Automated Spontaneous Echo Contrast Detection Using a Multisequence Attention Convolutional Neural Network

OBJECTIVE

Spontaneous echo contrast (SEC) is a vascular ultrasound finding associated with increased thromboembolism risk. However, identification requires expert determination and clinician time to report. We developed a deep learning model that can automatically identify SEC. Our model can be applied retrospectively without deviating from routine clinical practice. The retrospective nature of our model means future works could scan archival data to opportunistically correlate SEC findings with documented clinical outcomes.

METHODS

We curated a data set of 801 archival acquisitions along the femoral vein from 201 patients. We used a multisequence convolutional neural network (CNN) with ResNetv2 backbone and visualized keyframe importance using soft attention. We evaluated SEC prediction performance using an 80/20 train/test split. We report receiver operating characteristic area under the curve (ROC-AUC), along with the Youden threshold-associated sensitivity, specificity, F1 score, true negative, false negative, false positive and true positive.

RESULTS

Using soft attention, we can identify SEC with an AUC of 0.74, sensitivity of 0.73 and specificity of 0.68. Without soft attention, our model achieves an AUC of 0.69, sensitivity of 0.71 and specificity of 0.60. Additionally, we provide attention visualizations and note that our model assigns higher attention score to ultrasound frames containing more vessel lumen.

CONCLUSION

Our multisequence CNN model can identify the presence of SEC from ultrasound keyframes with an AUC of 0.74, which could enable screening applications and enable more SEC data discovery. The model does not require the expert intervention or additional clinician reporting time that are currently significant barriers to SEC adoption. Model and processed data sets are publicly available at https://github.com/Ouwen/automatic-spontaneous-echo-contrast.

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.

A Hybrid Deep Learning Approach to Identify Preventable Childhood Hearing Loss

OBJECTIVE

Childhood hearing loss has well-known, lifelong consequences. Infection-related hearing loss disproportionately affects underserved communities yet can be prevented with early identification and treatment. This study evaluates the utility of machine learning in automating tympanogram classifications of the middle ear to facilitate layperson-guided tympanometry in resource-constrained communities.

DESIGN

Diagnostic performance of a hybrid deep learning model for classifying narrow-band tympanometry tracings was evaluated. Using 10-fold cross-validation, a machine learning model was trained and evaluated on 4810 pairs of tympanometry tracings acquired by an audiologist and layperson. The model was trained to classify tracings into types A (normal), B (effusion or perforation), and C (retraction), with the audiologist interpretation serving as reference standard. Tympanometry data were collected from 1635 children from October 10, 2017, to March 28, 2019, from two previous cluster-randomized hearing screening trials (NCT03309553, NCT03662256). Participants were school-aged children from an underserved population in rural Alaska with a high prevalence of infection-related hearing loss. Two-level classification performance statistics were calculated by treating type A as pass and types B and C as refer.

RESULTS

For layperson-acquired data, the machine-learning model achieved a sensitivity of 95.2% (93.3, 97.1), specificity of 92.3% (91.5, 93.1), and area under curve of 0.968 (0.955, 0.978). The model's sensitivity was greater than that of the tympanometer's built-in classifier [79.2% (75.5, 82.8)] and a decision tree based on clinically recommended normative values [56.9% (52.4, 61.3)]. For audiologist-acquired data, the model achieved a higher AUC of 0.987 (0.980, 0.993), had an equivalent sensitivity of 95.2 (93.3, 97.1), and a higher specificity of 97.7 (97.3, 98.2).

CONCLUSIONS

Machine learning can detect middle ear disease with comparable performance to an audiologist using tympanograms acquired either by an audiologist or a layperson. Automated classification enables the use of layperson-guided tympanometry in hearing screening programs in rural and underserved communities, where early detection of treatable pathology in children is crucial to prevent the lifelong adverse effects of childhood hearing loss.

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.

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.

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].

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.

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.

Prostate Cancer Detection Using 3-D Shear Wave Elasticity Imaging

Transrectal ultrasound (TRUS) B-mode imaging provides insufficient sensitivity and specificity for prostate cancer (PCa) targeting when used for biopsy guidance. Shear wave elasticity imaging (SWEI) is an elasticity imaging technique that has been commercially implemented and is sensitive and specific for PCa. We have developed a SWEI system capable of 3-D data acquisition using a dense acoustic radiation force (ARF) push approach that leads to enhanced shear wave signal-to-noise ratio compared with that of the commercially available SWEI systems and facilitates screening of the entire gland before biopsy. Additionally, we imaged and assessed 36 patients undergoing radical prostatectomy using 3-D SWEI and determined a shear wave speed threshold separating PCa from healthy prostate tissue with sensitivities and specificities akin to those for multiparametric magnetic resonance imaging fusion biopsy. The approach measured the mean shear wave speed in each prostate region to be 4.8 m/s (Young's modulus E = 69.1 kPa) in the peripheral zone, 5.3 m/s (E = 84.3 kPa) in the central gland and 6.0 m/s (E = 108.0 kPa) for PCa with statistically significant (p < 0.0001) differences among all regions. Three-dimensional SWEI receiver operating characteristic analyses identified a threshold of 5.6 m/s (E = 94.1 kPa) to separate PCa from healthy tissue with a sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under the curve (AUC) of 81%, 82%, 69%, 89% and 0.84, respectively. Additionally, a shear wave speed ratio was assessed to normalize for tissue compression and patient variability, which yielded a threshold of 1.11 to separate PCa from healthy prostate tissue and was accompanied by a substantial increase in specificity, PPV and AUC, where the sensitivity, specificity, PPV, NPV and AUC were 75%, 90%, 79%, 88% and 0.90, respectively. This work illustrates the feasibility of using 3-D SWEI data to detect and localize PCa and demonstrates the benefits of normalizing for applied compression during data acquisition for use in biopsy targeting studies.

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.

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.

Shear wave dispersion as a potential biomarker for cervical remodeling during pregnancy: evidence from a non-human primate model

Shear wave dispersion (variation of phase velocity with frequency) occurs in tissues with layered and anisotropic microstructure and viscous components, such as the uterine cervix. This phenomenon, mostly overlooked in previous applications of cervical Shear Wave Elasticity Imaging (SWEI) for preterm birth risk assessment, is expected to change drastically during pregnancy due to cervical remodeling. Here we demonstrate the potential of SWEI-based descriptors of dispersion as potential biomarkers for cervical remodeling during pregnancy. First, we performed a simulation-based pre-selection of two SWEI-based dispersion descriptors: the ratio R of group velocities computed with particle-velocity and particle-displacement, and the slope S of the phase velocity vs. frequency. The pre-selection consisted of comparing the contrast-to-noise ratio (CNR) of dispersion descriptors in materials with different degrees of dispersion with respect to a low-dispersive medium. Shear waves induced in these media by SWEI were simulated with a finite-element model of Zener viscoelastic solids. The pre-selection also considered two denoising strategies to improve CNR: a low-pass filter with automatic frequency cutoff determination, and singular value decomposition of shear wave displacements. After pre-selection, the descriptor-denoising combination that produced the largest CNR was applied to SWEI cervix data from 18 pregnant Rhesus macaques acquired at weeks 10 (mid-pregnancy stage) and 23 (late pregnancy stage) of the 24.5-week full pregnancy. A maximum likelihood linear mixed-effects model (LME) was used to evaluate the dependence of the dispersion descriptor on pregnancy stage, maternal age, parity and other experimental factors. The pre-selection study showed that descriptor S combined with singular value decomposition produced a CNR 11.6 times larger than the other descriptor and denoising strategy combinations. In the Non-Human Primates (NHP) study, the LME model showed that descriptor S significantly decreased from mid to late pregnancy (-0.37 ± 0.07 m/s-kHz per week, p <0.00001) with respect to the base value of 15.5 ± 1.9 m/s-kHz. This change was more significant than changes in other SWEI features such as the group velocity previously reported. Also, S varied significantly between the anterior and posterior portions of the cervix (p =0.02) and with maternal age (p =0.008). Given the potential of shear wave dispersion to track cervical remodeling, we will extend its application to ongoing longitudinal human studies.

Multiparametric Ultrasound for Targeting Prostate Cancer: Combining ARFI, SWEI, QUS and B-Mode

Diagnosing prostate cancer through standard transrectal ultrasound (TRUS)-guided biopsy is challenging because of the sensitivity and specificity limitations of B-mode imaging. We used a linear support vector machine (SVM) to combine standard TRUS imaging data with acoustic radiation force impulse (ARFI) imaging data, shear wave elasticity imaging (SWEI) data and quantitative ultrasound (QUS) midband fit data to enhance lesion contrast into a synthesized multiparametric ultrasound volume. This SVM was trained and validated using a subset of 20 patients and tested on a second subset of 10 patients. Multiparametric US led to a statistically significant improvements in contrast, contrast-to-noise ratio (CNR) and generalized CNR (gCNR) when compared with standard TRUS B-mode and SWEI; in contrast and CNR when compared with MF; and in CNR when compared with ARFI. ARFI, MF and SWEI also outperformed TRUS B-mode in contrast, with MF outperforming B-mode in CNR and gCNR as well. ARFI, although only yielding statistically significant differences in contrast compared with TRUS B-mode, captured critical qualitative features for lesion identification. Multiparametric US enhanced lesion visibility metrics and is a promising technique for targeted TRUS-guided prostate biopsy in the future.

MimickNet, Mimicking Clinical Image Post- Processing Under Black-Box Constraints

Image post-processing is used in clinical-grade ultrasound scanners to improve image quality (e.g., reduce speckle noise and enhance contrast). These post-processing techniques vary across manufacturers and are generally kept proprietary, which presents a challenge for researchers looking to match current clinical-grade workflows. We introduce a deep learning framework, MimickNet, that transforms conventional delay-and-summed (DAS) beams into the approximate Dynamic Tissue Contrast Enhanced (DTCE™) post-processed images found on Siemens clinical-grade scanners. Training MimickNet only requires post-processed image samples from a scanner of interest without the need for explicit pairing to DAS data. This flexibility allows MimickNet to hypothetically approximate any manufacturer's post-processing without access to the pre-processed data. MimickNet post-processing achieves a 0.940 ± 0.018 structural similarity index measurement (SSIM) compared to clinical-grade post-processing on a 400 cine-loop test set, 0.937 ± 0.025 SSIM on a prospectively acquired dataset, and 0.928 ± 0.003 SSIM on an out-of-distribution cardiac cine-loop after gain adjustment. To our knowledge, this is the first work to establish deep learning models that closely approximate ultrasound post-processing found in current medical practice. MimickNet serves as a clinical post-processing baseline for future works in ultrasound image formation to compare against. Additionally, it can be used as a pretrained model for fine-tuning towards different post-processing techniques. To this end, we have made the MimickNet software, phantom data, and permitted in vivo data open-source at https://github.com/ouwen/MimickNet.

Measurement of Viscoelastic Material Model Parameters Using Fractional Derivative Group Shear Wave Speeds in Simulation and Phantom Data

While ultrasound shear wave elastography originally focused on tissue stiffness under the assumption of elasticity, recent work has investigated the higher order, viscoelastic properties of the tissue. This article presents a method to use group shear wave speeds (gSWSs) at a series of derivative orders to characterize viscoelastic materials. This method uses a least squares fitting algorithm to match the experimental data to the calculated gSWS data, using an assumed material model and excitation geometry matched to the experimental imaging configuration. Building on a previous study that used particle displacement, velocity, and acceleration signals, this study extends the analysis to a continuous range of fractional derivative orders between 0 and 2. The method can be applied to any material model. Herein, material characterization was performed for three different two-parameter models and three different three-parameter models. This group speed-based method was applied to both shear wave simulations with ultrasonic tracking and experimental acquisitions in viscoelastic phantoms [similar to the Phase II Quantitative Imaging Biomarkers Alliance (QIBA) phantoms]. In both the cases, the group speed method produced more repeatable characterization overall than fitting the phase velocity results from the peak of the 2-D Fourier transform. Results suggest that the linear attenuation model is a better fit than the Voigt model for the viscoelastic QIBA phantoms.

Tractable calculation of the Green's tensor for shear wave propagation in an incompressible, transversely isotropic material

Assessing material properties from observations of shear wave propagation following an acoustic radiation force impulse (ARFI) excitation is difficult in anisotropic materials because of the complex relations among the propagation direction, shear wave polarizations, and material symmetries. In this paper, we describe a method to calculate shear wave signals using Green’s tensor methods in an incompressible, transversely isotropic (TI) material characterized by three material parameters. The Green’s tensor is written as the sum of an analytic expression for the SH propagation mode, and an integral expression for the SV propagation mode that can be evaluated by interpolation within precomputed integral functions with an efficiency comparable to the evaluation of a closed-form expression. By using parametrized integral functions, the number of requried numerical integrations is reduced by a factor of 10² − 10⁹ depending on the specific problem under consideration. Results are presented for the case of a point source positioned at the origin and a tall Gaussian source similar to an ARFI excitation. For an experimental configuration with a tilted material symmetry axis, results show that shear wave signals exhibit structures that are sufficiently complex to allow measurement of all three material parameters that characterize an incompressible, TI material.

Corrections to "On the Quantitative Potential of Viscoelastic Response (VisR) Ultrasound Using the One-Dimensional Mass-Spring-Damper Model"

In the original publication of this paper [1], equation (3) contained sign errors for the amplitude of the third and fourth Heaviside functions. The corrected equation is shown in the following: [Formula: see text].

Characterization of Viscoelastic Materials Using Group Shear Wave Speeds

Recent investigations of viscoelastic properties of materials have been performed by observing shear wave propagation following localized, impulsive excitations, and Fourier decomposing the shear wave signal to parameterize the frequency-dependent phase velocity using a material model. This paper describes a new method to characterize viscoelastic materials using group shear wave speeds , , and determined from the shear wave displacement, velocity, and acceleration signals, respectively. Materials are modeled using a two-parameter linear attenuation model with phase velocity and dispersion slope at a reference frequency of 200 Hz. Analytically calculated lookup tables are used to determine the two material parameters from pairs of measured group shear wave speeds. Green's function calculations are used to validate the analytic model. Results are reported for measurements in viscoelastic and approximately elastic phantoms and demonstrate good agreement with phase velocities measured using Fourier analysis of the measured shear wave signals. The calculated lookup tables are relatively insensitive to the excitation configuration. While many commercial shear wave elasticity imaging systems report group shear wave speeds as the measures of material stiffness, this paper demonstrates that differences , , and of group speeds are first-order measures of the viscous properties of materials.

Quantitative assessment of cervical softening during pregnancy in the Rhesus macaque with shear wave elasticity imaging

Abnormal parturition, e.g. pre- or post-term birth, is associated with maternal and neonatal morbidity and increased economic burden. This could potentially be prevented by accurate detection of abnormal softening of the uterine cervix. Shear wave elasticity imaging (SWEI) techniques that quantify tissue softness, such as shear wave speed (SWS) measurement, are promising for evaluation of the cervix. Still, interpretation of results can be complicated by biological variability (i.e. spatial variations of cervix stiffness, parity), as well as by experimental factors (i.e. type of transducer, posture during scanning). Here we investigated the ability of SWEI to detect cervical softening, as well as sources of SWS variability that can affect this task, in the pregnant and nonpregnant Rhesus macaque. Specifically, we evaluated SWS differences when imaging the cervix transabdominally with a typical linear array abdominal transducer, and transrectally with a prototype intracavitary linear array transducer. Linear mixed effects (LME) models were used to model SWS as a function of menstrual cycle day (in nonpregnant animals) and gestational age (in pregnant animals). Other variables included parity, shear wave direction, and cervix side (anterior versus posterior). In the nonpregnant cervix, the LME model indicated that SWS increased by 2% (95% confidence interval 0-3%) per day, starting eight days before menstruation. During pregnancy, SWS significantly decreased at a rate of 6% (95% CI 5-7%) per week (intracavitary approach) and 3% (95% CI 2-4%) per week (transabdominal approach), and interactions between the scanning approach and other fixed effects were also significant. These results suggest that, while absolute SWS values are influenced by factors such as scanning approach and SWEI implementation, these sources of variability do not compromise the sensitivity of SWEI to cervical softening. Our results also highlight the importance of standardizing SWEI approaches to improve their accuracy for cervical assessment.

Impact of Acoustic Radiation Force Excitation Geometry on Shear Wave Dispersion and Attenuation Estimates

Shear wave elasticity imaging (SWEI) characterizes the mechanical properties of human tissues to differentiate healthy from diseased tissue. Commercial scanners tend to reconstruct shear wave speeds for a region of interest using time-of-flight methods reporting a single shear wave speed (or elastic modulus) to the end user under the assumptions that tissue is elastic and shear wave speeds are not dependent on the frequency content of the shear waves. Human tissues, however, are known to be viscoelastic, resulting in dispersion and attenuation. Shear wave spectroscopy and spectral methods have been previously reported in the literature to quantify shear wave dispersion and attenuation, commonly making an assumption that the acoustic radiation force excitation acts as a cylindrical source with a known geometric shear wave amplitude decay. This work quantifies the bias in shear dispersion and attenuation estimates associated with making this cylindrical wave assumption when applied to shear wave sources with finite depth extents, as commonly occurs with realistic focal geometries, in elastic and viscoelastic media. Bias is quantified using analytically derived shear wave data and shear wave data generated using finite-element method models. Shear wave dispersion and attenuation bias (up to 15% for dispersion and 41% for attenuation) is greater for more tightly focused acoustic radiation force sources with smaller depths of field relative to their lateral extent (height-to-width ratios <16). Dispersion and attenuation errors associated with assuming a cylindrical geometric shear wave decay in SWEI can be appreciable and should be considered when analyzing the viscoelastic properties of tissues with acoustic radiation force source distributions with limited depths of field.

Detection of Changes in Cervical Softness Using Shear Wave Speed in Early versus Late Pregnancy: An in Vivo Cross-Sectional Study

The aim of this study was to assess the ability of shear wave elasticity imaging (SWEI) to detect changes in cervical softness between early and late pregnancy. Using a cross-sectional study design, shear wave speed (SWS) measurements were obtained from women in the first trimester (5-14 wk of gestation) and compared with estimates from a previous study of women at term (37-41 wk). Two sets of five SWS measurements were made using commercial SWEI applications on an ultrasound system equipped with a prototype catheter transducer (128 elements, 3-mm diameter, 14-mm aperture). Average SWS estimates were 4.42 ± 0.32 m/s (n = 12) for the first trimester and 2.13 ± 0.66 m/s (n = 18) for the third trimester (p <0.0001). The area under the curve was 0.95 (95% confidence interval: 0.82-0.99) with a sensitivity and specificity of 83%. SWS estimates indicated that the third-trimester cervix is significantly softer than the first-trimester cervix. SWEI methods may be promising for assessing changes in cervical softness.

Evaluating the Benefit of Elevated Acoustic Output in Harmonic Motion Estimation in Ultrasonic Shear Wave Elasticity Imaging

Harmonic imaging techniques have been applied in ultrasonic elasticity imaging to obtain higher-quality tissue motion tracking data. However, harmonic tracking can be signal-to-noise ratio and penetration depth limited during clinical imaging, resulting in decreased yield of successful shear wave speed measurements. A logical approach is to increase the source pressure, but the in situ pressures used in diagnostic ultrasound have been subject to a de facto upper limit based on the Food and Drug Administration guideline for the mechanical index (MI <1.9). A recent American Institute of Ultrasound in Medicine report concluded that an in situ MI up to 4.0 could be warranted without concern for increased risk of cavitation in non-fetal tissues without gas bodies if there were a concurrent clinical benefit. This work evaluates the impact of using an elevated MI in harmonic motion tracking for hepatic shear wave elasticity imaging. The studies indicate that high-MI harmonic tracking increased shear wave speed estimation yield by 27% at a focal depth of 5 cm, with larger yield increase in more difficult-to-image patients. High-MI tracking improved harmonic tracking data quality by increasing the signal-to-noise ratio and decreasing jitter in the tissue motion data. We conclude that there is clinical benefit to use of elevated acoustic output in shear wave tracking, particularly in difficult-to-image patients.

Quantifying Image Quality Improvement Using Elevated Acoustic Output in B-Mode Harmonic Imaging

Tissue harmonic imaging has been widely used in abdominal imaging because of its significant reduction in acoustic noise compared with fundamental imaging. However, tissue harmonic imaging can be limited by both signal-to-noise ratio and penetration depth during clinical imaging, resulting in decreased diagnostic utility. A logical approach would be to increase the source pressure, but the in situ pressures used in diagnostic ultrasound are subject to a de facto upper limit based on the U.S. Food and Drug Administration guideline for the mechanical index (<1.9). A recent American Institute of Ultrasound in Medicine report concluded that an effective mechanical index ≤4.0 could be warranted without concern for increased risk of cavitation in non-fetal tissues without gas bodies, but would only be justified if there were a concurrent improvement in image quality and diagnostic utility. This work evaluates image quality differences between normal and elevated acoustic output hepatic harmonic imaging using a transmit frequency of 1.8 MHz. The results indicate that harmonic imaging using elevated acoustic output leads to modest improvements (3%-7%) in contrast-to-noise ratio of hypo-echoic hepatic vessels and increases in imaging penetration depth on the order of 4 mm per mechanical index increase of 0.1 for a given focal depth. Difficult-to-image patients who suffer from poor ultrasound image quality exhibited larger improvements than easy-to-image study participants.

Accounting for the Spatial Observation Window in the 2-D Fourier Transform Analysis of Shear Wave Attenuation

Recent measurements of shear wave propagation in viscoelastic materials have been analyzed by constructing the 2-D Fourier transform (2DFT) of the shear wave signal and measuring the phase velocity c(ω) and attenuation α(ω) from the peak location and full width at half-maximum (FWHM) of the 2DFT signal at discrete frequencies. However, when the shear wave is observed over a finite spatial range, the 2DFT signal is a convolution of the true signal and the observation window, and measurements using the FWHM can yield biased results. In this study, we describe a method to account for the size of the spatial observation window using a model of the 2DFT signal and a non-linear, least-squares fitting procedure to determine c(ω) and α(ω). Results from the analysis of finite-element simulation data agree with c(ω) and α(ω) calculated from the material parameters used in the simulation. Results obtained in a viscoelastic phantom indicate that the measured attenuation is independent of the observation window and agree with measurements of c(ω) and α(ω) obtained using the previously described progressive phase and exponential decay analysis.

Assessment of Structural Heterogeneity and Viscosity in the Cervix Using Shear Wave Elasticity Imaging: Initial Results from a Rhesus Macaque Model

Shear wave elasticity imaging has shown promise in evaluation of the pregnant cervix. Changes in shear wave group velocity have been attributed exclusively to changes in stiffness. This assumes homogeneity within the region of interest and purely elastic tissue behavior. However, the cervix is structurally/microstructurally heterogeneous and viscoelastic. We therefore developed strategies to investigate these complex tissue properties. Shear wave elasticity imaging was performed ex vivo on 14 unripened and 13 misoprostol-ripened cervix specimens from rhesus macaques. After tests of significant and uniform shear wave displacement, as well as reliability of estimates, group velocity decreased significantly from the distal (vaginal) to proximal (uterine) end of unripened, but not ripened, specimens. Viscosity was quantified by the slope of the phase velocity versus frequency. Dispersion was observed in both groups (median: 5.5 m/s/kHz, interquartile range: 1.5-12.0 m/s/kHz), also decreasing toward the proximal cervix. This work suggests that comprehensive assessment of complex tissues such as cervix requires consideration of structural heterogeneity and viscosity.

Ultrasonic Shear Wave Elasticity Imaging Sequencing and Data Processing Using a Verasonics Research Scanner

Ultrasound elasticity imaging has been developed over the last decade to estimate tissue stiffness. Shear wave elasticity imaging (SWEI) quantifies tissue stiffness by measuring the speed of propagating shear waves following acoustic radiation force excitation. This paper presents the sequencing and data processing protocols of SWEI using a Verasonics system. The selection of the sequence parameters in a Verasonics programming script is discussed in detail. The data processing pipeline to calculate group shear wave speed (SWS), including tissue motion estimation, data filtering, and SWS estimation, is demonstrated. In addition, the procedures for calibration of beam position, scanner timing, and transducer face heating are provided to avoid SWS measurement bias and transducer damage.

Guidelines for Finite-Element Modeling of Acoustic Radiation Force-Induced Shear Wave Propagation in Tissue-Mimicking Media

Ultrasound shear wave elastography is emerging as an important imaging modality for evaluating tissue material properties. In its practice, some systematic biases have been associated with ultrasound frequencies, focal depths and configuration, and transducer types (linear versus curvilinear), along with displacement estimation and shear wave speed estimation algorithms. Added to that, soft tissues are not purely elastic, so shear waves will travel at different speeds depending on their spectral content, which can be modulated by the acoustic radiation force (ARF) excitation focusing, duration, and the frequency-dependent stiffness of the tissue. To understand how these different acquisition and material property parameters may affect the measurements of shear wave velocity, the simulations of the propagation of shear waves generated by ARF excitations in viscoelastic media are a very important tool. This paper serves to provide an in-depth description of how these simulations are performed. The general scheme is broken into three components: 1) simulation of the 3-D ARF push beam; 2) applying that force distribution to a finite-element model; and 3) extraction of the motion data for post-processing. All three components will be described in detail and combined to create a simulation platform that is powerful for developing and testing algorithms for academic and industrial researchers involved in making quantitative shear-wave-based measurements of tissue material properties.

Estimation of Shear Wave Speed in the Rhesus Macaques' Uterine Cervix

Cervical softness is a critical parameter in pregnancy. Clinically, preterm birth is associated with premature cervical softening and postdates birth is associated with delayed cervical softening. In practice, the assessment of softness is subjective, based on digital examination. Fortunately, objective, quantitative techniques to assess softness, and other parameters associated with microstructural cervical change are emerging. One of these is shear wave speed (SWS) estimation. In principle, this allows objective characterization of stiffness because waves travel more slowly in softer tissue. We are studying SWS in humans and rhesus macaques, the latter in order to accelerate translation from bench to bedside. For the current study, we estimated SWS in ex vivo cervices of rhesus macaques, n=24 nulliparous (never given birth) and n=9 multiparous (delivered at least one baby). Misoprostol (a prostaglandin used to soften human cervices prior to gynecological procedures) was administered to 13 macaques prior to necropsy (nulliparous: 7; multiparous: 6). SWS measurements were made at predetermined locations from the distal to proximal end of the cervix on both the anterior and posterior cervix, with five repeat measures at each location. The intent was to explore macaque cervical microstructure, including biological and spatial variability, to elucidate the similarities and differences between the macaque and the human cervix in order to facilitate future in vivo studies. We found that SWS is dependent on location in the normal nonpregnant macaque cervix, as in the human cervix. Unlike the human cervix, we detected no difference between ripened and unripened rhesus macaque cervix samples, nor nulliparous versus multiparous samples, although we observed a trend toward stiffer tissue in nulliparous samples. We found rhesus macaque cervix to be much stiffer than human, which is important for technique refinement. These findings are useful for guiding study of cervical microstructure in both humans and macaques.

On the Quantitative Potential of Viscoelastic Response (VisR) Ultrasound Using the One-Dimensional Mass-Spring-Damper Model

Viscoelastic response (VisR) ultrasound is an acoustic radiation force (ARF)-based imaging method that fits induced displacements to a one-dimensional (1-D) mass-spring-damper (MSD) model to estimate the ratio of viscous to elastic moduli, τ, in viscoelastic materials. Error in VisR τ estimation arises from inertia and acoustic displacement underestimation. These error sources are herein evaluated using finite-element method (FEM) simulations, error correction methods are developed, and corrected VisR τ estimates are compared with true simulated τ values to assess VisR's relevance to quantifying viscoelasticity. With regard to inertia, adding a mass term in series with the Voigt model, to achieve the MSD model, accounts for inertia due to tissue mass when ideal point force excitations are used. However, when volumetric ARF excitations are applied, the induced complex system inertia is not described by the single-degree-of-freedom MSD model, causing VisR to overestimate τ. Regarding acoustic displacement underestimation, associated deformation of ARF-induced displacement profiles further distorts VisR τ estimates. However, median error in VisR τ is reduced to approximately -10% using empirically derived error correction functions applied to simulated viscoelastic materials with viscous and elastic properties representative of tissue. The feasibility of corrected VisR imaging is then demonstrated in vivo in the rectus femoris muscle of an adult with no known neuromuscular disorders. These results suggest VisR's potential relevance to quantifying viscoelastic properties clinically.

Evaluating the Improvement in Shear Wave Speed Image Quality Using Multidimensional Directional Filters in the Presence of Reflection Artifacts

Shear waves propagating through interfaces where there is a change in stiffness cause reflected waves that can lead to artifacts in shear wave speed (SWS) reconstructions. Two-dimensional (2-D) directional filters are commonly used to reduce in-plane reflected waves; however, SWS artifacts arise from both in- and out-of-imaging-plane reflected waves. Herein, we introduce 3-D shear wave reconstruction methods as an extension of the previous 2-D estimation methods and quantify the reduction in image artifacts through the use of volumetric SWS monitoring and 4-D-directional filters. A Gaussian acoustic radiation force impulse excitation was simulated in phantoms with Young's modulus (E) of 3 kPa and a 5-mm spherical lesion with E = 6, 12, or 18.75 kPa. The 2-D-, 3-D-, and 4-D-directional filters were applied to the displacement profiles to reduce in-and out-of-plane reflected wave artifacts. Contrast-to-noise ratio and SWS bias within the lesion were calculated for each reconstructed SWS image to evaluate the image quality. For 2-D SWS image reconstructions, the 3-D-directional filters showed greater improvements in image quality than the 2-D filters, and the 4-D-directional filters showed marginal improvement over the 3-D filters. Although 4-D-directional filters can further reduce the impact of large magnitude out-of-plane reflection artifacts in SWS images, computational overhead and transducer costs to acquire 3-D data may outweigh the modest improvements in image quality. The 4-D-directional filters have the largest impact in reducing reflection artifacts in 3-D SWS volumes.

Evaluating the Improvement in Shear Wave Speed Image Quality Using Multidimensional Directional Filters in the Presence of Reflection Artifacts

Shear waves propagating through interfaces where there is a change in stiffness cause reflected waves that can lead to artifacts in shear wave speed (SWS) reconstructions. Two-dimensional (2-D) directional filters are commonly used to reduce in-plane reflected waves; however, SWS artifacts arise from both in- and out-of-imaging-plane reflected waves. Herein, we introduce 3-D shear wave reconstruction methods as an extension of the previous 2-D estimation methods and quantify the reduction in image artifacts through the use of volumetric SWS monitoring and 4-D-directional filters. A Gaussian acoustic radiation force impulse excitation was simulated in phantoms with Young's modulus (E) of 3 kPa and a 5-mm spherical lesion with E = 6, 12, or 18.75 kPa. The 2-D-, 3-D-, and 4-D-directional filters were applied to the displacement profiles to reduce in-and out-of-plane reflected wave artifacts. Contrast-to-noise ratio and SWS bias within the lesion were calculated for each reconstructed SWS image to evaluate the image quality. For 2-D SWS image reconstructions, the 3-D-directional filters showed greater improvements in image quality than the 2-D filters, and the 4-D-directional filters showed marginal improvement over the 3-D filters. Although 4-D-directional filters can further reduce the impact of large magnitude out-of-plane reflection artifacts in SWS images, computational overhead and transducer costs to acquire 3-D data may outweigh the modest improvements in image quality. The 4-D-directional filters have the largest impact in reducing reflection artifacts in 3-D SWS volumes.

Identifying Clinically Significant Prostate Cancers using 3-D In Vivo Acoustic Radiation Force Impulse Imaging with Whole-Mount Histology Validation

Overly aggressive prostate cancer (PCa) treatment adversely affects patients and places an unnecessary burden on our health care system. The inability to identify and grade clinically significant PCa lesions is a factor contributing to excessively aggressive PCa treatment, such as radical prostatectomy, instead of more focal, prostate-sparing procedures such as cryotherapy and high-dose radiation therapy. We have performed 3-D in vivo B-mode and acoustic radiation force impulse (ARFI) imaging using a mechanically rotated, side-fire endorectal imaging array to identify regions suspicious for PCa in 29 patients being treated with radical prostatectomies for biopsy-confirmed PCa. Whole-mount histopathology analyses were performed to identify regions of clinically significant/insignificant PCa lesions, atrophy and benign prostatic hyperplasia. Regions of suspicion for PCa were reader-identified in ARFI images based on boundary delineation, contrast, texture and location. These regions of suspicion were compared with histopathology identified lesions using a nearest-neighbor regional localization approach. Of all clinically significant lesions identified on histopathology, 71.4% were also identified using ARFI imaging, including 79.3% of posterior and 33.3% of anterior lesions. Among the ARFI-identified lesions, 79.3% corresponded to clinically significant PCa lesions, with these lesions having higher indices of suspicion than clinically insignificant PCa. ARFI imaging had greater sensitivity for posterior versus anterior lesions because of greater displacement signal-to-noise ratio and finer spatial sampling. Atrophy and benign prostatic hyperplasia can cause appreciable prostate anatomy distortion and heterogeneity that confounds ARFI PCa lesion identification; however, in general, ARFI regions of suspicion did not coincide with these benign pathologies.

On System-Dependent Sources of Uncertainty and Bias in Ultrasonic Quantitative Shear-Wave Imaging

Ultrasonic quantitative shear-wave imaging methods have been developed over the last decade to estimate tissue elasticity by measuring the speed of propagating shear waves following acoustic radiation force excitation. This work discusses eight sources of uncertainty and bias arising from ultrasound system-dependent parameters in ultrasound shear-wave speed (SWS) measurements. Each of the eight sources of error is discussed in the context of a linear, isotropic, elastic, homogeneous medium, combining previously reported analyses with Field II simulations, full-wave 2-D acoustic propagation simulations, and experimental studies. Errors arising from both spatial and temporal sources lead to errors in SWS measurements. Arrival time estimation noise, speckle bias, hardware fluctuations, and phase aberration cause uncertainties (variance) in SWS measurements, while pulse repetition frequency (PRF) and beamforming errors, as well as coupling medium sound speed mismatch, cause biases in SWS measurements (accuracy errors). Calibration of the sources of bias is an important step in the development of shear-wave imaging systems. In a well-calibrated system, where the sources of bias are minimized, and averaging over a region of interest (ROI) is employed to reduce the sources of uncertainty, an SWS error can be expected.

Pathway-Specific Striatal Substrates for Habitual Behavior

The dorsolateral striatum (DLS) is implicated in habit formation. However, the DLS circuit mechanisms underlying habit remain unclear. A key role for DLS is to transform sensorimotor cortical input into firing of output neurons that project to the mutually antagonistic direct and indirect basal ganglia pathways. Here we examine whether habit alters this input-output function. By imaging cortically evoked firing in large populations of pathway-defined striatal projection neurons (SPNs), we identify features that strongly correlate with habitual behavior on a subject-by-subject basis. Habitual behavior correlated with strengthened DLS output to both pathways as well as a tendency for action-promoting direct pathway SPNs to fire before indirect pathway SPNs. In contrast, habit suppression correlated solely with a weakened direct pathway output. Surprisingly, all effects were broadly distributed in space. Together, these findings indicate that the striatum imposes broad, pathway-specific modulations of incoming activity to render learned motor behaviors habitual.

Detection of prostate cancer with multiparametric MRI (mpMRI): effect of dedicated reader education on accuracy and confidence of index and anterior cancer diagnosis

PURPOSE

To evaluate the impact of dedicated reader education on accuracy/confidence of peripheral zone index cancer and anterior prostate cancer (PCa) diagnosis with mpMRI; secondary aim was to assess the ability of readers to differentiate low-grade cancer (Gleason 6 or below) from high-grade cancer (Gleason 7+).

MATERIALS AND METHODS

Five blinded radiology fellows evaluated 31 total prostate mpMRIs in this IRB-approved, HIPAA-compliant, retrospective study for index lesion detection, confidence in lesion diagnosis (1-5 scale), and Gleason grade (Gleason 6 or lower vs. Gleason 7+). Following a dedicated education program, readers reinterpreted cases after a memory extinction period, blinded to initial reads. Reference standard was established combining whole mount histopathology with mpMRI findings by a board-certified radiologist with 5 years of prostate mpMRI experience.

RESULTS

Index cancer detection: pre-education accuracy 74.2%; post-education accuracy 87.7% (p = 0.003). Confidence in index lesion diagnosis: pre-education 4.22 ± 1.04; post-education 3.75 ± 1.41 (p = 0.0004). Anterior PCa detection: pre-education accuracy 54.3%; post-education accuracy 94.3% (p = 0.001). Confidence in anterior PCa diagnosis: pre-education 3.22 ± 1.54; post-education 4.29 ± 0.83 (p = 0.0003). Gleason score accuracy: pre-education 54.8%; post-education 73.5% (p = 0.0005).

CONCLUSIONS

A dedicated reader education program on PCa detection with mpMRI was associated with a statistically significant increase in diagnostic accuracy of index cancer and anterior cancer detection as well as Gleason grade identification as compared to pre-education values. This was also associated with a significant increase in reader diagnostic confidence. This suggests that substantial interobserver variability in mpMRI interpretation can potentially be reduced with a focus on education and that this can occur over a fellowship training year.

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.

Analyzing the Impact of Increasing Mechanical Index and Energy Deposition on Shear Wave Speed Reconstruction in Human Liver

Shear wave elasticity imaging (SWEI) has found success in liver fibrosis staging. This work evaluates hepatic SWEI measurement success as a function of push pulse energy using two mechanical index (MI) values (1.6 and 2.2) over a range of pulse durations. Shear wave speed (SWS) was measured in the livers of 26 study subjects with known or potential chronic liver diseases. Each measurement consisted of eight SWEI sequences, each with different push energy configurations. The rate of successful SWS estimation was linearly proportional to the push energy. SWEI measurements with higher push energy were successful in patients for whom standard push energy levels failed. The findings also suggest that liver capsule depth could be used prospectively to identify patients who would benefit from elevated output. We conclude that there is clinical benefit to using elevated acoustic output for hepatic SWS measurement in patients with deeper livers.

Changes in shear wave speed pre- and post-induction of labor: a feasibility study

OBJECTIVE

To explore the feasibility of using shear wave speed (SWS) estimates to detect differences in cervical softening pre- and post-ripening in women undergoing induction of labor.

METHODS

Subjects at 37-41 weeks' gestation undergoing cervical ripening before induction of labor were recruited (n = 20). Examinations, performed prior to administration of misoprostol and 4 h later included Bishop score, transvaginal ultrasound measurement of cervical length, and 10 replicate SWS measurements using an ultrasound system equipped with a prototype transducer (128 element, 3 mm diameter, 14 mm aperture) attached to the clinician's hand. Subjects were divided into two groups, 'not-in-labor' and 'marked-progression', based on cervical evaluation at the second examination. Measurements were compared via individual paired hypotheses tests and using a linear mixed model, with the latter also used to compare groups. Spearman's rank correlation coefficient was used to compare SWS with Bishop score. The linear mixed model can take into account clustered data and accommodate multiple predictors simultaneously.

RESULTS

The Wilcoxon signed-rank paired test established a significant difference in pre- and post-ripening SWS, with mean SWS estimates of 2.53 ± 0.75 and 1.54 ± 0.31 m/s, respectively (P < 0.001) in the not-in-labor group (decrease in stiffness) and 1.58 ± 0.33 and 2.35 ± 0.65 m/s for the marked-progression group (increase in stiffness). The linear mixed model corroborated significant differences in pre- and post-ripening measurements in individual subjects (P < 0.001) as well as between groups (P < 0.0001). SWS estimates were significantly correlated with digitally-assessed cervical softness and marginally correlated with Bishop score as assessed by Spearman's rank correlation coefficient.

CONCLUSIONS

In-vivo SWS estimates detected stiffness differences before and after misoprostol-induced softening in term pregnancies. This ultrasonic shear elasticity imaging technique shows promise for assessing cervical softness.

Elastography Assessment of Liver Fibrosis: Society of Radiologists in Ultrasound Consensus Conference Statement

The Society of Radiologists in Ultrasound convened a panel of specialists from radiology, hepatology, pathology, and basic science and physics to arrive at a consensus regarding the use of elastography in the assessment of liver fibrosis in chronic liver disease. The panel met in Denver, Colo, on October 21-22, 2014, and drafted this consensus statement. The recommendations in this statement are based on analysis of current literature and common practice strategies and are thought to represent a reasonable approach to the noninvasive assessment of diffuse liver fibrosis.

WFUMB guidelines and recommendations for clinical use of ultrasound elastography: Part 2: breast

The breast section of these Guidelines and Recommendations for Elastography produced under the auspices of the World Federation of Ultrasound in Medicine and Biology (WFUMB) assesses the clinically used applications of all forms of elastography used in breast imaging. The literature on various breast elastography techniques is reviewed, and recommendations are made on evidence-based results. Practical advice is given on how to perform and interpret breast elastography for optimal results, with emphasis placed on avoiding pitfalls. Artifacts are reviewed, and the clinical utility of some artifacts is discussed. Both strain and shear wave techniques have been shown to be highly accurate in characterizing breast lesions as benign or malignant. The relationship between the various techniques is discussed, and recommended interpretation based on a BI-RADS-like malignancy probability scale is provided. This document is intended to be used as a reference and to guide clinical users in a practical way.

WFUMB guidelines and recommendations for clinical use of ultrasound elastography: Part 1: basic principles and terminology

Conventional diagnostic ultrasound images of the anatomy (as opposed to blood flow) reveal differences in the acoustic properties of soft tissues (mainly echogenicity but also, to some extent, attenuation), whereas ultrasound-based elasticity images are able to reveal the differences in the elastic properties of soft tissues (e.g., elasticity and viscosity). The benefit of elasticity imaging lies in the fact that many soft tissues can share similar ultrasonic echogenicities but may have different mechanical properties that can be used to clearly visualize normal anatomy and delineate pathologic lesions. Typically, all elasticity measurement and imaging methods introduce a mechanical excitation and monitor the resulting tissue response. Some of the most widely available commercial elasticity imaging methods are 'quasi-static' and use external tissue compression to generate images of the resulting tissue strain (or deformation). In addition, many manufacturers now provide shear wave imaging and measurement methods, which deliver stiffness images based upon the shear wave propagation speed. The goal of this review is to describe the fundamental physics and the associated terminology underlying these technologies. We have included a questions and answers section, an extensive appendix, and a glossary of terms in this manuscript. We have also endeavored to ensure that the terminology and descriptions, although not identical, are broadly compatible across the WFUMB and EFSUMB sets of guidelines on elastography (Bamber et al. 2013; Cosgrove et al. 2013).

WFUMB guidelines and recommendations for clinical use of ultrasound elastography: Part 3: liver

The World Federation for Ultrasound in Medicine and Biology (WFUMB) has produced these guidelines for the use of elastography techniques in liver disease. For each available technique, the reproducibility, results, and limitations are analyzed, and recommendations are given. Finally, recommendations based on the international literature and the findings of the WFUMB expert group are established as answers to common questions. The document has a clinical perspective and is aimed at assessing the usefulness of elastography in the management of liver diseases.

Material characterization of in vivo and in vitro porcine brain using shear wave elasticity

Realistic computer simulation of closed head trauma requires accurate mechanical properties of brain tissue, ideally in vivo. A substantive deficiency of most existing experimental brain data is that properties were identified through in vitro mechanical testing. This study develops a novel application of shear wave elasticity imaging to assess porcine brain tissue shear modulus in vivo. Shear wave elasticity imaging is a quantitative ultrasound technique that has been used here to examine changes in brain tissue shear modulus as a function of several experimental and physiologic parameters. Animal studies were performed using two different ultrasound transducers to explore the differences in physical response between closed skull and open skull arrangements. In vivo intracranial pressure in four animals was varied over a relevant physiologic range (2-40 mmHg) and was correlated with shear wave speed and stiffness estimates in brain tissue. We found that stiffness does not vary with modulation of intracranial pressure. Additional in vitro porcine specimens (n = 14) were used to investigate variation in brain tissue stiffness with temperature, confinement, spatial location and transducer orientation. We observed a statistically significant decrease in stiffness with increased temperature (23%) and an increase in stiffness with decreasing external confinement (22-37%). This study determined the feasibility of using shear wave elasticity imaging to characterize porcine brain tissue both in vitro and in vivo. Our results underline the importance of temperature- and skull-derived boundary conditions to brain stiffness and suggest that physiologic ranges of intracranial pressure do not significantly affect in situ brain tissue properties. Shear wave elasticity imaging allowed for brain material properties to be experimentally characterized in a physiologic setting and provides a stronger basis for assessing brain injury in computational models.

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.

Derivation and analysis of viscoelastic properties in human liver: impact of frequency on fibrosis and steatosis staging

Commercially-available shear wave imaging systems measure group shear wave speed (SWS) and often report stiffness parameters applying purely elastic material models. Soft tissues, however, are viscoelastic, and higher-order material models are necessary to characterize the dispersion associated with broadband shear waves. In this paper, we describe a robust, model-based algorithm and use a linear dispersion model to perform shear wave dispersion analysis in traditionally difficult-to-image subjects. In a cohort of 135 non-alcoholic fatty liver disease patients, we compare the performance of group SWS with dispersion analysis-derived phase velocity c(200 Hz) and dispersion slope dc/df parameters to stage hepatic fibrosis and steatosis. Area under the ROC curve (AUROC) analysis demonstrates correlation between all parameters [group SWS, c(200 Hz), and, to a lesser extent dc/df ] and fibrosis stage, whereas no correlation was observed between steatosis stage and any of the material parameters. Interestingly, optimal AUROC threshold SWS values separating advanced liver fibrosis (≥F3) from mild-to-moderate fibrosis (≤F2) were shown to be frequency-dependent, and to increase from 1.8 to 3.3 m/s over the 0 to 400 Hz shear wave frequency range.

Statistical analysis of shear wave speed in the uterine cervix

Although cervical softening is critical in pregnancy, there currently is no objective method for assessing the softness of the cervix. Shear wave speed (SWS) estimation is a noninvasive tool used to measure tissue mechanical properties such as stiffness. The goal of this study was to determine the spatial variability and assess the ability of SWS to classify ripened versus unripened tissue samples. Ex vivo human hysterectomy samples (n = 22) were collected; a subset (n = 13) were ripened. SWS estimates were made at 4 to 5 locations along the length of the canal on both anterior and posterior halves. A linear mixed model was used for a robust multivariate analysis. Receiver operating characteristic (ROC) analysis and the area under the ROC curve (AUC) were calculated to describe the utility of SWS to classify ripened versus unripened tissue samples. Results showed that all variables used in the linear mixed model were significant ( p < 0.05). Estimates at the mid location for the unripened group were 3.45 ± 0.95 m/s (anterior) and 3.56 ± 0.92 m/s (posterior), and 2.11 ± 0.45 m/s (anterior) and 2.68 ± 0.57 m/s (posterior) for the ripened ( p < 0.001). The AUCs were 0.91 and 0.84 for anterior and posterior, respectively, suggesting that SWS estimates may be useful for quantifying cervical softening.

Estimation of shear wave speed in the human uterine cervix

OBJECTIVES

To explore spatial variability within the cervix and the sensitivity of shear wave speed (SWS) to assess softness/stiffness differences in ripened (softened) vs unripened tissue.

METHODS

We obtained SWS estimates from hysterectomy specimens (n = 22), a subset of which were ripened (n = 13). Multiple measurements were made longitudinally along the cervical canal on both the anterior and posterior sides of the cervix. Statistical tests of differences in the proximal vs distal, anterior vs posterior and ripened vs unripened cervix were performed with individual two-sample t-tests and a linear mixed model.

RESULTS

Estimates of SWS increase monotonically from distal to proximal longitudinally along the cervix, they vary in the anterior compared to the posterior cervix and they are significantly different in ripened vs unripened cervical tissue. Specifically, the mid position SWS estimates for the unripened group were 3.45 ± 0.95 m/s (anterior; mean ± SD) and 3.56 ± 0.92 m/s (posterior), and 2.11 ± 0.45 m/s (anterior) and 2.68 ± 0.57 m/s (posterior) for the ripened group (P < 0.001).

CONCLUSIONS

We propose that SWS estimation may be a valuable research and, ultimately, diagnostic tool for objective quantification of cervical stiffness/softness.

Evaluating the feasibility of acoustic radiation force impulse shear wave elasticity imaging of the uterine cervix with an intracavity array: a simulation study

The uterine cervix softens, shortens, and dilates throughout pregnancy in response to progressive disorganization of its layered collagen microstructure. This process is an essential part of normal pregnancy, but premature changes are associated with preterm birth. Clinically, there are no reliable noninvasive methods to objectively measure cervical softening or assess cervical microstructure. The goal of these preliminary studies was to evaluate the feasibility of using an intracavity ultrasound array to generate acoustic radiation force impulse (ARFI) excitations in the uterine cervix through simulation, and to optimize the acoustic radiation force (ARF) excitation for shear wave elasticity imaging (SWEI) of the tissue stiffness. The cervix is a unique soft tissue target for SWEI because it has significantly greater acoustic attenuation (α = 1.3 to 2.0 dB·cm(-1)·MHz(-)1) than other soft tissues, and the pathology being studied tends to lead to an increase in tissue compliance, with healthy cervix being relatively stiff compared with other soft tissues (E ≈ 25 kPa). Additionally, the cervix can only be accessed in vivo using a transvaginal or catheter-based array, which places additional constraints on the excitation focal characteristics that can be used during SWEI. Finite element method (FEM) models of SWEI show that larger-aperture, catheter-based arrays can utilize excitation frequencies up to 7 MHz to generate adequate focal gain up to focal depths 10 to 15 mm deep, with higher frequencies suffering from excessive amounts of near-field acoustic attenuation. Using full-aperture excitations can yield ~40% increases in ARFI-induced displacements, but also restricts the depth of field of the excitation to ~0.5 mm, compared with 2 to 6 mm, which limits the range that can be used for shear wave characterization of the tissue. The center-frequency content of the shear wave particle velocity profiles ranges from 1.5 to 2.5 kHz, depending on the focal configuration and the stiffness of the material being imaged. Overall, SWEI is possible using catheter-based imaging arrays to generate adequate displacements in cervical tissue for shear wave imaging, although specific considerations must be made when optimizing these arrays for this shear wave imaging application.

Finite element modeling of impulsive excitation and shear wave propagation in an incompressible, transversely isotropic medium

Elastic properties of materials can be measured by observing shear wave propagation following localized, impulsive excitations and relating the propagation velocity to a model of the material. However, characterization of anisotropic materials is difficult because of the number of elasticity constants in the material model and the complex dependence of propagation velocity relative to the excitation axis, material symmetries, and propagation directions. In this study, we develop a model of wave propagation following impulsive excitation in an incompressible, transversely isotropic (TI) material such as muscle. Wave motion is described in terms of three propagation modes identified by their polarization relative to the material symmetry axis and propagation direction. Phase velocities for these propagation modes are expressed in terms of five elasticity constants needed to describe a general TI material, and also in terms of three constants after the application of two constraints that hold in the limit of an incompressible material. Group propagation velocities are derived from the phase velocities to describe the propagation of wave packets away from the excitation region following localized excitation. The theoretical model is compared to the results of finite element (FE) simulations performed using a nearly incompressible material model with the five elasticity constants chosen to preserve the essential properties of the material in the incompressible limit. Propagation velocities calculated from the FE displacement data show complex structure that agrees quantitatively with the theoretical model and demonstrates the possibility of measuring all three elasticity constants needed to characterize an incompressible, TI material.