Citations

AbstractBecause of the rapidly growing use of ultrasound shear wave elastography (SWE) in clinical practices, there is a significant need for development of clinical physics performance assessment methods for this technology. This study aims to report two clinical medical physicists’ tasks: (a) acceptance testing (AT) of SWE function on ten commercial ultrasound systems for clinical liver application and (b) comparison of SWE measurements of targets across vendors for clinical musculoskeletal application. For AT, ten GE LOGIQ E9 XDclear 2.0 scanners with ten C1‐6‐D and ten 9L‐D transducers were studied using two commercial homogenous phantoms. Five measurements were acquired at two depths for each scanner/transducer pair by two operators. Additional tests were performed to access effects of different coupling media, phantom locations and operators. System deviations were less than 5% of group mean or three times standard deviation; therefore, all systems passed AT. A test protocol was provided based on results that no statistically significant difference was observed between using ultrasound gel and salt water for coupling, among different phantom locations, and that interoperator and intraoperator coefficient of variation was less than 3%. For SWE target measurements, two systems were compared — a Supersonic Aixplorer scanner with a SL10‐2 and a SL15‐4 transducer, and an abovementioned GE scanner with 9L‐D transducer. Two stepped cylinders with diameters of 4.05–10.40 mm were measured both longitudinally and transaxially. Target shear wave speed quantification was performed using an in‐house MATLAB program. Using the target shear wave speed deduced from phantom specs as a reference, SL15‐4 performed the best at the measured depth. However, it was challenging to reliably measure a 4.05 mm target for either system. The reported test methods and results could provide important information when dealing with SWE‐related tasks in the clinical environment.

Shear wave elastography (SWE) is a powerful method for the diagnosis of tissue disorders or degeneration based on tissue elasticity. In SWE application, it was recognized that the wave speed depends not only on the tissue elasticity but also on the structural shape, leading to different theoretical models. For liver, skin and myocardium, the appropriate theoretical model is known to be shear wave, Rayleigh wave and Lamb wave theory, respectively. Therefore, appropriate theoretical model should be adopted for the proper application of SWE. In this study, we verify these theoretical models in gelatin samples of different thicknesses, using experimental and numerical SWE tests. The results indicate that the wave speed was influenced by the ratio of the wavelength and sample thickness and the measurement region. Based on these results, the selection of theoretical model could be divided into three cases, and the appropriate theoretical model can be selected accordingly.

ObjectivesTo prospectively evaluate the diagnostic performance of 3‐dimensional (3D) shear wave elastography (SWE) for assessing thyroid nodules.MethodsA total of 176 surgically or cytologically confirmed thyroid nodules (63 malignant and 113 benign) in 176 patients who had undergone conventional ultrasound (US), 2‐dimensional (2D) SWE, and 3D SWE examinations were included in this study. Quantitative elasticity values (mean elasticity, maximum elasticity, and standard deviation of elasticity of a large region of interest and mean elasticity of a 2‐mm region of interest) were measured on 2D and 3D SWE. Diagnostic performances of conventional US, 2D SWE, and 3D SWE were assessed. The role of 2D and 3D SWE in reducing unnecessary fine‐needle aspiration (FNA) for nodules with low suspicion was also evaluated.ResultsThe diagnostic performances in terms of the area under the receiver operating characteristic curve were 0.612 for conventional US, 0.836 for 2D SWE (P < .001 in comparison with conventional US), and 0.839 for 3D SWE (P < .001 in comparison with conventional US). The mean elasticity achieved the highest diagnostic performance in 2D SWE, whereas the standard deviation of elasticity achieved the highest performance in 3D SWE, although no significant difference was found between them (P > .05). Three‐dimensional SWE increased the specificity in comparison with 2D SWE (88.5% versus 82.3%; P = .039). For the 37 nodules with low suspicion on conventional US imaging, 2D SWE was able to avoid unnecessary FNA in 77.1% (27 of 35) of benign nodules, and 3D SWE further increased the number to 88.6% (31 of 35).ConclusionsThree‐dimensional SWE is a useful tool for predicting thyroid nodule malignancy and reducing unnecessary FNA procedures in thyroid nodules with low suspicion of malignancy.

Shear wave elasticity imaging determines the mechanical parameters of soft tissue by analyzing measured shear waves induced by an acoustic radiation force. Currently, the widely used time-of-flight method calculates the correlation between shear waveforms at adjacent lateral observation points to estimate the shear elasticity value. Although this method provides accurate estimates of the shear elasticity in purely elastic media, our experience suggests that this approach overestimates the shear elasticity values in viscoelastic media because the effects of diffraction, attenuation, and dispersion are not taken into account. To address this problem, we have developed an approach that directly accounts for all of these effects when estimating the shear elasticity. This new approach simulates shear waveforms using a Green’s function-based approach with a Voigt model, while the shear elasticity and viscosity values are estimated using an optimization-based approach by comparing measured shear waveforms with simulated shear waveforms in the time-domain. This operation is then performed on a point-by-point basis to generate images. The results indicate that there is good agreement between the simulated and measured shear velocity waveforms, and that this approach yields improved images of the shear elasticity and shear viscosity. [Work supported, in part, by NIH Grant R01DK092255.]

Shear wave elastography (SWE) is clinically used for the measurement of soft tissue mechanical properties. Most SWE methods assume that the tissue is elastic, but soft tissues are inherently viscoelastic. The viscoelasticity can be characterized by examining phase velocity dispersion. Methods to extract the phase velocities from the spatiotemporal data, v(x,t), involve using a two-dimensional Fourier transform. The Fourier representation, V(k,f), is searched for peaks that correspond to the phase velocities. We present a method that uses the Multiple Signal Classification (MUSIC) method to provide robust estimation of the phase velocity dispersion curves. We compared results from the MUSIC method with the current approach of searching for peaks in the V(k,f) representation. We tested this method on digital phantom data created using finite element models (FEMs) in viscoelastic media excited by a simulated acoustic radiation force push from a curved linear array. We evaluated the algorithm with different levels of added noise. Additionally, we tested the methods on data acquired in viscoelastic phantoms with a Verasonics system. The MUSIC algorithm provided dispersion estimation with lower errors than the conventional peak search strategy. This method can be used for evaluation of wave velocity dispersion in viscoelastic tissues and guided wave propagation. [This work was supported in part by grant R01DK092255.]

Abstract Ultrasound and magnetic resonance elastography techniques are used to assess mechanical properties of soft tissues. Tissue stiffness is related to various pathologies such as fibrosis, loss of compliance, and cancer. One way to perform elastography is measuring shear wave velocity of propagating waves in tissue induced by intrinsic motion or an external source of vibration, and relating the shear wave velocity to tissue elasticity. All tissues are inherently viscoelastic and ignoring viscosity biases the velocity-based estimates of elasticity and ignores a potentially important parameter of tissue health. We present attenuation measuring ultrasound shearwave elastography (AMUSE), a technique that independently measures both shear wave velocity and attenuation in tissue and therefore allows characterization of viscoelasticity without using a rheological model. The theoretical basis for AMUSE is first derived and validated in finite element simulations. AMUSE is validated against the traditional methods for assessing shear wave velocity (phase gradient) and attenuation (amplitude decay) in tissue mimicking phantoms and excised tissue. The results agreed within one standard deviation. AMUSE was used to measure shear wave velocity and attenuation in 15 transplanted livers in patients with potential acute rejection, and the results were compared with the biopsy findings in a preliminary study. The comparison showed excellent agreement and suggests that AMUSE can be used to separate transplanted livers with acute rejection from livers with no rejection.

A total of 136 subjects (51 SS patients, 35 sicca syndrome patients without SS, and 50 healthy volunteers) were enrolled in this study. The mean SWV value for salivary glands of SS patients was statistically higher than that of controls (2.81 ± 0.66 m/s versus 1.85 ± 0.28 m/s for parotid glands and 2.29 ± 0.34 m/s versus 1.82 ± 0.25 m/s for submandibular glands, resp.). Combining SWV values of parotid and submandibular glands gives a sensitivity of 88.2% (95% CI: 76.1–95.6%) and specificity of 96.0% (95% CI: 86.3–99.5%) at the cutoff point of 2.19 m/s, with an AUROC of 0.954 (95% CI: 0.893–0.986). In addition, combining SGUS score and SWV value yields a sensitivity of 98.0% (95% CI: 89.6–100%), specificity of 90.0% (95% CI: 78.2–96.7%), and AUROC of 0.962 (95% CI: 0.904–0.990). Classification tree considering the sequential use of SGUS score and SWV value achieved 92.1% accuracy for diagnosis of SS. Similarly, the ROC curve of combined SGUS scores and SWV values yields an AUROC of 0.954 (95% CI: 0.885–0.987), sensitivity of 97.1% (95% CI: 85.1–99.9%), and specificity of 92.2% (95% CI: 81.1–97.8%) for separating sicca syndrome patients (without SS) from SS patients. Combining SGUS and VTQ provides a promising tool for diagnosis of SS.

Abstract The myocardium is known to be an anisotropic medium where the muscle fiber orientation changes through the thickness of the wall. Shear wave elastography methods use propagating waves which are measured by ultrasound or magnetic resonance imaging (MRI) techniques to characterize the mechanical properties of various tissues. Ultrasound- or MR-based methods have been used and the excitation frequency ranges for these various methods cover a large range from 24–500 Hz. Some of the ultrasound-based methods have been shown to be able to estimate the fiber direction. We constructed a model with layers of elastic, transversely isotropic materials that were oriented at different angles to simulate the heart wall in systole and diastole. We investigated the effect of frequency on the wave propagation and the estimation of fiber direction and wave speeds in the different layers of the assembled models. We found that waves propagating at low frequencies such as 30 or 50 Hz showed low sensitivity to the fiber direction but also had substantial bias in estimating the wave speeds in the layers. Using waves with higher frequency content (>200 Hz) allowed for more accurate fiber direction and wave speed estimation. These results have particular relevance for MR- and ultrasound-based elastography applications in the heart.

Evaluation of tissue engineering constructs is performed by a series of different tests. In many cases it is important to match the mechanical properties of these constructs to those of native tissues. However, many mechanical testing methods are destructive in nature which increases cost for evaluation because of the need for additional samples reserved for these assessments. A wave propagation method is proposed for characterizing the shear elasticity of thin layers bounded by a rigid substrate and fluid-loading, similar to the configuration for many tissue engineering applications. An analytic wave propagation model was derived for this configuration and compared against finite element model simulations and numerical solutions from the software package Disperse. The results from the different models found very good agreement. Experiments were performed in tissue-mimicking gelatin phantoms with thicknesses of 1 and 4 mm and found that the wave propagation method could resolve the shear modulus with very good accuracy, no more than 4.10% error. This method could be used in tissue engineering applications to monitor tissue engineering construct maturation with a nondestructive wave propagation method to evaluate the shear modulus of a material.

Many methods for characterization of the mechanical properties of soft tissues using propagating shear waves have been developed over the past two decades. Most of these methods assume that the shear wave is traveling in an elastic, isotropic tissue. However, many soft tissues are viscoelastic and have material properties that are directionally dependent or anisotropic. We have been developing methods to measure waves propagating in soft tissues to estimate the anisotropic viscoelastic material properties. To refine our measurement methods, we have also developed techniques and models for simulating the wave propagation in these types of materials. We have developed specialized finite element and pseudo-spectral models that can simulate viscoelastic transversely isotropic materials and compared our results with measurements in ex vivo porcine muscle. Additionally, we have developed a finite element model that simulates wave propagation in the myocardium by creating a model of layered transverse isotropic media oriented at different angles. We examined the effect of frequency of the waves for estimating of the angle of propagation. We compared these simulation results with experimental results from an ex vivo porcine left ventricular wall. These simulation methods provide insight for optimizing our measurement methods for in vivo characterization of material properties.