Combined ARFI and Shear Wave Imaging of Prostate Cancer: Optimizing Beam Sequences and Parameter Reconstruction Approaches.

This study demonstrates the implementation of a shear wave reconstruction algorithm that enables concurrent acoustic radiation force impulse (ARFI) imaging and shear wave elasticity imaging (SWEI) of prostate cancer and zonal anatomy. The combined ARFI/SWEI sequence uses closely spaced push beams across the lateral field of view and simultaneously tracks both on-axis (within the region of excitation) and off-axis (laterally offset from the excitation) after each push beam. Using a large number of push beams across the lateral field of view enables the collection of higher signal-to-noise ratio (SNR) shear wave data to reconstruct the SWEI volume than is typically acquired. The shear wave arrival times were determined with cross-correlation of shear wave velocity signals in two dimensions after 3-D directional filtering to remove reflection artifacts. To combine data from serially interrogated lateral push locations, arrival times from different pushes were aligned by estimating the shear wave propagation time between push locations. Shear wave data acquired in an elasticity lesion phantom and reconstructed using this algorithm demonstrate benefits to contrast-to-noise ratio (CNR) with increased push beam density and 3-D directional filtering. Increasing the push beam spacing from 0.3 to 11.6 mm (typical for commercial SWEI systems) resulted in a 53% decrease in CNR. In human in vivo data, this imaging approach enabled high CNR (1.61-1.86) imaging of histologically-confirmed prostate cancer. The in vivo images had improved spatial resolution and CNR and fewer reflection artifacts as a result of the high push beam density, the high shear wave SNR, the use of multidimensional directional filtering, and the combination of shear wave data from different push beams.

Radiological Society of North America/Quantitative Imaging Biomarker Alliance Shear Wave Speed Bias Quantification in Elastic and Viscoelastic Phantoms.

OBJECTIVES: To quantify the bias of shear wave speed (SWS) measurements between different commercial ultrasonic shear elasticity systems and a magnetic resonance elastography (MRE) system in elastic and viscoelastic phantoms. METHODS: Two elastic phantoms, representing healthy through fibrotic liver, were measured with 5 different ultrasound platforms, and 3 viscoelastic phantoms, representing healthy through fibrotic liver tissue, were measured with 12 different ultrasound platforms. Measurements were performed with different systems at different sites, at 3 focal depths, and with different appraisers. The SWS bias across the systems was quantified as a function of the system, site, focal depth, and appraiser. A single MRE research system was also used to characterize these phantoms using discrete frequencies from 60 to 500 Hz. RESULTS: The SWS from different systems had mean difference 95% confidence intervals of ±0.145 m/s (±9.6%) across both elastic phantoms and ± 0.340 m/s (±15.3%) across the viscoelastic phantoms. The focal depth and appraiser were less significant sources of SWS variability than the system and site. Magnetic resonance elastography best matched the ultrasonic SWS in the viscoelastic phantoms using a 140 Hz source but had a - 0.27 ± 0.027-m/s (-12.2% ± 1.2%) bias when using the clinically implemented 60-Hz vibration source. CONCLUSIONS: Shear wave speed reconstruction across different manufacturer systems is more consistent in elastic than viscoelastic phantoms, with a mean difference bias of < ±10% in all cases. Magnetic resonance elastographic measurements in the elastic and viscoelastic phantoms best match the ultrasound systems with a 140-Hz excitation but have a significant negative bias operating at 60 Hz. This study establishes a foundation for meaningful comparison of SWS measurements made with different platforms.

Semi-automated weak annotation for deep neural network skin thickness measurement.

Correctly calculating skin stiffness with ultrasound shear wave elastography techniques requires an accurate measurement of skin thickness. We developed and compared two algorithms, a thresholding method and a deep learning method, to measure skin thickness on ultrasound images. Here, we also present a framework for weakly annotating an unlabeled dataset in a time-effective manner to train the deep neural network. Segmentation labels for training were proposed using the thresholding method and validated with visual inspection by a human expert reader. We reduced decision ambiguity by only inspecting segmentations at the center A-line. This weak annotation approach facilitated validation of over 1000 segmentation labels in 2 hours. A lightweight deep neural network that segments entire 2D images was designed and trained on this weakly-labeled dataset. Averaged over six folds of cross-validation, segmentation accuracy was 57% for the thresholding method and 78% for the neural network. In particular, the network was better at finding the distal skin margin, which is the primary challenge for skin segmentation. Both algorithms have been made publicly available to aid future applications in skin characterization and elastography.

Conditionally Increased Acoustic Pressures in Nonfetal Diagnostic Ultrasound Examinations Without Contrast Agents: A Preliminary Assessment.

The mechanical index (MI) has been used by the US Food and Drug Administration (FDA) since 1992 for regulatory decisions regarding the acoustic output of diagnostic ultrasound equipment. Its formula is based on predictions of acoustic cavitation under specific conditions. Since its implementation over 2 decades ago, new imaging modes have been developed that employ unique beam sequences exploiting higher-order acoustic phenomena, and, concurrently, studies of the bioeffects of ultrasound under a range of imaging scenarios have been conducted. In 2012, the American Institute of Ultrasound in Medicine Technical Standards Committee convened a working group of its Output Standards Subcommittee to examine and report on the potential risks and benefits of the use of conditionally increased acoustic pressures (CIP) under specific diagnostic imaging scenarios. The term "conditionally" is included to indicate that CIP would be considered on a per-patient basis for the duration required to obtain the necessary diagnostic information. This document is a result of that effort. In summary, a fundamental assumption in the MI calculation is the presence of a preexisting gas body. For tissues not known to contain preexisting gas bodies, based on theoretical predications and experimentally reported cavitation thresholds, we find this assumption to be invalid. We thus conclude that exceeding the recommended maximum MI level given in the FDA guidance could be warranted without concern for increased risk of cavitation in these tissues. However, there is limited literature assessing the potential clinical benefit of exceeding the MI guidelines in these tissues. The report proposes a 3-tiered approach for CIP that follows the model for employing elevated output in magnetic resonance imaging and concludes with summary recommendations to facilitate Institutional Review Board (IRB)-monitored clinical studies investigating CIP in specific tissues.

An analytic, Fourier domain description of shear wave propagation in a viscoelastic medium using asymmetric Gaussian sources.

Recent measurements of shear wave propagation in viscoelastic materials have been analyzed by constructing the two-dimensional Fourier transform (2D-FT) of the spatial-temporal shear wave signal and using an analysis procedure derived under the assumption the wave is described as a plane wave, or as the asymptotic form of a wave expanding radially from a cylindrically symmetric source. This study presents an exact, analytic expression for the 2D-FT description of shear wave propagation in viscoelastic materials following asymmetric Gaussian excitations and uses this expression to evaluate the bias in 2D-FT measurements obtained using the plane or cylindrical wave assumptions. A wide range of biases are observed depending on specific values of frequency, aspect ratio R of the source asymmetry, and material properties. These biases can be reduced significantly by weighting the shear wave signal in the spatial domain to correct for the geometric spreading of the shear wavefront using a factor of x(p). The optimal weighting power p is found to be near the theoretical value of 0.5 for the case of a cylindrical source with R = 1, and decreases for asymmetric sources with R > 1.

B-mode and acoustic radiation force impulse (ARFI) imaging of prostate zonal anatomy: comparison with 3T T2-weighted MR imaging.

Prostate cancer (PCa) is the most common non-cutaneous malignancy among men in the United States and the second leading cause of cancer-related death. Multi-parametric magnetic resonance imaging (mpMRI) has gained recent popularity to characterize PCa. Acoustic Radiation Force Impulse (ARFI) imaging has the potential to aid PCa diagnosis and management by using tissue stiffness to evaluate prostate zonal anatomy and lesions. MR and B-mode/ARFI in vivo imaging datasets were compared with one another and with gross pathology measurements made immediately after radical prostatectomy. Images were manually segmented in 3D Slicer to delineate the central gland (CG) and prostate capsule, and 3D models were rendered to evaluate zonal anatomy dimensions and volumes. Both imaging modalities showed good correlation between estimated organ volume and gross pathologic weights. Ultrasound and MR total prostate volumes were well correlated (R(2) = 0.77), but B-mode images yielded prostate volumes that were larger (16.82% ± 22.45%) than MR images, due to overestimation of the lateral dimension (18.4% ± 13.9%), with less significant differences in the other dimensions (7.4% ± 17.6%, anterior-to-posterior, and -10.8% ± 13.9%, apex-to-base). ARFI and MR CG volumes were also well correlated (R(2) = 0.85). CG volume differences were attributed to ARFI underestimation of the apex-to-base axis (-28.8% ± 9.4%) and ARFI overestimation of the lateral dimension (21.5% ± 14.3%). B-mode/ARFI imaging yielded prostate volumes and dimensions that were well correlated with MR T2-weighted image (T2WI) estimates, with biases in the lateral dimension due to poor contrast caused by extraprostatic fat. B-mode combined with ARFI imaging is a promising low-cost, portable, real-time modality that can complement mpMRI for PCa diagnosis, treatment planning, and management.

Ultrasound Shear Wave Elastography in Cardiology.

The advent of high-frame rate imaging in ultrasound allowed the development of shear wave elastography as a noninvasive alternative for myocardial stiffness assessment. It measures mechanical waves propagating along the cardiac wall with speeds that are related to stiffness. The use of cardiac shear wave elastography in clinical studies is increasing, but a proper understanding of the different factors that affect wave propagation is required to correctly interpret results because of the heart's thin-walled geometry and intricate material properties. The aims of this review are to give an overview of the general concepts in cardiac shear wave elastography and to discuss in depth the effects of age, hemodynamic loading, cardiac morphology, fiber architecture, contractility, viscoelasticity, and system-dependent factors on the measurements, with a focus on clinical application. It also describes how these factors should be considered during acquisition, analysis, and reporting to ensure an accurate, robust, and reproducible measurement of the shear wave.

Rotational 3D shear wave elasticity imaging: Effect of knee flexion on 3D shear wave propagation in in vivo vastus lateralis.

Skeletal muscle is a complex tissue, exhibiting not only direction-dependent material properties (commonly modeled as a transversely isotropic material), but also changes in observed material properties due to factors such as contraction and passive stretch. In this work, we evaluated the effect of muscle passive stretch on shear wave propagation along and across the muscle fibers using a rotational 3D shear wave elasticity imaging system and automatic analysis methods. We imaged the vastus lateralis of 10 healthy volunteers, modulating passive stretch by imaging at 8 different knee flexion angles (controlled by a BioDex system). In addition to demonstrating the ability of this acquisition and automatic processing system to estimate muscle shear moduli over a range of values, we evaluated potential higher order biomarkers for muscle health that capture the change in muscle stiffness along and across the fibers with changing knee flexion. The median within-subject variability of these biomarkers is found to be <16%, suggesting promise as a repeatable clinical metric. Additionally, we report an unexpected observation: that shear wave signal amplitude along the fibers increases with increasing flexion and muscle stiffness, which is not predicted by transversely isotropic (TI) material simulations. This observation may point to an additional potential biomarker for muscle health or inform other material modeling choices for muscle.

Quantifying the Impact of Imaging Through Body Walls on Shear Wave Elasticity Measurements.

In the context of ultrasonic hepatic shear wave elasticity imaging (SWEI), measurement success has been determined to increase when using elevated acoustic output pressures. As SWEI sequences consist of two distinct operations (pushing and tracking), acquisition failures could be attributed to (i) insufficient acoustic radiation force generation resulting in inadequate shear wave amplitude and/or (ii) distorted ultrasonic tissue motion tracking. In the study described here, an opposing window experimental setup that isolated body wall effects separately between the push and track SWEI operations was implemented. A commonly employed commercial track configuration was used, harmonic multiple-track-location SWEI. The effects of imaging through body walls on the pushing and tracking operations of SWEI as a function of mechanical index (MI), spanning 5 different push beam MIs and 10 track beam MIs, were independently assessed using porcine body walls. Shear wave speed yield was found to increase with both increasing push and track MI. Although not consistent across all samples, measurements in a subset of body walls were found to be signal limited during tracking and to increase yield by up to 35% when increasing electronic signal-to-noise ratio by increasing harmonic track transmit pressure.

Repeatability of Rotational 3-D Shear Wave Elasticity Imaging Measurements in Skeletal Muscle.

Shear wave elasticity imaging (SWEI) usually assumes an isotropic material; however, skeletal muscle is typically modeled as a transversely isotropic material with independent shear wave speeds in the directions along and across the muscle fibers. To capture these direction-dependent properties, we implemented a rotational 3-D SWEI system that measures the shear wave speed both along and across the fibers in a single 3-D acquisition, with automatic detection of the muscle fiber orientation. We tested and examined the repeatability of this system's measurements in the vastus lateralis of 10 healthy volunteers. The average coefficient of variation of the measurements from this 3-D SWEI system was 5.3% along the fibers and 8.1% across the fibers. When compared with estimated respective 2-D SWEI values of 16.0% and 83.4%, these results suggest using 3-D SWEI has the potential to improve the precision of SWEI measurements in muscle. Additionally, we observed no significant difference in shear wave speed between the dominant and non-dominant legs along (p = 0.26) or across (p = 0.65) the muscle fibers.

Phase and group velocities for shear wave propagation in an incompressible, hyperelastic material with uniaxial stretch.

Objective.Determining elastic properties of materials from observations of shear wave propagation is difficult in anisotropic materials because of the complex relations among the propagation direction, shear wave polarizations, and material symmetries. In this study, we derive expressions for the phase velocities of the SH and SV propagation modes as a function of propagation direction in an incompressible, hyperelastic material with uniaxial stretch.Approach.Wave motion is included in the material model by adding incremental, small amplitude motion to the initial, finite deformation. Equations of motion for the SH and SV propagation modes are constructed using the Cauchy stress tensor derived from the strain energy function of the material. Group velocities for the SH and SV propagation modes are derived from the angle-dependent phase velocities.Main results.Sample results are presented for the Arruda-Boyce, Mooney-Rivlin, and Isihara material models using model parameters previously determined in a phantom.Significance.Results for the Mooney-Rivlin and Isihara models demonstrate shear splitting in which the SH and SV propagation modes have unequal group velocities for propagation across the material symmetry axis. In addition, for sufficiently large stretch, the Arruda-Boyce and Isihara material models show cusp structures with triple-valued group velocities for the SV mode at angles of roughly 15° to the material symmetry axis.

Perspective on ultrasound bioeffects and possible implications for continuous post-dive monitoring safety.

Ultrasound monitoring, both in the form of Doppler and 2D echocardiography, has been used post-dive to detect decompression bubbles circulating in the bloodstream. With large variability in both bubble time course and loads, it has been hypothesised that shorter periods between imaging, or even continuous imaging, could provide more accurate post-dive assessments. However, while considering applications of ultrasound imaging post-decompression, it may also be prudent to consider the possibility of ultrasound-induced bioeffects. Clinical ultrasound studies using microbubble contrast agents have shown bioeffect generation with acoustic powers much lower than those used in post-dive monitoring. However, to date no studies have specifically investigated potential bioeffect generation from continuous post-dive echocardiography. This review discusses what can be drawn from the current ultrasound and diving literature on the safety of bubble sonication and highlights areas where more studies are needed. An overview of the ultrasound-bubble mechanisms that lead to bioeffects and analyses of ultrasound contrast agent studies on bioeffect generation in the pulmonary and cardiovascular systems are provided to illustrate how bubbles under ultrasound can cause damage within the body. Along with clinical ultrasound studies, studies investigating the effects of decompression bubbles under ultrasound are analysed and open questions regarding continuous post-dive monitoring safety are discussed.

Assessing cardiac stiffness using ultrasound shear wave elastography.

Shear wave elastography offers a new dimension to echocardiography: it measures myocardial stiffness. Therefore, it could provide additional insights into the pathophysiology of cardiac diseases affecting myocardial stiffness and potentially improve diagnosis or guide patient treatment. The technique detects fast mechanical waves on the heart wall with high frame rate echography, and converts their propagation speed into a stiffness value. A proper interpretation of shear wave data is required as the shear wave interacts with the intrinsic, yet dynamically changing geometrical and material characteristics of the heart under pressure. This dramatically alters the wave physics of the propagating wave, demanding adapted processing methods compared to other shear wave elastography applications as breast tumor and liver stiffness staging. Furthermore, several advanced analysis methods have been proposed to extract supplementary material features such as viscosity and anisotropy, potentially offering additional diagnostic value. This review explains the general mechanical concepts underlying cardiac shear wave elastography and provides an overview of the preclinical and clinical studies within the field. We also identify the mechanical and technical challenges ahead to make shear wave elastography a valuable tool for clinical practice.

Full Characterization of in vivo Muscle as an Elastic, Incompressible, Transversely Isotropic Material Using Ultrasonic Rotational 3D Shear Wave Elasticity Imaging.

Using a 3D rotational shear wave elasticity imaging (SWEI) setup, 3D shear wave data were acquired in the vastus lateralis of a healthy volunteer. The innate tilt between the transducer face and the muscle fibers results in the excitation of multiple shear wave modes, allowing for more complete characterization of muscle as an elastic, incompressible, transversely isotropic (ITI) material. The ability to measure both the shear vertical (SV) and shear horizontal (SH) wave speed allows for measurement of three independent parameters needed for full ITI material characterization: the longitudinal shear modulus µL , the transverse shear modulus µT , and the tensile anisotropy χE . Herein we develop and validate methodology to estimate these parameters and measure them in vivo, with µL = 5.77±1.00 kPa, µT = 1.93±0.41 kPa (giving shear anisotropy χµ = 2.11±0.92 ), and χE = 4.67±1.40 in a relaxed vastus lateralis muscle. We also demonstrate that 3D SWEI can be used to more accurately characterize muscle mechanical properties as compared to 2D SWEI.

Parametric Analysis of SV Mode Shear Waves in Transversely Isotropic Materials Using Ultrasonic Rotational 3-D SWEI.

Ultrasonic rotational 3-D shear wave elasticity imaging (SWEI) has been used to induce and evaluate multiple shear wave modes, including both the shear horizontal (SH) and shear vertical (SV) modes in in vivo muscle. Observations of both the SH and SV modes allow the muscle to be characterized as an elastic, incompressible, transversely isotropic (ITI) material with three parameters: the longitudinal shear modulus µL , the transverse shear modulus µT , and the tensile anisotropy χE . Measurement of the SV wave is necessary to characterize χE , but the factors that influence SV mode generation and characterization with ultrasonic SWEI are complicated. This work uses Green's function (GF) simulations to perform a parametric analysis to determine the optimal interrogation parameters to facilitate visualization and quantification of SV mode shear waves in muscle. We evaluate the impact of five factors: µL , µT , χE , fiber tilt angle [Formula: see text], and F-number of the push geometry on SV mode speed, amplitude, and rotational distribution. These analyses demonstrate that the following hold: 1) as µL increases, SV waves decrease in amplitude so are more difficult to measure in SWEI imaging; 2) as µT increases, the SV wave speeds increase; 3) as χE increases, the SV waves increase in speed and separate from the SH waves; 4) as fiber tilt angle [Formula: see text] increases, the measurable SV waves remain approximately the same speed, but change in strength and in rotational distribution; and 5) as the push beam geometry changes with F-number, the measurable SV waves remain approximately the same speed, but change in strength and rotational distribution. While specific SV mode speeds depend on the combinations of all parameters considered, measurable SV waves can be generated and characterized across the range of parameters considered. To maximize measurable SV waves separate from the SH waves, it is recommended to use an F/1 push geometry and [Formula: see text].

Noninvasive evaluation of hepatic fibrosis using acoustic radiation force-based shear stiffness in patients with nonalcoholic fatty liver disease.

BACKGROUND & AIMS: Nonalcoholic fatty liver disease (NAFLD), the most common form of chronic liver disease in developed countries, may progress to nonalcoholic steatohepatitis (NASH) in a minority of people. Those with NASH are at increased risk for cirrhosis and hepatocellular carcinoma. The potential risk and economic burden of utilizing liver biopsy to stage NAFLD in an overwhelmingly large at-risk population are enormous; thus, the discovery of sensitive, inexpensive, and reliable noninvasive diagnostic modalities is essential for population-based screening. METHODS: Acoustic Radiation Force Impulse (ARFI) shear wave imaging, a noninvasive method of assessing tissue stiffness, was used to evaluate liver fibrosis in 172 patients diagnosed with NAFLD. Liver shear stiffness measures in three different imaging locations were reconstructed and compared to the histologic features of NAFLD and AST-to-platelet ratio indices (APRI). RESULTS: Reconstructed shear stiffnesses were not associated with ballooned hepatocytes (p=0.11), inflammation (p=0.69), nor imaging location (p=0.11). Using a predictive shear stiffness threshold of 4.24kPa, shear stiffness distinguished low (fibrosis stage 0-2) from high (fibrosis stage 3-4) fibrosis stages with a sensitivity of 90% and a specificity of 90% (AUC of 0.90). Shear stiffness had a mild correlation with APRI (R(2)=0.22). BMI>40kg/m(2) was not a limiting factor for ARFI imaging, and no correlation was noted between BMI and shear stiffness (R(2)=0.05). CONCLUSIONS: ARFI imaging is a promising imaging modality for assessing the presence or absence of advanced fibrosis in patients with obesity-related liver disease.

On the Relationship between Spatial Coherence and In Situ Pressure for Abdominal Imaging.

Tissue harmonic signal quality has been shown to improve with elevated acoustic pressure. The peak rarefaction pressure (PRP) for a given transmit, however, is limited by the Food and Drug Administration guidelines for mechanical index. We have previously demonstrated that the mechanical index overestimates in situ PRP for tightly focused beams in vivo, due primarily to phase aberration. In this study, we evaluate two spatial coherence-based image quality metrics-short-lag spatial coherence and harmonic short-lag spatial coherence-as proxy estimates for phase aberration and assess their correlation with in situ PRP in simulations and experiments when imaging through abdominal body walls. We demonstrate strong correlation between both spatial coherence-based metrics and in situ PRP (R2 = 0.77 for harmonic short-lag spatial coherence, R2 = 0.67 for short-lag spatial coherence), an observation that could be leveraged in the future for patient-specific selection of acoustic output.

Uniqueness of shear wave modeling in an incompressible, transversely isotropic (ITI) material.

Five material parameters are required to describe a transversely isotropic (TI) material including two Poisson's ratios that characterize the compressibility of the material. Both Poisson's ratios must be specified to model an incompressible, TI (ITI) material. However, a previous analysis of the procedure used to evaluate the incompressible limit in a two-dimensional (2D) space of Poisson's ratios has shown that elements of the stiffness tensor are not unique in this limit, and that an additional, fourth parameter is required to model these elements for an ITI material. In this study, we extend this analysis to the case of shear wave propagation in an ITI material. Shear wave signals are modeled using analytic Green's tensor methods to express the signals in terms of the phase velocity and polarization vectors of the shear horizontal (SH) and shear vertical (SV) propagation modes. In contrast to the previous result, the current analysis demonstrates that the phase velocity and polarization vectors are independent of the procedure used to evaluate the 2D limit of Poisson's ratios without the need to include an additional parameter. Thus, calculated shear wave signals are unique and can be used for comparison with experimental measurements to determine all three model parameters that characterize an ITI material.

Quantifying the Effect of Abdominal Body Wall on In Situ Peak Rarefaction Pressure During Diagnostic Ultrasound Imaging.

In this study, 3-D non-linear ultrasound simulations and experimental measurements were used to estimate the range of in situ pressures that can occur during transcutaneous abdominal imaging and to identify the sources of error when estimating in situ peak rarefaction pressures (PRPs) using linear derating, as specified by the mechanical index (MI) guideline. Using simulations, it was found that, for a large transmit aperture (F/1.5), MI consistently over-estimated in situ PRP by 20%-48% primarily owing to phase aberration. For a medium transmit aperture (F/3), the MI accurately estimated the in situ PRP to within 8%. For a small transmit aperture (F/5), MI consistently underestimated the in situ PRP by 32%-50%, with peak locations occurring 1-2 cm before the focal depth, often within the body wall itself. The large variability across body wall samples and focal configurations demonstrates the limitations of the simplified linear derating scheme. The results suggest that patient-specific in situ PRP estimation would allow for increases in transmit pressures, particularly for tightly focused beams, to improve diagnostic image quality while ensuring patient safety.

Deep Convolutional Neural Networks for Displacement Estimation in ARFI Imaging.

Ultrasound elasticity imaging in soft tissue with acoustic radiation force requires the estimation of displacements, typically on the order of several microns, from serially acquired raw data A-lines. In this work, we implement a fully convolutional neural network (CNN) for ultrasound displacement estimation. We present a novel method for generating ultrasound training data, in which synthetic 3-D displacement volumes with a combination of randomly seeded ellipsoids are created and used to displace scatterers, from which simulated ultrasonic imaging is performed using Field II. Network performance was tested on these virtual displacement volumes, as well as an experimental ARFI phantom data set and a human in vivo prostate ARFI data set. In the simulated data, the proposed neural network performed comparably to Loupas's algorithm, a conventional phase-based displacement estimation algorithm; the rms error was [Formula: see text] for the CNN and 0.73 [Formula: see text] for Loupas. Similarly, in the phantom data, the contrast-to-noise ratio (CNR) of a stiff inclusion was 2.27 for the CNN-estimated image and 2.21 for the Loupas-estimated image. Applying the trained network to in vivo data enabled the visualization of prostate cancer and prostate anatomy. The proposed training method provided 26 000 training cases, which allowed robust network training. The CNN had a computation time that was comparable to Loupas's algorithm; further refinements to the network architecture may provide an improvement in the computation time. We conclude that deep neural network-based displacement estimation from ultrasonic data is feasible, providing comparable performance with respect to both accuracy and speed compared to current standard time-delay estimation approaches.