High-Frame-Rate Echocardiography Using Coherent Compounding With Doppler-Based Motion-Compensation

Adaptive multilevel thresholding for SVD-based clutter filtering in ultrafast transthoracic coronary flow imaging

BACKGROUND AND OBJECTIVE

The integration of ultrafast Doppler imaging with singular value decomposition clutter filtering has demonstrated notable enhancements in flow measurement and Doppler sensitivity, surpassing conventional Doppler techniques. However, in the context of transthoracic coronary flow imaging, additional challenges arise due to factors such as the utilization of unfocused diverging waves, constraints in spatial and temporal resolution for achieving deep penetration, and rapid tissue motion. These challenges pose difficulties for ultrafast Doppler imaging and singular value decomposition in determining optimal tissue-blood (TB) and blood-noise (BN) thresholds, thereby limiting their ability to deliver high-contrast Doppler images.

METHODS

This study introduces a novel local blood subspace detection method that utilizes multilevel thresholding by the valley-emphasized Otsu's method to estimate the TB and BN thresholds on a pixel-based level, operating under the assumption that the magnitude of the spatial singular vector curve of each pixel resembles the shape of a trimodal Gaussian. Upon obtaining the local TB and BN thresholds, a weighted mask (WM) is generated to assess the blood content in each pixel. To enhance the computational efficiency of this pixel-based algorithm, a dedicated tree-structure k-means clustering approach, further enhanced by noise rejection (NR) at each singular vector order, is proposed to group pixels with similar spatial singular vector curves, subsequently applying local thresholding (LT) on a cluster-based (CB) level.

RESULTS

The effectiveness of the proposed method was evaluated using an ex-vivo setup featuring a Langendorff swine heart. Comparative analysis with power Doppler images filtered using the conventional global thresholding method, which uniformly applies TB and BN thresholds to all pixels, revealed noteworthy enhancements. Specifically, our proposed CBLT+NR+WM approach demonstrated an average 10.8-dB and 11.2-dB increase in Contrast-to-Noise ratio and Contrast in suppressing the tissue signal, paralleled by an average 5-dB (Contrast-to-Noise ratio) and 9-dB (Contrast) increase in suppressing the noise signal.

CONCLUSIONS

These results clearly indicate the capability of our method to attenuate residual tissue and noise signals compared to the global thresholding method, suggesting its promising utility in challenging transthoracic settings for coronary flow measurement.

A unified framework combining coherent compounding, harmonic imaging and angular coherence for simultaneous high-quality B-mode and tissue Doppler in ultrafast echocardiography

Various methods have been proposed to enhance image quality in ultrafast ultrasound. Coherent compounding can improve image quality using multiple steered diverging transmits when motion occurring between transmits is corrected for. Harmonic imaging, a standard technique in conventional focused echocardiography, has been adapted for ultrafast imaging, reducing clutter. Coherence-based approaches have also been shown to increase contrast in clinical settings by enhancing signals from coherent echoes and reducing clutter. Herein, we introduce a simple, unified framework that combines motion-correction, harmonic imaging, and angular-coherence, showing for the first time that their benefits can be combined in real-time. Validation was conducted through in vitro testing on a spinning disk model and in vivo on 4 volunteers. In vitro results confirmed the unified framework capability to achieve high contrast in large-motion contexts up to 17 cm/s. In vivo testing highlighted proficiency in generating images of high quality during low and high tissue velocity phases of the cardiac cycle. Specifically, during ventricular filling, the unified framework increased the gCNR from 0.47 to 0.87 when compared against coherent compounding.

Curved Toroidal Row Column Addressed Transducer for 3D Ultrafast Ultrasound Imaging

3D Imaging of the human heart at high frame rate is of major interest for various clinical applications. Electronic complexity and cost has prevented the dissemination of 3D ultrafast imaging into the clinic. Row column addressed (RCA) transducers provide volumetric imaging at ultrafast frame rate by using a low electronic channel count, but current models are ill-suited for transthoracic cardiac imaging due to field-of-view limitations. In this study, we proposed a mechanically curved RCA with an aperture adapted for transthoracic cardiac imaging ( 24×16 mm2). The RCA has a toroidal curved surface of 96 elements along columns (curvature radius rC = 4.47 cm) and 64 elements along rows (curvature radius rR = 3 cm). We implemented delay and sum beamforming with an analytical calculation of the propagation of a toroidal wave which was validated using simulations (Field II). The imaging performance was evaluated on a calibrated phantom. Experimental 3D imaging was achieved up to 12 cm deep with a total angular aperture of 30° for both lateral dimensions. The Contrast-to-Noise ratio increased by 12 dB from 2 to 128 virtual sources. Then, 3D Ultrasound Localization Microscopy (ULM) was characterized in a sub-wavelength tube diameter. Finally, 3D ULM was demonstrated on a perfused ex-vivo swine heart to image the coronary microcirculation.

Deep Learning With Physics-Embedded Neural Network for Full Waveform Ultrasonic Brain Imaging

The convenience, safety, and affordability of ultrasound imaging make it a vital non-invasive diagnostic technique for examining soft tissues. However, significant differences in acoustic impedance between the skull and soft tissues hinder the successful application of traditional ultrasound for brain imaging. In this study, we propose a physics-embedded neural network with deep learning based full waveform inversion (PEN-FWI), which can achieve reliable quantitative imaging of brain tissues. The network consists of two fundamental components: forward convolutional neural network (FCNN) and inversion sub-neural network (ISNN). The FCNN explores the nonlinear mapping relationship between the brain model and the wavefield, replacing the tedious wavefield calculation process based on the finite difference method. The ISNN implements the mapping from the wavefield to the model. PEN-FWI includes three iterative steps, each embedding the F CNN into the ISNN, ultimately achieving tomography from wavefield to brain models. Simulation and laboratory tests indicate that PEN-FWI can produce high-quality imaging of the skull and soft tissues, even starting from a homogeneous water model. PEN-FWI can achieve excellent imaging of clot models with constant uniform distribution of velocity, randomly Gaussian distribution of velocity, and irregularly shaped randomly distributed velocity. Robust differentiation can also be achieved for brain slices of various tissues and skulls, resulting in high-quality imaging. The imaging time for a horizontal cross-sectional imag e of the brain is only 1.13 seconds. This algorithm can effectively promote ultrasound-based brain tomography and provide feasible solutions in other fields.

Transthoracic ultrasound localization microscopy of myocardial vasculature in patients

Myocardial microvasculature and haemodynamics are indicative of potential microvascular diseases for patients with symptoms of coronary heart disease in the absence of obstructive coronary arteries. However, imaging microvascular structure and flow within the myocardium is challenging owing to the small size of the vessels and the constant movement of the patient's heart. Here we show the feasibility of transthoracic ultrasound localization microscopy for imaging myocardial microvasculature and haemodynamics in explanted pig hearts and in patients in vivo. Through a customized data-acquisition and processing pipeline with a cardiac phased-array probe, we leveraged motion correction and tracking to reconstruct the dynamics of microcirculation. For four patients, two of whom had impaired myocardial function, we obtained super-resolution images of myocardial vascular structure and flow using data acquired within a breath hold. Myocardial ultrasound localization microscopy may facilitate the understanding of myocardial microcirculation and the management of patients with cardiac microvascular diseases.

Adaptive higher-order singular value decomposition clutter filter for ultrafast Doppler imaging of coronary flow under non-negligible tissue motion

BACKGROUND AND OBJECTIVE

With the development of advanced clutter-filtering techniques by singular value decomposition (SVD) and leveraging favorable acquisition settings such as open-chest imaging by a linear high-frequency probe and plane waves, several studies have shown the feasibility of cardiac flow measurements during the entire cardiac cycle, ranging from coronary flow to myocardial perfusion. When applying these techniques in a routine clinical setting, using transthoracic ultrasound imaging, new challenges emerge. Firstly, a smaller aperture is needed that can fit between ribs. Consequently, diverging waves are employed instead of plane waves to achieve an adequate field of view. Secondly, to ensure imaging at a larger depth, the maximum pulse repetition frequency has to be reduced. Lastly, in comparison to the open-chest scenario, tissue motion induced by the heartbeat is significantly stronger. The latter complicates substantially the distinction between clutter and blood signals.

METHODS

This study investigates a strategy to overcome these challenges by diverging wave imaging with an optimal number of tilt angles, in combination with dedicated clutter-filtering techniques. In particular, a novel, adaptive, higher-order SVD (HOSVD) clutter filter, which utilizes spatial, temporal, and angular information of the received ultrasound signals, is proposed to enhance clutter and blood separation.

RESULTS

When non-negligible tissue motion is present, using fewer tilt angles not only reduces the decorrelation between the received waveforms but also allows for collecting more temporal samples at a given ensemble duration, contributing to improved Doppler performance. The addition of a third angular dimension enables the application of HOSVD, providing greater flexibility in selecting blood separation thresholds from a 3-D tensor. This differs from the conventional threshold selection method in a 2-D spatiotemporal space using SVD. Exhaustive threshold search has shown a significant improvement in Contrast and Contrast-to-Noise ratio for Power Doppler images filtered with HOSVD compared to the SVD-based clutter filter.

CONCLUSION

With the improved settings, the obtained Power Doppler images show the feasibility of measuring coronary flow under the influence of non-negligible tissue motion in both in vitro and ex vivo.

Improved Spatiotemporal Resolution in Echocardiography Using Mixed Geometry Imaging Sequences

Cardiac ultrasound seeks to image the most dynamic environment in the body-the moving heart. Many modern ultrasound imaging techniques address the tradeoff between spatial and temporal resolution using either narrow focused beams or with broad beam, synthetic aperture (SA) sequences that have been shown to suffer from motion artifacts. Retrospective encoding for conventional ultrasound sequences (REFoCUS) unifies the processing of these various geometric sequences, but the motion sensitivity of this approach has yet to be investigated. We hypothesize that a "mixed sequence" enabled by the REFoCUS method incorporating several beam geometries may better resolve cardiac motion over a wide field of view (FOV) and at a high frame rate. First, the motion sensitivity of REFoCUS was evaluated in simulation for several focused and broad transmit profiles. Focused transmissions resolve both lateral and axial motion much more effectively than broad transmissions, with performance similar to conventional beamforming techniques. Second, a mixed sequence was designed that insonifies the full field-of-view with plane wave (PW) transmissions and key moving targets with focused transmissions. This mixed sequence was tested in simulation and in vivo and was used to image the heart as well as the liver, a low-motion control. By combining a sparse PW sequence ( n=60 ) with a small group of targeted focused transmissions ( n = 10), the anterior mitral valve leaflet (AML) at its peak observed velocity was better resolved. We believe that mixed sequences have strong potential to resolve cardiac motion at clinically relevant frame rates.

Passive Elastography for Clinical HIFU Lesion Detection

High-intensity Focused Ultrasound (HIFU) is a promising treatment modality for a wide range of pathologies including prostate cancer. However, the lack of a reliable ultrasound-based monitoring technique limits its clinical use. Ultrasound currently provides real-time HIFU planning, but its use for monitoring is usually limited to detecting the backscatter increase resulting from chaotic bubble appearance. HIFU has been shown to generate stiffening in various tissues, so elastography is an interesting lead for ablation monitoring. However, the standard techniques usually require the generation of a controlled push which can be problematic in deeper organs. Passive elastography offers a potential alternative as it uses the physiological wave field to estimate the elasticity in tissues and not an external perturbation. This technique was adapted to process B-mode images acquired with a clinical system. It was first shown to faithfully assess elasticity in calibrated phantoms. The technique was then implemented on the Focal One® clinical system to evaluate its capacity to detect HIFU lesions in vitro (CNR = 9.2 dB) showing its independence regarding the bubbles resulting from HIFU and in vivo where the physiological wave field was successfully used to detect and delineate lesions of different sizes in porcine liver. Finally, the technique was performed for the very first time in four prostate cancer patients showing strong variation in elasticity before and after HIFU treatment (average variation of 33.0 ± 16.0 % ). Passive elastography has shown evidence of its potential to monitor HIFU treatment and thus help spread its use.

On the Role of Coherent Plane Wave Compounding in Shear Wave Elasticity Imaging: The Convolution Effect and Its Implications

OBJECTIVE

The clinical applicability of shear wave elasticity imaging (SWEI) has been confounded by its appreciable inter-system variability and unsatisfactory sensitivity. While SWEI relies on plane wave imaging (PWI) to achieve real-time rendering, it has been rarely noticed that PWI can affect SWEI's performance. This work is aimed at demonstrating that the use of coherent plane wave compounding (CPWC) can be a factor causing SWEI's underperformance.

METHODS

We presented a model to formally describe the slow-time behavior of CPWC in motion tracking. This model reveals that CPWC introduces temporal convolution on the observed motion, making the motion sampling process a low-pass filter (LPF). For validation, shear waves were produced in a phantom in the same way but sampled via PWI using different compounding numbers (CN) and pulse repetition frequencies (PRF), with the obtained signals compared with the inferences drawn from our model. Similar experiments were performed to reconstruct two small targets in the phantom in order to appraise the impact of CPWC on SWEI's sensitivity.

DISCUSSION

The validation experiment shows that the measurements match well with the model inferences, which verifies the LPF nature of CPWC. The phantom study also shows that either increasing CN or decreasing PRF can cause the loss of high-frequency motion information, leading to blurred target delineation by SWEI.

CONCLUSION

The convolution effect can help understand the variability of SWEI. Researchers should beware this effect when working on SWEI standardization. Clinicians using SWEI should also be cautious because this effect makes it harder to identify small lesions.

The Effect of Spatial Velocity Gradients on Block-Matching Accuracy for Ultrasound Velocimetry

OBJECTIVE

Block matching serves as the foundation for ultrasound velocimetry techniques such as blood speckle tracking and echo-particle image velocimetry. Any spatial velocity gradients (SVGs) inside a block-matching pair will result in tracking error, due to both the finite block size and the ultrasound point-spread-function. We assess, using an in silico sinusoidal flow phantom, the effect of SVG magnitude and beam-to-flow angle on block-matching bias and precision. Secondarily we assess the effect that SVGs have on velocimetry bias when using angled plane-wave compounding.

METHODS

The magnitude and angle of SVGs were varied by adjusting the wavelength and direction of a sinusoidal flow profile. Scatterers displaced by this flow profile were used for simulating ultrasound radio frequency data at discrete time points. After beamforming, the 2-D flow field was estimated using block matching. Two imaging sequences were tested, a single plane-wave and a three-angled plane-wave.

RESULTS

Smaller sinusoidal flow wavelengths resulted in increased bias and reduced precision, revealing an inverse relationship between sinusoidal flow wavelength and tracking error, with median errors ranging from 69%-90% for the smallest flow wavelengths (highest SVGs) down to 3%-5% for the largest (lowest SVGs). The SVG angle was also important, in which lateral SVGs (with axially oriented flows) resulted in significant speckle decorrelation and high tracking errors in regions with high SVGs. Conversely, axial SVGs (laterally oriented flow) experienced higher bias in the peak velocity regions of the flow profile. Coherent compounding resulted in higher velocity errors than using a single transmission for lateral SVGs but not for axial SVGs.

CONCLUSION

The highest SVGs that could be measured with ≤10% error was when the sinusoidal flow wavelength was less than 20 times the ultrasound pulse wavelength. The clinical significance is that the high SVGs present in high kinetic energy flows, such as severe carotid stenosis and aortic regurgitation, will limit the ability to accurately quantify the velocities in these flow structures.

Ultrafast Cardiac Imaging Using Deep Learning for Speckle-Tracking Echocardiography

High-quality ultrafast ultrasound imaging is based on coherent compounding from multiple transmissions of plane waves (PW) or diverging waves (DW). However, compounding results in reduced frame rate, as well as destructive interferences from high-velocity tissue motion if motion compensation (MoCo) is not considered. While many studies have recently shown the interest of deep learning for the reconstruction of high-quality static images from PW or DW, its ability to achieve such performance while maintaining the capability of tracking cardiac motion has yet to be assessed. In this article, we addressed such issue by deploying a complex-weighted convolutional neural network (CNN) for image reconstruction and a state-of-the-art speckle-tracking method. The evaluation of this approach was first performed by designing an adapted simulation framework, which provides specific reference data, i.e., high-quality, motion artifact-free cardiac images. The obtained results showed that, while using only three DWs as input, the CNN-based approach yielded an image quality and a motion accuracy equivalent to those obtained by compounding 31 DWs free of motion artifacts. The performance was then further evaluated on nonsimulated, experimental in vitro data, using a spinning disk phantom. This experiment demonstrated that our approach yielded high-quality image reconstruction and motion estimation, under a large range of velocities and outperforms a state-of-the-art MoCo-based approach at high velocities. Our method was finally assessed on in vivo datasets and showed consistent improvement in image quality and motion estimation compared to standard compounding. This demonstrates the feasibility and effectiveness of deep learning reconstruction for ultrafast speckle-tracking echocardiography.

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.

Unsupervised deep learning-based displacement estimation for vascular elasticity imaging applications

Objective. Arterial wall stiffness can provide valuable information on the proper function of the cardiovascular system. Ultrasound elasticity imaging techniques have shown great promise as a low-cost and non-invasive tool to enable localized maps of arterial wall stiffness. Such techniques rely upon motion detection algorithms that provide arterial wall displacement estimation.Approach. In this study, we propose an unsupervised deep learning-based approach, originally proposed for image registration, in order to enable improved quality arterial wall displacement estimation at high temporal and spatial resolutions. The performance of the proposed network was assessed through phantom experiments, where various models were trained by using ultrasound RF signals, or B-mode images, as well as different loss functions.Main results. Using the mean square error (MSE) for the training process provided the highest signal-to-noise ratio when training on the B-modes images (30.36 ± 1.14 dB) and highest contrast-to-noise ratio when training on the RF signals (32.84 ± 1.89 dB). In addition, training the model on RF signals demonstrated the capability of providing accurate localized pulse wave velocity (PWV) maps, with a mean relative error (MREPWV) of 3.32 ± 1.80% and anR2 of 0.97 ± 0.03. Finally, the developed model was tested in human common carotid arteriesin vivo, providing accurate tracking of the distension pulse wave propagation, with an MREPWV= 3.86 ± 2.69% andR2 = 0.95 ± 0.03.Significance. In conclusion, a novel displacement estimation approach was presented, showing promise in improving vascular elasticity imaging techniques.

A study of wide unfocused wavefront for convex-array ultrasound imaging

Ultrafast ultrasound imaging modalities have attracted a lot of attention in the ultrasound community. It breaks the compromise between the frame rate and the region of interest by insonifying the whole medium with wide unfocused waves. Coherent compounding can be performed to enhance the image quality at a cost of frame rate. Ultrafast imaging has wide clinical applications, such as vector Doppler imaging and shear elastography. On the other hand, the use of unfocused waves is still marginal with convex-array transducers. For convex array, plane wave imaging is limited by the complicated transmission delay calculation, limited field-of-view, and inefficient coherent compounding. In this article, we study three wide unfocused wavefronts, namely, lateral virtual-source defined diverging wave imaging (latDWI), tilt virtual-source defined diverging wave imaging (tiltDWI), and Archimedean-spiral-based imaging (AMI) for convex-array imaging using the full-aperture transmission. The analytical monochromatic wave solutions to this three imaging are given. The mainlobe width and grating lobe position are given explicitly. Theoretical -6 dB beamwidth and synthetic transmit field response are studied. Simulation studies are carried on with the point targets and hypoechoic cysts. Time-of-flight formulas are given explicitly for beamforming. The conclusions are in good agreement with the theory: latDWI provides the finest lateral resolution but generates the severest axial lobe level for scatterers with large obliquities (i.e., for scatterers located at the image border) which degrades the image contrast. This effect gets worsen as the compound number increases. The tiltDWI and AMI give a very close performance on resolution and image contrast. AMI displays better contrast with a small compound number.

Ultrafast Myocardial Principal Strain Ultrasound Elastography During Stress Tests: In Vitro Validation and In Vivo Feasibility

Objective myocardial contractility assessment during stress tests aims to improve the diagnosis of myocardial ischemia. Tissue Doppler imaging (TDI) or optical flow (OF) speckle tracking echocardiography (STE) has been used to quantify myocardial contractility at rest. However, this is more challenging during stress tests due to image decorrelation at high heart rates. Moreover, stress tests imply a high frame rate which leads to a limited lateral field of view. Therefore, a large lateral field-of-view robust ultrafast myocardial regularized OF-TDI principal strain estimator has been developed for high-frame-rate echocardiography of coherently compounded transmitted diverging waves. The feasibility and accuracy of the proposed estimator were validated in vitro (using sonomicrometry as the gold standard) and in vivo stress experiments. Compared with OF strain imaging, the proposed estimator improved the accuracy of principal major and minor strains during stress tests, with an average contrast-to-noise ratio improvement of 4.4 ± 2.7 dB ( p -value < 0.01). Moreover, there was a significant correlation and a very close agreement between the proposed estimator and sonomicrometry for tested heart rates between 60 and 180 beats per minute (bpm). The averages ± standard deviations (STD) of R² and biases ± STD between them were 0.96 ± 0.04 ( p -value < 0.01) and 0.01 ± 0.03% in the axial direction, respectively; and 0.94 ± 0.02 ( p -value < 0.01) and 0.04 ± 0.06% in the lateral direction, respectively. These results suggest that the proposed estimator could be useful clinically to provide an accurate and quantitative 2-D large lateral field-of-view myocardial strain assessment at high heart rates during stress echocardiography.

A High-Performance 3-D Imaging Technique Using Simultaneous Azimuth and Elevation Compounding

A new technique for 3-D imaging with a row-column array (RCA) configuration has been developed. The technique requires an electrostrictive piezoelectric for the active substrate. While the top set of electrodes is connected to RF transmit and receive channels for conventional diverging wave imaging (DWI), the orthogonal bottom set of electrodes is connected to independently controlled variable dc bias channels. By implementing modulated bias patterns compounded across multiple pulses, fine delay control across the bottom elements can be achieved simultaneously with imaging with the top set of electrodes. This resulted in a high-quality two-way focus in both azimuth and elevation. A 20-MHz electrostrictive composite substrate was fabricated, and 64 top ×64 bottom electrodes were patterned and connected to custom beamforming and biasing electronics. The point spread functions were generated in all dimensions, and the -6 dB resolution was measured to be 93 [Formula: see text] axially, [Formula: see text] in the azimuth, and 328 [Formula: see text] in the elevation dimension. This was in good agreement with the simulated resolutions of 80, 273, and 280 [Formula: see text], respectively.

High-Frame-Rate Speckle Tracking for Echocardiographic Stress Testing

Stress echocardiography helps to diagnose cardiac diseases that cannot easily be detected or do not even manifest at rest. In clinical practice, assessment of the stress test is usually performed visually and, therefore, in a qualitative and subjective way. Although speckle tracking echocardiography (STE) has been proposed for the quantification of function during stress, its time resolution is inadequate at high heart rates. Recently, high-frame-rate (HFR) imaging approaches have been proposed together with dedicated STE algorithms capable of handling small interframe displacements. The aim of this study was to determine if HFR STE is effective in assessing strain and strain rate parameters during echocardiographic stress testing. Specifically, stress echocardiography, at four different workload intensities, was performed in 25 healthy volunteers. At each stress level, HFR images from the apical four-chamber view were recorded using the ULA-OP 256 experimental scanner. Then, the myocardium was tracked with HFR STE, and strain and strain rate biomarkers were extracted to further analyze systolic and diastolic (early and late) peaks, as well as a short-lived isovolumic relaxation peak during stress testing. The global systolic strain response was monophasic, revealing a significant (p < 0.001) increase at low stress but then reaching a plateau. In contrast, all strain rate indices linearly increased (p < 0.001) with increasing stress level. These findings are in line with those reported using tissue Doppler imaging and, thus, indicate that HFR STE can be a useful tool in assessing cardiac function during stress echocardiography.

Requirements and Hardware Limitations of High-Frame-Rate 3-D Ultrasound Imaging Systems

The spread of high frame rate and 3-D imaging techniques has raised pressing requirements for ultrasound systems. In particular, the processing power and data transfer rate requirements may be so demanding to hinder the real-time (RT) implementation of such techniques. This paper first analyzes the general requirements involved in RT ultrasound systems. Then, it identifies the main bottlenecks in the receiving section of a specific RT scanner, the ULA-OP 256, which is one of the most powerful available open scanners and may therefore be assumed as a reference. This case study has evidenced that the “star” topology, used to digitally interconnect the system’s boards, may easily saturate the data transfer bandwidth, thus impacting the achievable frame/volume rates in RT. The architecture of the digital scanner was exploited to tackle the bottlenecks by enabling a new “ring“ communication topology. Experimental 2-D and 3-D high-frame-rate imaging tests were conducted to evaluate the frame rates achievable with both interconnection modalities. It is shown that the ring topology enables up to 4400 frames/s and 510 volumes/s, with mean increments of +230% (up to +620%) compared to the star topology.

SIMUS: An open-source simulator for medical ultrasound imaging. Part II: Comparison with four simulators

BACKGROUND AND OBJECTIVE

Computational ultrasound imaging has become a well-established methodology in the ultrasound community. In the accompanying paper (part I), we described a new ultrasound simulator (SIMUS) for MATLAB, which belongs to the Matlab UltraSound Toolbox (MUST). SIMUS can generate pressure fields and radiofrequency RF signals for simulations in medical ultrasound imaging. It works in a harmonic domain and uses far-field and paraxial linear equations.

METHODS

In this article (part II), we illustrate how SIMUS compares with other ultrasound simulators (Field II, k-Wave, FOCUS, and Verasonics) for a homogeneous medium. We designed different transmit sequences (focused, planar, and diverging wavefronts) and calculated the corresponding 2-D and 3-D (with elevation focusing) RMS pressure fields.

RESULTS

SIMUS produced pressure fields similar to those of Field II, FOCUS, and k-Wave. The acoustic fields provided by the Verasonics simulator were significantly different from those of SIMUS and k-Wave, although the overall appearance remained consistent.

CONCLUSION

Our simulations tend to demonstrate that SIMUS is reliable and can be used for realistic medical ultrasound simulations.

High-Spatiotemporal-Resolution Visualization of Myocardial Strains Through Vector Doppler Estimation: A Small-Animal Study

High-frequency ultrasound (HFUS) imaging is extensively used for cardiac diseases in small animals due to its high spatial resolution. However, there is a lack of a system that can provide a 2-D high-spatiotemporal dynamic visualization of mouse myocardial strains. In this article, a dynamic HFUS (40 MHz) high-resolution strain imaging was developed through the vector Doppler imaging. Following in vitro tests using a rubber balloon phantom, in vivo experiments were performed on wild-type (WT) and myocardial infarction (MI) mice. High-resolution dynamic images of myocardial strains were obtained in the longitudinal, radial, and circumferential directions at a frame rate of 1 kHz. Global peak strain values for WT mice were -19.3% ± 1.3% (longitudinal), 31.4% ± 1.7% (radial in the long axis), -19.9% ±.8% (circumferential), and 34.4% ± 1.9% (radial in the short axis); those for the MI mice were -16.1% ±.9% (longitudinal), 26.8% ± 2.9% (radial in the long axis), -15.2% ± 2.7% (circumferential), and 21.6% ± 4.8% (radial in the short axis). These results indicate that the strains for MI mice are significantly lower than those for WT mice. Regional longitudinal strain curves in the epicardial, midcardial, and endocardial layers were measured and the peak strain values for WT mice were -22.% and -16.8% in the endocardial and epicardial layers, respectively. However, no significant difference in the layer-based values was noted for the MI mice. Regional analysis results revealed obvious myocardial strain variation in the apical anterior region in the MI mice. The experimental results demonstrate that the proposed dynamic cardiac strain imaging can be useful in high-performance imaging of small-animal cardiac diseases.

SIMUS: An open-source simulator for medical ultrasound imaging. Part I: Theory & examples

BACKGROUND AND OBJECTIVE

Computational ultrasound imaging has become a well-established methodology in the ultrasound community. Simulations of ultrasound sequences and images allow the study of innovative techniques in terms of emission strategy, beamforming, and probe design. There is a wide spectrum of software dedicated to ultrasound imaging, each having its specificities in its applications and the numerical method.

METHODS

We describe in this two-part paper a new ultrasound simulator (SIMUS) for MATLAB, which belongs to the MATLAB UltraSound Toolbox (MUST). The SIMUS software simulates acoustic pressure fields and radiofrequency RF signals for uniform linear or convex probes. SIMUS is an open-source software whose features are 1) ease of use, 2) time-harmonic analysis, 3) pedagogy. The main goal was to offer a comprehensive turnkey tool, along with a detailed theory for pedagogical and research purposes.

RESULTS

This article describes in detail the underlying linear theory of SIMUS and provides examples of simulated acoustic fields and ultrasound images. The accompanying article (part II) is devoted to the comparison of SIMUS with several software packages: Field II, k-Wave, FOCUS, and the Verasonics simulator. The MATLAB open codes for the simulator SIMUS are distributed under the terms of the GNU Lesser General Public License, and can be downloaded from https://www.biomecardio.com/MUST.

CONCLUSIONS

The simulations described in this part and in the accompanying paper (Part II) show that SIMUS can be used for realistic simulations in medical ultrasound imaging.

A Real-Time Dual-Mode High-Frequency Beamformer for Ultrafast and Focused Imaging

A firmware-based high-frequency beam- former implementing both conventional transmit focused B-mode imaging and diverging wave ultrafast (UF) imaging for Doppler overlay was developed. The beamformer can generate one transmit focused frame with four transmit focal zones (FZs), and 68 UF frames with 16 diverging waves each at a 10-Hz frame rate. The beamformer firmware stores the beamforming delays as a single bit, enabling efficient compression within the internal memory. The beamformer was characterized using a 30-MHz 64-element phased array endoscope. The hybrid system generates a 128 line by 768-pixel focused B-mode image spanning 1.2-12.6 mm axially over a ±32° range of steering angles. In addition, the system generates an UF image that is 64 lines by 384-pixels spanning 3.5-10.8 mm axially over a ±16° angle.

Signal-to-noise ratio of diverging waves in multiscattering media: Effects of signal duration and divergence angle

In this paper, SNR maximization in coded diverging waves is studied, and experimental verification of the results is presented. Complementary Golay sequences and binary phase shift keying modulation are used to code the transmitted signal. The SNR in speckle and pin targets is maximized with respect to chip signal length. The maximum SNR is obtained in diverging wave transmission when the chip signal is as short a duration as the array permits. We determined the optimum diverging wave profile to confine the transmitted ultrasound energy in the imaging sector. The optimized profile also contributes to the SNR maximization. The SNR performances of the optimized coded diverging wave and conventional single-focused phased array imaging are compared on a single frame basis. The SNR of the optimized coded diverging wave is higher than that of the conventional single-focused phased array imaging at all depths and regions.

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.

Deformability of ascending thoracic aorta aneurysms assessed using ultrafast ultrasound and a principal strain estimator: In vitro evaluation and in vivo feasibility

BACKGROUND

Noninvasive vascular strain imaging under conventional line-by-line scanning has a low frame rate and lateral resolution, and depends on the coordinate system. It is thus affected by high deformations due to image decorrelation between frames.

PURPOSE

To develop an ultrafast time-ensemble regularized tissue-Doppler optical-flow principal strain estimator for aorta deformability assessment in a long-axis view.

METHODS

This approach alleviated the impact of lateral resolution using image compounding and that of the coordinate system dependency using principal strain. Accuracy and feasibility were evaluated in two aorta-mimicking phantoms first, and then in four age-matched individuals with either a normal aorta or a pathological ascending thoracic aorta aneurysm (TAA).

RESULTS

Instantaneous aortic maximum and minimum principal strain maps and regional accumulated strains during each cardiac cycle were estimated at systolic and diastolic phases to characterize the normal aorta and TAA. In vitro, principal strain results matched sonomicrometry measurements. In vivo, a significant decrease in maximum and minimum principal strains was observed in TAA cases, whose range was respectively 7.9 ± 6.4% and 8.2 ± 2.6% smaller than in normal aortas.

CONCLUSIONS

The proposed principal strain estimator showed an ability to potentially assess TAA deformability, which may provide an individualized and reliable evaluation method for TAA rupture risk assessment. This article is protected by copyright. All rights reserved.

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.

Speckle-Tracking Echocardiography with Novel Imaging Technique of Higher Frame Rate

Background: The accuracy of speckle-tracking echocardiography (STE) depends on temporal resolution. The goal of this study was to demonstrate the feasibility of relatively high frame rate (rHi-FR) (~200 fps) for STE. Methods: In this prospective study, echocardiographic images were acquired using clinical scanners on patients with normal left ventricular systolic function using rHi-FR and conventional frame rate (Reg-FR) (~50 FPS). GLS values were evaluated on apical 4-, 2- and 3-chamber images acquired in both rHi-FR and Reg-FR. Inter-observer and intra-observer variabilities were assessed in rHi-FR and Reg-FR. Results: There were 143 echocardiograms evaluated in this study. The frame rate of rHi-FR was 190 ± 25 and Reg-FR was 50 ± 3, and the heart rate was 71 ± 13. Absolute strain values measured in rHi-FR were significantly higher than those measured in Reg-FR (all p < 0.001). Inter-observer and intra-observer correlations were strong in both rHi-FR and Reg-FR. Conclusions: We demonstrated that absolute strain values were significantly higher using rHi-FR when compared with Reg-FR. It is plausible that higher temporal resolution enabled the measurement of myocardial strain at desired time point. Further investigations are necessary to evaluate the value of rHi-FR to assess myocardial strain in the setting of tachycardia.

In Vivo Comparison of Multiline Transmission and Diverging Wave Imaging for High-Frame-Rate Speckle-Tracking Echocardiography

High-frame-rate (HFR) speckle-tracking echocardiography (STE) assesses myocardial function by quantifying motion and deformation at high temporal resolution. Among the proposed HFR techniques, multiline transmission (MLT) and diverging wave (DW) imaging have been used in this context both being characterized by specific advantages and disadvantages. Therefore, in this article, we directly contrast both approaches in an in vivo setting while operating at the same frame rate (FR). First, images were recorded at baseline (resting condition) from healthy volunteers and patients. Next, additional acquisitions during stress echocardiography were performed on volunteers. Each scan was contoured and processed by a previously proposed 2-D HFR STE algorithm based on cross correlation. Then, strain curves and their end-systolic (ES) values were extracted for all myocardial segments for further statistical analysis. The baseline acquisitions did not reveal differences in estimated strain between the acquisition modes ( ); myocardial segments ( ); or an interaction between imaging mode and depth ( ). Similarly, during stress testing, no difference ( p = 0.7 ) was observed for the two scan sequences, stress levels or an interaction sequence-stress level ( p = 0.94 ). Overall, our findings show that MLT and DW compoundings give comparable HFR STE strain values and that the choice for using one method or the other may thus rather be based on other factors, for example, system requirements or computational cost.

CNN-Based Ultrasound Image Reconstruction for Ultrafast Displacement Tracking

Thanks to its capability of acquiring full-view frames at multiple kilohertz, ultrafast ultrasound imaging unlocked the analysis of rapidly changing physical phenomena in the human body, with pioneering applications such as ultrasensitive flow imaging in the cardiovascular system or shear-wave elastography. The accuracy achievable with these motion estimation techniques is strongly contingent upon two contradictory requirements: a high quality of consecutive frames and a high frame rate. Indeed, the image quality can usually be improved by increasing the number of steered ultrafast acquisitions, but at the expense of a reduced frame rate and possible motion artifacts. To achieve accurate motion estimation at uncompromised frame rates and immune to motion artifacts, the proposed approach relies on single ultrafast acquisitions to reconstruct high-quality frames and on only two consecutive frames to obtain 2-D displacement estimates. To this end, we deployed a convolutional neural network-based image reconstruction method combined with a speckle tracking algorithm based on cross-correlation. Numerical and in vivo experiments, conducted in the context of plane-wave imaging, demonstrate that the proposed approach is capable of estimating displacements in regions where the presence of side lobe and grating lobe artifacts prevents any displacement estimation with a state-of-the-art technique that relies on conventional delay-and-sum beamforming. The proposed approach may therefore unlock the full potential of ultrafast ultrasound, in applications such as ultrasensitive cardiovascular motion and flow analysis or shear-wave elastography.

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.

Reconstruction for Diverging-Wave Imaging Using Deep Convolutional Neural Networks

In recent years, diverging wave (DW) ultrasound imaging has become a very promising methodology for cardiovascular imaging due to its high temporal resolution. However, if they are limited in number, DW transmits provide lower image quality compared with classical focused schemes. A conventional reconstruction approach consists in summing series of ultrasound signals coherently, at the expense of frame rate, data volume, and computation time. To deal with this limitation, we propose a convolutional neural network (CNN) architecture, Inception for DW Network (IDNet), for high-quality reconstruction of DW ultrasound images using a small number of transmissions. In order to cope with the specificities induced by the sectorial geometry associated with DW imaging, we adopted the inception model composed of the concatenation of multiscale convolution kernels. Incorporating inception modules aims at capturing different image features with multiscale receptive fields. A mapping between low-quality images and corresponding high-quality compounded reconstruction was learned by training the network using in vitro and in vivo samples. The performance of the proposed approach was evaluated in terms of contrast ratio (CR), contrast-to-noise ratio (CNR), and lateral resolution (LR), and compared with standard compounding method and conventional CNN methods. The results demonstrated that our method could produce high-quality images using only 3 DWs, yielding an image quality equivalent to that obtained with compounding of 31 DWs and outperforming more conventional CNN architectures in terms of complexity, inference time, and image quality.

A Pilot Study on Convolutional Neural Networks for Motion Estimation From Ultrasound Images

In recent years, deep learning (DL) has been successfully applied to the analysis and processing of ultrasound images. To date, most of this research has focused on segmentation and view recognition. This article benchmarks different convolutional neural network algorithms for motion estimation in ultrasound imaging. We evaluated and compared several networks derived from FlowNet2, one of the most efficient architectures in computer vision. The networks were tested with and without transfer learning, and the best configuration was compared against the particle imaging velocimetry method, a popular state-of-the-art block-matching algorithm. Rotations are known to be difficult to track from ultrasound images due to a significant speckle decorrelation. We thus focused on the images of rotating disks, which could be tracked through speckle features only. Our database consisted of synthetic and in vitro B-mode images after log compression and covered a large range of rotational speeds. One of the FlowNet2 subnetworks, FlowNet2SD, produced competitive results with a motion field error smaller than 1 pixel on real data after transfer learning based on the simulated data. These errors remain small for a large velocity range without the need for hyperparameter tuning, which indicates the high potential and adaptability of DL solutions to motion estimation in ultrasound imaging.

Transthoracic echocardiography: from guidelines for humans to cardiac ultrasound of the heart in rats

Ultrasound examination of the heart is a cornerstone of clinical evaluation of patients with established or suspected cardiovascular conditions. Advancements in ultrasound imaging technology have brought transthoracic echocardiography to preclinical murine models of cardiovascular diseases. The translational potential of cardiac ultrasound is critically important in rat models of myocardial infarction and ischemia-reperfusion injury, congestive heart failure, arterial hypertension, cardiac hypertrophy, pulmonary hypertension, right heart failure, Takotsubo cardiomyopathy, hypertrophic and dilated cardiomyopathies, developmental disorders, and metabolic syndrome. Modern echocardiographic machines capable of high-frame-rate image acquisition and fitted with high-frequency transducers allow for cardiac ultrasound in rats that yields most of the echocardiographic measurements and indices recommended by international guidelines for cardiac ultrasound in human patients. Among them are dimensions of cardiac chambers and walls, indices of systolic and diastolic cardiac function, and valvular function. In addition, measurements of cardiac dimensions and ejection fraction can be significantly improved by intravenous administration of ultrasound enhancing agents (UEAs). In this article we discuss echocardiography in rats, describe a technique for minimally invasive intravenous administration of UEAs via the saphenous vein and present a step-by-step approach to cardiac ultrasound in rats.

In Vivo Evaluation of Plane Wave Imaging for Abdominal Ultrasonography

Although plane wave imaging (PWI) has been extensively employed for ultrafast ultrasound imaging, its potential for sectorial B-mode imaging with a convex array transducer has not yet been widely recognized. Recently, we reported an optimized PWI approach for sector scanning that exploits the dynamic transmit focusing capability. In this paper, we first report the clinical applicability of the optimized PWI for abdominal ultrasonography by in vivo image and video evaluations and compare it with conventional focusing (CF) and diverging wave imaging (DWI), which is another dynamic transmit focusing technique generally used for sectorial imaging. In vivo images and videos of the liver, kidney, and gallbladder were obtained from 30 healthy volunteers using PWI, DWI, and CF. Three radiologists assessed the phantom images, 156 in vivo images, and 66 in vivo videos. PWI showed significantly enhanced (p < 0.05) spatial resolution, contrast, and noise and artifact reduction, and a 4-fold higher acquisition rate compared to CF and provided similar performances compared to DWI. Because the computations required for PWI are considerably lower than that for DWI, PWI may represent a promising technique for sectorial imaging in abdominal ultrasonography that provides better image quality and eliminates the need for focal depth adjustment.

Ultrafast Phased-Array Imaging Using Sparse Orthogonal Diverging Waves

We present a new transmit pulse encoding scheme for ultrafast phased-array imaging called sparse orthogonal diverging wave imaging (SODWI). In SODWI, Hadamard encoding is used to selectively invert transmit pulse phases beamformed with a diverging wave delay profile. This approach has the advantage of delivering energy to a much wider field of view than conventional Hadamard-encoded multielement synthetic transmit aperture (HMSTA), making it more suitable for phased-array applications. With SODWI, we use a synthetic transmit element delay insertion (STEDI) approach which produces significant improvements in resolution, grating lobe level, and signal-to-noise ratio (SNR) over HMSTA. We also show how in SODWI a subset of the Hadamard codes can be sparsely selected to increase the imaging frame rate at the expense of image quality. SODWI is then compared with a variety of beamforming schemes for phased-array applications, including HMSTA, STEDI-HMSTA, diverging wave imaging (DWI), synthetic aperture (SA), and focused imaging. We present the results by implementing this technique on a 64-channel custom beamforming platform with a 40-MHz phased array. When a full set of codes is used, SODWI outperforms focused imaging contrast and SNR by 2.7 and 1.8 dB in addition to an 8× increase in frame rate, respectively.

A Novel 2-D Speckle Tracking Method for High-Frame-Rate Echocardiography

Speckle tracking echocardiography (STE) is a clinical tool to noninvasively assess regional myocardial function through the quantification of regional motion and deformation. Even if the time resolution of STE can be improved by high-frame-rate (HFR) imaging, dedicated HFR STE algorithms have to be developed to detect very small interframe motions. Therefore, in this article, we propose a novel 2-D STE method, purposely developed for HFR echocardiography. The 2-D motion estimator consists of a two-step algorithm based on the 1-D cross correlations to separately estimate the axial and lateral displacements. The method was first optimized and validated on simulated data giving an accuracy of ~3.3% and ~10.5% for the axial and lateral estimates, respectively. Then, it was preliminarily tested in vivo on ten healthy volunteers showing its clinical applicability and feasibility. Moreover, the extracted clinical markers were in the same range as those reported in the literature. Also, the estimated peak global longitudinal strain was compared with that measured with a clinical scanner showing good correlation and negligible differences (-20.94% versus -20.31%, p -value = 0.44). In conclusion, a novel algorithm for STE was developed: the radio frequency (RF) signals were preferred for the axial motion estimation, while envelope data were preferred for the lateral motion. Furthermore, using 2-D kernels, even for 1-D cross correlation, makes the method less sensitive to noise.

Contractile Fronts In The Interventricular Septum: A Case For High Frame Rate Echocardiographic Imaging

The real time high frame rate (HFR) 2-dimensional ultrasound system, T5, at Duke University is capable of imaging at up to 1000 images per second for adult cardiac imaging. A method for detecting and visualizing the mechanical contraction fronts using HFR echocardioagraphy-derived Strain Rate Image (SRI) was described in 26 patients. The Tissue Shortening Onset front durations for echocardiographic normal patients were significantly shorter than conduction disorder patients with left bundle branch block (LBBB) with intrinsic conduction and conduction disorder patients without LBBB (non-LBBB) with simulated LBBB (sLBBB). Echocardiographic normal patients had significantly higher correlation coefficients between their SRIs and spatially inverted versions of themselves compared to non-LBBB patients with intrinsic conduction and sLBBB. In conclusion, SRIs could spatially resolve contractile event fronts in patients.

In vivo Ultrafast Quantitative Ultrasound and Shear Wave Elastography Imaging on Farm-Raised Duck Livers during Force Feeding

Shear wave elastography (speed and dispersion), local attenuation coefficient slope and homodyned-K parametric imaging were used for liver steatosis grading. These ultrasound biomarkers rely on physical interactions between shear and compression waves with tissues at both macroscopic and microscopic scales. These techniques were applied in a context not yet studied with ultrasound imaging, that is, monitoring steatosis of force-fed duck livers from pre-force-fed to foie gras stages. Each estimated feature presented a statistically significant trend along the feeding process (p values <10^-3). However, whereas a monotonic increase in the shear wave speed was observed along the process, most quantitative ultrasound features exhibited an absolute maximum value halfway through the process. As the liver fat fraction in foie gras is much higher than that seen clinically, we hypothesized that a change in the ultrasound scattering regime is encountered for high-fat fractions, and consequently, care has to be taken when applying ultrasound biomarkers to grading of severe states of steatosis.

High-Frame-Rate Color Doppler Echocardiography: A Quantitative Comparison of Different Approaches

Ultrasound color Doppler imaging (CDI) provides a map of the axial blood flow velocities in a 2-D/3-D region of interest. While CDI is clinically effective for a qualitative analysis of abnormal blood flows, e.g., for valvular disease in cardiology, it is in limited use for quantitative measures, mainly hampered by low frame rate and measurement bias. These limitations can be reduced by different approaches toward high-frame-rate (HFR) imaging at the expense of reduced image quality and penetration depth. The aim of this study was to compare the impact of different HFR sequences on CDI quantitatively. Different cardiac scan sequences, including diverging waves and multiline transmission, were designed, implemented on a research system, and compared in terms of patient safety parameters, image quality, and penetration depth. Furthermore, in vivo images were acquired and compared for healthy volunteers. Results showed that the HFR techniques spread artifacts on larger areas than the standard single-line scans (> +50%). In addition, due to patient safety limitations, they reduce the penetration depth up to -5 cm. On the other hand, the HFR techniques provide comparable velocity estimates (relative difference <6%) and enhance the time resolution of the color Doppler images, achieving frame rates up to 625 Hz in continuous acquisition.

A novel transcranial ultrasound imaging method with diverging wave transmission and deep learning approach

Real time brain transcranial ultrasound imaging is extremely intriguing because of its numerous applications. However, the skull causes phase distortion and amplitude attenuation of ultrasound signals due to its density: the speed of sound is significantly different in bone tissue than in soft tissue. In this study, we propose an ultrafast transcranial ultrasound imaging technique with diverging wave (DW) transmission and a deep learning approach to achieve large field-of-view with high resolution and real time brain ultrasound imaging. DW transmission provides a frame rate of several kiloHz and a large field of view that is suitable for human brain imaging via a small acoustic window. However, it suffers from poor image quality because the diverging waves are all unfocused. Here, we adopted adaptive beamforming algorithms to improve both the image contrast and the lateral resolution. Both simulated and in situ experiments with a human skull resulted in significant image improvements. However, the skull still introduces a wavefront offset and distortion, which degrades the image quality even when adaptive beamforming methods are used. Thus, we also employed a U-Net neural network to detect the contour and position of the skull directly from the acquired RF signal matrix. This approach avoids the need for beamforming, image reconstruction, and image segmentation, making it more suitable for clinical use.

A novel transcranial ultrasound imaging method with diverging wave

Real time transcranial ultrasound imaging of brain can be extremely intriguing because of its numerous applications. In this study, we proposed an ultrafast transcranial ultrasound imaging technique with diverging wave (DW) transmission, which has been a promising technique to image moving objects, such as complex blood flow field and transient elastography. However, diverging waves are all unfocused waves, which makes their image quality, especially the lateral resolution and contrast, has not yet been satisfactory. Here we tried to apply the adaptive beamforming algorithms to improve both the image contrast and the lateral resolution. Simulation and phantom experiments proved that our methods can significantly improve the DW image quality. Finally, transcranial ultrasound imaging collected through temporal bone were presented and analyzed. The ultrasound frequency used in this study ranges from 2 MHz to 4 MHz, centered at 2.8 MHz. Since the wavefront was offset and distorted after passing through temporal bone, the image quality will be slightly degraded. Even then, it was demonstrated that these adaptive algorithms can significantly improve the transcranial image quality, especially the image contrast.

High-Frame-Rate Tri-Plane Echocardiography With Spiral Arrays: From Simulation to Real-Time Implementation

Major cardiovascular diseases (CVDs) are associated with (regional) dysfunction of the left ventricle. Despite the 3-D nature of the heart and its dynamics, the assessment of myocardial function is still largely based on 2-D ultrasound imaging, thereby making diagnosis heavily susceptible to the operator's expertise. Unfortunately, to date, 3-D echocardiography cannot provide adequate spatiotemporal resolution in real-time. Hence, tri-plane imaging has been introduced as a compromise between 2-D and true volumetric ultrasound imaging. However, tri-plane imaging typically requires high-end ultrasound systems equipped with fully populated matrix array probes embedded with expensive and little flexible electronics for two-stage beamforming. This article presents an advanced ultrasound system for real-time, high frame rate (HFR), and tri-plane echocardiography based on low element count sparse arrays, i.e., the so-called spiral arrays. The system was simulated, experimentally validated, and implemented for real-time operation on the ULA-OP 256 system. Five different array configurations were tested together with four different scan sequences, including multi-line and planar diverging wave transmission. In particular, the former can be exploited to achieve, in tri-plane imaging, the same temporal resolution currently used in clinical 2-D echocardiography, at the expenses of contrast (-3.5 dB) and signal-to-noise ratio (SNR) (-8.7 dB). On the other hand, the transmission of planar diverging waves boosts the frame rate up to 250 Hz, but further compromises contrast (-10.5 dB), SNR (-9.7 dB), and lateral resolution (+46%). In conclusion, despite an unavoidable loss in image quality and sensitivity due to the limited number of elements, HFR tri-plane imaging with spiral arrays is shown to be feasible in real-time and may enable real-time functional analysis of all left ventricular segments of the heart.

Comparison Between Multiline Transmission and Diverging Wave Imaging: Assessment of Image Quality and Motion Estimation Accuracy

High frame rate imaging is particularly important in echocardiography for better assessment of the cardiac function. Several studies showed that diverging wave imaging (DWI) and multiline transmission (MLT) are promising methods for achieving a high temporal resolution. The aim of this study was to compare MLT and compounded motion compensation (MoCo) DWI for the same transmitted power, same frame rates [image quality and speckle tracking echocardiography (STE) assessment], and same packet size [tissue Doppler imaging (TDI) assessment]. Our results on static images showed that MLT outperforms DW in terms of resolution (by 30% on average). However, in terms of contrast, MLT outperforms DW only for the depth of 11 cm (by 40% on average), the result being reversed at a depth of 4 cm (by 27% on average). In vitro results on a spinning phantom at nine different velocities showed that similar STE axial errors (up to 2.3% difference in median errors and up to 2.1% difference in the interquartile ranges) are obtained with both ultrafast methods. On the other hand, the median lateral STE estimates were up to 13% more accurate with DW than with MLT. On the contrary, the accuracy of TDI was only up to ~3% better with MLT, but the achievable DW Doppler frame rate was up to 20 times higher. However, our overall results showed that the choice of one method relative to the other is therefore dependent on the application. More precisely, in terms of image quality, DW is more suitable for imaging structures at low depths, while MLT can provide an improved image quality at the focal point that can be placed at higher depths. In terms of motion estimation, DW is more suitable for color Doppler-related applications, while MLT could be used to estimate velocities along selected lines of the image.

Wide Field-of-View Ultrafast Curved Array Imaging Using Diverging Waves

Ultrafast ultrasound imaging provides great opportunities for very high frame rate applications, such as shear wave elastography and microvascular imaging. However, ultrafast imaging with curved array transducers remains challenging in terms of element directivity and a limited field-of-view (FOV) for a fully synthetic area. In this paper, a wide FOV ultrafast curved array imaging method based on diverging wave transmissions is presented for high frame rate abdominal ultrasound applications. For this method, a theoretical model for a diverging wave solution based on a virtual point source originating from a circular line is proposed, and the FOV and element directivity are analyzed by this model. Furthermore, an integrated model for plane wave and diverging wave imaging along the location of the virtual point source is derived. The proposed method was evaluated with simulation, phantom, and in vivo studies. In the simulation and phantom studies, the image quality (i.e., spatial resolution, cystic resolution, and contrast-to-noise ratio), and effective FOV were assessed. For the in vivo study, a preliminary result from abdominal microvascular imaging, where diverging wave excitation was utilized to depict the vasculature, was also presented. In the renal cortex microvessels, the diverging wave imaging yielded a higher signal-to-clutter ratio value than the plane wave imaging, i.e., 6.35 vs. 4.26 dB, due to the wider synthetic field. These studies demonstrated that the proposed ultrafast curved array imaging technique based on diverging wave excitation allowed for an extended FOV with high spatiotemporal resolution.

Imaging Heart Dynamics With Ultrafast Cascaded-Wave Ultrasound

The heart is an organ with highly dynamic complexity, including cyclic fast electrical activation, muscle kinematics, and blood dynamics. Although ultrafast cardiac imaging techniques based on pulsed-wave ultrasound (PUS) have rapidly emerged to permit mapping of heart dynamics, they suffer from limited sonographic signal-to-noise ratio (SNR) and penetration due to insufficient energy delivery and inevitable attenuation through the chest wall. We hereby propose ultrafast cascaded-wave ultrasound (uCUS) imaging to depict heart dynamics in higher SNR and larger penetration than conventional ultrafast PUS. To solve the known tradeoff between the length of transmitted ultrasound signals and spatial resolution while achieving ultrafast frame rates (>1000 Hz), we develop a cascaded synthetic aperture (CaSA) imaging method. In CaSA, an array probe is divided into subapertures; each subaperture transmits a train of diverging waves. These diverging waves are weighted in both the aperture (i.e., spatial) and range (i.e., temporal) directions with a coding matrix containing only +1 and -1 polarity coefficients. A corresponding spatiotemporal decoding matrix is designed to recover backscattered signals. The decoded signals are thereafter beamformed and coherently compounded to obtain one high-SNR beamformed image frame. For CaSA with M subapertures and N cascaded diverging waves, sonographic SNR is increased by 10× log ₁₀ (N ×M) (dB) compared with conventional synthetic aperture (SA) imaging. The proposed uCUS with CaSA was evaluated with conventional SA and Hadamard-encoded SA (H-SA) methods in a calibration phantom for B-mode image quality and an in vivo human heart in a transthoracic setting for the quality assessment of anatomical, myocardial motion, and chamber blood power Doppler images. Our results demonstrated that the proposed uCUS with CaSA (4 subapertures, 32 cascaded waves) improved SNR (+20.46 dB versus SA, +14.83 dB versus H-SA) and contrast ratio (+8.44 dB versus SA, +7.81 dB versus H-SA) with comparable spatial resolutions to and at the same frame rates as benchmarks.

Quantitative Parameters of High-Frame-Rate Strain in Patients with Echocardiographically Normal Function

Recently, we developed a high-frame-rate echocardiographic imaging system capable of acquiring images at rates up to 2500 per second. High imaging rates were used to quantify longitudinal strain parameters in patients with echocardiographically normal function. These data can serve as a baseline for comparing strain parameters in disease states. The derived timing data also reveal the propagation of mechanical events in the left ventricle throughout the cardiac cycle. High-frame-rate echocardiographic images were acquired from 17 patients in the apical four-chamber view using Duke University's phased array ultrasound system, T5. B-Mode images were acquired at 500-1000 images per second by employing 16:1 or 32:1 parallel processing in receive, a scan depth ≤14 cm and an 80° field of view with a 3.5-MegaHertZ (MHz), 96-element linear array. The images were analyzed using a speckle tracking algorithm tailored for high-frame-rate echocardiographic images developed at Aalborg and Duke University. Four specific mechanical events were defined using strain curves from six regions along the myocardial contour of the left ventricle. The strain curves measure the local deformation events of the myocardium and are independent of the overall cardiac motion. We observed statistically significant differences in the temporal sequence among different myocardial segments for the first mechanical event described, myocardial tissue shortening onset (p < 0.01). We found that the spatial origin of tissue shortening was located near the middle of the interventricular septum in patients with echocardiographically normal function. The quantitative parameters defined here, based on high-speed strain measurements in patients with echocardiographically normal function, can serve as a means of assessing degree of contractile abnormality in the myocardium and enable the identification of contraction propagation. The relative timing pattern among specific events with respect to the Q wave may become an important new metric in assessing cardiac function and may, in turn, improve diagnosis and prognosis.

Live Ultrasound Color-Encoded Speckle Imaging Platform for Real-Time Complex Flow Visualization In Vivo

Complex flow patterns are prevalent in the vasculature, but they are difficult to image noninvasively in real time. This paper presents the first real-time scanning platform for a high-frame-rate ultrasound technique called color-encoded speckle imaging (CESI) and its use in visualizing arterial flow dynamics in vivo. CESI works by simultaneously rendering flow speckles and color-coded flow velocity estimates on a time-resolved basis. Its live implementation was achieved by integrating a 192-channel programmable ultrasound front-end module, a 4.8-GB/s capacity data streaming link, and a series of computing kernels implemented on the graphical processing unit (GPU) for beamforming and Doppler processing. A slow-motion replay mode was also included to offer coherent visualization of CESI frames acquired at high frame rate [3000 frames per second (fps) in our experiments]. The live CESI scanning platform was found to be effective in facilitating real-time image guidance (at least 20 fps for live video display with 55-fps GPU processing throughout). In vivo pilot trials also showed that live CESI, when running in replay mode, can temporally resolve triphasic flow at the brachial bifurcation and can reveal flow dynamics in the brachial vein during a fist-clenching maneuver. Overall, live CESI has potential for use in routine investigations in vivo that seek to identify complex flow dynamics in real time and relate these dynamics to vascular physiology.

Coupling Myocardium and Vortex Dynamics in Diverging-Wave Echocardiography

Echocardiography is widely used to provide critical left ventricular indices describing myocardial motion and blood inflow velocity. Tissue motion and blood flow are strongly connected and interdependent in the ventricle. During cardiac relaxation, rapid filling leads to the formation of a vortical blood flow pattern. In this paper, we introduce a high-frame-rate method to track vortex dynamics alongside myocardium motion, in a single heartbeat. Cardiac triplex imaging (B-mode + tissue Doppler + color Doppler) was obtained by insonating the left ventricle with diverging waves. We used coherent compounding with integrated motion compensation to obtain high-quality B-mode images. Tissue Doppler was retrieved and the septal and lateral velocities of the mitral annulus were deduced. A rate of ~80 triplex images/s was obtained. Vortex dynamics was analyzed by Doppler vortography. Blood vortex signature maps were used to track the vortex and compute core vorticities. The sequence was implemented in a Verasonics scanner with a 2.5-MHz phased array and tested in vivo in 12 healthy volunteers. Two main peaks appeared on the vorticity curves. These peaks were synchronized with the mitral inflow velocities with a small delay. We observed a relationship between the tissue and vortex waveforms, though also with a delay, which denoted the lag between the wall and the flow motion. Clinical diastolic indices combining basal and mitral inflow velocities (E/A ratio and E/ e' ratio) were determined and compared with those measured using a conventional ultrasound scanner; a good correlation was obtained ( r² = 0.96 ). High-frame-rate Doppler echocardiography enabled us to retrieve time-resolved dynamics of the myocardium and vortex flow within the same cardiac cycle. Coupling wall-flow analysis could be of clinical relevance for early diagnosis of filling impairment.

Natural Shear Wave Imaging in the Human Heart: Normal Values, Feasibility, and Reproducibility

Left ventricular myocardial stiffness could offer superior quantification of cardiac systolic and diastolic function when compared to the current diagnostic tools. Shear wave elastography in combination with acoustic radiation force has been widely proposed to noninvasively assess tissue stiffness. Interestingly, shear waves can also result from intrinsic cardiac mechanical events (e.g., closure of valves) without the need for external excitation. However, it remains unknown whether these natural shear waves always occur, how reproducible they can be detected and what the normal range of shear wave propagation speed is. The present study, therefore, aimed at establishing the feasibility of detecting shear waves created after mitral valve closure (MVC) and aortic valve closure (AVC), the variability of the measurements, and at reporting the normal values of propagation velocity. Hereto, a group of 30 healthy volunteers was scanned with high-frame rate imaging (>1000 Hz) using an experimental ultrasound system transmitting a diverging wave sequence. Tissue Doppler velocity and acceleration were used to create septal color M-modes, on which the shear waves were tracked and their velocities measured. Overall, the methodology was capable of detecting the transient vibrations that spread throughout the intraventricular septum in response to the closure of the cardiac valves in 92% of the recordings. Reference velocities of 3.2±0.6 m/s at MVC and 3.5±0.6 m/s at AVC were obtained. Moreover, in order to show the diagnostic potential of this approach, two patients (one with cardiac amyloidosis and one undergoing a dobutamine stress echocardiography) were scanned with the same protocol and showed markedly higher propagation speeds: the former presented velocities of 6.6 and 5.6 m/s; the latter revealed normal propagation velocities at baseline, and largely increased during the dobutamine infusion (>15 m/s). Both cases showed values consistent with the expected changes in stiffness and cardiac loading conditions.

Assessment of Mechanical Properties of Tissue in Breast Cancer-Related Lymphedema Using Ultrasound Elastography

Breast cancer-related lymphedema is a consequence of a malfunctioning lymphatic drainage system resulting from surgery or some other form of treatment. In the initial stages, minor and reversible increases in the fluid volume of the arm are evident. As the stages progress over time, the underlying pathophysiology dramatically changes with an irreversible increase in arm volume most likely due to a chronic local inflammation leading to adipose tissue hypertrophy and fibrosis. Clinicians have subjective ways to stage the degree and severity such as the pitting test which entails manually comparing the elasticity of the affected and unaffected arms. Several imaging modalities can be used but ultrasound appears to be the most preferred because it is affordable, safe, and portable. Unfortunately, ultrasonography is not typically used for staging lymphedema, because the appearance of the affected and unaffected arms is similar in B-mode ultrasound images. However, novel ultrasound techniques have emerged, such as elastography, which may be able to identify changes in mechanical properties of the tissue related to detection and staging of lymphedema. This paper presents a novel technique to compare the mechanical properties of the affected and unaffected arms using quasi-static ultrasound elastography to provide an objective alternative to the current subjective assessment. Elastography is based on time delay estimation (TDE) from ultrasound images to infer displacement and mechanical properties of the tissue. We further introduce a novel method for TDE by incorporating higher order derivatives of the ultrasound data into a cost function and propose a novel optimization approach to efficiently minimize the cost function. This method works reliably with our challenging patient data. We collected radio frequency ultrasound data from both arms of seven patients with stage 2 lymphedema, at six different locations in each arm. The ratio of strain in skin, subcutaneous fat, and skeletal muscle divided by strain in the standoff gel pad was calculated in the unaffected and affected arms. The p -values using a Wilcoxon sign-rank test for the skin, subcutaneous fat, and skeletal muscle were 1.24×10^-5 , 1.77×10^-8 , and 8.11×10^-7 respectively, showing differences between the unaffected and affected arms with a very high level of significance.