Strain Images Research Articles

Kistik Fibrozisli Çocuklarda Karaciğer Tutulumunun Shear-Wave Elastografi ile Non-invaziv Değerlendirilmesi

Objectives: Hepatobiliary complications commonly occur in cystic fibrosis with increasing prevalence due to longer life expectancies and widespread screening efforts. Shear-wave elastography is a novel noninvasive method that involves application of local mechanical compression on soft tissue using focused ultrasonography and acquiring strain images that show tissue response. We aimed to compare abdominal ultrasonography and Shear-wave elastography and also clinical and laboratory findings of children with cystic fibrosis prospectively. Methods: This study is a prospective study conducted in 13 cystic fibrosis patients followed between February 2018 and March 2019. The severity of cystic fibrosis-related liver disease was categorized according to international criteria. Elastography measurement was performed in the same session with the evaluation of the liver by abdominal ultrasonography in the patients. The liver stiffness measurements were compared with clinical data, biochemistry parameters and ultrasound findings. Results: Measurements were performed in 13 cystic fibrosis children (3 boys, 10 girls). The mean kiloPascal values of liver stiffness measurements with shear-wave elastography were 8.68 (4.1-20.2). The median liver stiffness measurement in subjects without cystic fibrosis-related liver disease was 7.79 kiloPascals (n=5); The median liver stiffness measurement in subjects with cystic fibrosis-related liver disease was 9.23 kiloPascals. Conclusion: Cystic fibrosis-related liver disease has a significantly varying disease burden, its prevalence is increasing, and its early recognition is crucial for treatment and follow-up. Although there are no clear range values determined for children in tissue stiffness measurements in Shear-wave elastography, clinical and other laboratory and imaging methods and follow-up and evaluation are important.

Lateral Strain Imaging using Self-supervised and Physically Inspired Constraints in Unsupervised Regularized Elastography.

Convolutional Neural Networks (CNN) have shown promising results for displacement estimation in UltraSound Elastography (USE). Many modifications have been proposed to improve the displacement estimation of CNNs for USE in the axial direction. However, the lateral strain, which is essential in several downstream tasks such as the inverse problem of elasticity imaging, remains a challenge. The lateral strain estimation is complicated since the motion and the sampling frequency in this direction are substantially lower than the axial one, and a lack of carrier signal in this direction. In computer vision applications, the axial and the lateral motions are independent. In contrast, the tissue motion pattern in USE is governed by laws of physics which link the axial and lateral displacements. In this paper, inspired by Hooke's law, we first propose Physically Inspired ConsTraint for Unsupervised Regularized Elastography (PICTURE), where we impose a constraint on the Effective Poisson's ratio (EPR) to improve the lateral strain estimation. In the next step, we propose self-supervised PICTURE (sPICTURE) to further enhance the strain image estimation. Extensive experiments on simulation, experimental phantom and in vivo data demonstrate that the proposed methods estimate accurate axial and lateral strain maps.

Comparison of strain elastography and shear wave elastography in diagnosis of fibrosis in nonalcoholic fatty liver disease.

To reveal the ability of S-Map strain elastography to diagnose fibrosis in nonalcoholic fatty liver disease (NAFLD) and to compare its diagnostic ability with that of shear wave elastography (SWE). Participants were patients with NAFLD who were scheduled to undergo liver biopsy at our institution between 2015 and 2019. A GE Healthcare LOGIQ E9 ultrasound system was used. For S-Map, the right lobe of the liver was visualized in the section where the heartbeat was detected by right intercostal scanning, a 4 × 2-cm region of interest (ROI) was defined at 5cm from the liver surface, and ROI strain images were acquired. Measurements were repeated six times, with the average taken as the S-Map value. Correlations of S-Map and SWE values with fibrosis stage determined by liver biopsy were analyzed using multiple comparisons. The diagnostic performance of S-Map for fibrosis staging was assessed using receiver operating characteristic curves. In total, 107 patients (65 men, 42 women; mean age 51 ± 14years) were analyzed. The S-Map value by fibrosis stage was 34.4 ± 10.9 for F0, 32.9 ± 9.1 for F1, 29.5 ± 5.6 for F2, 26.7 ± 6.0 for F3, and 22.8 ± 4.19 for F4. By fibrosis stage, the SWE value was 1.27 ± 0.25 for F0, 1.39 ± 0.20 for F1, 1.59 ± 0.20 for F2, 1.64 ± 0.17 for F3, and 1.88 ± 0.19 for F4. The diagnostic performance of S-Map (measured by area under the curve) was 0.75 for F2, 0.80 for F3, and 0.85 for F4. The diagnostic performance of SWE (measured by area under the curve) was 0.88 for F2, 0.87 for F3, and 0.92 for F4. S-Map strain elastography was inferior to SWE in terms of ability to diagnose fibrosis in NAFLD.

Utility of Ultrasound Elastography to Evaluate Poststroke Spasticity and Therapeutic Efficacy: A Narrative Review.

Poststroke spasticity (PSS) is a common complication that affects function and daily self-care. Conservative PSS treatments include traditional rehabilitation, botulinum toxin injection, and extracorporeal shock wave therapy. Currently, the Modified Ashworth Scale and Modified Tardieu Scale are widely used tools to clinically evaluate spasticity, but the best tool for PSS assessment remained controversial. Ultrasound elastography (UE), including shear wave and strain image as the emerging method to evaluate soft tissue elasticity, became popular in clinical applications. Spastic biceps and gastrocnemius muscles were reported to be significantly stiffer compared to nonparetic muscles or healthy control using shear wave or strain elastography. More studies investigated the utility, reliability, and validity of UE in patients with PSS, but the contemporary consensus for the utility of UE in the measurement and therapeutic follow-up of PSS remained lacking. Therefore, this narrative review aimed to appraise the literature on the shear wave and strain elastography on PSS and summarize the roles of UE in assessing the therapeutic efficacy of different PSS interventions.

In Vivo Longitudinal Monitoring of Cardiac Remodeling in Murine Ischemia Models With Adaptive Bayesian Regularized Cardiac Strain Imaging: Validation Against Histology.

Adaptive Bayesian regularized cardiac strain imaging (ABR-CSI) uses raw radiofrequency signals to estimate myocardial wall contractility as a surrogate measure of relative tissue elasticity incorporating regularization in the Bayesian sense. We determined the feasibility of using ABR-CSI -derived strain for in vivo longitudinal monitoring of cardiac remodeling in a murine ischemic injury model (myocardial infarction [MI] and ischemia-reperfusion [IR]) and validated the findings against ground truth histology. We randomly stratified 30 BALB/CJ mice (17 females, 13 males, median age=10 wk) into three surgical groups (MI=10, IR=12, sham=8) and imaged pre-surgery (baseline) and 1, 2, 7 and 14 d post-surgery using a pre-clinical high-frequency ultrasound system (VisualSonics Vevo 2100). We then used ABR-CSI to estimate end-systolic and peak radial (er) and longitudinal (el) strain estimates. ABR-CSI was found to have the ability to serially monitor non-uniform cardiac remodeling associated with murine MI and IR non-invasively through temporal variation of strain estimates post-surgery. Furthermore, radial end-systole (ES) strain images and segmental strain curves exhibited improved discrimination among infarct, border and remote regions around the myocardium compared with longitudinal strain results. For example, the MI group had significantly lower (Friedman's with Bonferroni-Dunn test, p=0.002) ES er values in the anterior middle (infarcted) region at day 14 (n=9, 9.23 ± 7.39%) compared with the BL group (n=9, 44.32 ± 5.49). In contrast, anterior basal (remote region) mean ES er values did not differ significantly (non-significant Friedman's test, χ2=8.93, p=0.06) at day 14 (n=6, 33.05 ± 6.99%) compared with baseline (n=6, 34.02 ± 6.75%). Histology slides stained with Masson's trichrome (MT) together with a machine learning model (random forest classifier) were used to derive the ground truth cardiac fibrosis parameter termed histology percentage of myocardial fibrosis (PMF). Both radial and longitudinal strain were found to have strong statistically significant correlations with the PMF parameter. However, radial strain had a higher Spearman's correlation value (εresρ=-0.67, n=172, p < 0.001) compared with longitudinal strain (εlesρ=-0.60, n=172, p < 0.001). Overall, the results of this study indicate that ABR-CSI can reliably perform non-invasive detection of infarcted and remote myocardium in small animal studies.

A novel tissue mechanics-based method for improved motion tracking in quasi-static ultrasound elastography.

Most cancers are associated with biological and structural changes that lead to tissue stiffening. Therefore, imaging tissue stiffness using quasi-static ultrasound elastography (USE) can potentially be effective in cancer diagnosis. USE techniques developed for stiffness image reconstruction use noisy displacement data to obtain the stiffness images. In this study, we propose a technique to substantially improve the accuracy of the displacement data computed through ultrasound tissue motion tracking techniques, especially in the lateral direction. The proposed technique uses mathematical constraints derived from fundamental tissue mechanics principles to regularize displacement and strain fields obtained using Global Ultrasound Elastography (GLUE) and Second-Order Ultrasound Elastography (SOUL) methods. The principles include a novel technique to enforce (1) tissue incompressibility using 3D Boussinesq model and (2) deformation compatibility using the compatibility differential equation. The technique was validated thoroughly using metrics pertaining to Signal-to-Noise-Ratio (SNR), Contrast-to-Noise-Ratio (CNR) and Normalized Cross Correlation (NCC) for four tissue-mimicking phantom models and two clinical breast ultrasound elastography cases. The results show substantial improvement in the displacement and strain images generated using the proposed technique. The tissue-mimicking phantom study results indicate that the proposed method is superior in improving image quality compared to the GLUE and SOUL techniques as it shows an average axial strain SNR and CNR improvement of 44% and 63%, and lateral strain SNR and CNR improvement of 130% and 435%, respectively. The results of the phantom study also indicate higher accuracy of displacement images obtained using the proposed technique, including improvement ranges of 7-84% and 26-140% for axial and lateral displacement images, respectively. For the clinical cases, the results indicate average improvement of 48% and 64% in SNR and CNR, respectively, in the axial strain images, and average improvement of 40% and 41% in SNR and CNR, respectively, in the lateral strain images. The proposed method is very effective in producing improved estimate of tissue displacement and strain images, especially with the lateral displacement and strain where the improvement is highly remarkable. While the method shows promise for clinical applications, further investigation is necessary for rigorous assessment of the method's performance in the clinic.

Displacement and strain data-driven damage detection in multi-component and heterogeneous composite structures

This work introduces the use of convolutional neural network (CNN) in combination with advanced structural theories for the damage detection of multi-component and composite structures. Well-established component-wise (CW) models based on the Carrera Unified Formulation (CUF) are developed first to demonstrate the effect of localized damages on the mechanical performance of thin-walled beams and laminates. Finite element Monte Carlo simulations of randomly damaged structures are then used to generate a large database of full-field displacement and strain images. These images are lately feed into a dedicated CNN for training purpose and for the prediction of location and intensity of structural damages occurring in unseen scenarios. The results demonstrate the validity of the present approach and suggest the importance of adopting opportune structural models to carry out localized damage detection by image-driven AI. Overall, the research provides good confidence for future investigation and experimental testing.

Abstract 12894: Murine Arterial Wall Strain Estimation With Ultrasound-Based Lagrangian Carotid Strain Imaging and Validation Against Histological Findings

Introduction: Early identification of arterial injury by non-invasive imaging can facilitate research into mechanisms of arterial injury and has the potential to improve patient management. We tested the hypothesis that Lagrangian carotid strain imaging (LCSI) combined with adaptive Bayesian regularization could detect early arterial injury and monitor atherogenesis in a murine model by associating findings with histological examinations. Methods: Radio-frequency (RF) data were collected from the right and left common carotid arteries (CCA) of 10 (5 male and 5 female) ApoE tm1Unc/J mice at 6, 16 and 24 weeks using a high frequency ultrasound system. Cumulative axial, lateral and shear strain images were estimated using LCSI and 3 strain indices: maximum accumulated strain index (MASI), peak mean strain of full ROI index (PMSRI) and strain at peak axial displacement index (SPADI). Mice were euthanized (n=2 at 6 and 16 weeks, n=6 at 24 weeks) for histological examination. Results: We observed sex-specific differences in the temporal variation of strain indices. For male mice, axial PMSRI and SPADI changed significantly from 6 to 24 weeks (mean axial SPADI at 6 = 14.10±6.30 % and 24 weeks = 0.24±6.22%; p=0.0004). For female mice, lateral MASI was significantly higher at 24 than 6 weeks (mean lateral MASI at 6 = 10.26±3.13 % and 24 weeks = 16.42±7.15% p=0.048). Both sexes had strong associations with histological findings. For males, axial PMSRI and SPADI showed significant correlation with the number of elastin fibers (axial PMSRI: r s =0.83, p=0.01; axial SPADI: r s =0.76, p=0.02). For females, lateral and shear MASI had significant correlations with plaque scores (lateral MASI: r s =0.66, p=0.04; shear MASI: r s 0.77, p =0.009). Conclusions: LCSI can quantify carotid arterial wall strain in a murine model non-invasively. Changes in strain were associated with changes in arterial wall microstructure after plaque formation.

Endosonografia a elastografia v diagnostike neuroendokrinných nádorov pankreasu

Summary: Introduction: The group of neuroendocrine tumors derived from pancreatic cells is called pancreatic neuroendocrine tumors (PNETs). The combination of EUS and elastography (EG) expands diagnostic and imaging capabilities. Aim: The aim of our work was to determine the representative images of B-mode for PNET, evaluation of a typical EG image of PNETs, use of strain ratio (SR) and “strain histogram” (SH) in differential diagnosis of PNETs, determination of SR and SH cut off value for PNETs and comparison of standardized measurements with literature. Methods: Patients examined at the Internal Gastroenterology Clinic were included in the cohort. A total of 31 patients were examined. The group included 25 patients (8 men, 17 women). The mean age in group was 52.76 years (14–74). Non-invasive examination by endoscopic ultrasonography was performed on all patients. After locating the lesion by ultrasound, the first recording was made after freezing the image in B-mode and performing size measurement. Subsequently, a Strain elastography measurement was performed. In the monitored group we recorded an average size of 12.75 mm. Results: The characteristics of the image in B-mode were as follows for PNETs 68% hypoechogenic, 12% hyperechogenic, 12% isoechogenic and 8% mixed echogenicity. 80% of PNETs in B-mode were sharply demarcated and 20% with blurred borders. The accuracy of the value assignment typical of pancreatic malignancies using elastography was 96% for PNET in 5-degree classification system and 88% for a 4-degree classification, for SR cut off &gt;3.2 with a sensitivity of 80% and SH cut off &lt;50 100%. Discussion: Given the average tumor sizes observed in our study, EUS provides high sensitivity in PNET diagnostics and allows diagnostics at a time when minimally invasive removal is still possible. In addition to the typical picture of hypoechogenicity and the less frequently described pictures of hyperechogenicity and isoechogenicity for PNET, we also observed mixed echogenicity. The elastographic qualitative strain image evaluated by the four- and five- -degree classification proved to be reliable in distinguishing PNET from benign tumors. In quantitative elastography, the values of SR are between malignant and benign deposits of the pancreas, one of the reasons for such values may be the diversity of this group of diseases with different mitotic activity – grade of the tumor. Conclusion: Consistency of the results published by us, shows the applicability of this method in deciding on a definitive diagnosis if tumor histology is not and cannot be available. Key words: neuroendocrine tumor – pancreas – ultrasonography – elastography

Ultrasound strain elastography-based characterization of in vivo breast lesions using deep learning

Ultrasound strain elastography showed great promise for breast lesion characterization. With the readily available computational power in the clinical workflow, machine learning-based is gaining acceptance in cancer imaging applications. In this study, we combine the latest developments in motion tracking that enables us to obtain high-quality axial strain and full shear strain images to test the deep-learning-based prediction of breast lesion malignancy. To our knowledge, total shear strain images have not been widely used for breast lesion differentiation. More specifically, a PDE-based regularization method [Guo et al., Ultrasonic Imaging (2015)] developed by our group has been improved to get high-quality two-dimensional displacement data. From those high-quality displacement data, total shear strain images can be constructed. We adopted three variants of convolution neural network (CNN) models with attention modules to predict breast lesion malignancy by combining B-mode, axial strain, and total shear strain images and their radiomic features. From our internal database, 150 cases of pathologically-confirmed breast ultrasound data [Hall et al., UMB (2003)] with data augmentation are used to evaluate our machine learning models. Our initial testing results are encouraging with the accuracy and area under the curve being around 0.75.

The Investigation of Mechanical Properties of Polycrystalline Nb Nanowire Under Applied Tensile Deformation by Molecular Dynamics Simulation

In this study, the change in the mechanical properties of Niobium (Nb) nanowire with different grain numbers under applied uniaxial tensile deformation was tried to be investigated by Molecular Dynamics (MD) simulation method. The Embedded Atom Method (EAM), which includes many-body interactions, was used to determine the force interactions between atoms. To determine the effect of grain number on the mechanical properties of Nb nanowire, stress-strain curve, young modulus, yield strain and atomic images obtained from the common neighbor analysis method (CNA) were used. It has been determined that necking and breaking of the model nanowire occur at the grain boundaries, however, the number of grains has important effects on the mechanical properties.

X-ray diffraction imaging of fully packaged n-p-n transistors under accelerated ageing conditions.

X-ray diffraction imaging was used to monitor the local strains that developed around individual n-p-n bipolar transistors within fully encapsulated packages under conditions of extremely high forward bias to simulate accelerated ageing. Die warpage associated with the packaging was observed to relax systematically as the polymer became viscous due to the temperature rise associated with the dissipation of heat in the transistor. The direct image size and intensity from the individual transistors were interpreted in terms of a model in which local thermal expansion is treated as a cylindrical inclusion of distorted material, contrast arising principally from lattice tilt. The extension of the thermal strain image along the emitter with increasing power dissipation was ascribed to the effect of current crowding in the emitter region. Weaker large-area contrast associated with the base-collector region was interpreted as arising from the smaller change in effective misorientation at the high X-ray energy of thermal lattice dilation in the base region.

An Enhanced Method for Full-Inversion-Based Ultrasound Elastography of the Liver.

Similar to many other types of cancer, liver cancer is associated with biological changes that lead to tissue stiffening. An effective imaging technique that can be used for liver cancer detection through visualizing tissue stiffness is ultrasound elastography. In this paper, we show the effectiveness of an enhanced method of quasi-static ultrasound elastography for liver cancer assessment. The method utilizes initial estimates of axial and lateral displacement fields obtained using conventional time delay estimation (TDE) methods in conjunction with a recently proposed strain refinement algorithm to generate enhanced versions of the axial and lateral strain images. Another primary objective of this work is to investigate the sensitivity of the proposed method to the quality of these initial displacement estimates. The strain refinement algorithm is founded on the tissue mechanics principles of incompressibility and strain compatibility. Tissue strain images can serve as input for full-inversion-based elasticity image reconstruction algorithm. In this work, we use strain images generated by the proposed method with an iterative elasticity reconstruction algorithm. Ultrasound RF data collected from a tissue-mimicking phantom and in-vivo data of a liver cancer patient were used to evaluate the proposed method. Results show that while there is some sensitivity to the displacement field initial estimates, overall, the proposed method is robust to the quality of the initial estimates. Clinical Relevance- Improved elasticity images of the liver can aid in achieving more reliable diagnosis of liver cancer.

Influence of key parameters on motion artifacts in lateral strain estimation with spatial angular compounding

Strain imaging can reveal the changes in tissue mechanical properties related to pathological alterations by estimating tissue strains in the lateral and axial directions of ultrasound imaging. The estimation performance in the lateral direction is usually worse than that in the axial direction. Spatial angular compounding (SAC) has been demonstrated to improve the quality of lateral estimation by deriving the lateral displacements using axial displacements obtained from multi-angle transmissions. However, motion and deformation of tissues during multiple transmissions may cause motion artifacts, and thus deteriorate the quality of strain estimation. These artifacts can be reduced by choosing appropriate imaging parameters. However, few studies have been conducted to evaluate the influences of key parameters in strain estimation, such as the pulse repetition frequency (PRF), the number of steering angles (NSA), and the maximum steering angles (MSA), in terms of performance optimization. Therefore, this study aims to investigate the effects of these parameters through simulations and phantom experiments. The performance of strain estimation is evaluated by measuring the root-mean-square error (RMSE) and the standard deviation (SD) in the simulations and phantom experiments, respectively. The contrast-to-noise ratio (CNR) of strain images is calculated in both the simulations and phantom experiments. The results show that motion artifacts in strain estimation can be reduced by increasing the PRF to 1 kHz. When the PRF reaches 1 kHz, further increase of the PRF shows little obvious improvement in strain estimation. An increase in the NSA can cause larger motion artifacts and deteriorate the quality of strain images, and the improvement of strain estimation is limited when the NSA is increased from 3 to 7. An NSA of 3 is thus recommended to balance the influences of motion artifacts and the improvement for strain estimation. The MSA has little influence on the motion artifacts, while increased MSA can achieve improved lateral estimation performance at the cost of a smaller imaging region. In light of the lateral strain estimation performance and imaging region, an MSA of 15° is recommended. The influences of these key parameters obtained from this study may provide insights for parameter optimization in strain estimation with SAC to minimize the effects of motion artifacts.

Mechanical response and strain localization in coal under uniaxial loading, using digital volume correlation on X-ray tomography images

A comprehensive analysis of crack initiation and propagation in coal is critical for understanding its mechanical behavior and its impact on permeability. The finite element-based digital volume correlation (DVC) of time-resolved X-ray tomography images under cleat-parallel uniaxial compression provides 3D incremental strain fields to understand the evolution and propagation of cracks. In this study, DVC coupled with quantitative image analysis was used to understand the role of cleats in guiding and initiating cracks in coal. Simulation of fluid flow through coal at different loading segments provides dynamic quantification of evolution in permeability. After each loading stage, quantification of strain eigen vectors and image analysis indicates appearance, coexistence, and coalescence of tensile and shear cracks guided by the organic matter in coal. We established that constructive interference between tensile and shear crack systems enhances permeability and decreases tortuosity by almost 3x and 7x respectively in coal by widening crack aperture, however, destructive interference is likely to lead to matrix pulverization and clogging of larger crack apertures. During compression, while one part of the coal matrix shows extension perpendicular to the loading direction, another part shows slippage parallel to the loading direction. Based on the variation in crack propagation behavior, four distinct crack morphology zones were identified and discussed. We found that the tortuosity of the cracks decreases exponentially, while permeability and crack volume fraction increase exponentially up to 2.8 μm2 and 28.6% respectively with increasing load. The box-counting-based fractal dimension for the cracks shows a steady increase from 1.58 to 1.78 with loading due to the evolution of existing cracks, and the formation of new cracks.

Murine cardiac fibrosis localization using adaptive Bayesian cardiac strain imaging in vivo

An adaptive Bayesian regularized cardiac strain imaging (ABR-CSI) algorithm for in vivo murine myocardial function assessment is presented. We report on 31 BALB/CJ mice (n = 17 females, n = 14 males), randomly stratified into three surgical groups: myocardial infarction (MI, n = 10), ischemia–reperfusion (IR, n = 13) and control (sham, n = 8) imaged pre-surgery (baseline- BL), and 1, 2, 7 and 14 days post-surgery using a high frequency ultrasound imaging system (Vevo 2100). End-systole (ES) radial and longitudinal strain images were used to generate cardiac fibrosis maps using binary thresholding. Percentage fibrotic myocardium (PFM) computed from regional fibrosis maps demonstrated statistically significant differences post-surgery in scar regions. For example, the MI group had significantly higher PFMRadial (%) values in the anterior mid region (p = 0.006) at Day 14 (n = 8, 42.30 ± 14.57) compared to BL (n = 12, 1.32 ± 0.85). A random forest classifier automatically detected fibrotic regions from ground truth Masson’s trichrome stained histopathology whole slide images. Both PFMRadial (r = 0.70) and PFMLongitudinal (r = 0.60) results demonstrated strong, positive correlation with PFMHistopathology (p < 0.001).

Incorporating Gradient Similarity for Robust Time Delay Estimation in Ultrasound Elastography.

Energy-based ultrasound elastography techniques minimize a regularized cost function consisting of data and continuity terms to obtain local displacement estimates based on the local time-delay estimation (TDE) between radio frequency (RF) frames. The data term associated with the existing techniques takes only the amplitude similarity into account and hence is not sufficiently robust to the outlier samples present in the RF frames under consideration. This drawback creates noticeable artifacts in the strain image. To resolve this issue, we propose to formulate the data function as a linear combination of the amplitude and gradient similarity constraints. We estimate the adaptive weight concerning each similarity term following an iterative scheme. Finally, we optimize the nonlinear cost function in an efficient manner to convert the problem to a sparse system of linear equations which are solved for millions of variables. We call our technique rGLUE: robust data term in GLobal Ultrasound Elastography. rGLUE has been validated using simulation, phantom, in vivo liver, and breast datasets. In all our experiments, rGLUE substantially outperforms the recent elastography methods both visually and quantitatively. For simulated, phantom, and in vivo datasets, respectively, rGLUE achieves 107%, 18%, and 23% improvements of signal-to-noise ratio (SNR) and 61%, 19%, and 25% improvements of contrast-to-noise ratio (CNR) over global ultrasound elastography (GLUE), a recently published elastography algorithm.

Experimental research on deformation failure process of roadway tunnel in fractured rock mass induced by mining excavation.

Deformation failure of roadways in fractured rock can lead to large-volume collapse and other engineering accidents. Failure mechanisms in fractured rock are complex and poorly understood, so to explore this issue, we simulated fractured rock masses using physical model tests in combination with numerical computations. A set of experimental techniques for roadway excavation under jointed surrounding rock included a mixed pouring–bricking method and a roadway excavation device, which can reproduce the structural characteristics of the prototype and replicate the excavation conditions of the roadway. Stress distribution characteristics of the roadway, from loading to excavation, were obtained based on strain monitoring and image acquisition, and the process of roadway deformation and failure was described in detail. A series of numerical simulations were conducted to investigate the deformation failure mechanisms of roadways under different excavation conditions. Results indicate that the deformation failure modes of roadways including collapse, rock burst, and floor heaving that were similar regardless of depth. Deformation failure modes of the roadway were determined by rock mass structure, and the deformation intensity was determined by geo-stress. Model testing and numerical simulation were consistent; hence, findings provide a theoretical basis and technical guidance for roadway engineering in fractured rock masses.

Hadamard-Encoded Synthetic Transmit Aperture Imaging for Improved Lateral Motion Estimation in Ultrasound Elastography.

Lateral motion estimation has been a challenge in ultrasound elastography mainly due to the low resolution, low sampling frequency, and lack of phase information in the lateral direction. Synthetic transmit aperture (STA) can achieve high resolution due to two-way focusing and can beamform high-density image lines for improved lateral motion estimation with the disadvantages of low signal-to-noise ratio (SNR) and limited penetration depth. In this study, Hadamard-encoded STA (Hadamard-STA) is proposed for the improvement of lateral motion estimation in elastography, and it is compared with STA and conventional focused wave (CFW) imaging. Simulations, phantom, and in vivo experiments were conducted to make the comparison. The normalized root mean square error (NRMSE) and the contrast-to-noise ratio (CNR) were calculated as the evaluation criteria in the simulations. The results show that, at a noise level of -10 dB and an applied strain of -1% (compression), Hadamard-STA decreases the NRMSEs of lateral displacements by 46.92% and 35.35%, decreases the NRMSEs of lateral strains by 52.34% and 39.75%, and increases the CNRs by 9.70 and 9.75 dB compared with STA and CFW, respectively. In the phantom experiments performed on a heterogeneous tissue-mimicking phantom, the sum of squared differences (SSD) between the reference and the motion-compensated RF data, and the CNR were calculated as the evaluation criteria. At an applied strain of -1.80%, Hadamard-STA is found to decrease the SSDs by 20.91% and 30.99% and increase the CNRs by 14.15 and 24.66 dB compared with STA and CFW, respectively. In the experiments performed on a breast phantom, Hadamard-STA achieves better visualization of the breast inclusion with a clearer boundary between the inclusion and the background than STA and CFW. The in vivo experiments were performed on a patient with a breast tumor, and the tumor could also be better visualized with a more homogeneous background in the strain image obtained by Hadamard-STA than by STA and CFW. These results demonstrate that Hadamard-STA achieves a substantial improvement in lateral motion estimation and maybe a competitive method for quasi-static elastography.

Supine dynamic simulation and latex pillow design for Chinese women based on finite element method

The ergonomics on body pressure distribution of latex product design is the future trend in bedding product design. The numerical simulation of latex pillow compression performance is critical for the optimal design of bedding products. This paper reports the use of the finite element method to simulate the compression performance of latex foam and the design of latex pillows based on the pressure distribution and displacement changes of the human pillow system. The compression performance, shear performance and tensile performance of the latex foam are tested, and the stress and strain images of three mechanical experiments are obtained. Combined with the experimental results, three methods of ‘hyper foam test data, hyper foam model parameter method and low-density foam method’ were used to perform uniaxial compression simulation on bedding latex foam using the finite element software ABAQUS. The simulation results and experimental values were fitted and analyzed. The analysis found that the low-density foam simulation method has the largest R2, which is 0.9871, and the simulation result is the most accurate. The optimal simulation method was selected to simulate the dynamic pressure changes and cervical displacement of the human head and latex pillow models, as well as the simulation experiments with latex pillows of different heights. The curve is fitted to obtain the second-order polynomial equations of pressure and cervical socket displacement. In contrast, it can be concluded that latex pillow products with a neck height of 100 mm are better for the supine position of younger adult women in China.