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

Left atrial cardiomyopathy: Pathophysiological insights, assessment methods and clinical implications

Atrial cardiomyopathy is defined as any complex of structural, architectural, contractile or electrophysiological changes affecting atria, with the potential to produce clinically relevant manifestations. Most of our knowledge about the mechanistic aspects of atrial cardiomyopathy is derived from studies investigating animal models of atrial fibrillation and atrial tissue samples obtained from individuals who have a history of atrial fibrillation. Several noninvasive tools have been reported to characterize atrial cardiomyopathy in patients, which may be relevant for predicting the risk of incident atrial fibrillation and its related outcomes, such as stroke. Here, we provide an overview of the pathophysiological mechanisms involved in atrial cardiomyopathy, and discuss the complex interplay of these mechanisms, including aging, left atrial pressure overload, metabolic disorders and genetic factors. We discuss clinical tools currently available to characterize atrial cardiomyopathy, including electrocardiograms, cardiac imaging and serum biomarkers. Finally, we discuss the clinical impact of atrial cardiomyopathy, and its potential role for predicting atrial fibrillation, stroke, heart failure and dementia. Overall, this review aims to highlight the critical need for a clinically relevant definition of atrial cardiomyopathy to improve treatment strategies.

K-t PCA accelerated in-plane balanced steady-state free precession phase-contrast (PC-SSFP) for all-in-one diastolic function evaluation

PURPOSE

Diastolic function evaluation requires estimates of early and late diastolic mitral filling velocities (E and A) and of mitral annulus tissue velocity (e'). We aimed to develop an MRI method for simultaneous all-in-one diastolic function evaluation in a single scan by generating a 2D phase-contrast (PC) sequence with balanced steady-state free precession (bSSFP) contrast (PC-SSFP). E and A could then be measured with PC, and e' estimated by valve tracking on the magnitude images, using an established deep learning framework.

METHODS

Our PC-SSFP used in-plane flow-encoding, with zeroth and first moment nulling over each TR. For further acceleration, different k-t principal component analysis (PCA) methods were investigated with both retrospective and prospective undersampling. PC-SSFP was compared to separate balanced SSFP cine and PC-gradient echo acquisitions in phantoms and in 10 healthy subjects.

RESULTS

Phantom experiments showed that PC-SSFP measured accurate velocities compared to PC-gradient echo (r = 0.98 for a range of pixel-wise velocities -80 cm/s to 80 cm/s). In subjects, PC-SSFP generated high SNR and myocardium-blood contrast, and excellent agreement for E (limits of agreement [LOA] 0.8 ± 2.4 cm/s, r = 0.98), A (LOA 2.5 ± 4.1 cm/s, r = 0.97), and e' (LOA 0.3 ± 2.6 cm/s, r = 1.00), versus the standard methods. The best k-t PCA approach processed the complex difference data and substituted in raw k-space data. With prospective k-t PCA acceleration, higher frame rates were achieved (50 vs. 25 frames per second without k-t PCA), yielding a 13% higher e'.

CONCLUSION

The proposed PC-SSFP method achieved all-in-one diastolic function evaluation.

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.

Motion-resolved real-time 4D flow MRI with low-rank and subspace modeling

PURPOSE

To develop a new motion-resolved real-time four-dimensional (4D) flow MRI method, which enables the quantification and visualization of blood flow velocities with three-directional flow encodings and volumetric coverage without electrocardiogram (ECG) synchronization and respiration control.

METHODS

An integrated imaging method is presented for real-time 4D flow MRI, which encompasses data acquisition, image reconstruction, and postprocessing. The proposed method features a specialized continuous ( k , t ) $$ \left(\mathbf{k},t\right) $$ -space acquisition scheme, which collects two sets of data (i.e., training data and imaging data) in an interleaved manner. By exploiting strong spatiotemporal correlation of 4D flow data, it reconstructs time-series images from highly-undersampled ( k , t ) $$ \left(\mathbf{k},t\right) $$ -space measurements with a low-rank and subspace model. Through data-binning-based postprocessing, it constructs a five-dimensional dataset (i.e., x-y-z-cardiac-respiratory), from which respiration-dependent flow information is further analyzed. The proposed method was evaluated in aortic flow imaging experiments with ten healthy subjects and two patients with atrial fibrillation.

RESULTS

The proposed method achieves 2.4 mm isotropic spatial resolution and 34.4 ms temporal resolution for measuring the blood flow of the aorta. For the healthy subjects, it provides flow measurements in good agreement with those from the conventional 4D flow MRI technique. For the patients with atrial fibrillation, it is able to resolve beat-by-beat pathological flow variations, which cannot be obtained from the conventional technique. The postprocessing further provides respiration-dependent flow information.

CONCLUSION

The proposed method enables high-resolution motion-resolved real-time 4D flow imaging without ECG gating and respiration control. It is able to resolve beat-by-beat blood flow variations as well as respiration-dependent flow information.

Atrial cardiomyopathy: Current and future imaging methods for assessment of atrial structure and function

Changes in atrial size and function have historically been considered a surrogate marker of ventricular dysfunction. However, it is now recognized that atrial cardiomyopathy (ACM) may also occur as a primary myocardial disorder. Emerging evidence that ACM is a major risk factor for atrial fibrillation, heart failure, and thromboembolic stroke, has highlighted the significance of this disorder and the need for better assessment of atrial metrics in clinical practice. Key barriers in this regard include a lack of standardized criteria or hierarchy for the diagnosis of ACM and lack of consensus for the most accurate phenotyping methods. In this article we review existing literature on ACM, with a focus on current and future non-invasive imaging methods for detecting abnormalities of atrial structure and function. We discuss the relative advantages and disadvantages of transthoracic echocardiography and cardiac magnetic resonance imaging for assessing a range of parameters, including atrial size and contractile function, strain, tissue characteristics, and epicardial adipose tissue. We will also present the potential application of novel imaging methods such as sphericity index and four- or five-dimensional flow.

Latest Advances in Image Acceleration: All Dimensions are Fair Game

Magnetic resonance imaging (MRI) is a versatile modality that can generate high-resolution images with a variety of tissue contrasts. However, MRI is a slow technique and requires long acquisition times, which increase with higher temporal and spatial resolution and/or when multiple contrasts and large volumetric coverage is required. In order to speedup MR data acquisition, several approaches have been introduced in the literature. Most of these techniques acquire less data than required and exploit intrinsic redundancies in the MR images to recover the information that was not sampled. This article presents a review of MR acquisition and reconstruction methods that have exploited redundancies in the temporal, spatial, and contrast/parametric dimensions to accelerate image data acquisition, focusing on cardiac and abdominal MR imaging applications. The review describes how each of these dimensions has been separately exploited for speeding up MR acquisition to then discuss more advanced techniques where multiple dimensions are exploited together for further reducing scan times. Finally, future directions for multidimensional image acceleration and remaining technical challenges are discussed. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: 1.

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.

Simultaneous multi-parametric acquisition and reconstruction techniques in cardiac magnetic resonance imaging: Basic concepts and status of clinical development

Simultaneous multi-parametric acquisition and reconstruction techniques (SMART) are gaining attention for their potential to overcome some of cardiovascular magnetic resonance imaging's (CMR) clinical limitations. The major advantages of SMART lie within their ability to simultaneously capture multiple "features" such as cardiac motion, respiratory motion, T1/T2 relaxation. This review aims to summarize the overarching theory of SMART, describing key concepts that many of these techniques share to produce co-registered, high quality CMR images in less time and with less requirements for specialized personnel. Further, this review provides an overview of the recent developments in the field of SMART by describing how they work, the parameters they can acquire, their status of clinical testing and validation, and by providing examples for how their use can improve the current state of clinical CMR workflows. Many of the SMART are in early phases of development and testing, thus larger scale, controlled trials are needed to evaluate their use in clinical setting and with different cardiac pathologies.

Dos and don'ts in large animal models of aortic insufficiency

Aortic insufficiency caused by paravalvular leakage (PVL) is one of the most feared complications following transcatheter aortic valve replacement (TAVI) in patients. Domestic pigs (Sus scrofa domestica) are a popular large animal model to study such conditions and develop novel diagnostic and therapeutic techniques. However, the models based on prosthetic valve implantation are time intensive, costly, and often hamper further hemodynamic measurements such as PV loop and 4D MRI flow by causing implantation-related wall motion abnormalities and degradation of MR image quality. This study describes in detail, the establishment of a minimally invasive porcine model suitable to study the effects of mild-to-moderate “paravalvular“ aortic regurgitation on left ventricular (LV) performance and blood flow patterns, particularly under the influence of altered afterload, preload, inotropic state, and heart rate. Six domestic pigs (Swiss large white, female, 60–70 kg of body weight) were used to establish this model. The defects on the hinge point of aortic leaflets and annulus were created percutaneously by the pierce-and-dilate technique either in the right coronary cusp (RCC) or in the non-coronary cusp (NCC). The hemodynamic changes as well as LV performance were recorded by PV loop measurements, while blood flow patterns were assessed by 4D MRI. LV performance was additionally challenged by pharmaceutically altering cardiac inotropy, chronotropy, and afterload. The presented work aims to elaborate the dos and don'ts in porcine models of aortic insufficiency and intends to steepen the learning curve for researchers planning to use this or similar models by giving valuable insights ranging from animal selection to vascular access choices, placement of PV Loop catheter, improvement of PV loop data acquisition and post-processing and finally the induction of paravalvular regurgitation of the aortic valve by a standardized and reproducible balloon induced defect in a precisely targeted region of the aortic valve.

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.

Free-breathing motion-informed locally low-rank quantitative 3D myocardial perfusion imaging

Purpose

To propose respiratory motion‐informed locally low‐rank reconstruction (MI‐LLR) for robust free‐breathing single‐bolus quantitative 3D myocardial perfusion CMR imaging. Simulation and in‐vivo results are compared to locally low‐rank (LLR) and compressed sensing reconstructions (CS) for reference.

Methods

Data were acquired using a 3D Cartesian pseudo‐spiral in‐out k‐t undersampling scheme (R = 10) and reconstructed using MI‐LLR, which encompasses two stages. In the first stage, approximate displacement fields are derived from an initial LLR reconstruction to feed a motion‐compensated reference system to a second reconstruction stage, which reduces the rank of the inverse problem. For comparison, data were also reconstructed with LLR and frame‐by‐frame CS using wavelets as sparsifying transform (ℓ1‐wavelet).

Reconstruction accuracy relative to ground truth was assessed using synthetic data for realistic ranges of breathing motion, heart rates, and SNRs. In‐vivo experiments were conducted in healthy subjects at rest and during adenosine stress. Myocardial blood flow (MBF) maps were derived using a Fermi model.

Results

Improved uniformity of MBF maps with reduced local variations was achieved with MI‐LLR. For rest and stress, intra‐volunteer variation of absolute and relative MBF was lower in MI‐LLR (±0.17 mL/g/min [26%] and ±1.07 mL/g/min [33%]) versus LLR (±0.19 mL/g/min [28%] and ±1.22 mL/g/min [36%]) and versus ℓ1‐wavelet (±1.17 mL/g/min [113%] and ±6.87 mL/g/min [115%]). At rest, intra‐subject MBF variation was reduced significantly with MI‐LLR.

Conclusion

The combination of pseudo‐spiral Cartesian undersampling and dual‐stage MI‐LLR reconstruction improves free‐breathing quantitative 3D myocardial perfusion CMR imaging under rest and stress condition.

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4D Flow MR Imaging of the Left Atrium: What is Non-physiological Blood Flow in the Cardiac System?

Most cardiac diseases cause a non-physiological blood flow pattern known as turbulence around the heart and great vessels, which further worsen the disease itself. However, there is no consensus on how blood flow can be defined in disease conditions. Especially, in the left atrium, the fact that vortex flow already exists makes this debate more complicated. 3D time-resolved phase-contrast (4D flow) MRI is expected to be able to capture blood flow patterns from multiple aspects, such as blood flow velocity, stasis, and vortex quantification. Previous studies have confirmed that physiological vortex flow is predominantly induced by the higher-volume flow from the superior left pulmonary vein. In atrial fibrillation, 4D flow MRI reveals a non-physiological blood flow pattern, which information may add value to well-established clinical risk factors. Currently, the research target of LA analysis has also widened to lung surgeons, pulmonary vein stump thrombosis after left upper lobectomy. 4D flow MRI is expected to be utilized for many more variable diseases that are currently unimaginable.

Evaluation of intraventricular flow by multimodality imaging: a review and meta-analysis

Background

The aim of this systematic review was to evaluate current inter-modality agreement of noninvasive clinical intraventricular flow (IVF) assessment with 3 emerging imaging modalities: echocardiographic particle image velocimetry (EPIV), vector flow mapping (VFM), and 4-dimensional flow cardiovascular magnetic resonance imaging (4D flow CMR).

Methods

We performed a systematic literature review in the databases EMBASE, Medline OVID and Cochrane Central for identification of studies evaluating left ventricular (LV) flow patterns using one of these flow visualization modalities. Of the 2224 initially retrieved records, 10 EPIV, 23 VFM, and 25 4D flow CMR studies were included in the final analysis.

Results

Vortex parameters were more extensively studied with EPIV, while LV energetics and LV transport mechanics were mainly studied with 4D flow CMR, and LV energy loss and vortex circulation were implemented by VFM studies. Pooled normative values are provided for these parameters. The meta- analysis for the values of two vortex morphology parameters, vortex length and vortex depth, failed to reveal a significant change between heart failure patients and healthy controls.

Conclusion

Agreement between the different modalities studying intraventricular flow is low and different methods of measurement and reporting were used among studies. A multimodality framework with a standardized set of flow parameters is necessary for implementation of noninvasive flow visualization in daily clinical practice. The full potential of noninvasive flow visualization in addition to diagnostics could also include guiding medical or interventional treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12947-021-00269-8.

Pathology and Advanced Imaging—Characterization of a Congenital Cardiac Defect and Complex Hemodynamics in a Pig: A Case Report

Domestic pigs are widely used in cardiovascular research as the porcine circulatory system bears a remarkable resemblance to that of humans. In order to reduce variability, only clinically healthy animals enter the study as their health status is assessed in entry examination. Like humans, pigs can also suffer from congenital heart disease, such as an atrial septal defect (ASD), which often remains undetected. Due to the malformation of the endocardial cushion during organ development, mitral valve defects (e.g., mitral clefts) are sometimes associated with ASDs, further contributing to hemodynamic instability. In this work, we report an incidental finding of a hemodynamically highly relevant ASD in the presence of incompetent mitral and tricuspid valves, in an asymptomatic, otherwise healthy juvenile pig. In-depth characterization of the cardiac blood flow by four-dimensional (4D) flow magnetic resonance imaging (MRI) revealed a prominent diastolic left-to-right and discrete systolic right-to-left shunt, resulting in a pulmonary-to-systemic flow ratio of 1.8. Severe mitral (15 mL/stroke) and tricuspid (22 mL/stroke) regurgitation further reduced cardiac output. Pathological examination confirmed the presence of an ostium primum ASD and found a serous cyst of lymphatic origin that was filled with clear fluid partially occluding the ASD. A large mitral cleft was identified as the most likely cause of severe regurgitation, and histology showed mild to moderate endocardiosis in the coaptation area of both atrio-ventricular valves. In summary, although not common, congenital heart defects could play a role as a cause of experimental variability or even intra-experimental mortality when working with apparently heathy, juvenile pigs.

Echo planar imaging-induced errors in intracardiac 4D flow MRI quantification

Purpose

To assess errors associated with EPI‐accelerated intracardiac 4D flow MRI (4DEPI) with EPI factor 5, compared with non‐EPI gradient echo (4DGRE).

Methods

Three 3T MRI experiments were performed comparing 4DEPI to 4DGRE: steady flow through straight tubes, pulsatile flow in a left‐ventricle phantom, and intracardiac flow in 10 healthy volunteers. For each experiment, 4DEPI was repeated with readout and blip phase‐encoding gradient in different orientations, parallel or perpendicular to the flow direction. In vitro flow rates were compared with timed volumetric collection. In the left‐ventricle phantom and in vivo, voxel‐based speed and spatio‐temporal median speed were compared between sequences, as well as mitral and aortic transvalvular net forward volume.

Results

In steady‐flow phantoms, the flow rate error was largest (12%) for high velocity (>2 m/s) with 4DEPI readout gradient parallel to the flow. Voxel‐based speed and median speed in the left‐ventricle phantom were ≤5.5% different between sequences. In vivo, mean net forward volume inconsistency was largest (6.4 ± 8.5%) for 4DEPI with nonblip phase‐encoding gradient parallel to the main flow. The difference in median speed for 4DEPI versus 4DGRE was largest (9%) when the 4DEPI readout gradient was parallel to the flow.

Conclusions

Velocity and flow rate are inaccurate for 4DEPI with EPI factor 5 when flow is parallel to the readout or blip phase‐encoding gradient. However, mean differences in flow rate, voxel‐based speed, and spatio‐temporal median speed were acceptable (≤10%) when comparing 4DEPI to 4DGRE for intracardiac flow in healthy volunteers.

Fundamentals of turbulent flow spectrum imaging

PURPOSE

To introduce a mathematical framework and in-silico validation of turbulent flow spectrum imaging (TFSI) of stenotic flow using phase-contrast MRI, evaluate systematic errors in quantitative turbulence parameter estimation, and propose a novel method for probing the Lagrangian velocity spectra of turbulent flows.

THEORY AND METHODS

The spectral response of velocity-encoding gradients is derived theoretically and linked to turbulence parameter estimation including the velocity autocorrelation function spectrum. Using a phase-contrast MRI simulation framework, the encoding properties of bipolar gradient waveforms with identical first gradient moments but different duration are investigated on turbulent flow data of defined characteristics as derived from computational fluid dynamics. Based on theoretical insights, an approach using velocity-compensated gradient waveforms is proposed to specifically probe desired ranges of the velocity autocorrelation function spectrum with increased accuracy.

RESULTS

Practical velocity-encoding gradients exhibit limited encoding power of typical turbulent flow spectra, resulting in up to 50% systematic underestimation of intravoxel SD values. Depending on the turbulence level in fluids, the error due to a single encoding gradient spectral response can vary by 20%. When using tailored velocity-compensated gradients, improved quantification of the Lagrangian velocity spectrum on a voxel-by-voxel basis is achieved and used for quantitative correction of intravoxel SD values estimated with velocity-encoding gradients.

CONCLUSION

To address systematic underestimation of turbulence parameters using bipolar velocity-encoding gradients in phase-contrast MRI of stenotic flows with short correlation times, tailored velocity-compensated gradients are proposed to improve quantitative mapping of turbulent blood flow characteristics.

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

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

Improving Blood Flow Visualization of Recirculation Regions at Carotid Bulb in 4D Flow MRI Using Semi-Automatic Segmentation with ITK-SNAP

Assessment of carotid bulb hemodynamics using four-dimensional (4D) flow magnetic resonance imaging (MRI) requires accurate segmentation of recirculation regions that is frequently hampered by limited resolution. This study aims to improve the accuracy of 4D flow MRI carotid bulb segmentation and subsequent recirculation regions analysis. Time-of-flight (TOF) MRI and 4D flow MRI were performed on bilateral carotid artery bifurcations in seven healthy volunteers. TOF-MRI data was segmented into 3D geometry for computational fluid dynamics (CFD) simulations. ITK-SNAP segmentation software was included in the workflow for the semi-automatic generation of 4D flow MRI angiographic data. This study compared the velocities calculated at the carotid bifurcations and the 3D blood flow visualization at the carotid bulbs obtained by 4D flow MRI and CFD. By applying ITK-SNAP segmentation software, an obvious improvement in the 4D flow MRI visualization of the recirculation regions was observed. The 4D flow MRI images of the recirculation flow characteristics of the carotid artery bulbs coincided with the CFD. A reasonable agreement was found in terms of velocity calculated at the carotid bifurcation between CFD and 4D flow MRI. However, the dispersion of velocity data points relative to the local errors of measurement in 4D flow MRI remains. Our proposed strategy showed the feasibility of improving recirculation regions segmentation and the potential for reliable blood flow visualization in 4D flow MRI. However, quantitative analysis of recirculation regions in 4D flow MRI with ITK-SNAP should be enhanced for use in clinical situations.

Pilot tone navigation for respiratory and cardiac motion-resolved free-running 5D flow MRI

Purpose

In this work, we integrated the pilot tone (PT) navigation system into a reconstruction framework for respiratory and cardiac motion‐resolved 5D flow. We tested the hypotheses that PT would provide equivalent respiratory curves, cardiac triggers, and corresponding flow measurements to a previously established self‐gating (SG) technique while being independent from changes to the acquisition parameters.

Methods

Fifteen volunteers and 9 patients were scanned with a free‐running 5D flow sequence, with PT integrated. Respiratory curves and cardiac triggers from PT and SG were compared across all subjects. Flow measurements from 5D flow reconstructions using both PT and SG were compared to each other and to a reference electrocardiogram‐gated and respiratory triggered 4D flow acquisition. Radial trajectories with variable readouts per interleave were also tested in 1 subject to compare cardiac trigger quality between PT and SG.

Results

The correlation between PT and SG respiratory curves were 0.95 ± 0.06 for volunteers and 0.95 ± 0.04 for patients. Heartbeat duration measurements in volunteers and patients showed a bias to electrocardiogram measurements of, respectively, 0.16 ± 64.94 ms and 0.01 ± 39.29 ms for PT versus electrocardiogram and of 0.24 ± 63.68 ms and 0.09 ± 32.79 ms for SG versus electrocardiogram. No significant differences were reported for the flow measurements between 5D flow PT and from 5D flow SG. A decrease in the cardiac triggering quality of SG was observed for increasing readouts per interleave, whereas PT quality remained constant.

Conclusion

PT has been successfully integrated in 5D flow MRI and has shown equivalent results to the previously described 5D flow SG technique, while being completely acquisition‐independent.

The role of 4D flow MRI for clinical applications in cardiovascular disease: current status and future perspectives

Magnetic resonance imaging (MRI) four-dimensional (4D) flow is a type of phase-contrast (PC) MRI that uses blood flow encoded in 3 directions, which is resolved relative to 3 spatial and temporal dimensions of cardiac circulation. It can be used to simultaneously quantify and visualize hemodynamics or morphology disorders. 4D flow MRI is more comprehensive and accurate than two-dimensional (2D) PC MRI and echocardiography. 4D flow MRI provides numerous hemodynamic parameters that are not limited to the basic 2D parameters, including wall shear stress (WSS), pulse wave velocity (PWV), kinetic energy, turbulent kinetic energy (TKE), pressure gradient, and flow component analysis. 4D flow MRI is widely used to image many parts of the body, such as the neck, brain, and liver, and has a wide application spectrum to cardiac diseases and large vessels. This present review aims to summarize the hemodynamic parameters of 4D flow MRI technology and generalize their usefulness in clinical practice in relation to the cardiovascular system. In addition, we note the improvements that have been made to 4D flow MRI with the application of new technologies. The application of new technologies can improve the speed of 4D flow, which would benefit clinical applications.

Using 5D flow MRI to decode the effects of rhythm on left atrial 3D flow dynamics in patients with atrial fibrillation

PURPOSE

This study used a 5D flow framework to explore the influence of arrhythmia on thrombogenic hemodynamic parameters in patients with atrial fibrillation (AF).

METHODS

A fully self-gated, 3D radial, highly accelerated free-running 5D flow sequence with interleaved four-point velocity-encoding was acquired using an in vitro arrhythmic flow phantom and in 25 patients with a history of AF (68 ± 8 y, 6 female). Self-gating signals were used to calculate AF burden, bin data, and tag each k-space line with its RRLength . Data were binned as an RR-resolved dataset with four RR-interval bins (RR1-RR4, short-to-long) for compressed sensing reconstruction. AF burden was calculated as interquartile range of all intrascan RR-intervals divided by median RR-interval, and left atrial (LA) stasis as the percent of the cardiac cycle where the velocity was <0.1 m/s.

RESULTS

In vitro results demonstrated successful recovery of RR-binned flow curves using RR-resolved 5D flow compared to a real-time PC reference standard. In vivo, 5D flow was acquired in 8:48 minutes. AF burden was significantly correlated with 5D flow-derived peak (PV) and mean (MV) velocity and stasis (|ρ| = 0.54-0.75, P < .001). Sensitivity analyses determined a threshold for low versus high AF burden at 9.7%. High burden patients had increased LA mean stasis (up to +42%, P < .01), and lower MV and PV (-30%, -40.6%, respectively, P < .01). RR4 deviated furthest from respiratory-resolved reconstruction (end-expiration) with increased mean stasis (7.6% ± 14.0%, P = .10) and decreased PV (-12.7 ± 14.2%, P = .09).

CONCLUSIONS

RR-resolved 5D flow can capture temporal and RR-resolved 3D hemodynamics in <10 minutes and offers a novel approach to investigate arrhythmias.

Blood Flow Quantification in Peripheral Arterial Disease: Emerging Diagnostic Techniques in Vascular Surgery

The assessment of local blood flow patterns in patients with peripheral arterial disease is clinically relevant, since these patterns are related to atherosclerotic disease progression and loss of patency in stents placed in peripheral arteries, through mechanisms such as recirculating flow and low wall shear stress (WSS). However, imaging of vascular flow in these patients is technically challenging due to the often complex flow patterns that occur near atherosclerotic lesions. While several flow quantification techniques have been developed that could improve the outcomes of vascular interventions, accurate 2D or 3D blood flow quantification is not yet used in clinical practice. This article provides an overview of several important topics that concern the quantification of blood flow in patients with peripheral arterial disease. The hemodynamic mechanisms involved in the development of atherosclerosis and the current clinical practice in the diagnosis of this disease are discussed, showing the unmet need for improved and validated flow quantification techniques in daily clinical practice. This discussion is followed by a showcase of state-of-the-art blood flow quantification techniques and how these could be used before, during and after treatment of stenotic lesions to improve clinical outcomes. These techniques include novel ultrasound-based methods, Phase-Contrast Magnetic Resonance Imaging (PC-MRI) and Computational Fluid Dynamics (CFD). The last section discusses future perspectives, with advanced (hybrid) imaging techniques and artificial intelligence, including the implementation of these techniques in clinical practice.

Blood Flow Quantification in Peripheral Arterial Disease: Emerging Diagnostic Techniques in Vascular Surgery

The assessment of local blood flow patterns in patients with peripheral arterial disease is clinically relevant, since these patterns are related to atherosclerotic disease progression and loss of patency in stents placed in peripheral arteries, through mechanisms such as recirculating flow and low wall shear stress (WSS). However, imaging of vascular flow in these patients is technically challenging due to the often complex flow patterns that occur near atherosclerotic lesions. While several flow quantification techniques have been developed that could improve the outcomes of vascular interventions, accurate 2D or 3D blood flow quantification is not yet used in clinical practice. This article provides an overview of several important topics that concern the quantification of blood flow in patients with peripheral arterial disease. The hemodynamic mechanisms involved in the development of atherosclerosis and the current clinical practice in the diagnosis of this disease are discussed, showing the unmet need for improved and validated flow quantification techniques in daily clinical practice. This discussion is followed by a showcase of state-of-the-art blood flow quantification techniques and how these could be used before, during and after treatment of stenotic lesions to improve clinical outcomes. These techniques include novel ultrasound-based methods, Phase-Contrast Magnetic Resonance Imaging (PC-MRI) and Computational Fluid Dynamics (CFD). The last section discusses future perspectives, with advanced (hybrid) imaging techniques and artificial intelligence, including the implementation of these techniques in clinical practice.

Retrospective Camera-Based Respiratory Gating in Clinical Whole-Heart 4D Flow MRI

Background

Respiratory gating is generally recommended in 4D flow MRI of the heart to avoid blurring and motion artifacts. Recently, a novel automated contact‐less camera‐based respiratory motion sensor has been introduced.

Purpose

To compare camera‐based respiratory gating (CAM) with liver‐lung‐navigator‐based gating (NAV) and no gating (NO) for whole‐heart 4D flow MRI.

Study Type

Retrospective.

Subjects

Thirty two patients with a spectrum of cardiovascular diseases.

Field Strength/Sequence

A 3T, 3D‐cine spoiled‐gradient‐echo‐T1‐weighted‐sequence with flow‐encoding in three spatial directions.

Assessment

Respiratory phases were derived and compared against each other by cross‐correlation. Three radiologists/cardiologist scored images reconstructed with camera‐based, navigator‐based, and no respiratory gating with a 4‐point Likert scale (qualitative analysis). Quantitative image quality analysis, in form of signal‐to‐noise ratio (SNR) and liver‐lung‐edge (LLE) for sharpness and quantitative flow analysis of the valves were performed semi‐automatically.

Statistical Tests

One‐way repeated measured analysis of variance (ANOVA) with Wilks's lambda testing and follow‐up pairwise comparisons. Significance level of P ≤ 0.05. Krippendorff's‐alpha‐test for inter‐rater reliability.

Results

The respiratory signal analysis revealed that CAM and NAV phases were highly correlated (C = 0.93 ± 0.09, P < 0.01). Image scoring showed poor inter‐rater reliability and no significant differences were observed (P ≥ 0.16). The image quality comparison showed that NAV and CAM were superior to NO with higher SNR (P = 0.02) and smaller LLE (P < 0.01). The quantitative flow analysis showed significant differences between the three respiratory‐gated reconstructions in the tricuspid and pulmonary valves (P ≤ 0.05), but not in the mitral and aortic valves (P > 0.05). Pairwise comparisons showed that reconstructions without respiratory gating were different in flow measurements to either CAM or NAV or both, but no differences were found between CAM and NAV reconstructions.

Data Conclusion

Camera‐based respiratory gating performed as well as conventional liver‐lung‐navigator‐based respiratory gating. Quantitative image quality analysis showed that both techniques were equivalent and superior to no‐gating‐reconstructions. Quantitative flow analysis revealed local flow differences (tricuspid/pulmonary valves) in images of no‐gating‐reconstructions, but no differences were found between images reconstructed with camera‐based and navigator‐based respiratory gating.

Level of Evidence

3

Technical Efficacy

Stage 2

2020 - State of our JCMR

There were 79 articles published in the Journal of Cardiovascular Magnetic Resonance (JCMR) in 2019, including 65 original research papers, 2 reviews, 8 technical notes, 1 Society for Cardiovascular Magnetic Resonacne (SCMR) guideline, and 3 corrections. The volume was down slightly from 2018 (n = 89) with a corresponding 5.5% increase in manuscript submissions from 345 to 366. This led to a slight decrease in the acceptance rate from 25 to 22%. The quality of the submissions continues to be high. The 2019 JCMR Impact Factor (which is published in June 2020) increased from 5.07 to 5.36. The 2020 impact factor means that on average, each JCMR published in 2017 and 2018 was cited 5.36 times in 2019. Our 5 year impact factor was 5.2. We are now finishing the 13th year of JCMR as an open-access publication with BMC. As outlined in this report, the Open-Access system has dramatically increased the reading and citation of JCMR publications. I hope that our authors will continue to send their very best, high quality manuscripts for JCMR consideration and that our readers will continue to look to JCMR for the very best/state-of-the-art publications in our field. It takes a village to run a journal. JCMR is blessed to have very dedicated Associate Editors, Guest Editors, and Reviewers. I thank each of them for their efforts to ensure that the review process occurs in a timely and responsible manner. These efforts have allowed the JCMR to continue as the premier journal of our field. My role, and the entire process would not be possible without the dedication and efforts of our managing editor, Diana Gethers (who will leaving the journal in the coming months) and our assistant managing editor, Jennifer Rodriguez, who has agreed to increase her reponsibilities. Finally, I thank you for entrusting me with the editorship of the JCMR. As I begin my 5th year as your editor-in-chief, please know that I fully recognize we are not perfect in our review process. We try our best to objectively assess every submission in a timely manner, but sometimes don't get it "right." The editorial process is a tremendously fulfilling experience for me. The opportunity to review manuscripts that reflect the best in our field remains a great joy and a highlight of my week!

Additional value and new insights by four-dimensional flow magnetic resonance imaging in congenital heart disease: application in neonates and young children

Cardiovascular MRI has become an essential imaging modality in children with congenital heart disease (CHD) in the last 15-20 years. With use of appropriate sequences, it provides important information on cardiovascular anatomy, blood flow and function for initial diagnosis and post-surgical or -interventional monitoring in children. Although considered as more sophisticated and challenging than CT, in particular in neonates and infants, MRI is able to provide information on intra- and extracardiac haemodynamics, in contrast to CT. In recent years, four-dimensional (4-D) flow MRI has emerged as an additional MR technique for retrospective assessment and visualisation of blood flow within the heart and any vessel of interest within the acquired three-dimensional (3-D) volume. Its application in young children requires special adaptations for the smaller vessel size and faster heart rate compared to adolescents or adults. In this article, we provide an overview of 4-D flow MRI in various types of complex CHD in neonates and infants to demonstrate its potential indications and beneficial application for optimised individual cardiovascular assessment. We focus on its application in clinical routine cardiovascular workup and, in addition, show some examples with pathologies other than CHD to highlight that 4-D flow MRI yields new insights in disease understanding and therapy planning. We shortly review the essentials of 4-D flow data acquisition, pre- and post-processing techniques in neonates, infants and young children. Finally, we conclude with some details on accuracy, limitations and pitfalls of the technique.

5D Flow MRI: A Fully Self-gated, Free-running Framework for Cardiac and Respiratory Motion-resolved 3D Hemodynamics

PURPOSE

To implement, validate, and apply a self-gated free-running whole-heart five-dimensional (5D) flow MRI framework to evaluate respiration-driven effects on three-dimensional (3D) hemodynamics in a clinical setting.

MATERIALS AND METHODS

In this prospective study, a free-running five-dimensional (5D) flow sequence was implemented with 3D radial sampling, self-gating, and a compressed-sensing reconstruction. The 5D flow was evaluated in a pulsatile phantom and adult participants with aortic and/or valvular disease who were enrolled between May and August 2019. Conventional twofold-accelerated four-dimensional (4D) flow of the thoracic aorta with navigator gating was performed as a reference comparison. Continuous parameters were evaluated for parameter normality and were compared between conventional 4D flow and 5D flow using a signed-rank or two-tailed paired t test. Differences between respiratory states were evaluated using a repeated-measure analysis of variance or a nonparametric Friedman test.

RESULTS

A total of 20 adult participants (mean age, 49 years ± 17 [standard deviation]; 18 men and two women) were included. In vitro 5D flow results showed excellent agreement with conventional 4D flow-derived values (peak and net flow, <7% difference over all quantified planes). Whole-heart 5D flow data were collected in all participants in 7.65 minutes ± 0.35 (acceleration rate = 36.0-76.9) versus 9.88 minutes ± 3.17 for conventional aortic 4D flow. In vivo, 5D flow demonstrated moderate agreement with conventional 4D flow but demonstrated overestimation in net flow and peak velocity (up to 26% and 12%, respectively) in the ascending aorta and underestimation (<12%) in the arch and descending aorta. Respiratory-resolved analyses of caval veins showed significantly increased net and peak flow in the inferior vena cava in end inspiration compared with end expiration, and the opposite trend was shown in the superior vena cava.

CONCLUSION

A free-running 5D flow MRI framework consistently captured cardiac and respiratory motion-resolved 3D hemodynamics in less than 8 minutes. Supplemental material is available for this article. © RSNA, 2020.

Fully self-gated whole-heart 4D flow imaging from a 5-minute scan

PURPOSE

To develop and validate an acquisition and processing technique that enables fully self-gated 4D flow imaging with whole-heart coverage in a fixed 5-minute scan.

THEORY AND METHODS

The data are acquired continuously using Cartesian sampling and sorted into respiratory and cardiac bins using the self-gating signal. The reconstruction is performed using a recently proposed Bayesian method called ReVEAL4D. ReVEAL4D is validated using data from 8 healthy volunteers and 2 patients and compared with compressed sensing technique, L1-SENSE.

RESULTS

Healthy subjects-Compared with 2D phase-contrast MRI (2D-PC), flow quantification from ReVEAL4D shows no significant bias. In contrast, the peak velocity and peak flow rate for L1-SENSE are significantly underestimated. Compared with traditional parallel MRI-based 4D flow imaging, ReVEAL4D demonstrates small but significant biases in net flow and peak flow rate, with no significant bias in peak velocity. All 3 indices are significantly and more markedly underestimated by L1-SENSE. Patients-Flow quantification from ReVEAL4D agrees well with the 2D-PC reference. In contrast, L1-SENSE markedly underestimated peak velocity.

CONCLUSIONS

The combination of highly accelerated 5-minute Cartesian acquisition, self-gating, and ReVEAL4D enables whole-heart 4D flow imaging with accurate flow quantification.

Heritability of haemodynamics in the ascending aorta

Blood flow in the vasculature can be characterised by dimensionless numbers commonly used to define the level of instabilities in the flow, for example the Reynolds number, Re. Haemodynamics play a key role in cardiovascular disease (CVD) progression. Genetic studies have identified mechanosensitive genes with causal roles in CVD. Given that CVD is highly heritable and abnormal blood flow may increase risk, we investigated the heritability of fluid metrics in the ascending aorta calculated using patient-specific data from cardiac magnetic resonance (CMR) imaging. 341 participants from 108 British Caucasian families were phenotyped by CMR and genotyped for 557,124 SNPs. Flow metrics were derived from the CMR images to provide some local information about blood flow in the ascending aorta, based on maximum values at systole at a single location, denoted max, and a 'peak mean' value averaged over the area of the cross section, denoted pm. Heritability was estimated using pedigree-based (QTDT) and SNP-based (GCTA-GREML) methods. Estimates of Reynolds number based on spatially averaged local flow during systole showed substantial heritability ([Formula: see text], [Formula: see text]), while the estimated heritability for Reynolds number calculated using the absolute local maximum velocity was not statistically significant (12-13%; [Formula: see text]). Heritability estimates of the geometric quantities alone; e.g. aortic diameter ([Formula: see text], [Formula: see text]), were also substantially heritable, as described previously. These findings indicate the potential for the discovery of genetic factors influencing haemodynamic traits in large-scale genotyped and phenotyped cohorts where local spatial averaging is used, rather than instantaneous values. Future Mendelian randomisation studies of aortic haemodynamic estimates, which are swift to derive in a clinical setting, will allow for the investigation of causality of abnormal blood flow in CVD.

High Spatiotemporal Resolution 4D Flow MRI of Intracranial Aneurysms at 7T in 10 Minutes

BACKGROUND AND PURPOSE

Patients with intracranial aneurysms may benefit from 4D flow MR imaging because the derived wall shear stress is considered a useful marker for risk assessment and growth of aneurysms. However, long scan times limit the clinical implementation of 4D flow MR imaging. Therefore, this study aimed to investigate whether highly accelerated, high resolution, 4D flow MR imaging at 7T provides reliable quantitative blood flow values in intracranial arteries and aneurysms.

MATERIALS AND METHODS

We used pseudospiral Cartesian undersampling with compressed sensing reconstruction to achieve high spatiotemporal resolution (0.5 mm isotropic, ∼30 ms) in a scan time of 10 minutes. We analyzed the repeatability of accelerated 4D flow scans and compared flow rates, stroke volume, and the pulsatility index with 2D flow and conventional 4D flow MR imaging in a flow phantom and 15 healthy subjects. Additionally, accelerated 4D flow MR imaging with high spatiotemporal resolution was acquired in 5 patients with aneurysms to derive wall shear stress.

RESULTS

Flow-rate bias compared with 2D flow was lower for accelerated than for conventional 4D flow MR imaging (0.31 ± 0.13, P = .22, versus 0.79 ± 0.17 mL/s, P < .01). Pulsatility index bias gave similar results. Stroke volume bias showed no difference for accelerated as well as for conventional 4D flow compared to 2D flow MR imaging. Repeatability for accelerated 4D flow was similar to that of 2D flow MR imaging. Increased temporal resolution for wall shear stress measurements in 5 intracranial aneurysms did not show a consistent effect for the wall shear stress but did show an effect for the oscillatory shear index.

CONCLUSIONS

Highly accelerated high spatiotemporal resolution 4D flow MR imaging at 7T in intracranial arteries and aneurysms provides repeatable and accurate quantitative flow values. Flow rate accuracy is significantly increased compared with conventional 4D flow scans.

Pseudo-spiral sampling and compressed sensing reconstruction provides flexibility of temporal resolution in accelerated aortic 4D flow MRI: A comparison with k-t principal component analysis

INTRODUCTION

Time-resolved three-dimensional phase contrast MRI (4D flow) of aortic blood flow requires acceleration to reduce scan time. Two established techniques for highly accelerated 4D flow MRI are k-t principal component analysis (k-t PCA) and compressed sensing (CS), which employ either regular or random k-space undersampling. The goal of this study was to gain insights into the quantitative differences between k-t PCA- and CS-derived aortic blood flow, especially for high temporal resolution CS 4D flow MRI.

METHODS

The scan protocol consisted of both k-t PCA and CS accelerated 4D flow MRI, as well as a 2D flow reference scan through the ascending aorta acquired in 15 subjects. 4D flow scans were accelerated with factor R = 8. For CS accelerated scans, we used a pseudo-spiral Cartesian sampling scheme, which could additionally be reconstructed at higher temporal resolution, resulting in R = 13. 4D flow data were compared with the 2D flow scan in terms of flow, peak flow and stroke volume. A 3D peak systolic voxel-wise velocity and wall shear stress (WSS) comparison between k-t PCA and CS 4D flow was also performed.

RESULTS

The mean difference in flow/peak flow/stroke volume between the 2D flow scan and the 4D flow CS with R = 8 and R = 13 was 4.2%/9.1%/3.0% and 5.3%/7.1%/1.9%, respectively, whereas for k-t PCA with R = 8 the difference was 9.7%/25.8%/10.4%. In the voxel-by-voxel 4D flow comparison we found 13.6% and 3.5% lower velocity and WSS values of k-t PCA compared with CS with R = 8, and 15.9% and 5.5% lower velocity and WSS values of k-t PCA compared with CS with R = 13.

CONCLUSION

Pseudo-spiral accelerated 4D flow acquisitions in combination with CS reconstruction provides a flexible choice of temporal resolution. We showed that our proposed strategy achieves better agreement in flow values with 2D reference scans compared with using k-t PCA accelerated acquisitions.

On the limitations of echo planar 4D flow MRI

PURPOSE

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

THEORY AND METHODS

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

RESULTS

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

CONCLUSIONS

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

From Compressed-Sensing to Artificial Intelligence-Based Cardiac MRI Reconstruction

Cardiac magnetic resonance (CMR) imaging is an important tool for the non-invasive assessment of cardiovascular disease. However, CMR suffers from long acquisition times due to the need of obtaining images with high temporal and spatial resolution, different contrasts, and/or whole-heart coverage. In addition, both cardiac and respiratory-induced motion of the heart during the acquisition need to be accounted for, further increasing the scan time. Several undersampling reconstruction techniques have been proposed during the last decades to speed up CMR acquisition. These techniques rely on acquiring less data than needed and estimating the non-acquired data exploiting some sort of prior information. Parallel imaging and compressed sensing undersampling reconstruction techniques have revolutionized the field, enabling 2- to 3-fold scan time accelerations to become standard in clinical practice. Recent scientific advances in CMR reconstruction hinge on the thriving field of artificial intelligence. Machine learning reconstruction approaches have been recently proposed to learn the non-linear optimization process employed in CMR reconstruction. Unlike analytical methods for which the reconstruction problem is explicitly defined into the optimization process, machine learning techniques make use of large data sets to learn the key reconstruction parameters and priors. In particular, deep learning techniques promise to use deep neural networks (DNN) to learn the reconstruction process from existing datasets in advance, providing a fast and efficient reconstruction that can be applied to all newly acquired data. However, before machine learning and DNN can realize their full potentials and enter widespread clinical routine for CMR image reconstruction, there are several technical hurdles that need to be addressed. In this article, we provide an overview of the recent developments in the area of artificial intelligence for CMR image reconstruction. The underlying assumptions of established techniques such as compressed sensing and low-rank reconstruction are briefly summarized, while a greater focus is given to recent advances in dictionary learning and deep learning based CMR reconstruction. In particular, approaches that exploit neural networks as implicit or explicit priors are discussed for 2D dynamic cardiac imaging and 3D whole-heart CMR imaging. Current limitations, challenges, and potential future directions of these techniques are also discussed.

Non-invasive estimation of relative pressure in turbulent flow using virtual work-energy

Vascular pressure differences are established risk markers for a number of cardiovascular diseases. Relative pressures are, however, often driven by turbulence-induced flow fluctuations, where conventional non-invasive methods may yield inaccurate results. Recently, we proposed a novel method for non-turbulent flows, νWERP, utilizing the concept of virtual work-energy to accurately probe relative pressure through complex branching vasculature. Here, we present an extension of this approach for turbulent flows: νWERP-t. We present a theoretical method derivation based on flow covariance, quantifying the impact of flow fluctuations on relative pressure. νWERP-t is tested on a set of in-vitro stenotic flow phantoms with data acquired by 4D flow MRI with six-directional flow encoding, as well as on a patient-specific in-silico model of an acute aortic dissection. Over all tests νWERP-t shows improved accuracy over alternative energy-based approaches, with excellent recovery of estimated relative pressures. In particular, the use of a guaranteed divergence-free virtual field improves accuracy in cases where turbulent flows skew the apparent divergence of the acquired field. With the original νWERP allowing for assessment of relative pressure into previously inaccessible vasculatures, the extended νWERP-t further enlarges the method's clinical scope, underlining its potential as a novel tool for assessing relative pressure in-vivo.

5D Flow Tensor MRI to Efficiently Map Reynolds Stresses of Aortic Blood Flow In-Vivo

Diseased heart valves perturb normal blood flow with a range of hemodynamic and pathologic consequences. In order to better stratify patients with heart valve disease, a comprehensive characterization of blood flow including turbulent contributions is desired. In this work we present a framework to efficiently quantify velocities and Reynolds stresses in the aorta in-vivo. Using a highly undersampled 5D Flow MRI acquisition scheme with locally low-rank image reconstruction, multipoint flow tensor encoding in short and predictable scan times becomes feasible (here, 10 minutes), enabling incorporation of the protocol into clinical workflows. Based on computer simulations, a 19-point 5D Flow Tensor MRI encoding approach is proposed. It is demonstrated that, for in-vivo resolution and signal-to-noise ratios, sufficient accuracy and precision of velocity and turbulent shear stress quantification is achievable. In-vivo proof of concept is demonstrated on patients with a bio-prosthetic heart valve and healthy controls. Results demonstrate that aortic turbulent shear stresses and turbulent kinetic energy are elevated in the patients compared to the healthy subjects. Based on these data, it is concluded that 5D Flow Tensor MRI holds promise to provide comprehensive flow assessment in patients with heart valve diseases.