Elasticity Imaging Research Articles

Diagnosis of Benign and Malignant Breast Nodules by Conventional Ultrasound in Combination with S-Detect Technology and Elastic Imaging.

To determine the diagnostic value of conventional ultrasound combined with S-Detect and elastic imaging technology in differentiating between benign and malignant breast nodules. Observational study. Place and Duration of the Study: Department of Ultrasound Imaging, Yichang Central People's Hospital, Yichang, China, from October 2019 to October 2022. The study included all breast nodules diagnosed using ultrasound, with patients undergoing conventional ultrasound for BI-RADS classification, elasticity score, and S-Detect examination. Benign and malignant breast nodules were classified according to the three tests and their combinations. The diagnostic sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and area under curve (AUV) of those alone and combinations were calculated and compared. Of the three methods, BI-RADS, elasticity score, and S-Detect, BI-RADS had the highest accuracy (89.29%), elasticity score had the highest specificity (96.20%), and S-Detect had the highest sensitivity (93.92%). The accuracy of combined groups were higher than that of the single group. When combined with elasticity score, the AUC of the new BI-RADS increased from 0.882 to 0.917 (p <0.001); and combined with S-Detect, the AUC of the new BI-RADS increased from 0.882 to 0.927 (p <0.001). The combination of conventional ultrasound BI-RADS classification with elasticity score or S-Detect technology has a higher diagnostic efficacy for breast nodules, which can improve breast cancer detection and provide valuable diagnostic evidence for clinical practice. S-Detect technology, Ultrasound elastic imaging, Elasticity scoring, Elasticity strain ratio value, Breast tumour.

Application of Lightweight Deep Learning Model-Based Shear Wave Elastic Imaging with Abdominal Probe to Diagnose Prostate Cancer: A Biomedical Approach

We aimed to investigate the diagnostic value of lightweight convolutional neural network (CNN) model abdominal probe shear wave elastic imaging (SWE) in the perineal diagnosis and guided puncture biopsy of prostate cancer (PCa), and to provide reference for the clinical diagnosis of PCa. 100 PCa patients were assigned to group I (malignant) and group II (benign), with 50 cases in each. Ultrasonic elastic imaging based on lightweight convolutional neural network denoising model was adopted for detection. In both systolic and diastolic blood pressure (SBP/DBP), there was not a significant intergroup difference (P &gt; 0.05). The levels of prostate specific antigen (PSA) and its free variant (fPSA) in group II were markedly lower (P &lt; 0.05). Patients in group II had obviously more cystic components and fewer solid components. Patients with hyperechogenicity was more in group II. Patients had clearly fewer irregular margins and outward margin spread in group II. Patients without focal hyperechogenicity and punctate hyperechogenicity was more in group II, and the number of calcifications in group II was less. Patients with type 0 and type I was more and patients with type IIa and type IIb was less in group II. The Emean level of patients in group II was clearly higher, and the Emax level and Esd level of patients in group II were clearly lower. The SI level of patients was clearly lower in group II TTP was higher in group II (P &lt; 0.05). Multivariate logistic regression analysis of abdominal probe SWE for transperineal diagnosis of PCa and guided puncture biopsy showed that internal echoes had the greatest OR and were associated with the occurrence of PCa. Ultrasonic elastic imaging index based on the lightweight convolutional neural network denoising model can be used for the benign and malignant diagnosis of PCa patients.

Image-domain least-squares imaging in an elastic vertically transversely isotropic medium: Multiparameter point-spread function deconvolution

By solving a linear inverse problem, least-squares migration (LSM) can provide higher-precision images of complex subsurface structures than traditional adjoint-operator-based migration. LSM can be conducted in the data domain and the image domain (IDLSM). IDLSM in acoustic media has been extensively studied, commonly using single-parameter point-spread function (PSF) deconvolution. For high-accuracy imaging of complex media, we develop an image-domain elastic least-squares imaging method using multiparameter PSF deconvolution for vertically transversely isotropic (VTI) media. The multiparameter PSFs, including P-P, P-S, S-P, and S-S components, are calculated on a sparse grid using elastic VTI wave equation Born modeling and migration. The traditional migration result is then decomposed into individual local results, each corresponding to the size of a single PSF, through unit partitioning. Finally, a set of filters is derived from four elastic VTI PSF components to approximate the Hessian inverse, which are subsequently assembled to reconstruct an entire deconvolved image. The numerical experiments confirm that our method can significantly decrease multiparameter crosstalk artifacts and improve spatial resolution and amplitude fidelity.

Multimodal mechano-microscopy reveals mechanical phenotypes of breast cancer spheroids in three dimensions.

Cancer cell invasion relies on an equilibrium between cell deformability and the biophysical constraints imposed by the extracellular matrix (ECM). However, there is little consensus on the nature of the local biomechanical alterations in cancer cell dissemination in the context of three-dimensional (3D) tumor microenvironments (TMEs). While the shortcomings of two-dimensional (2D) models in replicating in situ cell behavior are well known, 3D TME models remain underutilized because contemporary mechanical quantification tools are limited to surface measurements. Here, we overcome this major challenge by quantifying local mechanics of cancer cell spheroids in 3D TMEs. We achieve this using multimodal mechano-microscopy, integrating optical coherence microscopy-based elasticity imaging with confocal fluorescence microscopy. We observe that non-metastatic cancer spheroids show no invasion while showing increased peripheral cell elasticity in both stiff and soft environments. Metastatic cancer spheroids, however, show ECM-mediated softening in a stiff microenvironment and, in a soft environment, initiate cell invasion with peripheral softening associated with early metastatic dissemination. This exemplar of live-cell 3D mechanotyping supports that invasion increases cell deformability in a 3D context, illustrating the power of multimodal mechano-microscopy for quantitative mechanobiology in situ.

A novel explicit optimized scheme for numerical simulation of elastic-wavefield separation

Abstract Numerical simulation of elastic wave equation helps us better understand the information of underground structures and elastic wave imaging has attracted the widespread attention of researchers. Using elastic wave imaging requires separating the compressional and shear wavefields. Therefore, we develop a novel explicit optimized scheme to simulate the separated elastic wavefield. We construct a kind of 1-norm objective function directly utilizing the dispersion error and employ the simulated annealing algorithm to acquire improved finite-difference operators, whose optimal coefficients can effectively suppress spatial numerical dispersion. Meanwhile, we introduce a rotated staggered-grid (RSG) approach to enhance computational stability. Then, our proposed scheme also called the optimized RSG approach is applied to the elastic wave equations and decoupled elastic wave equations to simulate the decoupled compressional and shear wavefield propagation. Numerical dispersion analysis is consistent with numerical results. The waveform comparison shows that the optimized RSG approach possesses higher accuracy, and several complex models are used to validate the applicability and effectiveness of the presented scheme.

Validity of Elastic Imaging Evaluation of Hamstring Muscles With Knee Contracture Using Ultrasound Shear Wave Elastography.

This study used ultrasound shear wave elastography (SWE) to evaluate the mechanical properties of hamstring muscles from cadaveric specimens with knee flexion contractures. Hamstring muscles for tensile testing were harvested from Thiel soft-embalmed cadavers with and without knee flexion contracture. Muscle specimens were mounted on a testing machine. The initial load detected when a tensile load was applied to the distal end was used as the slack length. The cross-sectional areas of the muscle at slack length were measured at the proximal and distal sites using B-mode ultrasonography. Subsequently, the muscle specimen was elongated from the slack length to 8% strain, with the shear modulus measured using SWE. Young's modulus (stress/strain) was calculated based on the displacement and tensile force obtained from the tensile test. Regression analysis showed a significant positive linear relationship between the Young's and shear moduli for all specimens at all the sites (P < 0.01 and coefficient of determination: 0.95-0.99). The Young's and average shear moduli at the proximal and distal sites were higher in all hamstring muscles with contractures than in those without contractures. SWE can be used to estimate Young's moduli of hamstring muscles with contractures. Muscle specimens with contractures exhibited higher resistance to elongation, thereby indicating that their mechanical properties differed from those of muscles without contractures.

Differential phase contrast from electrons that cause inner shell ionization

Differential Phase Contrast (DPC) imaging, in which deviations in the bright field beam are in proportion to the electric field, has been extensively studied in the context of pure elastic scattering. Here we discuss differential phase contrast formed from core-loss scattered electrons, i.e. those that have caused inner shell ionization of atoms in the specimen, using a transition potential approach for which we study the number of final states needed for a converged calculation. In the phase object approximation, we show formally that differential phase contrast formed from core-loss scattered electrons is mainly a result of preservation of elastic contrast. Through simulation we demonstrate that whether the inelastic DPC images show element selective contrast depends on the spatial range of the ionization interaction, and specifically that when the energy loss is low the delocalisation can lead to contributions to the contrast from atoms other than that ionized. We further show that inelastic DPC images remain robustly interpretable to larger thicknesses than is the case for elastic DPC images, owing to the incoherence of the inelastic wavefields, though subtleties due to channelling remain. Lastly, we show that while a very high dose will be needed for sufficient counting statistics to discern differential phase contrast from core-loss scattered electrons, there is some enhancement of the signal-to-noise ratio with thickness that makes inelastic DPC imaging more achievable for thicker samples.

Tumor spheroid elasticity estimation using mechano-microscopy combined with a conditional generative adversarial network

Background and ObjectivesTechniques for imaging the mechanical properties of cells are needed to study how cell mechanics influence cell function and disease progression. Mechano-microscopy (a high-resolution variant of compression optical coherence elastography) generates elasticity images of a sample undergoing compression from the phase difference between optical coherence microscopy (OCM) B-scans. However, the existing mechano-microscopy signal processing chain (referred to as the algebraic method) assumes the sample stress is uniaxial and axially uniform, such that violation of these assumptions reduces the accuracy and precision of elasticity images. Furthermore, it does not account for prior information regarding the sample geometry or mechanical property distribution. In this study, we investigate the feasibility of training a conditional generative adversarial network (cGAN) to generate elasticity images from phase difference images of samples containing a cell spheroid embedded in a hydrogel. MethodsTo construct the cGAN training and simulated test sets, we generated 30,000 artificial elasticity images using a parametric model and computed the corresponding phase difference images using finite element analysis to simulate compression applied to the artificial samples. We also imaged real MCF7 breast tumor spheroids embedded in hydrogel using mechano-microscopy to construct the experimental test set and evaluated the cGAN using the algebraic elasticity images and co-registered OCM and confocal fluorescence microscopy (CFM) images. ResultsComparison with the simulated test set ground truth elasticity images shows the cGAN produces a lower root mean square error (median: 3.47 kPa, 95 % confidence interval (CI) [3.41, 3.52]) than the algebraic method (median: 4.91 kPa, 95 % CI [4.85, 4.97]). For the experimental test set, the cGAN elasticity images contain features resembling stiff nuclei at locations corresponding to nuclei seen in the algebraic elasticity, OCM, and CFM images. Furthermore, the cGAN elasticity images are higher resolution and more robust to noise than the algebraic elasticity images. ConclusionsThe cGAN elasticity images exhibit better accuracy, spatial resolution, sensitivity, and robustness to noise than the algebraic elasticity images for both simulated and real experimental data.

DFA-UNet: dual-stream feature-fusion attention U-Net for lymph node segmentation in lung cancer diagnosis.

In bronchial ultrasound elastography, accurately segmenting mediastinal lymph nodes is of great significance for diagnosing whether lung cancer has metastasized. However, due to the ill-defined margin of ultrasound images and the complexity of lymph node structure, accurate segmentation of fine contours is still challenging. Therefore, we propose a dual-stream feature-fusion attention U-Net (DFA-UNet). Firstly, a dual-stream encoder (DSE) is designed by combining ConvNext with a lightweight vision transformer (ViT) to extract the local information and global information of images; Secondly, we propose a hybrid attention module (HAM) at the bottleneck, which incorporates spatial and channel attention to optimize the features transmission process by optimizing high-dimensional features at the bottom of the network. Finally, the feature-enhanced residual decoder (FRD) is developed to improve the fusion of features obtained from the encoder and decoder, ensuring a more comprehensive integration. Extensive experiments on the ultrasound elasticity image dataset show the superiority of our DFA-UNet over 9 state-of-the-art image segmentation models. Additionally, visual analysis, ablation studies, and generalization assessments highlight the significant enhancement effects of DFA-UNet. Comprehensive experiments confirm the excellent segmentation effectiveness of the DFA-UNet combined attention mechanism for ultrasound images, underscoring its important significance for future research on medical images.

Biomechanically based Fu’s subcutaneous needling treatment for senile knee osteoarthritis: protocol for a randomized controlled trial

IntroductionFu’s subcutaneous needling (FSN) is a new type of acupuncture that uses subcutaneous tissue to oscillate from side to side to improve muscle pathology status and can be effective in treating Knee osteoarthritis. Nonetheless, whether the clinical effect is similar to that of most commonly used drugs is unclear. Thus, this study aims to determine the pain-relieving effect and improvement in the joint function of the FSN therapy by comparing it with that of a positive control drug (celecoxib). Furthermore, this clinical trial also aims to evaluate the effect of FSN on gait and lower limb muscle flexibility, which can further explore the scientific mechanisms of the FSN therapy.Methods and analysisThis study is a randomized, parallel-controlled, single-center prospective clinical study that includes 60 participants, with an FSN group (n = 30) and a drug group (n = 30). The Fu’s subcutaneous needling (FSN) group undergo the FSN therapy 3 times a week for 2 weeks, while the drug group receives 0.2 g/day oral celecoxib for 2 weeks, with a follow-up period of 4 weeks after the completion of treatment. The primary outcome is the difference in the visual analog scale score after 2 weeks of treatment compared with baseline. The Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index, joint active range of motion test, three-dimensional gait analysis, and shear wave elastic imaging technology analysis in lower limb muscles are also performed to demonstrate clinical efficacy.Ethics and disseminationThe trial is performed following the Declaration of Helsinki. The study protocol and consent form have been approved by the Ethics Committee of Guangdong Provincial Hospital of Chinese Medicine. All patients will give informed consent before participation and the trial is initiated after approval. The results of this trial will be disseminated through publication in peer-reviewed journals.Trial registration number: NCT06328153.

Discovering 3D hidden elasticity in isotropic and transversely isotropic materials with physics-informed UNets

Three-dimensional variation in structural components or fiber alignments results in complex mechanical property distribution in tissues and biomaterials. In this paper, we use a physics-informed UNet-based neural network model (El-UNet) to discover the three-dimensional (3D) internal composition and space-dependent material properties of heterogeneous isotropic and transversely isotropic materials without a priori knowledge of the composition. We then show the capabilities of El-UNet by validating against data obtained from finite-element simulations of two soft tissues, namely, brain tissue and articular cartilage, under various loading conditions. We first simulated compressive loading of 3D brain tissue comprising of distinct white matter and gray matter mechanical properties undergoing small strains with isotropic linear elastic behavior, where El-UNet reached mean absolute relative errors under 1.5 % for elastic modulus and Poisson's ratio estimations across the 3D volume. We showed that the 3D solution achieved by El-UNet was superior to relative stiffness mapping by inverse of axial strain and two-dimensional plane stress/plane strain approximations. Additionally, we simulated a transversely isotropic articular cartilage with known fiber orientations undergoing compressive loading, and accurately estimated the spatial distribution of all five material parameters, with mean absolute relative errors under 5 %. Our work demonstrates the application of the computationally efficient physics-informed El-UNet in 3D elasticity imaging and provides methods for translation to experimental 3D characterization of soft tissues and other materials. The proposed El-UNet offers a powerful tool for both in vitro and ex vivo tissue analysis, with potential extensions to in vivo diagnostics. Statement of significanceElasticity imaging is a technique that reconstructs mechanical properties of tissue using deformation and force measurements. Given the complexity of this reconstruction, most existing methods have mostly focused on 2D problems. Our work is the first implementation of physics-informed UNets to reconstruct three-dimensional material parameter distributions for isotropic and transversely isotropic linear elastic materials by having deformation and force measurements. We comprehensively validate our model using synthetic data generated using finite element models of biological tissues with high bio-fidelity–the brain and articular cartilage. Our method can be implemented in elasticity imaging scenarios for in vitro and ex vivo mechanical characterization of biomaterials and biological tissues, with potential extensions to in vivo diagnostics.

Elastic reverse time migration based on first-order velocity-dilatation-rotation equations using the optical flow vector

The determination of the P- and S-wave propagation directions is crucial for wavefield decomposition, polarity reversal correction, and noise suppression in elastic reverse time migration (RTM). Compared with the conventional decoupled elastic wave equation, the first-order velocity-dilatation-rotation equations enable more accurate computation of propagation directions for P and S waves. Moreover, compared with the Poynting vector, the optical flow vector signifies the wavefield propagation directions more accurately. To effectively enhance the accuracy of elastic wave imaging, we develop an elastic RTM based on first-order velocity-dilatation-rotation equations using the optical flow vector. Numerical tests illustrate that our method, with or without noise, can better eliminate migration artifacts and improve the imaging accuracy of the elastic RTM than conventional methods, achieving more accurate wavefield decomposition and superior S-wave polarity reversal correction.

Structural tuning of anisotropic mechanical properties in 3D-Printed hydrogel lattices

We investigated the ability to tune the anisotropic mechanical properties of 3D-printed hydrogel lattices by modifying their geometry (lattice strut diameter, unit cell size, and unit cell scaling factor). Many soft tissues are anisotropic and the ability to mimic natural anisotropy would be valuable for developing tissue-surrogate “phantoms” for elasticity imaging (shear wave elastography or magnetic resonance elastography). Vintile lattices were 3D-printed in polyethylene glycol di-acrylate (PEGDA) using digital light projection printing. Two mechanical benchtop tests, dynamic shear testing and unconfined compression, were used to measure the apparent shear storage moduli (G′) and apparent Young's moduli (E) of lattice samples. Increasing the unit cell size from 1.25 mm to 2.00 mm reduced the Young's and shear moduli of the lattices by 91% and 85%, respectively. Decreasing the strut diameter from 300 μm to 200 μm reduced the apparent shear moduli of the lattices by 95%. Increasing the geometric scaling ratio of the lattice unit cells from 1.00 × to 2.00 × increased mechanical anisotropy in shear (by a factor of 3.1) and in compression (by a factor of 2.9). Both simulations and experiments show that the effects of unit cell size and strut diameter are consistent with power law relationships between volume fraction and apparent elastic moduli. In particular, experimental measurements of apparent Young's moduli agree well with predictions of the theoretical Gibson-Ashby model. Thus, the anisotropic mechanical properties of a lattice can be tuned by the unit cell size, the strut diameter, and scaling factors. This approach will be valuable in designing tissue-mimicking hydrogel lattice-based composite materials for elastography phantoms and tissue engineered scaffolds.

Comparison of polystyrene and hydrogel microcarriers for optical imaging of adherent cells.

The ability to observe and monitor cell density and morphology has been imperative for assessing the health of a cell culture and for producing high quality, high yield cell cultures for decades. Microcarrier-based cultures, used for large-scale cellular expansion processes, are not compatible with traditional visualization-based methods, such as widefield microscopy, due to their thickness and material composition. Here, we assess the optical imaging compatibilities of commercial polystyrene microcarriers versus custom-fabricated gelatin methacryloyl (gelMA) microcarriers for non-destructive and non-invasive visualization of the entire microcarrier surface, direct cell enumeration, and sub-cellular visualization of mesenchymal stem/stromal cells. Mie scattering and wavefront error simulations of the polystyrene and gelMA microcarriers were performed to assess the potential for elastic scattering-based imaging of adherent cells. A Zeiss Z.1 light-sheet microscope was adapted to perform light-sheet tomography using label-free elastic scattering contrast from planar side illumination to achieve optical sectioning and permit non-invasive and non-destructive, in toto, three-dimensional, high-resolution visualization of cells cultured on microcarriers. The polystyrene microcarrier prevents visualization of cells on the distal half of the microcarrier using either fluorescence or elastic scattering contrast, whereas the gelMA microcarrier allows for high fidelity visualization of cell morphology and quantification of cell density using light-sheet fluorescence microscopy and tomography. The combination of optical-quality gelMA microcarriers and label-free light-sheet tomography will facilitate enhanced control of bioreactor-microcarrier cell culture processes.

Elastic time-reverse imaging of backscattered surface-wave data

Imaging shallow near-vertical or short-wavelength structure using seismic data is an important goal in near-surface geophysical applications. Numerous seismic analysis approaches use backscattered analysis of surface waves for these purposes; however, there is a need for new associated frameworks that can take advantage of these events to generate interpretable images in the depth-migrated domain. By drawing a connection with elastic time-reverse imaging (E-TRI) approaches developed for microseismic event analysis, an efficient elastic migration approach is developed that uses two adjoint wavefields defined by partitioned outward-propagating transmission and inward-propagating scattered surface-wave data. Subsurface images are generated by applying the energy-norm imaging condition that correlates temporally and spatially colocated energy throughout the two time-reversed adjoint wavefield domains. Synthetic tests highlight the ability of the E-TRI framework to image shallow (quasi)vertical subsurface discontinuities. Results from a field test using near-surface seismic data acquired in the Majes region of Arequipa, Peru, demonstrate the ability of the E-TRI framework to highlight short-wavelength structure identified in a parallel elastic full-waveform inversion analysis. The results suggest that the E-TRI technique should be applicable in a range of near-surface geotechnical and environmental applications.

Reflected shear wave computed tomography for elasticity imaging of 3D cell cultures using a single-element transducer

Shear wave elasticity imaging (SWEI) has long been used to quantify tissue stiffness in clinical diagnoses. In comparison with conventional bulk-based measurement methods, SWEI offers the distinct advantage of nondestructive sampling, thereby enabling the spatiotemporal monitoring of stiffness variations. However, applying SWEI to assessing millimeter-scale three-dimensional (3D) cell environments has faced limitations despite its potential in mechanobiology, and the existing techniques are insufficient for imaging inhomogeneous media environments. In this study, we investigated a computed tomography technique specifically designed for reflected SWEI (called R-SWCT) by rotational scanning in a sample using a 20-MHz ultrasound single-element transducer. We focused on samples containing a single inclusion with higher stiffness than the surrounding medium, mimicking the situation of a tumor sphere embedded in a 3D gel. Our method reconstructs the stiffness distribution using a curve-fitting method, wherein coefficients of Gaussian curves are fitted to the wavefronts of simulated signals. This reconstruction method yielded coefficients that closely approximated the wavefronts obtained experimentally, with a maximum difference between the measured and predicted shear wave speeds of only 0.1 m/s for phantom samples and 0.2 m/s for cell samples. The system and methodologies proposed in this research have demonstrated the feasibility of employing R-SWCT to study the remodeling dynamics of a cell group within its surrounding matrix in an in vitro setting. This noninvasive method also facilitates an exploration of how irradiation dosage used in radiation therapy can induce temporal alterations in the shear wave speed in 3D cancer cell cultures.

Mouse brain elastography changes with sleep/wake cycles, aging, and Alzheimer's disease

Understanding the physiological processes in aging and how neurodegenerative disorders affect cognitive function is a high priority for advancing human health. One specific area of recently enabled research is the in vivo biomechanical state of the brain. This study utilized reverberant optical coherence elastography, a high-resolution elasticity imaging method, to investigate stiffness changes during the sleep/wake cycle, aging, and Alzheimer's disease in murine models. Four-dimensional scans of 44 wildtype mice, 13 mice with deletion of aquaporin-4 water channel, and 12 mice with Alzheimer-related pathology (APP/PS1) demonstrated that (1) cortical tissue became softer (on the order of a 10% decrease in shear wave speed) when young wildtype mice transitioned from wake to anesthetized, yet this effect was lost in aging and with mice overexpressing amyloid-β or lacking the water channel AQP4. (2) Cortical stiffness increased with age in all mice lines, but wildtype mice exhibited the most prominent changes as a function of aging. The study provides novel insight into the brain's biomechanics, the constraints of fluid flow, and how the state of brain activity affects basic properties of cortical tissues.

Evaluation of Carotid Stiffness in Metabolic Syndrome by Real-Time Shear Wave Elasticity Imaging and Ultrafast Pulse Wave Velocity

ObjectiveThis study utilized real-time shear wave elasticity imaging (SWE) and ultrafast pulse wave velocity (ufPWV) to assess carotid arterial stiffness, aiming to predict atherosclerosis risk in patients with metabolic syndrome (MS). MethodsIn this study, 181 patients with metabolic syndrome (MS group) were compared with 73 healthy adults. The MS group was divided into three groups: MS I group: CIMT was normal (CIMT < 1.0 mm, no plaque, n = 61); MS II group: CIMT thickening (1.0 mm ≤ CIMT<1.5 mm, no plaque, n = 39); MS III group: plaque group (CIMT ≥ 1.5 mm, plaque, n = 81). Concurrently, the group of 73 healthy individuals was designated as the control set (NC). Parameters assessed include carotid intima-media thickness (CIMT), elastic modulus values of the carotid artery's anterior and posterior walls (Mean, Max, Min), pulse wave velocity at systole's commencement (PWV-BS), and pulse wave velocity at systole's termination (PWV-ES). Differences, distribution characteristics, and correlations across these groups were analyzed. ResultsA significant association was found between PWV-BS, PWV-ES, and arteriosclerosis severity, with these factors gaining importance as arteriosclerosis progressed. Notably, PWV-ES differences were significant across the four groups (p < 0.05). Both MS III and MS II groups exhibited higher PWV-ES values compared to the MS I group and controls. Statistically significant differences were observed between MS III, MS II, and MS I groups relative to the control group (p < 0.05). Additionally, the Mean, Max, and Min values of the anterior and posterior carotid walls in the MS III group surpassed those of the other groups. ConclusionReal-time shear wave elasticity imaging and ultrafast pulse wave velocity are valuable tools for assessing atherosclerosis risk in MS patients. These non-invasive, safe, and reproducible imaging techniques can quantitatively evaluate the stiffness of the common carotid artery's wall, offering important insights into cardiovascular risk assessment.

Endometrial Elasticity is an Ultrasound Marker for Predicting Clinical Pregnancy Outcomes after Embryo Transfer.

Endometrial elasticity is a potential new marker for assessing endometrial receptivity and pregnancy outcomes based on endometrial thickness and type. Currently, little research has been conducted on the elasticity of the endometrium using shear wave elasticity imaging (SWEI). This study aimed to explore whether endometrial elasticity is an ultrasound marker for predicting clinical pregnancy outcomes after embryo transfer. A total of 245 infertile women underwent ultrasonography before embryo transfer at the Peking University Third Hospital. We compared the endometrial elasticity and sub-endometrial blood flow rate using SWEI in the groups with different pregnancy outcomes. Trends in clinical pregnancy outcomes across the quartiles of endometrial elasticity in the fundus of the uterus (E1) were assessed. Logistic regression analysis was performed to obtain odds ratios for clinical pregnancy outcomes based on the quartiles of E1, with or without adjusting for potential confounding variables. Women in the clinical pregnancy group had higher E1 values and sub-endometrial blood flow rates in the uterine fundus than those in the non-pregnancy group. Women in the highest quartile of E1 had the most favorable clinical pregnancy rates. Endometrial elasticity measured using SWEI is a promising ultrasound marker for predicting clinical pregnancy outcomes after embryo transfer.

Negative elastic wave refraction and focusing regulation of single-phase solid phononic crystals

This paper presents the design of a single-phase solid phononic crystal (PnC) structure featuring a regular hexagonal perforation pattern. The structure manifests three negative refraction bands, encompassing one for transverse waves and two for longitudinal waves, thereby enabling simultaneous control of shear and longitudinal waves. Due to the high symmetry of the triangular lattice, the equal frequency curves corresponding to the negative refraction band approach circular shapes, suggesting a nearly isotropic negative refraction effect. This negative refraction effect is achieved through specific mass resonance modes closely related to the porous structure designed in this paper. Initially, we analyze the band structure of the PnC, followed by designing the PnC plate structure to achieve negative refraction control for transverse waves at a frequency of 32.4 kHz, with a negative refraction index of −1. Additionally, negative refraction control for longitudinal waves is attained at frequencies of 44 and 64.54 kHz. Subsequently, we scrutinize the influence of various conditions on negative refraction, including different structural parameters, incident angles, and operating frequencies, while verifying the robustness of the designed phonon crystal structure. Leveraging the negative refraction characteristics of the structure, we construct an elastic wave lens to achieve perfect imaging of shear and longitudinal waves. Finally, employing finite element simulation and analyzing focusing imaging characteristics with different source positions, we validate that the results closely align with theoretical expectations. The solid PnC structure designed in this study holds significant potential for applications in the fields of elastic wave imaging.