Inclusion Phantom Research Articles

Three-Dimensional Shear Wave Elastography Using Acoustic Radiation Force and a 2-D Row-Column Addressing (RCA) Array.

Acoustic radiation force (ARF)-based shear wave elastography (SWE) is a clinically available ultrasound imaging mode that noninvasively and quantitatively measures tissue stiffness. Current implementations of ARF-SWE are largely limited to 2-D imaging, which does not provide a robust estimation of heterogeneous tissue mechanical properties. Existing 3-D ARF-SWE solutions that are clinically available are based on wobbler probes, which cannot provide true 3-D shear wave motion detection. Although 3-D ARF-SWE based on 2-D matrix arrays have been previously demonstrated, they do not provide a practical solution because of the need for a high channel-count ultrasound system (e.g., 1024-channel) to provide adequate volume rates and the delicate circuitries (e.g., multiplexers) that are vulnerable to the long-duration "push" pulses. To address these issues, here we propose a new 3-D ARF-SWE method based on the 2-D row-column addressing (RCA) array which has a much lower element count (e.g., 256), provides an ultrafast imaging volume rate (e.g., 2000 Hz), and can withstand the push pulses. In this study, we combined the comb-push shear elastography (CUSE) technique with 2-D RCA for enhanced SWE imaging field-of-view (FOV). In vitro phantom studies demonstrated that the proposed method had robust 3-D SWE performance in both homogenous and inclusion phantoms. An in vivo study on a breast cancer patient showed that the proposed method could reconstruct 3-D elasticity maps of the breast lesion, which was validated using a commercial ultrasound scanner. These results demonstrate strong potential for the proposed method to provide a viable and practical solution for clinical 3-D ARF-SWE.

Solid optical tissue phantom tools based on upconverting nanoparticles for biomedical applications.

Phantoms play a critical role in the development of biophotonics techniques. There is a lack of novel phantom tools in the emerging field of upconverting nanoparticles (UCNPs) for biophotonics application. This work provides a range of UCNP-based phantom tools and a manufacturing recipe to bridge the gap and accelerate the development of UCNP-based biophotonics applications. The study aims to provide a well-characterized UCNP-based solid phantom recipe and set of phantom tools to address a wide range of UCNP-based biophotonics applications. A solid phantom recipe based on silicone matrix was developed to manufacture UCNP-based phantoms. A lab built UCNP imaging system was used to characterize upconverted fluorescence emission of phantoms for linearity, homogeneity, and long-term stability. A photon time-of-flight spectroscopy technique was used to characterize the optical properties of the phantoms. In total, 24 phantoms classified into 4 types, namely homogeneous, multilayer, inclusion, and base phantoms, were manufactured. The phantoms exhibit linear behavior over the dosage range of UCNPs. The phantoms were found to be stable over a limited observed period of 4 months with a coefficient of variation of . The deep tissue imaging case showed that increasing the thickness of tissue reduced the UCNP emission. A first-of-its-kind UCNP-based solid phantom recipe was developed, and four types of UCNP phantom tools to explore biophotonics applications were presented. The UCNP phantoms exhibited a linear behavior with dosage and were stable over time. An example case showed the potential use of the phantom for deep tissue imaging applications. With recent advance in the use of UCNPs for biophotonics, we believe our recipe and tools will play a pivotal role in the growth of the UCNPs for biophotonics applications.

Regularized Ultrasound Phantom-Free Local Attenuation Coefficient Slope (ACS) Imaging in Homogeneous and Heterogeneous Tissues.

Attenuation maps or measurements based on the local attenuation coefficient slope (ACS) in quantitative ultrasound (QUS) have shown potential for the diagnosis of liver steatosis. In liver cancers, tissue abnormalities and tumors detected using ACS are also of interest to provide new image contrast to clinicians. Current phantom-based approaches have the limitation of assuming a comparable speed of sound between the reference phantom and insonified tissues. Moreover, these methods present the inconvenience for operators to acquire data on phantoms and patients. The main goal was to alleviate these drawbacks by proposing a methodology for constructing phantom-free regularized (PF-R) local ACS maps and investigate the performance in both homogeneous and heterogeneous media. The proposed method was tested on two tissue-mimicking media with different ACS constructed as homogeneous phantoms, side-by-side and top-to-bottom phantoms, and inclusion phantoms with different attenuations. Moreover, an in vivo proof-of-concept was performed on healthy, steatotic, and cancerous human liver datasets. Modifications brought to previous works include: 1) a linear interpolation of the power spectrum in the log scale; 2) the relaxation of the underlying hypothesis on the diffraction factor; 3) a generalization to nonhomogeneous local ACS; and 4) an adaptive restriction of frequencies to a more reliable range than the usable frequency range. Regularization was formulated as a generalized least absolute shrinkage and selection operator (LASSO), and a variant of the Bayesian information criterion (BIC) was applied to estimate the Lagrangian multiplier on the LASSO constraint. In addition, we evaluated the proposed algorithm when applying median filtering before and after regularization. Tests conducted showed that the PF-R yielded robust results in all tested conditions, suggesting potential for additional validation as a diagnosis method.

Two-dimensional shear wave elastography of the pancreas: measurement success rate, repeatability, and factors affecting measurement values.

We aimed to evaluate the success rate, repeatability, and factors affecting the measurement values of two-dimensional ultrasonic shear wave elastography (2D-SWE) for measuring pancreatic stiffness. This prospective study recruited 100 healthy participants. 2D-SWE was performed on the pancreatic head, body, and tail. We compared the success rates of pancreatic stiffness measurements of different body positions and ultrasonic scans, with and without probe pressurization, as well as the effects of sex, age, body mass index (BMI), and region of interest (ROI) depth on measurement values. Intra- and inter-operator repeatabilities were assessed in 20 participants. The influence of ROI depth was verified using a tissue-like phantom. The median 2D-SWE measurements of the pancreatic head, body, and tail were 1.44, 1.45, and 1.56m/s, respectively. The success rates for the pancreatic head and body were significantly higher than that of the tail. The success rate for the semi-recumbent position was higher than that of the supine position (P < 0.001). The intra-operator values for same-day and inter-operator reliability were excellent. Univariate analyses showed that probe pressurization, age, BMI, and ROI depth were correlated with pancreatic shear wave velocity (SWV) (P < 0.05); only ROI depth had a significant effect on SWV values. The inclusion phantom showed that the SWV value increased as the ROI depth increased. 2D-SWE had a high success rate and good repeatability for measuring pancreatic head and body stiffness. The ROI depth was the main factor affecting pancreatic SWV, which increased with ROI depth.

Evaluation of Robustness of Local Phase Velocity Imaging in Homogenous Tissue-Mimicking Phantoms

Shear wave elastography (SWE) is a method of evaluating mechanical properties of soft tissues. Most current implementations of SWE report the group velocity for shear wave velocity, which assumes an elastic, isotropic, homogenous and incompressible tissue. Local phase velocity imaging (LPVI) is a novel method of phase velocity reconstruction that allows for accurate evaluation of shear wave velocity at specified frequencies. This method's robustness was evaluated in 11 elastic and 8 viscoelastic phantoms using linear and curvilinear arrays. We acquired data with acoustic radiation force push beams with different focal depths and F-numbers and reconstructed phase velocity images over a wide range of frequencies. Regardless of phantom, push beam focal depth and reconstruction frequency, an F-number around 3.0 was found to produce the largest usable area in the phase velocity reconstructions. For elastic phantoms scanned with a linear array, the optimal focal depth, frequency range and maximum region of interest (ROI) were 20–30 mm, 100–400 Hz and 2.70 cm2, respectively. For viscoelastic phantoms scanned with a linear array, the optimal focal depth, frequency and maximum ROI were 20–30 mm, 100–300 Hz and 1.54 cm2, respectively. For the curvilinear array in the same phantoms, optimal focal depth, frequency range and maximum ROIs were 45–60 mm, 100–400 and 100–300 Hz and 1.54 cm2, respectively. In further work, LPVI reconstructions from inclusion phantoms will be evaluated to simulate non-homogeneous tissues. Additionally, LPVI will be evaluated in larger-volume phantoms to account for wave reflection from the containers when using the curvilinear array.

Magnetic resonance shear wave elastography using transient acoustic radiation force excitations and sinusoidal displacement encoding

A magnetic resonance (MR) shear wave elastography technique that uses transient acoustic radiation force impulses from a focused ultrasound (FUS) transducer and a sinusoidal-shaped MR displacement encoding strategy is presented. Using this encoding strategy, an analytic expression for calculating the shear wave speed in a heterogeneous medium was derived. Green’s function-based simulations were used to evaluate the feasibility of calculating shear wave speed maps using the analytic expression. Accuracy of simulation technique was confirmed experimentally in a homogeneous gelatin phantom. The elastography measurement was compared to harmonic MR elastography in a homogeneous phantom experiment and the measured shear wave speed values differed by less than 14%. This new transient elastography approach was able to map the position and shape of inclusions sized from 8.5 to 14 mm in an inclusion phantom experiment. These preliminary results demonstrate the feasibility of using a straightforward analytic expression to generate shear wave speed maps from MR images where sinusoidal-shaped motion encoding gradients are used to encode the displacement-time history of a transiently propagating wave-packet. This new measurement technique may be particularly well suited for performing elastography before, during, and after MR-guided FUS therapies since the same device used for therapy is also used as an excitation source for elastography.

Improving Ultrasound Lateral Strain Estimation Accuracy using Log Compression of Regularized Correlation Function.

Normalized cross-correlation (NCC) function used in ultrasound strain imaging can get corrupted due to signal decorrelation inducing large displacement errors. Bayesian regularization has been applied in an iterative manner to regularize the NCC function and to reduce estimation variance and peak-hopping errors. However, incorrect choice of the number of iterations can lead to over-regularization errors. In this paper, we propose the use of log compression of regularized NCC function to improve subsample estimation. Performance of parabolic interpolation before and after log compression of the regularized NCC function were compared in numerical simulations of uniform and inclusion phantoms. Significant improvement was achieved with the proposed scheme for lateral estimation results. For example, lateral signal-to-noise ratio (SNR) was 10 dB higher after log compression at 3% strain in a uniform phantom. Lateral contrast-to-noise ratio (CNR) was 1.81 dB higher with proposed method at 3% strain in inclusion phantom. No significant difference was observed in axial estimation due to presence of phase information and high sampling frequency. Our results suggest that this simple approach makes Bayesian regularization robust to over-regularization artifacts.

Denoising RF Data via Robust Principal Component Analysis: Results in Ultrasound Elastography.

Ultrasound data often suffers from an excessive amount of noise especially from deep tissue or in synthetic aperture imaging where the acoustic wave is weak. Such noisy data renders Time Delay Estimation (TDE) inaccurate in the context of ultrasound elastography. Herein, a novel two-step elastography technique is presented to ensure accurate TDE while dealing with noisy ultrasound data. In the first step, instead of one, we acquire several Radio-Frequency (RF) frames from both pre- and post-deformed positions of the tissue. We stack the frames collected from pre- and post-deformed planes in separate data matrices. Since each set is collected from the same level of tissue compression, we assume that the Casorati data matrices exhibit underlying low-rank structures, which are sought by taking the low-rank and sparse decomposition framework into account. This Robust Principal Component Analysis (RPCA) approach removes the random noise from the datasets as sparse error components. In the second step, we select one frame from each denoised ensemble and employ GLobal Ultrasound Elastography (GLUE) to perform the strain elastography. We call the proposed technique RPCA-GLUE. Our preliminary validation of RPCA-GLUE against simulation phantoms containing hard and soft inclusions proves its robustness to large noise. Substantial improvement in Signal-to-Noise Ratio (SNR) and Contrast-to-Noise Ratio (CNR) has also been observed. Simulation results show that in the presence of large noise, the proposed method substantially improves CNR from 5.0 to 22.6 in a soft inclusion and from 2.2 to 21.7 in a hard inclusion phantom.

Shear Induced Non-Linear Elasticity Imaging: Elastography for Compound Deformations.

The goal of non-linear ultrasound elastography is to characterize tissue mechanical properties under finite deformations. Existing methods produce high contrast non-linear elastograms under conditions of pure uni-axial compression, but exhibit bias errors of 10-50% when the applied deformation deviates from the uni-axial condition. Since freehand transducer motion generally does not produce pure uniaxial compression, a motion-agnostic non-linearity estimator is desirable for clinical translation. Here we derive an expression for measurement of the Non-Linear Shear Modulus (NLSM) of tissue subject to combined shear and axial deformations. This method gives consistent nonlinear elasticity estimates irrespective of the type of applied deformation, with a reduced bias in NLSM values to 6-13%. The method combines quasi-static strain imaging with Single-Track Location-Shear Wave Elastography (STL-SWEI) to generate local estimates of axial strain, shear strain, and Shear Wave Speed (SWS). These local values were registered and non-linear elastograms reconstructed with a novel nonlinear shear modulus estimation scheme for general deformations. Results on tissue mimicking phantoms were validated with mechanical measurements and multiphysics simulations for all deformation types with an error in NLSM of 6-13%. Quantitative performance metrics with the new compound-motion tracking strategy reveal a 10-15 dB improvement in Signal-to-Noise Ratio (SNR) for simple shear versus pure compressive deformation for NLSM elastograms of homogeneous phantoms. Similarly, the Contrast-to-Noise Ratio (CNR) of NLSM elastograms of inclusion phantoms improved by 25-30% for simple shear over pure uni-axial compression. Our results show that high fidelity NLSM estimates may be obtained at ~30% lower strain under conditions of shear deformation as opposed axial compression. The reduction in strain required could reduce sonographer effort and improve scan safety.

Locally optimized correlation-guided Bayesian adaptive regularization for ultrasound strain imaging

Ultrasound strain imaging utilizes radio-frequency (RF) ultrasound echo signals to estimate the relative elasticity of tissue under deformation. Due to the diagnostic value inherent in tissue elasticity, ultrasound strain imaging has found widespread clinical and preclinical applications. Accurate displacement estimation using pre and post-deformation RF signals is a crucial first step to derive high quality strain tensor images. Incorporating regularization into the displacement estimation framework is a commonly employed strategy to improve estimation accuracy and precision. In this work, we propose an adaptive variation of the iterative Bayesian regularization scheme utilizing RF similarity metric signal-to-noise ratio previously proposed by our group. The regularization scheme is incorporated into a 2D multi-level block matching (BM) algorithm for motion estimation. Adaptive nature of our algorithm is attributed to the dynamic variation of iteration number based on the normalized cross-correlation (NCC) function quality and a similarity measure between pre-deformation and motion compensated post-deformation RF signals. The proposed method is validated for either quasi-static and cardiac elastography or strain imaging applications using uniform and inclusion phantoms and canine cardiac deformation simulation models. Performance of adaptive Bayesian regularization was compared to conventional NCC and Bayesian regularization with fixed number of iterations. Results from uniform phantom simulation study show significant improvement in lateral displacement and strain estimation accuracy. For instance, at 1.5% lateral strain in a uniform phantom, Bayesian regularization with five iterations incurred a lateral strain error of 104.49%, which was significantly reduced using our adaptive approach to 27.51% (p < 0.001). Contrast-to-noise (CNRe) ratios obtained from inclusion phantom indicate improved lesion detectability for both axial and lateral strain images. For instance, at 1.5% lateral strain, Bayesian regularization with five iterations had lateral CNRe of −0.31 dB which was significantly increased using the adaptive approach to 7.42 dB (p < 0.001). Similar results are seen with cardiac deformation modelling with improvement in myocardial strain images. In vivo feasibility was also demonstrated using data from a healthy murine heart. Overall, the proposed method makes Bayesian regularization robust for clinical and preclinical applications.

Physiological Motion Reduction Using Lagrangian Tracking for Electrode Displacement Elastography

Minimally invasive treatments such as microwave ablation (MWA) have been growing in popularity for extending liver cancer survival rates in patients, when surgery is not an option. As a non-ionizing, real-time alternative to contrast-enhanced computed tomography, electrode displacement elastography (EDE) has shown promise as an imaging modality for MWA. Despite imaging efficacy, motion artifacts caused by physiological motion result in unintended speckle pattern variance, thereby inhibiting consistent and accurate ablated region visualization. To combat these unavoidable motion artifacts, a Lagrangian deformation tracking (LDT) approach based on freehand EDE was developed to track tissue movement and better define tissue properties. For validating LDT efficacy, a spherical inclusion phantom as well as seven in vivo data sets were processed, and strain tensor images were compared with identical time sampled images estimated using a traditional Eulerian approach. In vivo results revealed greater consistency among visualized LDT strain tensor images, with segmented ablated regions exhibiting standard deviation reductions of up to 98% when compared with Eulerian strain tensor images. Additionally, Lagrangian strain tensor images provided Dice coefficient improvements up to 25%, and success rates improved from approximately 50% to nearly 100% for ablated region visualization.

Fabrication of a spherical inclusion phantom for validation of magnetic resonance-based magnetic susceptibility imaging

Fabrication of a spherical multi-compartment MRI phantom is demonstrated that can be used to validate magnetic resonance (MR)-based susceptibility imaging reconstruction. The phantom consists of a 10 cm diameter gelatin sphere that encloses multiple smaller gelatin spheres doped with different concentrations of paramagnetic contrast agents. Compared to previous multi-compartment phantoms with cylindrical geometry, the phantom provides the following benefits: (1) no compartmental barrier materials are used that can introduce signal voids and spurious phase; (2) compartmental geometry is reproducible; (3) spherical susceptibility boundaries possess a ground-truth analytical phase solution for easy experimental validation; (4) spherical geometry of the overall phantom eliminates background phase due to air-phantom boundary in any scan orientation. The susceptibility of individual compartments can be controlled independently by doping. During fabrication, formalin cross-linking and water-proof surface coating effectively blocked water diffusion between the compartments to preserve the phantom's integrity. The spherical shapes were realized by molding the inner gel compartments in acrylic spherical shells, 3 cm in diameter, and constructing the whole phantom inside a larger acrylic shell. From gradient echo images obtained at 3T, we verified that the phantom produced phase images in agreement with the theoretical prediction. Factors that limit the agreement include: air bubbles trapped at the gel interfaces, imperfect magnet shimming, and the susceptibility of external materials such as the phantom support hardware. The phantom images were used to validate publicly available codes for quantitative susceptibility mapping. We believe that the proposed phantom can provide a useful testbed for validation of MR phase imaging and MR-based magnetic susceptibility reconstruction.

Finger-mounted quantitative micro-elastography.

We present a finger-mounted quantitative micro-elastography (QME) probe, capable of measuring the elasticity of biological tissue in a format that avails of the dexterity of the human finger. Finger-mounted QME represents the first demonstration of a wearable elastography probe. The approach realizes optical coherence tomography-based elastography by focusing the optical beam into the sample via a single-mode fiber that is fused to a length of graded-index fiber. The fiber is rigidly affixed to a 3D-printed thimble that is mounted on the finger. Analogous to manual palpation, the probe compresses the tissue through the force exerted by the finger. The resulting deformation is measured using optical coherence tomography. Elasticity is estimated as the ratio of local stress at the sample surface, measured using a compliant layer, to the local strain in the sample. We describe the probe fabrication method and the signal processing developed to achieve accurate elasticity measurements in the presence of motion artifact. We demonstrate the probe's performance in motion-mode scans performed on homogeneous, bi-layer and inclusion phantoms and its ability to measure a thermally-induced increase in elasticity in ex vivo muscle tissue. In addition, we demonstrate the ability to acquire 2D images with the finger-mounted probe where lateral scanning is achieved by swiping the probe across the sample surface.

Monocular 3D Probe Tracking for Generating Sub-Surface Optical Property Maps From Diffuse Optical Spectroscopic Imaging.

Diffuse optical spectroscopic imaging (DOSI) is a promising biophotonic technology for clinical tissue assessment, but is currently hampered by difficult wide area assessment. A co-integrative optical imaging system is proposed for dense sub-surface optical property spatial assessment. The proposed system fuses a co-aligned set of camera frames and diffuse optical spectroscopy measurements to generate spatial sub-surface optical property maps. A 3D rigid body motion estimation model was developed by fitting automatically detected target features to an a priori geometric model using a single overhead camera. Point-wise optical properties were measured across the tissue using frequency domain photon migration DOSI. The 3D probe trajectory and temporal optical property data were fused to generate 2D spatial optical property maps, which were projected onto the tissue image using pre-calibrated camera parameters. The system demonstrated sub-millimeter positional accuracy (error 0.24 ± 0.35mm) across different probe speeds (1.0-3.8cm/s), and displacement accuracy in overhead ([Formula: see text]mm) and tilted (0.51 ± 0.51mm) camera orientations. Unstructured scans on a tumor inclusion phantom showed strong contrast under different probe paths, and significant ( ) changes in optical properties in an in vivo leg cuff occlusion protocol with spatial anatomy localization. The proposed co-integrative optical imaging system generated dense sub-surface optical property distributions across wide tissue areas with sub-millimeter accuracy at different probe speeds and trajectories, and does not require pre-planned probe route for tissue assessment. This system provides a valuable tool for real-time non-invasive tissue health and cancer screening, and enables longitudinal disease progression assessment through unstructured probe-based optical tissue assessment.

Evaluation of Reconstruction Parameters for 2-D Comb-Push Ultrasound Shear Wave Elastography

Shear wave elastography (SWE) is a noninvasive ultrasound imaging modality used in the assessment of the mechanical properties of tissues such as the liver, kidney, skeletal muscle, thyroid, and the breast. Among the methods used to perform SWE is the comb-push ultrasound shear elastography method. This method uses multiple focused ultrasound beams to generate push beams with acoustic radiation force. Applying these push beams generates propagating shear waves. The propagation motion is measured with ultrafast ultrasound imaging. The shear wave motion data are directionally filtered, and a 2-D shear wave velocity (SWV) algorithm is applied to create group velocity maps. This algorithm uses a moving window and a specified patch for performing cross-correlations of time-domain signals. We performed a parametric study of how the choice of the patch and window size affected the reconstruction of the SWV in homogeneous and inclusion phantoms. We quantified the mean velocity and coefficient of variation in the homogeneous phantoms. We measured the contrast-to-noise ratio and bias in the inclusion phantoms. In each of these cases, we found that particular combinations of the patch and window provided optimal values of these evaluation metrics for the phantoms tested. This study provides a basis to construct algorithms to produce optimal SWV reconstructions for various clinical applications.

3D Quasi-Static Ultrasound Elastography With Plane Wave In Vivo.

In biological tissue, an increase in elasticity is often a marker of abnormalities. Techniques such as quasi-static ultrasound elastography have been developed to assess the strain distribution in soft tissues in two dimensions using a quasi-static compression. However, as abnormalities can exhibit very heterogeneous shapes, a three dimensional approach would be necessary to accurately measure their volume and remove operator dependency. Acquisition of volumes at high rates is also critical to performing real-time imaging with a simple freehand compression. In this study, we developed for the first time a 3D quasi-static ultrasound elastography method with plane waves that estimates axial strain distribution in vivo in entire volumes at high volume rate. Acquisitions were performed with a 2D matrix array probe of 2.5 MHz frequency and 256 elements. Plane waves were emitted at a volume rate of 100 volumes/s during a continuous motorized and freehand compression. 3D B-mode volumes and 3D cumulative axial strain volumes were successfully estimated in inclusion phantoms and in ex vivo canine liver before and after a high intensity focused ultrasound ablation. We also demonstrated the in vivo feasibility of the method using freehand compression on the calf muscle of a human volunteer and were able to retrieve 3D axial strain volume at a high volume rate depicting the differences in stiffness of the two muscles which compose the calf muscle. 3D ultrasound quasi-static elastography with plane waves could become an important technique for the imaging of the elasticity in human bodies in three dimensions using simple freehand scanning.

Shear Wave Speed Measurements Using Crawling Wave Sonoelastography and Single Tracking Location Shear Wave Elasticity Imaging for Tissue Characterization.

Elastography provides tissue stiffness information that attempts to characterize the elastic properties of tissue. However, there is still limited literature comparing elastographic modalities for tissue characterization. This study focuses on two quantitative techniques using different vibration sources that have not been compared to date: crawling wave sonoelastography (CWS) and single tracking location shear wave elasticity imaging (STL-SWEI). To understand each technique's performance, shear wave speed (SWS) was measured in homogeneous phantoms and ex vivo beef liver tissue. Then, the contrast, contrast-to-noise ratio (CNR), and lateral resolution were measured in an inclusion and two-layer phantoms. The SWS values obtained with both modalities were validated with mechanical measurements (MM) which serve as ground truth. The SWS results for the three different homogeneous phantoms (10%, 13%, and 16% gelatin concentrations) and ex vivo beef liver tissue showed good agreement between CWS, STL-SWEI, and MM as a function of frequency. For all gelatin phantoms, the maximum accuracy errors were 2.52% and 2.35% using CWS and STL-SWEI, respectively. For the ex vivo beef liver, the maximum accuracy errors were 9.40% and 7.93% using CWS and STL-SWEI, respectively. For lateral resolution, contrast, and CNR, both techniques obtained comparable measurements for vibration frequencies less than 300 Hz (CWS) and distances between the push beams ( ∆x ) between 3 mm and 5.31 mm (STL-SWEI). The results obtained in this study agree over an SWS range of 1-6 m/s. They are expected to agree in perfectly linear, homogeneous, and isotropic materials, but the SWS overlap is not guaranteed in all materials because each of the three methods have unique features.

Probe Oscillation Shear Elastography (PROSE): A High Frame-Rate Method for Two-Dimensional Ultrasound Shear Wave Elastography.

Ultrasound shear wave elastography (SWE) utilizes the propagation of induced shear waves to characterize the shear modulus of soft tissue. Many methods rely on an acoustic radiation force (ARF) "push beam" to generate shear waves. However, specialized hardware is required to generate the push beams, and the thermal stress that is placed upon the ultrasound system, transducer, and tissue by the push beams currently limits the frame-rate to about 1 Hz. These constraints have limited the implementation of ARF to high-end clinical systems. This paper presents Probe Oscillation Shear Elastography (PROSE) as an alternative method to measure tissue elasticity. PROSE generates shear waves using a harmonic mechanical vibration of an ultrasound transducer, while simultaneously detecting motion with the same transducer under pulse-echo mode. Motion of the transducer during detection produces a "strain-like" compression artifact that is coupled with the observed shear waves. A novel symmetric sampling scheme is proposed such that pulse-echo detection events are acquired when the ultrasound transducer returns to the same physical position, allowing the shear waves to be decoupled from the compression artifact. Full field-of-view (FOV) two-dimensional (2D) shear wave speed images were obtained by applying a local frequency estimation (LFE) technique, capable of generating a 2D map from a single frame of shear wave motion. The shear wave imaging frame rate of PROSE is comparable to the vibration frequency, which can be an order of magnitude higher than ARF based techniques. PROSE was able to produce smooth and accurate shear wave images from three homogeneous phantoms with different moduli, with an effective frame rate of 300 Hz. An inclusion phantom study showed that increased vibration frequencies improved the accuracy of inclusion imaging, and allowed targets as small as 6.5 mm to be resolved with good contrast (contrast-to-noise ratio ≥ 19 dB) between the target and background.

A new method for shear wave speed estimation in shear wave elastography.

Visualization of mechanical properties of tissue can aid in noninvasive pathology diagnosis. Shear wave elastography (SWE) measures the elastic properties of soft tissues by estimation of local shear wave propagation speed. In this paper, a new robust method for estimation of shear wave speed is introduced which has the potential for simplifying continuous filtering and real-time elasticity processing. Shear waves were generated by external mechanical excitation and imaged at a high frame rate. Three homogeneous phantoms of varying elastic moduli and one inclusion phantom were imaged. Waves propagating in separate directions were filtered and shear wave speed was estimated by inversion of the 1-D first-order wave equation. Final 2-D shear wave speed maps were constructed by weighted averaging of estimates from opposite traveling directions. Shear wave speed results for phantoms with gelatin concentrations of 5%, 7%, and 9% were 1.52 ± 0.10 m/s, 1.86 ± 0.10 m/s, and 2.37 ± 0.15 m/s, respectively, which were consistent with estimates computed from three other conventional methods, as well as compression tests done with a commercial texture analyzer. The method was shown to be able to reconstruct a 2-D speed map of an inclusion phantom with good image quality and variance comparable to conventional methods. Suggestions for further work are given.

Multi-source and multi-directional shear wave generation with intersecting steered ultrasound push beams.

Elasticity imaging is becoming established as a means of assisting in diagnosis of certain diseases. Shear wave-based methods have been developed to perform elasticity measurements in soft tissue. Comb-push ultrasound shear elastography (CUSE) is one of these methods that apply acoustic radiation force to induce the shear wave in soft tissues. CUSE uses multiple ultrasound beams that are transmitted simultaneously to induce multiple shear wave sources into the tissue, with improved shear wave SNR and increased shear wave imaging frame rate. We propose a novel method that uses steered push beams (SPB) that can be applied for beam formation for shear wave generation. In CUSE beamforming, either unfocused or focused beams are used to create the propagating shear waves. In SPB methods we use unfocused beams that are steered at specific angles. The interaction of these steered beams causes shear waves to be generated in more of a random nature than in CUSE. The beams are typically steered over a range of 3 to 7° and can either be steered to the left (-θ) or right (+θ).We performed simulations of 100 configurations using Field II and found the best configurations based on spatial distribution of peaks in the resulting intensity field. The best candidates were ones with a higher number of the intensity peaks distributed over all depths in the simulated beamformed results. Then these optimal configurations were applied on a homogeneous phantom and two different phantoms with inclusions. In one of the inhomogeneous phantoms we studied two spherical inclusions with 10 and 20 mm diameters, and in the other phantom we studied cylindrical inclusions with diameters ranging from 2.53 to 16.67 mm. We compared these results with those obtained using conventional CUSE with unfocused and focused beams. The mean and standard deviation of the resulting shear wave speeds were used to evaluate the accuracy of the reconstructions by examining bias with nominal values for the phantoms as well as the contrast-to-noise ratio in the inclusion phantom results. In general the contrast-to-noise ratio (CNR) was higher and the bias was lower using the SPB method compared with the CUSE realizations except in the largest inclusions. In the cylindrical inclusion with 10.4 mm diameter, the CNR in CUSE methods ranged between 18.52 and 22.02 and the bias ranged between 5.50 and 11.12%, whereas for SPB methods provided CNR values between 23.07 and 48.90 and bias values between 3.78 and 9.22%. In a smaller cylindrical inclusion with diameter of 4.05 mm, CUSE methods gave CNR between 14.69 and 22.28 and bias ranging between 28.95 and 29.28%, whereas the SPB methods provided CNR values between 16.7 and 25.2 and bias values varying from 25.54 to 30.44%. The SPB method provides a flexible framework to produce shear wave sources that are widely distributed within the field-of-view for robust shear wave speed imaging.