Conventional Shear Wave Research Articles

Shear wave velocity prediction for fractured limestone reservoirs based on artificial neural network

AbstractShear wave velocity is an essential parameter in reservoir characterization and evaluation, fluid identification and prestack inversion. However, conventional data‐driven or model‐driven shear wave velocity prediction methods exhibit several limitations, such as lack of training data sets, poor model generalization and weak model robustness. In this study, a model‐ and data‐driven approach is presented to facilitate the solution of these problems. We develop a theoretical rock physics model for fractured limestone reservoirs and then use the model to generate synthetic data that incorporates geological and geophysical knowledge. The synthetic data with random noise is utilized as the training data set for the artificial neural network, and a well‐trained shear wave velocity prediction model, random noise shear wave velocity prediction neural network, is established by parameter tuning, which fits the synthetic data with noise well. The neural network is applied directly to the real field area. Compared with conventional shear wave prediction methods, such as empirical formulas and the improved Xu–White model, the prediction results show that the random noise shear wave velocity prediction neural network has better prediction performance and generalization. Furthermore, the prediction results demonstrate the efficacy of the proposed approach, and the approach has the potential to perform shear wave velocity prediction in real areas where training data sets are unavailable.

A Scholte wave approach for ultrasonic surface acoustic wave elastography.

Pathological changes in tissues are often related to changes in tissue mechanical properties, making elastography an important tool for medical applications. Among the existing elastography methods, ultrasound elastography is of great interest due to the inherent advantages of ultrasound imaging technology, such as low cost, portability, safety, and wide availability. Although ultrasonic shear wave elastography, as a platform technology, can potentially quantify the elasticity of tissue at any depth, its current implementation cannot assess superficial tissue but can only image deep tissue. To address this challenge, we proposed an ultrasonic Scholte-wave-based approach for imaging the elasticity of superficial tissue. The feasibility of the proposed technique was tested using a gelatin phantom with a cylindrical inclusion. To generate Scholte wave in the superficial region of the phantom, we proposed a new experimental configuration in which a liquid layer was introduced between an ultrasound imaging transducer and the tissue-mimicking phantom. We utilized an acoustic radiation force impulse to excite the tissue-mimicking phantom, analyzed the properties of the generated Scholte waves, and applied the waves for elasticity imaging. In this study, we first reported the observation that Scholte (surface) waves and shear (bulk) waves were simultaneously generated, and they propagated in the superficial and deeper regions of the phantom, respectively. Then, we presented some important properties of the generated Scholte waves. For a 5w/v% gelatin phantom, the generated Scholte waves have a speed of around 0.9m/s, a frequency of about 186Hz, and thus a wavelength of about 4.8mm. The speed ratio between the simultaneously generated Scholte wave and shear wave is about 0.717, which is 15% lower than the theoretical expectation. And we further demonstrated the feasibility of Scholte wave as a mechanism for imaging superficial tissue elasticity. Together with the simultaneously generated shear wave, the Scholte wave was shown to be able to quantitatively image both the background and the cylindrical inclusion (4mm in diameter) of the tissue-mimicking gelatin phantom. This work shows that the elasticity of superficial tissue can be evaluated by utilizing the generated Scholte wave alone, and it also shows that a comprehensive elasticity imaging of the tissue extending from the superficial to deep regions can be achieved by combining the proposed Scholte wave technique and the conventional shear wave technique.

A Scholte wave based ultrasound elastography method for imaging superficial tissue

Pathological changes in tissues are often related to changes in tissue mechanical properties, making elastography an important tool for medical applications. Among the existing elastography methods, ultrasound elastography is of great interest due to the inherent advantages of ultrasound imaging technology, such as low cost, portability, safety, and wide availability. However, the current ultrasound elastography methods, including shear wave elastography, can readily image deep tissue but cannot assess superficial tissue. To address this challenge, we proposed an ultrasonic Scholte-wave-based approach for imaging the elasticity of superficial tissue. The feasibility of the proposed technique was tested using a gelatin phantom with a cylindrical inclusion. In the tests, Scholte (surface) and shear (bulk) waves were simultaneously generated by the same excitation but propagated in the superficial and deeper regions of the phantom, respectively. In this study, we first demonstrated that the elasticity of superficial tissue could be evaluated by utilizing the generated Scholte wave alone and further showed that a comprehensive elasticity imaging of the tissue extending from the superficial to deep regions can be achieved by combining the proposed Scholte wave technique and the conventional shear wave technique.

Ultrasound Shear Wave Elasticity Imaging With Spatio-Temporal Deep Learning.

Ultrasound shear wave elasticity imaging is a valuable tool for quantifying the elastic properties of tissue. Typically, the shear wave velocity is derived and mapped to an elasticity value, which neglects information such as the shape of the propagating shear wave or push sequence characteristics. We present 3D spatio-temporal CNNs for fast local elasticity estimation from ultrasound data. This approach is based on retrieving elastic properties from shear wave propagation within small local regions. A large training data set is acquired with a robot from homogeneous gelatin phantoms ranging from 17.42 kPa to 126.05 kPa with various push locations. The results show that our approach can estimate elastic properties on a pixelwise basis with a mean absolute error of 5.01(437) kPa. Furthermore, we estimate local elasticity independent of the push location and can even perform accurate estimates inside the push region. For phantoms with embedded inclusions, we report a 53.93% lower MAE (7.50 kPa) and on the background of 85.24% (1.64 kPa) compared to a conventional shear wave method. Overall, our method offers fast local estimations of elastic properties with small spatio-temporal window sizes.

Added value of mass characteristic frequency to 2-D shear wave elastography for differentiation of benign and malignant thyroid nodules.

Mass characteristic frequency (fmass) is a novel shear wave (SW) parameter that represents the ratio of the averaged minimum SW speed within the regions of interest to the largest dimension of the mass. Our study objective was to evaluate if the addition of fmass to conventional 2-D shear wave elastography (SWE) parameters would improve the differentiation of benign from malignant thyroid nodules. Our cohort comprised 107 patients with 113 thyroid nodules, of which 67 (59%) were malignant. Two-dimensional SWE data were obtained using the Supersonic Imagine Aixplorer ultrasound system equipped with a 44- to 15-MHz15-MHz linear array transducer. A receiver operating characteristic curve was generated based on a multivariable logistic regression analysis to evaluate the ability of SWE parameters with/without fmass and with/without clinical factors to discriminate benign from malignant thyroid nodules. The addition of fmass to conventional SW elasticity parameters increased the area under the curve from 0.808 to 0.871 (p=0.02). The combination of SW elasticity parameters plus fmass plus clinical factors provided the strongest thyroid nodule malignancy probability estimate, with a sensitivity of 93.4% and specificity of 91.1% at the optimal threshold. In summary, fmass can be a valuable addition to conventional 2-D SWE parameters.

Measurement uncertainty of shear wave velocity: A case study of thirteen alluvium test sites in Taipei Basin

Field seismic methods are widely applied to site investigations for seismic design. The most often used ones are cross-hole, down-hole, SCPT, suspension P–S logging, and surface wave methods. The choice of seismic methods has a variety of technical and cost considerations. However, the measurement uncertainty among resulting shear wave velocities by above methods are rarely statistically characterized with mathematical models and sound database in the literature, even though it is an important factor to consider before choosing a method. In this study, thirteen alluvium sites in Taipei Basin were chosen and carefully planned to simultaneously measure the velocity profiles using each of the five most common seismic methods with conventional shear wave triggering techniques. Using the data from the test and statistical models, the differences between seismic methods were quantified as the calibrated measurement uncertainty, which can be used as a reference for selecting an appropriate method for measuring shear wave velocity. Finally, the effect of measurement uncertainty on seismic site classification and simplified soil liquefaction potential evaluations based on shear wave velocity was investigated.

Smart ultrasound device for real-time myocardial stiffness quantification of the human heart

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): ERC Introduction Myocardial stiffness (MS) is crucial to understand cardiac biomechanics and evaluate cardiac function. We recently demonstrated that shear wave imaging using acoustic radiation force can provide quantitative end-diastolic MS in human patients [1] . However, the dependence of shear wave velocity with myofiber orientation remained a limitation and required to perform Shear Wave Velocity (SWV) estimations from different probe orientations which is challenging in clinical practice. We propose a new approach to provide real-time quantitative assessment of MS without dependence of the probe orientation based on a dedicated smart ultrasound (US) device. Methods A new US probe was designed and manufactured to generate acoustic radiation force along the central axis and track the SWV simultaneously along three different orientations to obtain an elliptic profile of SWS. The probe was connected to dedicated electronics and software to provide real-time end-diastolic MS with ECG gating. Validation was performed on 4 in-vitro calibrated phantoms (0.92 – 1.49 – 2.58 – 3.49 m/s) and on ex vivo porcine hearts. MS along and across the fibers were compared to the values measured by conventional shear wave imaging with a linear probe mounted on a rotation motor (angular step of 10°) (Aixplorer, Supersonic imaging). Finally, the in vivo feasibility and reproducibility of measuring MS of the antero-septal wall and of the right ventricular (RV) wall was assessed transthoracically on four human volunteer . Results In vitro results on phantoms showed a good agreement with calibrated value (r2 = 0.98, std = 4.8%). Elliptic profiles on ex-vivo porcine heart showed good agreement with Aixplorer measurements acquired at different angles, with a relative difference along the long axis (LA) of: Δ=7.0%, Δ=7.1%, Δ=9% respectively for left ventricle (LV), right ventricle (RV) and septum. Finally, myocardial SWV assessment in human volunteers was obtained successfully on the RV and on the septum in late diastole. The mean MS was 1.79+/- 0.15 m/s along the fiber direction, the fractional anisotropy (FA) was 0.25 +/- 0.06 on septal wall in good agreement with previous results [1] and 1.06 +/- 0.11 m/s along fibers orientation and a FA of 0.27 +/- 0.08 on RV. Finally the beat to beat reproducibility of MS measurement was estimated to be 8.22%. Conclusion The new smart US device allowed non-invasive quantification of anisotropic myocardial tissues in real time. Results showed the accuracy of the methods. This approach could offer a new clinical tool for the evaluation of the myocardium in cardiomyopathies and in heart failure patients. Abstract Figure. SWV on myocardium human volonteer

DSWE-Net: A deep learning approach for shear wave elastography and lesion segmentation using single push acoustic radiation force

Ultrasound-based non-invasive elasticity imaging modalities have received significant consideration for tissue characterization over the last few years. Though substantial advances have been made, the conventional Shear Wave Elastography (SWE) methods still suffer from poor image quality in regions far from the push location, particularly those which rely on single focused ultrasound push beam to generate shear waves. In this study, we propose DSWE-Net, a novel deep learning-based approach that is able to construct Young’s modulus maps from ultrasonically tracked tissue velocity data resulting from a single acoustic radiation force (ARF) push. The proposed network employs a 3D convolutional encoder, followed by a recurrent block consisting of several Convolutional Long Short-Term Memory (ConvLSTM) layers to extract high-level spatio-temporal features from different time-frames of the input velocity data. Finally, a pair of coupled 2D convolutional decoder blocks reconstructs the modulus image and additionally performs inclusion segmentation by generating a binary mask. We also propose a multi-task learning loss function for end-to-end training of the network with 1260 data samples obtained from a simulation environment which include both bi-level and multi-level phantom structures. The performance of the proposed network is evaluated on 140 synthetic test data and the results are compared both qualitatively and quantitatively with that of the current state of the art method, Local Phase Velocity Based Imaging (LPVI). With an average SSIM of 0.90, RMSE of 0.10 and 20.69 dB PSNR, DSWE-Net performs much better on the imaging task compared to LPVI. Our method also achieves an average IoU score of 0.81 for the segmentation task which makes it suitable for localizing inclusions as well. In this initial study, we also show that our method gains an overall improvement of 0.09 in SSIM, 4.81 dB in PSNR, 2.02 dB in CNR, and 0.09 in RMSE over LPVI on a completely unseen set of CIRS tissue mimicking phantom data. This proves its better generalization capability and shows its potential for use in real-world clinical practice.

A comparative study of full-wave inversion and local time-of-flight approaches in elastography

Most of the current techniques for elastography rely on a pointwise measurement of the induced shear waves. A common assumption in these methods is plane wave propagation in an unbounded domain and local homogeneity of the medium. Because of these simplifying assumptions, complex wave patterns, boundary conditions, and interfaces can present significant challenges to these methods. On the other hand, general nonlinear optimization approaches with PDE constraints relax the underlying assumptions of planar waves and unbounded domains and, hence, can handle very general conditions. However, this generality usually leads to a higher computationally expense as compared to time-of-flight methods. Therefore, the added computational expense and higher complexity of these optimization approaches needs to be justified in the context of elastography. In this work, we present a recent study that compares shear modulus reconstructions obtained with a PDE-constrained optimization approach with a conventional shear wave...

Elasticity imaging of inhomogeneous media using inverse filtering with multiple shear wave generation

Most diseases like cancer cause to change of tissue mechanical properties described by elasticity. Elastography visualizes these changes and aids in early and differential diagnosis of diseases. Shear wave imaging is one of principles of elastography, and using the speed of shear wave generated by mechanical vibration or the acoustic radiation force impulse. Conventional shear wave imaging uses time-of-flight method; however, it causes artifact by reflection and refraction of shear wave. We proposed a method for shear wave elasticity imaging that combines inverse filtering with multiple shear wave sources induced by acoustic radiation force. Shear waves are induced by pushing pulse and recorded by ultrafast imaging, and repeated at multiple pushing points that are sparsely located. An inverse filter can be applied to virtually focus shear waves on an arbitrary point. Shear wave speed is obtained by a measured shear wavelength and its image is constructed by scanning the focal point. An inverse filter can ...

In vivo quantification of the shear modulus of the human Achilles tendon during passive loading using shear wave dispersion analysis

The shear wave velocity dispersion was analyzed in the Achilles tendon (AT) during passive dorsiflexion using a phase velocity method in order to obtain the tendon shear modulus (C55). Based on this analysis, the aims of the present study were (i) to assess the reproducibility of the shear modulus for different ankle angles, (ii) to assess the effect of the probe locations, and (iii) to compare results with elasticity values obtained with the supersonic shear imaging (SSI) technique. The AT shear modulus (C55) consistently increased with the ankle dorsiflexion (N = 10, p < 0.05). Furthermore, the technique showed a very good reproducibility (all standard error of the mean values <10.7 kPa and all coefficient of variation (CV) values ⩽0.05%). In addition, independently from the ankle dorsiflexion, the shear modulus was significantly higher in the proximal location compared to the more distal one. The shear modulus provided by SSI was always lower than C55 and the difference increased with the ankle dorsiflexion. However, shear modulus values provided by both methods were highly correlated (R = 0.84), indicating that the conventional shear wave elastography technique (SSI technique) can be used to compare tendon mechanical properties across populations. Future studies should determine the clinical relevance of the shear wave dispersion analysis, for instance in the case of tendinopathy or tendon tear.

Characterization of anisotropic media with shear waves

In conventional shear wave elastography materials are assumed to be linear, elastic, homogeneous, and isotropic. These assumptions are important to account for in certain tissues because they are not always appropriate. Many tissues such as skeletal muscle, the kidney, and the myocardium are anisotropic. Shear waves can be used to investigate the directionally dependent mechanical properties of anisotropic media. To study these tissues in a systematic way and to account for the effects of the anisotropic architecture, laboratory-based phantoms are desirable. We will report on several phantom-based approaches for studying shear wave anisotropy, assuming that these materials are transversely isotropic. Phantoms with embedded fibers were used to mimic anisotropic tissues. Homogeneous phantoms were compressed to induce transverse isotropy according to the acoustoelastic phenomenon, which is related to nonlinear behavior of the materials. The fractional anisotropy of these phantoms was quantified to compare with measurements made in soft tissues. In addition, soft tissues are also viscoelastic, and we have developed a method to model viscoelastic transversely isotropic materials with the finite element method (FEM). The viscoelastic property estimation from phantom experiments and FEM simulations will also be discussed.

Seismic anisotropy in the Izu‐Bonin subduction system

We evaluated shear wave splitting in local S and teleseismic sS phases from earthquakes that sample the Izu‐Bonin subduction system backarc to examine the dynamics of slab deformation and mantle flow. Splitting times for local S phases range from 0.6 to 1.7 s and 0.9 to 3.2 s for teleseismic sS phases. Fast polarization directions range from ∼NW‐SE to ∼ENE‐WSW and suggest complex mantle deformation across the region. Mantle flow induced by both plate motion and trench‐parallel flow likely combine with fossil slab fabric to control the shear wave splitting observations in the southern portion of Izu‐Bonin. Strong variations in fast polarization directions beneath northern Izu‐Bonin suggest a diversion to trench‐parallel mantle flow behind the Philippine Sea plate. This study demonstrates that many regions of subduction previously inaccessible by conventional shear wave splitting techniques may now be feasibly examined through the use of new, complementary shear wave splitting data sets.

Sonoelastographic imaging of interference patterns for estimation of the shear velocity of homogeneous biomaterials

The shear wave velocity is one of a few important parameters that characterize the mechanical properties of bio-materials. In this paper, two noninvasive methods are proposed to measure the shear velocity by inspecting the shear wave interference patterns. In one method, two shear wave sources are placed on the opposite two sides of a sample, driven by the identical sinusoidal signals. The shear waves from the two sources interact to create interference patterns, which are visualized by the vibration sonoelastography technique. The spacing between the pattern bands equals half of the shear wavelength. The shear velocity can be obtained by taking the product of the wavelength and the frequency. An alternative method is to drive the two vibration sources at slightly different frequencies. In this case, the interference patterns no longer remain stationary. It is proved that the apparent velocity of the moving patterns is proportional to the shear velocity in the medium. Since the apparent velocity of the patterns can be measured by analysing the video sequence, the shear velocity can be obtained thereafter. These approaches are validated by a conventional shear wave time-of-flight approach, and they are accurate within 4% on various homogeneous tissue-mimicking phantoms.