Mechanical Wave Velocities in Left Ventricular Walls in Healthy Subjects and Patients With Aortic Stenosis.

BACKGROUND: Mechanical wave velocity (MWV) measurement is a promising method for evaluating myocardial stiffness, because these velocities are higher in patients with myocardial disease. OBJECTIVES: Using high frame rate echocardiography and a novel method for detection of myocardial mechanical waves, this study aimed to estimate the MWVs for different left ventricular walls and events in healthy subjects and patients with aortic stenosis (AS). Feasibility and reproducibility were evaluated. METHODS: This study included 63 healthy subjects and 13 patients with severe AS. All participants underwent echocardiographic examination including 2-dimensional high frame rate recordings using a clinical scanner. Cardiac magnetic resonance was performed in 42 subjects. The authors estimated the MWVs at atrial kick and aortic valve closure in different left ventricular walls using the clutter filter wave imaging method. RESULTS: Mechanical wave imaging in healthy subjects demonstrated the highest feasibility for the atrial kick wave reaching >93% for all 4 examined left ventricular walls. The MWVs were higher for the inferolateral and anterolateral walls (2.2 and 2.6 m/s) compared with inferoseptal and anteroseptal walls (1.3 and 1.6 m/s) (P < 0.05) among healthy subjects. The septal MWVs at aortic valve closure were significantly higher for patients with severe AS than for healthy subjects. CONCLUSIONS: MWV estimation during atrial kick is feasible and demonstrates higher velocities in the lateral walls, compared with septal walls. The authors propose indicators for quality assessment of the mechanical wave slope as an aid for achieving consistent measurements. The discrimination between healthy subjects and patients with AS was best for the aortic valve closure mechanical waves. (Ultrasonic Markers for Myocardial Fibrosis and Prognosis in Aortic Stenosis; NCT03422770).

Single-Sided Ultrasound Imaging of the Bone Cortex: Anatomy, Tissue Characterization and Blood Flow.

In this chapter, we first review the reasons why conventional ultrasonography fails to image the interior of bones. Next we show our recent work on imaging a cortical bone layer with ultrasound. Revealing the shape of the cortex of a bone, in particular its thickness, is of interest for evaluating bone strength. In addition we describe how the process of reconstructing a truthful image of the bone cortex includes the estimation of ultrasound wave-speed in cortical bone tissue. Cortical bone exhibits elastic anisotropy, which causes anisotropy of ultrasound wave-speed as well. Therefore a faithful and high-quality picture of the bone cortex is obtained if wave-speed anisotropy is taken into account during image reconstruction. Capitalizing on prior knowledge on the elastic anisotropy of cortical bone, a procedure for estimating wave-speed and its anisotropy is described. It is based on the measurement of a head-wave velocity and an autofocus approach. The latter relies on the fact that the reconstructed ultrasound image shows optimal quality if the wave-speed model is correct. In order to achieve real-time imaging of a bone cortex, image reconstruction is performed with a delay-and-sum algorithm. Finally, we report recent advances in the measurement of blood flow in cortical bone.

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.

Revealing Intraosseous Blood Flow in the Human Tibia With Ultrasound.

Intraosseous blood circulation is thought to have a critical role in bone growth and remodeling, fracture healing, and bone disorders. However, it is rarely considered in clinical practice because of the absence of a suitable noninvasive in vivo measurement technique. In this work, we assessed blood perfusion in tibial cortical bone simultaneously with blood flow in the superficial femoral artery with ultrasound imaging in five healthy volunteers. After suppression of stationary signal with singular-value-decomposition, pulsatile blood flow in cortical bone tissue is revealed, following the heart rate measured in the femoral artery. Using a method combining transverse oscillations and phase-based motion estimation, 2D vector flow was obtained in the cortex of the tibia. After spatial averaging over the cortex, the peak blood velocity along the long axis of the tibia was measured at four times larger than the peak blood velocity across the bone cortex. This suggests that blood flow in central (Haversian) canals is larger than in perforating (Volkmann's) canals, as expected from the intracortical vascular organization in humans. The peak blood velocity indicates a flow from the endosteum to the periosteum and from the heart to the foot for all subjects. Because aging and the development of bone disorders are thought to modify the direction and velocity of intracortical blood flow, their quantification is crucial. This work reports for the first time an in vivo quantification of the direction and velocity of blood flow in human cortical bone. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

3D Myocardial Mechanical Wave Measurements: Toward In Vivo 3D Myocardial Elasticity Mapping.

OBJECTIVES: This study aimed to investigate the potential of a novel 3-dimensional (3D) mechanical wave velocity mapping technique, based on the natural mechanical waves produced by the heart itself, to approach a noninvasive 3D stiffness mapping of the left ventricle. BACKGROUND: Myocardial fibrosis is recognized as a pathophysiological substrate of major cardiovascular disorders such as cardiomyopathies and valvular heart disease. As fibrosis leads to increased myocardial stiffness, ultrasound elastography measurements could provide important clinical information. METHODS: A 3D high frame rate imaging sequence was implemented on a high-end clinical ultrasound scanner to achieve 820 volumes/s when gating over 4 consecutive cardiac cycles. Five healthy volunteers and 10 patients with various degrees of aortic stenosis were included to evaluate feasibility and reproducibility. Mechanical waves were detected using the novel Clutter Filter Wave Imaging approach, shown to be highly sensitive to the weak tissue displacements caused by natural mechanical waves. RESULTS: 3D spatiotemporal maps of mechanical wave velocities were produced for all subjects. Only the specific mechanical wave at atrial contraction provided a full 3D coverage of the left ventricle (LV). The average atrial kick propagation velocity was 1.6 ± 0.2 m/s in healthy volunteers and 2.8 ± 0.8 m/s in patients (p = 0.0016). A high correlation was found between mechanical wave velocity and age (R2 = 0.88, healthy group), septal wall thickness (R2 = 0.73, entire group), and peak jet velocity across the aortic valve (R2 = 0.70). For 3 of the patients, the higher mechanical wave velocity coexisted with the presence of late gadolinium enhancement on cardiac magnetic resonance. CONCLUSIONS: In this study, 3D LV mechanical wave velocities were visualized and measured in healthy volunteers and patients with aortic stenosis. The proposed imaging sequence and measurement technique allowed, for the first time, the measurement of full spatiotemporal 3D elasticity maps of the LV using ultrasound. (Ultrasonic markers for myocardial fibrosis and prognosis in aortic stenosis; NCT03422770).

Detection of Tissue Fibrosis using Natural Mechanical Wave Velocity Estimation: Feasibility Study.

In the feasibility study described here, we developed and tested a novel method for mechanical wave velocity estimation for tissue fibrosis detection in the myocardium. High-frame-rate ultrasound imaging and a novel signal processing method called clutter filter wave imaging was used. A mechanical wave propagating through the left ventricle shortly after the atrial contraction was measured in the three different apical acquisition planes, for 20 infarct patients and 10 healthy controls. The results obtained were correlated with fibrosis locations from magnetic resonance imaging, and a sensitivity ≥60% was achieved for all infarcts larger than 10% of the left ventricle. The stability of the wave through several heart cycles was assessed and found to be of high quality. This method therefore has potential for non-invasive fibrosis detection in the myocardium, but further validation in a larger group of subjects is needed.

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.

Clutter Filter Wave Imaging.

The elastic properties of human tissue can be evaluated through the study of mechanical wave propagation captured using high frame rate ultrasound imaging. Methods such as block-matching or phase-based motion estimation have been used to estimate the displacement induced by the mechanical waves. In this paper, a new method for detecting mechanical wave propagation without motion estimation is presented, where the motion of interest is accentuated by an appropriate clutter filter. Thus, the mechanical wave propagation will directly appear as bands of the attenuated signal moving in the B-mode sequence and corresponding anatomical M-mode images. While only the locality of tissue velocity induced by the mechanical wave is detected, it is shown that the method is more sensitive to subtle tissue displacements when compared to motion estimation techniques. The technique was evaluated for the propagation of the pulse wave in a carotid artery, mechanical waves on the left ventricle, and shear waves induced by radiation force on a tissue-mimicking phantom. The results were compared to tissue Doppler imaging (TDI) and demonstrated that clutter filter wave imaging (CFWI) was able to detect the mechanical wave propagating in tissue with a relative temporal and spatial resolution 30% higher and a relative consistency 40% higher than TDI. The results showed that CFWI was able to detect mechanical waves with a relative frequency content 40% higher than TDI in a shear wave imaging experiment.

Detection of Regional Mechanical Activation of the Left Ventricular Myocardium Using High Frame Rate Ultrasound Imaging.

We have investigated the feasibility of noninvasive mapping of mechanical activation patterns in the left ventricular (LV) myocardium using high frame rate ultrasound imaging for the purpose of detecting conduction abnormalities. Five anesthetized, open-chest dogs with implanted combined sonomicrometry and electromyography (EMG) crystals were studied. The animals were paced from the specified locations of the heart, while crystal and ultrasound data were acquired. Isochrone maps of the mechanical activation patterns were generated from the ultrasound data using a novel signal processing method called clutter filter wave imaging (CFWI). The isochrone maps showed the same mechanical activation pattern as the sonomicrometry crystals in 90% of the cases. For electrical activation, the activation sequences from ultrasound were the same in 92% of the cases. The coefficient of determination between the activation delay measured with EMG and ultrasound was R 2 = 0.79 , indicating a strong correlation. These results indicate that high frame rate ultrasound imaging processed with CFWI has the potential to be a valuable tool for mechanical activation detection.

Video Magnification Applied in Ultrasound.

GOAL: This paper describes a method to enhance, visualize, and reveal subtle motion that can be present in medical images. As proposed in vision applications, the principle is to magnify displacement applied, in this case, to cardiovascular tissues (carotid). METHODS: In the example presented, ultrasound data were acquired at a high frame rate and two-dimensional motion was estimated, amplified, and reapplied in ultrasound carotid sequences. RESULTS: Video magnification makes fast and complex phenomena of human tissue visible. In fact, not only pulse and reflected wave, but also global radial and longitudinal motion in the example presented are visible with video magnification. CONCLUSION: Video magnification can be used in medical imaging for subtle motion visualization. One of the many possible applications is direct visualization of a local modification in terms of stiffness of a tissue (due to local necrosis, for instance) from acquisition. Moreover, video magnification can be executed with any type of imaging modality. SIGNIFICANCE: Video magnification could be a new tool for physicians to highlight new pathology indicators or for long-term disease monitoring.

Full 3-D transverse oscillations: a method for tissue motion estimation.

We present a new method to estimate 4-D (3-D + time) tissue motion. The method used combines 3-D phase based motion estimation with an unconventional beamforming strategy. The beamforming technique allows us to obtain full 3-D RF volumes with axial, lateral, and elevation modulations. Based on these images, we propose a method to estimate 3-D motion that uses phase images instead of amplitude images. First, volumes featuring 3-D oscillations are created using only a single apodization function, and the 3-D displacement between two consecutive volumes is estimated simultaneously by applying this 3-D estimation. The validity of the method is investigated by conducting simulations and phantom experiments. The results are compared with those obtained with two other conventional estimation methods: block matching and optical flow. The results show that the proposed method outperforms the conventional methods, especially in the transverse directions.

2-D arterial wall motion imaging using ultrafast ultrasound and transverse oscillations.

Ultrafast ultrasound is a promising imaging modality that enabled, inter alia, the development of pulse wave imaging and the local velocity estimation of the so-called pulse wave for a quantitative evaluation of arterial stiffness. However, this technique only focuses on the propagation of the axial displacement of the artery wall, and most techniques are not specific to the intima-media complex and do not take into account the longitudinal motion of this complex. Within this perspective, this paper presents a study of two-dimensional tissue motion estimation in ultrafast imaging combining transverse oscillations, which can improve motion estimation in the transverse direction, i.e., perpendicular to the beam axis, and a phase-based motion estimation. First, the method was validated in simulation. Two-dimensional motion, inspired from a real data set acquired on a human carotid artery, was applied to a numerical phantom to produce a simulation data set. The estimated motion showed axial and lateral mean errors of 4.2 ± 3.4 µm and 9.9 ± 7.9 µm, respectively. Afterward, experimental results were obtained on three artery phantoms with different wall stiffnesses. In this study, the vessel phantoms did not contain a pure longitudinal displacement. The longitudinal displacements were induced by the axial force produced by the wall's axial dilatation. This paper shows that the approach presented is able to perform 2-D tissue motion estimation very accurately even if the displacement values are very small and even in the lateral direction, making it possible to estimate the pulse wave velocity in both the axial and longitudinal directions. This demonstrates the method's potential to estimate the velocity of purely longitudinal waves propagating in the longitudinal direction. Finally, the stiffnesses of the three vessel phantom walls investigated were estimated with an average relative error of 2.2%.

Real-time ultrasound-tagging to track the 2D motion of the common carotid artery wall in vivo.

PURPOSE: Tracking the motion of biological tissues represents an important issue in the field of medical ultrasound imaging. However, the longitudinal component of the motion (i.e., perpendicular to the beam axis) remains more challenging to extract due to the rather coarse resolution cell of ultrasound scanners along this direction. The aim of this study is to introduce a real-time beamforming strategy dedicated to acquire tagged images featuring a distinct pattern in the objective to ease the tracking. METHODS: Under the conditions of the Fraunhofer approximation, a specific apodization function was applied to the received raw channel data, in real-time during image acquisition, in order to introduce a periodic oscillations pattern along the longitudinal direction of the radio frequency signal. Analytic signals were then extracted from the tagged images, and subpixel motion tracking of the intima-media complex was subsequently performed offline, by means of a previously introduced bidimensional analytic phase-based estimator. RESULTS: The authors' framework was applied in vivo on the common carotid artery from 20 young healthy volunteers and 6 elderly patients with high atherosclerosis risk. Cine-loops of tagged images were acquired during three cardiac cycles. Evaluated against reference trajectories manually generated by three experienced analysts, the mean absolute tracking error was 98 ± 84 µm and 55 ± 44 µm in the longitudinal and axial directions, respectively. These errors corresponded to 28% ± 23% and 13% ± 9% of the longitudinal and axial amplitude of the assessed motion, respectively. CONCLUSIONS: The proposed framework enables tagged ultrasound images of in vivo tissues to be acquired in real-time. Such unconventional beamforming strategy contributes to improve tracking accuracy and could potentially benefit to the interpretation and diagnosis of biomedical images.

Experimental evaluation of spectral-based quantitative ultrasound imaging using plane wave compounding.

Quantitative ultrasound (QUS) based on backscatter coefficient (BSC) estimation has shown potential for tissue characterization. Beamforming using plane wave compounding has advantages for echographic, Doppler, and elastographic imaging; however, to date, plane wave compounding has not been experimentally evaluated for the purpose of BSC estimation. In this study, two BSC-derived parameters (i.e., the BSC midband fit and intercept) were estimated from experimental data obtained using compound plane wave beamforming. For comparison, QUS parameters were also estimated from data obtained using both fixed focus and dynamic receive beamforming. An ultrasound imaging system equipped with a 9-MHz center frequency, 64-element array was used to collect data up to a depth of 45 mm. Two gelatin phantoms with randomly distributed 20-µm inclusions with a homogeneous scatterer concentration and a two-region scatterer concentration were used for assessing the precision and lateral resolution of QUS imaging, respectively. The use of plane wave compounding resulted in accurate QUS estimation (i.e., bias in the BSC parameters of less than 2 dB) and relatively constant lateral resolution (i.e., BSC midband fit 10% to 90% rise distance ranging between 1.0 and 1.5 mm) throughout a 45 mm field of view. Although both fixed focus and dynamic receive beamforming provided the same performance around the focal depth, the reduction in SNR away from the focus resulted in a reduced field of view in the homogeneous phantom (i.e., only 28 mm). The lateral resolution also degraded away from the focus, with up to a 2-fold and 10-fold increase in the rise distance at 20 mm beyond the focal depth for dynamic receive and fixed focus beamforming, respectively. These results suggest that plane wave compounding has the potential to improve the performance of spectral-based quantitative ultrasound over other conventional beamforming strategies.