Coupling Myocardium and Vortex Dynamics in Diverging-Wave Echocardiography

Boosting Cardiac Color Doppler Frame Rates With Deep Learning

Color Doppler echocardiography enables visualization of blood flow within the heart. However, the limited frame rate impedes the quantitative assessment of blood velocity throughout the cardiac cycle, thereby compromising a comprehensive analysis of ventricular filling. Concurrently, deep learning is demonstrating promising outcomes in postprocessing of echocardiographic data for various applications. This work explores the use of deep learning models for intracardiac Doppler velocity estimation from a reduced number of filtered I/Q signals. We used a supervised learning approach by simulating patient-based cardiac color Doppler acquisitions and proposed data augmentation strategies to enlarge the training dataset. We implemented architectures based on convolutional neural networks (CNNs). In particular, we focused on comparing the U-Net model and the recent ConvNeXt model, alongside assessing real-valued versus complex-valued representations. We found that both models outperformed the state-of-the-art autocorrelator method, effectively mitigating aliasing and noise. We did not observe significant differences between the use of real and complex data. Finally, we validated the models on in vitro and in vivo experiments. All models produced quantitatively comparable results to the baseline and were more robust to noise. ConvNeXt emerged as the sole model to achieve high-quality results on in vivo aliased samples. These results demonstrate the interest of supervised deep learning methods for Doppler velocity estimation from a reduced number of acquisitions.

Automated cardiac vortex ring identification and characterization based on Recurrent All-Pairs Field Transforms and Lagrangian Averaged Vorticity Deviation

Automated identification of cardiac vortices is a formidable task due to the complex nature of blood flow within the heart chambers. This study proposes a novel approach that algorithmically characterizes the identification criteria of these cardiac vortices based on Lagrangian Averaged Vorticity Deviation (LAVD). For this purpose, the Recurrent All-Pairs Field Transforms (RAFT) is employed to assess the optical flow over the Phase Contrast Magnetic Resonance Imaging (PC-MRI), and to construct a continuous blood flow velocity field and reduce errors that arise from the integral process of LAVD. Additionally, Generalized Hough Transform (GHT) is applied for automated depiction of the structure of cardiac vortices. The effectiveness of this method is demonstrated and validated by the computation of the acquired cardiac flow data. The results of this comprehensive visual and analytical study show that the evolution of cardiac vortices can be effectively described and displayed, and the RAFT framework for optical flow can synthesize the in-between PC-MRIs with high accuracy. This allows cardiologists to acquire a deeper understanding of intracardiac hemodynamics and its impact on cardiac functional performance.

Mouse Cardiovascular Imaging

The mouse is the mammalian model of choice for investigating cardiovascular biology, given our ability to manipulate it by genetic, pharmacologic, mechanical, and environmental means. Imaging is an important approach to phenotyping both function and structure of cardiac and vascular components. This review details commonly used imaging approaches, with a focus on echocardiography and magnetic resonance imaging, with brief overviews of other imaging modalities. In this update, we also emphasize the importance of rigor and reproducibility in imaging approaches, experimental design, and documentation. Finally, we briefly outline emerging imaging approaches but caution that reliability and validity data may be lacking. © 2024 Wiley Periodicals LLC.

Doppler and Pair-Wise Optical Flow Constrained 3D Motion Compensation for 3D Ultrasound Imaging

Volumetric (3D) ultrasound imaging using a 2D matrix array probe is increasingly developed for various clinical procedures. However, 3D ultrasound imaging suffers from motion artifacts due to tissue motions and a relatively low frame rate. Current Doppler-based motion compensation (MoCo) methods only allow 1D compensation in the in-range dimension. In this work, we propose a new 3D-MoCo framework that combines 3D velocity field estimation and a two-step compensation strategy for 3D diverging wave compounding imaging. Specifically, our framework explores two constraints of a round-trip scan sequence of 3D diverging waves, i.e., Doppler and pair-wise optical flow, to formulate the estimation of the 3D velocity fields as a global optimization problem, which is further regularized by the divergence-free and first-order smoothness. The two-step compensation strategy is to first compensate for the 1D displacements in the in-range dimension and then the 2D displacements in the two mutually orthogonal cross-range dimensions. Systematical in-silico experiments were conducted to validate the effectiveness of our proposed 3D-MoCo method. The results demonstrate that our 3D-MoCo method achieves higher image contrast, higher structural similarity, and better speckle patterns than the corresponding 1D-MoCo method. Particularly, the 2D cross-range compensation is effective for fully recovering image quality.

Retrospective Ultrasound Doppler Quantification Using a Single Acquisition in Healthy Adults

OBJECTIVE

Using an experimental tool for retrospective ultrasound Doppler quantification-with high temporal resolution and large spatial coverage-simultaneous flow and tissue measurements were obtained. We compared and validated these experimental values against conventional measurements to determine if the experimental acquisition produced trustworthy tissue and flow velocities.

METHODS

We included 21 healthy volunteers. The only exclusion criterion was the presence of an irregular heartbeat. Two ultrasound examinations were performed for each participant, one using conventional and one using experimental acquisition. The experimental acquisition used multiple plane wave emissions combined with electrocardiography stitching to obtain continuous data with over 3500 frames per second. With two recordings covering a biplane apical view of the left ventricle, we retrospectively extracted selected flow and tissue velocities.

RESULTS

Flow and tissue velocities were compared between the two acquisitions. Statistical testing showed a small but significant difference. We also exemplified the possibility of extracting spectral tissue Doppler from different sample volumes in the myocardium within the imaging sector, showing a decrease in the velocities from the base to the apex.

CONCLUSION

This study demonstrates the feasibility of simultaneous, retrospective spectral and color Doppler of both tissue and flow from an experimental acquisition covering a full sector width. The measurements were significantly different between the two acquisitions but were still comparable, as the biases were small compared to clinical practice, and the two acquisitions were not done simultaneously. The experimental acquisition also enabled the study of deformation by simultaneous spectral velocity traces from all regions of the image sector.

Fast and Robust Clutter Filtering in Ultrafast Echocardiography

Singular value decomposition (SVD)-based filters have become the norm for clutter filtering in ultrasound blood flow applications but are computationally expensive and susceptible to large and fast tissue motion. Randomized SVD (rSVD) has later been shown to successfully accelerate filtering of in vivo stationary tissues. However, little is known about its performance on ultrafast echocardiography, which produces thousands of frames to assess complex myocardial deformation and blood dynamics. Neither has its inherently robust randomized scheme been proven in any ultrasound blood flow imaging methods. This study thus proposed to employ rSVD as a fast and robust clutter filter for ultrafast echocardiograms prior to power Doppler analysis. Ultrafast echocardiograms of nine normal human hearts were acquired in vivo by our cascaded synthetic aperture imaging method. One subject was additionally scanned under four different sonographic signal-to-noise ratio (SNR) levels. Contrast ratio (CR) and contrast-to-noise ratio (CNR) of in vivo power Doppler images obtained from filtered ultrafast echocardiograms were calculated, and their mean and standard deviation within a cardiac cycle represented temporal average and variation of contrast resolution, respectively. Our in vivo results showed that rSVD accelerated clutter filtering by 12-fold and provided significantly better local contrast (mean CNR values: p < 0.001) while being equally effective (mean CR values: p = 0.20) compared with full-SVD. rSVD yielded smaller standard deviations of CR (1.32 dB vs. 5.49 dB) and CNR (1.27 dB vs. 5.49 dB) than full-SVD in the lowest SNR scenario, thus substantiating its superior robustness. Our findings suggest using rSVD in ultrafast echocardiographic blood dynamics analysis.

Influence of key parameters on motion artifacts in lateral strain estimation with spatial angular compounding

Strain imaging can reveal the changes in tissue mechanical properties related to pathological alterations by estimating tissue strains in the lateral and axial directions of ultrasound imaging. The estimation performance in the lateral direction is usually worse than that in the axial direction. Spatial angular compounding (SAC) has been demonstrated to improve the quality of lateral estimation by deriving the lateral displacements using axial displacements obtained from multi-angle transmissions. However, motion and deformation of tissues during multiple transmissions may cause motion artifacts, and thus deteriorate the quality of strain estimation. These artifacts can be reduced by choosing appropriate imaging parameters. However, few studies have been conducted to evaluate the influences of key parameters in strain estimation, such as the pulse repetition frequency (PRF), the number of steering angles (NSA), and the maximum steering angles (MSA), in terms of performance optimization. Therefore, this study aims to investigate the effects of these parameters through simulations and phantom experiments. The performance of strain estimation is evaluated by measuring the root-mean-square error (RMSE) and the standard deviation (SD) in the simulations and phantom experiments, respectively. The contrast-to-noise ratio (CNR) of strain images is calculated in both the simulations and phantom experiments. The results show that motion artifacts in strain estimation can be reduced by increasing the PRF to 1 kHz. When the PRF reaches 1 kHz, further increase of the PRF shows little obvious improvement in strain estimation. An increase in the NSA can cause larger motion artifacts and deteriorate the quality of strain images, and the improvement of strain estimation is limited when the NSA is increased from 3 to 7. An NSA of 3 is thus recommended to balance the influences of motion artifacts and the improvement for strain estimation. The MSA has little influence on the motion artifacts, while increased MSA can achieve improved lateral estimation performance at the cost of a smaller imaging region. In light of the lateral strain estimation performance and imaging region, an MSA of 15° is recommended. The influences of these key parameters obtained from this study may provide insights for parameter optimization in strain estimation with SAC to minimize the effects of motion artifacts.

Full-volume three-component intraventricular vector flow mapping by triplane color Doppler

Objective. Intraventricular vector flow mapping (iVFM) is a velocimetric technique for retrieving two-dimensional velocity vector fields of blood flow in the left ventricular cavity. This method is based on conventional color Doppler imaging, which makes iVFM compatible with the clinical setting. We have generalized the iVFM for a three-dimensional reconstruction (3D-iVFM). Approach. 3D-iVFM is able to recover three-component velocity vector fields in a full intraventricular volume by using a clinical echocardiographic triplane mode. The 3D-iVFM problem was written in the spherical (radial, polar, azimuthal) coordinate system associated to the six half-planes produced by the triplane mode. As with the 2D version, the method is based on the mass conservation, and free-slip boundary conditions on the endocardial wall. These mechanical constraints were imposed in a least-squares minimization problem that was solved through the method of Lagrange multipliers. We validated 3D-iVFM in silico in a patient-specific CFD (computational fluid dynamics) model of cardiac flow and tested its clinical feasibility in vivo in patients and in one volunteer. Main results. The radial and polar components of the velocity were recovered satisfactorily in the CFD setup (correlation coefficients, r  = 0.99 and 0.78). The azimuthal components were estimated with larger errors ( r  = 0.57) as only six samples were available in this direction. In both in silico and in vivo investigations, the dynamics of the intraventricular vortex that forms during diastole was deciphered by 3D-iVFM. In particular, the CFD results showed that the mean vorticity can be estimated accurately by 3D-iVFM. Significance. Our results tend to indicate that 3D-iVFM could provide full-volume echocardiographic information on left intraventricular hemodynamics from the clinical modality of triplane color Doppler.

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

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

A Pipeline for the Generation of Synthetic Cardiac Color Doppler

Color Doppler imaging (CDI) is the modality of choice for simultaneous visualization of myocardium and intracavitary flow over a wide scan area. This visualization modality is subject to several sources of error, the main ones being aliasing and clutter. Mitigation of these artifacts is a major concern for better analysis of intracardiac flow. One option to address these issues is through simulations. In this article, we present a numerical framework for generating clinical-like CDI. Synthetic blood vector fields were obtained from a patient-specific computational fluid dynamics CFD model. Realistic texture and clutter artifacts were simulated from real clinical ultrasound cineloops. We simulated several scenarios highlighting the effects of 1) flow acceleration; 2) wall clutter; and 3) transmit wavefronts, on Doppler velocities. As a comparison, an "ideal" color Doppler was also simulated, without these harmful effects. This synthetic dataset is made publicly available and can be used to evaluate the quality of Doppler estimation techniques. Besides, this approach can be seen as a first step toward the generation of comprehensive datasets for training neural networks to improve the quality of Doppler imaging.

Complex Convolutional Neural Networks for Ultrafast Ultrasound Imaging Reconstruction From In-Phase/Quadrature Signal

Ultrafast ultrasound imaging remains an active area of interest in the ultrasound community due to its ultrahigh frame rates. Recently, a wide variety of studies based on deep learning have sought to improve ultrafast ultrasound imaging. Most of these approaches have been performed on radio frequency (RF) signals. However, in- phase/quadrature (I/Q) digital beamformers are now widely used as low-cost strategies. In this work, we used complex convolutional neural networks for reconstruction of ultrasound images from I/Q signals. We recently described a convolutional neural network architecture called ID-Net, which exploited an inception layer designed for reconstruction of RF diverging-wave ultrasound images. In the present study, we derive the complex equivalent of this network, i.e., complex-valued inception for diverging-wave network (CID-Net) that operates on I/Q data. We provide experimental evidence that CID-Net provides the same image quality as that obtained from RF-trained convolutional neural networks, i.e., using only three I/Q images, CID-Net produces high-quality images that can compete with those obtained by coherently compounding 31 RF images. Moreover, we show that CID-Net outperforms the straightforward architecture that consists of processing real and imaginary parts of the I/Q signal separately, which thereby indicates the importance of consistently processing the I/Q signals using a network that exploits the complex nature of such signals.

Intraventricular Vector Flow Imaging with Blood Speckle Tracking in Adults: Feasibility, Normal Physiology and Mechanisms in Healthy Volunteers

This study examines the feasibility of blood speckle tracking for vector flow imaging in healthy adults and describes the physiologic flow pattern and vortex formation in relation to the wall motion in the left ventricle. The study included 21 healthy volunteers and quantified and visualized flow patterns with high temporal resolution down to a depth of 10-12 cm without the use of contrast agents. Intraventricular flow seems to originate during the isovolumetric relaxation with a propagation of blood from base to apex. With the E-wave, rapid inflow and vortex formation occurred on both sides of the valve basally. During diastasis the flow gathers in a large vortex before the pattern from the E-wave repeats during the A-wave. In isovolumetric contraction, the flow again gathers in a large vortex that seems to facilitate the flow out in the aorta during systole. No signs of a persistent systolic vortex were visualized. The geometry of the left ventricle and the movement of the AV-plane is important in creating vortices that are favorable for the blood flow and facilitate outflow. The quantitative measurements are in concordance with these findings, but the clinical interpretation must be evaluated in future clinical studies.

Dealiasing High-Frame-Rate Color Doppler Using Dual-Wavelength Processing

Doppler ultrasound is the premier modality to analyze blood flow dynamics in clinical practice. With conventional systems, Doppler can either provide a time-resolved quantification of the flow dynamics in sample volumes (spectral Doppler) or an average Doppler velocity/power [color flow imaging (CFI)] in a wide field of view (FOV) but with a limited frame rate. The recent development of ultrafast parallel systems made it possible to evaluate simultaneously color, power, and spectral Doppler in a wide FOV and at high-frame rates but at the expense of signal-to-noise ratio (SNR). However, like conventional Doppler, ultrafast Doppler is subject to aliasing for large velocities and/or large depths. In a recent study, staggered multi-pulse repetition frequency (PRF) sequences were investigated to dealias color-Doppler images. In this work, we exploit the broadband nature of pulse-echo ultrasound and propose a dual-wavelength approach for CFI dealiasing with a constant PRF. We tested the dual-wavelength bandpass processing, in silico, in laminar flow phantom and validated it in vivo in human carotid arteries ( n = 25 ). The in silico results showed that the Nyquist velocity could be extended up to four times the theoretical limit. In vivo, dealiased CFI were highly consistent with unfolded Spectral Doppler ( r²=0.83 , y=1.1x+0.1 , N=25 ) and provided consistent vector flow images. Our results demonstrate that dual-wavelength processing is an efficient method for high-velocity CFI.

So you think you can DAS? A viewpoint on delay-and-sum beamforming

Delay-and-sum (DAS) is the most widespread digital beamformer in high-frame-rate ultrasound imaging. Its implementation is simple and compatible with real-time applications. In this viewpoint article, we describe the fundamentals of DAS beamforming. The underlying theory and numerical approach are detailed so that users can be aware of its functioning and limitations. In particular, we discuss the importance of the f-number and speed of sound on image quality, and propose one solution to set their values from a physical viewpoint. We suggest determining the f-number from the directivity of the transducer elements and the speed of sound from the phase dispersion of the delayed signals. Simplified Matlab codes are provided for the sake of clarity and openness. The effect of the f-number and speed of sound on the lateral resolution and contrast-to-noise ratio was investigated in vitro and in vivo. If not properly preset, these two factors had a substantial negative impact on standard metrics of image quality (namely CNR and FWHM). When beamforming with DAS in vitro or in vivo, it is recommended to optimize these parameters in order to use it wisely and prevent image degradation.

Translation of Simultaneous Vessel Wall Motion and Vectorial Blood Flow Imaging in Healthy and Diseased Carotids to the Clinic: A Pilot Study

This study aims to investigate the clinical feasibility of simultaneous extraction of vessel wall motion and vectorial blood flow at high frame rates for both extraction of clinical markers and visual inspection. If available in the clinic, such a technique would allow a better estimation of plaque vulnerability and improved evaluation of the overall arterial health of patients. In this study, both healthy volunteers and patients were recruited and scanned using a planewave acquisition scheme that provided a data set of 43 carotid recordings in total. The vessel wall motion was extracted based on the complex autocorrelation of the signals received, while the vector flow was extracted using the transverse oscillation technique. Wall motion and vector flow were extracted at high frame rates, which allowed for a visual appreciation of tissue movement and blood flow simultaneously. Several clinical markers were extracted, and visual inspections of the wall motion and flow were conducted. From all the potential markers, young healthy volunteers had smaller artery diameter (7.72 mm) compared with diseased patients (9.56 mm) ( p -value ≤ 0.001), 66% of diseased patients had backflow compared with less than 10% for the other patients ( p -value ≤ 0.05), a carotid with a pulse wave velocity extracted from the wall velocity greater than 7 m/s was always a diseased vessel, and the peak wall shear rate decreased as the risk increases. Based on both the pathological markers and the visual inspection of tissue motion and vector flow, we conclude that the clinical feasibility of this approach is demonstrated. Larger and more disease-specific studies using such an approach will lead to better understanding and evaluation of vessels, which can translate to future use in the clinic.

Characterization of Vortex Flow in a Mouse Model of Ventricular Dyssynchrony by Plane-Wave Ultrasound Using Hexplex Processing

The rodent heart is frequently used to study human cardiovascular disease (CVD). Although advanced cardiovascular ultrasound imaging methods are available for human clinical practice, application of these techniques to small animals remains limited due to the temporal and spatial-resolution demands. Here, an ultrasound vector-flow workflow is demonstrated that enables visualization and quantification of the complex hemodynamics within the mouse heart. Wild type (WT) and fibroblast growth factor homologous factor 2 (FHF2)-deficient mice (Fhf2 ^KO/Y ), which present with hyperthermia-induced ECG abnormalities highly reminiscent of Brugada syndrome, were used as a mouse model of human CVD. An 18-MHz linear array was used to acquire high-speed (30 kHz), plane-wave data of the left ventricle (LV) while increasing core body temperature up to 41.5 °C. Hexplex (i.e., six output) processing of the raw data sets produced the output of vector-flow estimates (magnitude and phase); B-mode and color-Doppler images; Doppler spectrograms; and local time histories of vorticity and pericardium motion. Fhf2 ^WT/Y mice had repeatable beat-to-beat cardiac function, including vortex formation during diastole, at all temperatures. In contrast, Fhf2 ^KO/Y mice displayed dyssynchronous contractile motion that disrupted normal inflow vortex formation and impaired LV filling as temperature rose. The hexplex processing approach demonstrates the ability to visualize and quantify the interplay between hemodynamic and mechanical function in a mouse model of human CVD.

A Comparison of Coherence-Based Beamforming Techniques in High-Frame-Rate Ultrasound Imaging With Multi-Line Transmission

One of the current challenges in ultrasound imaging is achieving higher frame rates, particularly in cardiac applications, where tracking the heart motion and other rapid events can provide potential valuable diagnostic information. The main drawback of ultrasound high-frame-rate strategies is that usually they partly sacrifice image quality in order to speed up the acquisition time. In particular, multi-line transmission (MLT), which consists in transmitting multiple ultrasound beams simultaneously in different directions, has been proven able to improve frame rates in echocardiography, unfortunately generating artifacts due to inter-beam crosstalk interferences. This work investigates the possibility to effectively suppress crosstalk artifacts in MLT while improving image quality by applying beamforming techniques based on backscattered signals spatial coherence. Several coherence-based algorithms (i.e., short-lag filtered-delay multiply and sum beamforming, coherence and generalized coherence factor, phase and sign coherence, and nonlinear beamforming with p th root compression) are implemented and compared, and their performance trends are evaluated when varying their design parameters. Indeed, experimental results of phantom and in vivo cardiac acquisitions demonstrate that this class of algorithms can provide significant benefits compared with delay and sum, well-suppressing artifacts (up to 48.5-dB lower crosstalk), and increasing image resolution (by up to 46.3%) and contrast (by up to 30 dB in terms of contrast ratio and 12.6% for generalized contrast-to-noise ratio) at the same time.