Brett Byram

Short-lag spatial coherence of backscattered echoes: imaging characteristics

Conventional ultrasound images are formed by delay-and-sum beamforming of the backscattered echoes received by individual elements of the transducer aperture. Although the delay-and-sum beamformer is well suited for ultrasound image formation, it is corrupted by speckle noise and challenged by acoustic clutter and phase aberration. We propose an alternative method of imaging utilizing the short-lag spatial coherence (SLSC) of the backscattered echoes. Compared with matched B-mode images, SLSC images demonstrate superior SNR and contrast-to-noise ratio in simulated and experimental speckle-generating phantom targets, but are shown to be challenged by limited point target conspicuity. Matched B-mode and SLSC images of a human thyroid are presented. The challenges and opportunities of real-time implementation of SLSC imaging are discussed.

Imaging Transverse Isotropic Properties of Muscle by Monitoring Acoustic Radiation Force Induced Shear Waves Using a 2-D Matrix Ultrasound Array

A 2-D matrix ultrasound array is used to monitor acoustic radiation force impulse (ARFI) induced shear wave propagation in 3-D in excised canine muscle. From a single acquisition, both the shear wave phase and group velocity can be calculated to estimate the shear wave speed (SWS) along and across the fibers, as well as the fiber orientation in 3-D. The true fiber orientation found using the 3-D radon transform on B-mode volumes of the muscle was used to verify the fiber direction estimated from shear wave data. For the simplified imaging case when the ARFI push can be oriented perpendicular to the fibers, the error in estimating the fiber orientation using phase and group velocity measurements was 3.5±2.6° and 3.4±1.4° (mean ± standard deviation), respectively, over six acquisitions in different muscle samples. For the more general case when the push is oblique to the fibers, the angle between the push and the fibers is found using the dominant orientation of the shear wave displacement magnitude. In 30 acquisitions on six different muscle samples with oblique push angles up to 40°, the error in the estimated fiber orientation using phase and group velocity measurements was 5.4±2.9° and 5.3±3.2°, respectively, after estimating and accounting for the additional unknown push angle. Either the phase or group velocity measurements can be used to estimate fiber orientation and SWS along and across the fibers. Although it is possible to perform these measurements when the push is not perpendicular to the fibers, highly oblique push angles induce lower shear wave amplitudes which can cause inaccurate SWS measurements.

3-D phantom and in vivo cardiac speckle tracking using a matrix array and raw echo data

Cardiac motion has been tracked using various methods, which vary in their invasiveness and dimensionality. One such noninvasive modality for cardiac motion tracking is ultrasound. Three-dimensional ultrasound motion tracking has been demonstrated using detected data at low volume rates. However, the effects of volume rate, kernel size, and data type (raw and detected) have not been sufficiently explored. First comparisons are made within the stated variables for 3-D speckle tracking. Volumetric data were obtained in a raw, baseband format using a matrix array attached to a high parallel receive beam count scanner. The scanner was used to acquire phantom and human in vivo cardiac volumetric data at 1000-Hz volume rates. Motion was tracked using phase-sensitive normalized cross-correlation. Subsample estimation in the lateral and elevational dimensions used the grid-slopes algorithm. The effects of frame rate, kernel size, and data type on 3-D tracking are shown. In general, the results show improvement of motion estimates at volume rates up to 200 Hz, above which they become stable. However, peak and pixel hopping continue to decrease at volume rates higher than 200 Hz. The tracking method and data show, qualitatively, good temporal and spatial stability (for independent kernels) at high volume rates.

On the precision of time-of-flight shear wave speed estimation in homogeneous soft solids: initial results using a matrix array transducer

A system capable of tracking radiation-force-induced shear wave propagation in a 3-D volume using ultrasound is presented. In contrast to existing systems, which use 1-D array transducers, a 2-D matrix array is used for tracking shear wave displacements. A separate single-element transducer is used for radiation force excitation. This system allows shear wave propagation in all directions away from the push to be observed. It is shown that for a limit of 64 tracking beams, by placing the beams at the edges of the measurement region of interest (ROI) at multiple directions from the push, time-of- flight (TOF) shear wave speed (SWS) measurement uncertainty can theoretically be reduced by 40% compared with equally spacing the tracking beams within the ROI along a single plane, as is typical when using a 1-D array for tracking. This was verified by simulation, and a reduction of 30% was experimentally observed on a homogeneous phantom. Analytical expressions are presented for the relationship between TOF SWS measurement uncertainty and various shear wave imaging parameters. It is shown that TOF SWS uncertainty is inversely proportional to ROI size, and inversely proportional to the square root of the number of tracking locations for a given distribution of beam locations relative to the push. TOF SWS uncertainty is shown to increase with the square of the SWS, indicating that TOF SWS measurements are intrinsically less precise for stiffer materials.

Ultrasonic multipath and beamforming clutter reduction: a chirp model approach

In vivo ultrasonic imaging with transducer arrays suffers from image degradation resulting from beamforming limitations, including diffraction-limited beamforming and beamforming degradation caused by tissue inhomogeneity. Additionally, based on recent studies, multipath scattering also causes significant image degradation. To reduce degradation from both sources, we propose a model-based signal decomposition scheme. The proposed algorithm identifies spatial frequency signatures to decompose received wavefronts into their most significant scattering sources. Scattering sources originating from a region of interest are used to reconstruct decluttered wavefronts, which are beamformed into decluttered RF scan lines or A-lines. To test the algorithm, ultrasound system channel data were acquired during liver scans from 8 patients. Multiple data sets were acquired from each patient, with 55 total data sets, 43 of which had identifiable hypoechoic regions on normal B-mode images. The data sets with identifiable hypoechoic regions were analyzed. The results show the decluttered B-mode images have an average improvement in contrast over normal images of 7.3 ± 4.6 dB. The contrast-to-noise ratio (CNR) changed little on average between normal and decluttered Bmode, -0.4 ± 5.9 dB. The in vivo speckle SNR decreased; the change was -0.65 ± 0.28. Phantom speckle SNR also decreased, but only by -0.40 ± 0.03.

Synthetic aperture focusing for short-lag spatial coherence imaging

It has been demonstrated that short-lag spatial coherence (SLSC) ultrasound imaging can provide improved speckle SNR and lesion CNR compared with conventional B-mode images, especially in the presence of noise and clutter. Application of the van Cittert-Zernike theorem predicts that coherence among the ultrasound echoes received across an array is reduced significantly away from the transmit focal depth, leading to a limited axial depth of field in SLSC images. Transmit focus throughout the field of view can be achieved using synthetic aperture methods to combine multiple transmit events into a single final image. A synthetic aperture can be formed with either focused or diverging transmit beams. We explore the application of these methods to form synthetically focused channel data to create SLSC images with an extended axial depth of field. An analytical expression of SLSC image brightness through depth is derived for the dynamic receive focus case. Experimental results in a phantom and in vivo are presented and compared with dynamic receive focused SLSC images, demonstrating improved SNR and CNR away from the transmit focus and an axial depth of field four to five times longer.

A model and regularization scheme for ultrasonic beamforming clutter reduction

Acoustic clutter produced by off-axis and multipath scattering is known to cause image degradation, and in some cases these sources may be the prime determinants of in vivo image quality. We have previously shown some success addressing these sources of image degradation by modeling the aperture domain signal from different sources of clutter, and then decomposing aperture domain data using the modeled sources. Our previous model had some shortcomings including model mismatch and failure to recover B-Mode speckle statistics. These shortcomings are addressed here by developing a better model and by using a general regularization approach appropriate for the model and data. We present results with L1 (lasso), L2 (ridge), and L1/L2 combined (elastic-net) regularization methods. We call our new method aperture domain model image reconstruction (ADMIRE). Our results demonstrate that ADMIRE with L1 regularization, or weighted toward L1 in the case of elastic-net regularization, have improved image quality. L1 by itself works well, but additional improvements are seen with elastic-net regularization over the pure L1 constraint. On in vivo example cases, L1 regularization showed mean contrast improvements of 4.6 and 6.8 dB on fundamental and harmonic images, respectively. Elastic net regularization (α = 0.9) showed mean contrast improvements of 17.8 dB on fundamental images and 11.8 dB on harmonic images. We also demonstrate that in uncluttered Field II simulations the de-cluttering algorithm produces the same contrast, contrast-to-noise ratio, and speckle SNR as normal B-mode imaging, demonstrating that ADMIRE preserves typical image features.

Comparison of Physiological Motion Filters for In Vivo Cardiac ARFI

Acoustic radiation force impulse (ARFI) imaging is being utilized to investigate mechanical properties of cardiac tissue. The underlying physiological motion, however, presents a major challenge. This paper aims to investigate the effectiveness of various physiological motion filters using in vivo canine data with a simulated ARFI push pulse. Ideally, the motion filter will exactly model the physiological motion and, when subtracted from the total displacement, leave only the simulated ARFI displacement profile. We investigated three temporal quadratic motion filters: (1) interpolation, (2) extrapolation and (3) a weighted technique. Additionally, the various motion filters were compared when using 1-D versus 2-D autocorrelation methods to estimate motion. It was found that 2D-autocorrelation always produced better physiological motion estimates regardless of the type of filter used. The extrapolation filter gives the most accurate estimate of the physiological motion at times immediately after the ARFI push (0.1 ms) while a close-time interpolation filter using displacement estimates at times before full tissue recovery gives the most accurate estimates at latertimes after the ARFI push (0.7 ms). While improvements to the motion filter during atrial systole and the onset of ventricular systole are needed, the weighted, close-time interpolation and extrapolation motion filters all offer promising results for estimating cardiac physiological motion more accurately, while allowing faster ARFI frame rates than previous motion filters. This study demonstrates the ability to eliminate physiological motion in a clinically-feasible manner, opening the door for more extensive clinical experimentation.

Ultrasonic characterization of the nonlinear properties of canine livers by measuring shear wave speed and axial strain with increasing portal venous pressure

Elevated hepatic venous pressure is the primary source of complications in advancing liver disease. Ultrasound imaging is ideal for potential noninvasive hepatic pressure measurements as it is widely used for liver imaging. Specifically, ultrasound based stiffness measures may be useful for clinically monitoring pressure, but the mechanism by which liver stiffness increases with hepatic pressure has not been well characterized. This study is designed to elucidate the nonlinear properties of the liver during pressurization by measuring both hepatic shear wave speed (SWS) and strain with increasing pressure. Tissue deformation during hepatic pressurization was tracked in 8 canine livers using successively acquired 3-D B-mode volumes and compared with concurrently measured SWS. When portal venous pressure was increased from clinically normal (0-5mmHg) to pressures representing highly diseased states at 20mmHg, the liver was observed to expand with axial strain measures up to 10%. At the same time, SWS estimates were observed to increase from 1.5-2m/s at 0-5mmHg (baseline) to 3.25-3.5m/s at 20mmHg.

Sources and characterization of clutter in cardiac B-mode images

In echocardiography, clutter is one of the most problematic image artifacts, often obscuring ventricular borders and introducing stationary noise in blood flow measurements. Clutter in transthoracic cardiac images is widely understood to originate from reverberations and off-axis echoes. The objective of this work is to investigate the sources of clutter in cardiac images and their relative contributions. Real-time 3D raw echo data was acquired at a volumetric frame rate of 1 kHz and speckle tracking was applied to resulting images to determine the motion characteristics of clutter and adjacent myocardium. When clutter adjacent to the myocardial wall was tracked, the clutter and adjacent myocardium had similar displacements. When clutter farther from the myocardial wall was tracked, displacements were temporally and spatially complex and did not correlate well with any portion of the myocardium. In addition, principal component analysis (PCA) was applied to the raw echo data and resulting eigenvectors were used to isolate various motion patterns in the cardiac data. Results support the hypothesis that echoes from stationary structures, such as the ribcage and chest wall, are contributors to stationary clutter noise, while the myocardium is a dominant source of nonstationary clutter.