgical intervention. Whilst transthoracic echocardiography is widely available and routinely used in the assessment of valvular heart disease, it is bound by several limitations. Although cardiovascular magnetic resonance (CMR) imaging can overcome many of the challenges encountered by echocardiography, it also has a number of limitations.

MAIN TEXT

4D Flow CMR is a novel technique, which allows time-resolved, 3-dimensional imaging. It enables visualisation and direct quantification of flow and peak velocities of all valves simultaneously in one simple acquisition, without any geometric assumptions. It also has the unique ability to measure advanced haemodynamic parameters such as turbulent kinetic energy, viscous energy loss rate and wall shear stress, which may add further diagnostic and prognostic information. Although 4D Flow CMR acquisition can take 5-10 min, emerging acceleration techniques can significantly reduce scan times, making 4D Flow CMR applicable in contemporary clinical practice.

CONCLUSION

4D Flow CMR is an emerging CMR technique, which has the potential to become the new reference-standard method for the evaluation of valvular lesions. In this review, we describe the clinical applications, advantages and disadvantages of 4D Flow CMR in the assessment of valvular heart disease.

Clinical implications of the biomechanics of bicuspid aortic valve and bicuspid aortopathy

Bicuspid aortic valve (BAV), which affects up to 2% of the general population, results from the abnormal fusion of the cusps of the aortic valve. Patients with BAV are at a higher risk for developing aortic dilatation, a condition known as bicuspid aortopathy, which is associated with potentially life-threatening sequelae such as aortic dissection and aortic rupture. Although BAV biomechanics have been shown to contribute to aortopathy, their precise impact is yet to be delineated. Herein, we present the latest literature related to BAV biomechanics. We present the most recent definitions and classifications for BAV. We also summarize the current evidence pertaining to the mechanisms that drive bicuspid aortopathy. We highlight how aberrant flow patterns can contribute to the development of aortic dilatation. Finally, we discuss the role cardiac magnetic resonance imaging can have in assessing and managing patient with BAV and bicuspid aortopathy.

SRflow: Deep learning based super-resolution of 4D-flow MRI data

Exploiting 4D-flow magnetic resonance imaging (MRI) data to quantify hemodynamics requires an adequate spatio-temporal vector field resolution at a low noise level. To address this challenge, we provide a learned solution to super-resolve in vivo 4D-flow MRI data at a post-processing level. We propose a deep convolutional neural network (CNN) that learns the inter-scale relationship of the velocity vector map and leverages an efficient residual learning scheme to make it computationally feasible. A novel, direction-sensitive, and robust loss function is crucial to learning vector-field data. We present a detailed comparative study between the proposed super-resolution and the conventional cubic B-spline based vector-field super-resolution. Our method improves the peak-velocity to noise ratio of the flow field by 10 and 30% for in vivo cardiovascular and cerebrovascular data, respectively, for 4 × super-resolution over the state-of-the-art cubic B-spline. Significantly, our method offers 10x faster inference over the cubic B-spline. The proposed approach for super-resolution of 4D-flow data would potentially improve the subsequent calculation of hemodynamic quantities.

Modeling Bias Error in 4D Flow MRI Velocity Measurements

We present a model to estimate the bias error of 4D flow magnetic resonance imaging (MRI) velocity measurements. The local instantaneous bias error is defined as the difference between the expectation of the voxel's measured velocity and actual velocity at the voxel center. The model accounts for bias error introduced by the intra-voxel velocity distribution and partial volume (PV) effects. We assess the intra-voxel velocity distribution using a 3D Taylor Series expansion. PV effects and numerical errors are considered using a Richardson extrapolation. The model is applied to synthetic Womersley flow and in vitro and in vivo 4D flow MRI measurements in a cerebral aneurysm. The bias error model is valid for measurements with at least 3.75 voxels across the vessel diameter and signal-to-noise ratio greater than 5. All test cases exceeded this diameter to voxel size ratio with diameters, isotropic voxel sizes, and velocity ranging from 3-15mm, 0.5-1mm, and 0-60cm/s, respectively. The model accurately estimates the bias error in voxels not affected by PV effects. In PV voxels, the bias error is an order of magnitude higher, and the accuracy of the bias error estimation in PV voxels ranges from 67.3% to 108% relative to the actual bias error. The bias error estimated for in vivo measurements increased two-fold at systole compared to diastole in partial volume and non-partial volume voxels, suggesting the bias error varies over the cardiac cycle. This bias error model quantifies 4D flow MRI measurement accuracy and can help plan 4D flow MRI scans.

Highlights of the Virtual Society for Cardiovascular Magnetic Resonance 2022 Scientific Conference: CMR: improving cardiovascular care around the world

The 25th Society for Cardiovascular Magnetic Resonance (SCMR) Annual Scientific Sessions saw 1524 registered participants from more than 50 countries attending the meeting virtually. Supporting the theme "CMR: Improving Cardiovascular Care Around the World", the meeting included 179 invited talks, 52 sessions including 3 plenary sessions, 2 keynote talks, and a total of 93 cases and 416 posters. The sessions were designed so as to showcase the multifaceted role of cardiovascular magnetic resonance (CMR) in identifying and prognosticating various myocardial pathologies. Additionally, various social networking sessions as well as fun activities were organized. The major areas of focus for the future are likely to be rapid efficient and high value CMR exams, automated and quantitative acquisition and post-processing using artificial intelligence and machine learning, multi-contrast imaging and advanced vascular imaging including 4D flow.

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.

Validation of aortic valve pressure gradient quantification using semi-automated 4D flow CMR pipeline

OBJECTIVE

Doppler echocardiographic aortic valve peak velocity and peak pressure gradient assessment across the aortic valve (AV) is the mainstay for diagnosing aortic stenosis. Four-dimensional flow cardiovascular magnetic resonance (4D flow CMR) is emerging as a valuable diagnostic tool for estimating the peak pressure drop across the aortic valve, but assessment remains cumbersome. We aimed to validate a novel semi-automated pipeline 4D flow CMR method of assessing peak aortic value pressure gradient (AVPG) using the commercially available software solution, CAAS MR Solutions, against invasive angiographic methods.

RESULTS

We enrolled 11 patients with severe AS on echocardiography from the EurValve programme. All patients had pre-intervention doppler echocardiography, invasive cardiac catheterisation with peak pressure drop assessment across the AV and 4D flow CMR. The peak AVPG was 51.9 ± 35.2 mmHg using the invasive pressure drop method and 52.2 ± 29.2 mmHg for the 4D flow CMR method (semi-automated pipeline), with good correlation between the two methods (r = 0.70, p = 0.017). Assessment of AVPG by 4D flow CMR using the novel semi-automated pipeline method shows excellent agreement to invasive assessment when compared to doppler-based methods and advocate for its use as complementary to echocardiography.

Deep learning-based velocity antialiasing of 4D-flow MRI

Purpose

To develop a convolutional neural network (CNN) for the robust and fast correction of velocity aliasing in 4D‐flow MRI.

Methods

This study included 667 adult subjects with aortic 4D‐flow MRI data with existing velocity aliasing (n = 362) and no velocity aliasing (n = 305). Additionally, 10 controls received back‐to‐back 4D‐flow scans with systemically varied velocity‐encoding sensitivity (vencs) at 60, 100, and 175 cm/s. The no‐aliasing data sets were used to simulate velocity aliasing by reducing the venc to 40%–70% of the original, alongside a ground truth locating all aliased voxels (153 training, 152 testing). The 152 simulated and 362 existing aliasing data sets were used for testing and compared with a conventional velocity antialiasing algorithm. Dice scores were calculated to quantify CNN performance. For controls, the venc 175‐cm/s scans were used as the ground truth and compared with the CNN‐corrected venc 60 and 100 cm/s data sets

Results

The CNN required 176 ± 30 s to perform compared with 162 ± 14 s for the conventional algorithm. The CNN showed excellent performance for the simulated data compared with the conventional algorithm (median range of Dice scores CNN: [0.89–0.99], conventional algorithm: [0.84–0.94], p < 0.001, across all simulated vencs) and detected more aliased voxels in existing velocity aliasing data sets (median detected CNN: 159 voxels [31–605], conventional algorithm: 65 [7–417], p < 0.001). For controls, the CNN showed Dice scores of 0.98 [0.95–0.99] and 0.96 [0.87–0.99] for venc = 60 cm/s and 100 cm/s, respectively, while flow comparisons showed moderate‐excellent agreement.

Conclusion

Deep learning enabled fast and robust velocity anti‐aliasing in 4D‐flow MRI.

The Role of Cardiac Magnetic Resonance in Aortic Stenosis and Regurgitation

Cardiac magnetic resonance (CMR) imaging is a well-set diagnostic technique for assessment of valvular heart diseases and is gaining ground in current clinical practice. It provides high-quality images without the administration of ionizing radiation and occasionally without the need of contrast agents. It offers the unique possibility of a comprehensive stand-alone assessment of the heart including biventricular function, left ventricle remodeling, myocardial fibrosis, and associated valvulopathies. CMR is the recognized reference for the quantification of ventricular volumes, mass, and function. A particular strength is the ability to quantify flow, especially with new techniques which allow accurate measurement of stenosis and regurgitation. Furthermore, tissue mapping enables the visualization and quantification of structural changes in the myocardium. In this way, CMR has the potential to yield important prognostic information predicting those patients who will progress to surgery and impact outcomes. In this review, the fundamentals of CMR in assessment of aortic valve diseases (AVD) are described, together with its strengths and weaknesses. This state-of-the-art review provides an updated overview of CMR potentials in all AVD issues, including valve anatomy, flow quantification, ventricular volumes and function, and tissue characterization.

Turbulent Kinetic Energy Loss and Shear Stresses Before and After Transcatheter Aortic Valve Replacement

Blood flow and shear stresses were quantified using 4-dimensional flow cardiac magnetic resonance and 3-dimensional particle velocimetry before and after transcatheter aortic valve replacement (TAVR). TAVR reduced turbulent kinetic energy by 47% and shear stresses by 33%, illustrating that the benefit of TAVR extends beyond a simple reduction in transvalvular gradients. (Level of Difficulty: Advanced.)

Valvular Cardiomyopathy: The Value of Cardiovascular Magnetic Resonance Imaging

Cardiovascular magnetic resonance (CMR) imaging has had a vast impact on the understanding of a wide range of disease processes and pathophysiological mechanisms. More recently, it has contributed significantly to the diagnosis and risk stratification of patients with valvular heart disease. With its increasing use, CMR allows for a detailed, reproducible, qualitative, and quantitative evaluation of left ventricular volumes and mass, thereby enabling assessment of the haemodynamic impact of a valvular lesion upon the myocardium. Postprocessing of the routinely acquired images with feature tracking CMR methodology can give invaluable information about myocardial deformation and strain parameters that suggest subclinical ventricular impairment that remains undetected by conventional measures such as the ejection fraction (EF). T1 mapping and late gadolinium enhancement (LGE) imaging provide deep myocardial tissue characterisation that is changing the approach towards risk stratification of patients as an increasing body of evidence suggests that the presence of fibrosis is related to adverse events and prognosis. This review summarises the current evidence regarding the utility of CMR in the left ventricular assessment of patients with aortic stenosis or mitral regurgitation and its value in diagnosis, risk stratification, and management.

Fully automated intracardiac 4D flow MRI post-processing using deep learning for biventricular segmentation

OBJECTIVES

4D flow MRI allows for a comprehensive assessment of intracardiac blood flow, useful for assessing cardiovascular diseases, but post-processing requires time-consuming ventricular segmentation throughout the cardiac cycle and is prone to subjective errors. Here, we evaluate the use of automatic left and right ventricular (LV and RV) segmentation based on deep learning (DL) network that operates on short-axis cine bSSFP images.

METHODS

A previously published DL network was fine-tuned via retraining on a local database of 106 subjects scanned at our institution. In 26 test subjects, the ventricles were segmented automatically by the network and manually by 3 human observers on bSSFP MRI. The bSSFP images were then registered to the corresponding 4D flow images to apply the segmentation to 4D flow velocity data. Dice coefficients and the relative deviation between measurements (automatic vs. manual and interobserver manual) of various hemodynamic parameters were assessed.

RESULTS

The automated segmentation resulted in similar Dice scores (LV: 0.92, RV: 0.86) and lower relative deviations from manual segmentation in left ventricular (LV) average kinetic energy (KE) (8%) and RV KE (15%) than the Dice scores (LV: 0.91, RV: 0.87) and relative deviations between manual segmentation observers (LV KE: 11%, p = 0.01; RV KE: 19%, p = 0.03).

CONCLUSIONS

The automated post-processing method using deep learning resulted in hemodynamic measurements that differ from a manual observer's measurements equally or less than the variation between manual observers. This approach can be used to decrease post-processing time on intraventricular 4D flow data and mitigate interobserver variability.

KEY POINTS

• Our proposed method allows for fully automated post-processing of intraventricular 4D flow MRI data. • Our method resulted in hemodynamic measurements that matched those derived from manual segmentation equally as well as interobserver variability. • Our method can be used to greatly accelerate intraventricular 4D flow post-processing and improve interobserver repeatability.