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

Image-Derived Skeletal Muscle Activation Metric Map: A Forearm Study Using Ultra-Fast Ultrasound Imaging and High-Density Electromyography

OBJECTIVE

Quantification of the skeletal muscle response can help better understand the fundamentals of the musculoskeletal system and can serve as a diagnostic measure or recovery assessment tool during rehabilitation for neurological injuries. Surface electromyography (EMG) is commonly used to measure muscle activity, but it is limited to detecting myoelectric signals without anatomy associated information. In this study, we proposed to use ultra-fast ultrasound imaging and introduced a new image analysis methodology to quantify a muscle's spatial-temporal mechanical response.

METHODS

The methodology is based on analyzing the spatial-temporal change of the impulsive kinetic energy during the period of muscle contraction. The analysis can derive an anatomy-registered muscle activation metric map that localizes regions of muscle activation. To demonstrate this, we intentionally evoked regional muscle responses in five participants without disabilities by electrically stimulating the median nerve and individual forearm muscle groups, respectively. Both ultrasound images and high-density EMG (HD-EMG) data were recorded and processed.

RESULTS

We presented the ultrasound image-derived activation localization from five participants and compared the results with HD-EMG measurements.

CONCLUSION

The comparison indicates a good resemblance for describing muscle recruitment pattern.

SIGNIFICANCE

The proposed methodology can potentially become an alternative or complementary approach to surface EMG for the study of skeletal muscle activation and for diagnosis and prognosis in clinical settings.

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 SIGNIFICANCE: Elasticity 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.

Wearable Ultrasound Imaging Device for Dynamic Dual-Direction Shear Wave Elastography of Shoulder Muscle

The shoulder is the most mobile joint in the human body, thus requiring intricate coordination of adjacent muscles. Patients suffered from rotator cuff muscle injuries have several typical symptoms including shoulder pain and difficulty raising the arm, thus reducing work efficiency and compromising the quality of life. Ultrasound has been used widely for shoulder soft tissue imaging as well as ultrasound elastography was introduced in shoulder examination for the dilemma of treating degenerative rotator cuff tears. However, most of the ultrasound examination was performed under a static condition. Providing dynamic information from shoulder muscle is important in clinical applications because the pains sometimes come from various positions of the shoulder during moving. In this study, a customized wearable T-shaped ultrasound transducer (128 + 128 elements) was proposed for shoulder dual-direction shear wave elastography (DDSWE), which provides the SWE for both longitudinal (SW along the muscle fiber) and transverse (SW cross the muscle fiber) directions dynamically. An optical tracking system was synchronized with an ultrasound imaging system to capture shoulder movements in 3-D space with their corresponding ultrasound images. The performance of DDSWE and the accuracy of optical tracking were verified by phantom experiments. Human studies were carried out by volunteers as they are moving their arms. The experimental results show that the bias and precision for the proposed DDSWE in elastic phantom were about 6% and 1.2% for both directions, respectively. A high accuracy of optical tracking was observed using a 3-D motor stage experimental setup. Human experiments show that the shear wave velocities (SWVs) were increased with the angles of shoulder abduction, and the average transverse and longitudinal SWVs were increased from 2.24 to 3.35 m/s and 2.95 to 5.95 m/s with abduction angle from 0° to 60°, respectively, which they are anisotropic-dependent. All the experimental results indicate that the proposed wearable ultrasound DDSWE can quantify the mechanical properties of shoulder muscles dynamically, thereby helping surgeons and physical therapists determine whether the intensity of rehabilitation shoulder be tuned down or escalated in the future.

Stretchable ultrasonic arrays for the three-dimensional mapping of the modulus of deep tissue

Serial assessment of the biomechanical properties of tissues can be used to aid the early detection and management of pathophysiological conditions, to track the evolution of lesions and to evaluate the progress of rehabilitation. However, current methods are invasive, can be used only for short-term measurements, or have insufficient penetration depth or spatial resolution. Here we describe a stretchable ultrasonic array for performing serial non-invasive elastographic measurements of tissues up to 4 cm beneath the skin at a spatial resolution of 0.5 mm. The array conforms to human skin and acoustically couples with it, allowing for accurate elastographic imaging, which we validated via magnetic resonance elastography. We used the device to map three-dimensional distributions of the Young's modulus of tissues ex vivo, to detect microstructural damage in the muscles of volunteers before the onset of soreness and to monitor the dynamic recovery process of muscle injuries during physiotherapies. The technology may facilitate the diagnosis and treatment of diseases affecting tissue biomechanics.

Doppler and Pair-Wise Optical Flow Constrained 3D Motion Compensation for 3D Ultrasound Imaging

Volumetric (3D) ultrasound imaging using a 2D matrix array probe is increasingly developed for various clinical procedures. However, 3D ultrasound imaging suffers from motion artifacts due to tissue motions and a relatively low frame rate. Current Doppler-based motion compensation (MoCo) methods only allow 1D compensation in the in-range dimension. In this work, we propose a new 3D-MoCo framework that combines 3D velocity field estimation and a two-step compensation strategy for 3D diverging wave compounding imaging. Specifically, our framework explores two constraints of a round-trip scan sequence of 3D diverging waves, i.e., Doppler and pair-wise optical flow, to formulate the estimation of the 3D velocity fields as a global optimization problem, which is further regularized by the divergence-free and first-order smoothness. The two-step compensation strategy is to first compensate for the 1D displacements in the in-range dimension and then the 2D displacements in the two mutually orthogonal cross-range dimensions. Systematical in-silico experiments were conducted to validate the effectiveness of our proposed 3D-MoCo method. The results demonstrate that our 3D-MoCo method achieves higher image contrast, higher structural similarity, and better speckle patterns than the corresponding 1D-MoCo method. Particularly, the 2D cross-range compensation is effective for fully recovering image quality.

Three-dimensional echo decorrelation monitoring of radiofrequency ablation in ex vivo bovine liver

Three-dimensional (3D) echo decorrelation imaging was investigated for monitoring radiofrequency ablation (RFA) in ex vivo bovine liver. RFA experiments (N = 14) were imaged by 3D ultrasound using a matrix array, with in-phase and quadrature complex echo volumes acquired about every 11 s. Tissue specimens were then frozen at -80 °C, sectioned, and semi-automatically segmented. Receiver operating characteristic (ROC) curves were constructed for assessing ablation prediction performance of 3D echo decorrelation with three potential normalization approaches, as well as 3D integrated backscatter (IBS). ROC analysis indicated that 3D echo decorrelation imaging is potentially a good predictor of local RFA, with the best prediction performance observed for globally normalized decorrelation. Tissue temperatures, recorded by four thermocouples integrated into the RFA probe, showed good correspondence with spatially averaged decorrelation and statistically significant but weak correlation with measured echo decorrelation at the same spatial locations. In tests predicting ablation zones using a weighted K-means clustering approach, echo decorrelation performed better than IBS, with smaller root mean square volume errors and higher Dice coefficients relative to measured ablation zones. These results suggest that 3D echo decorrelation and IBS imaging are capable of real-time monitoring of thermal ablation, with potential application to clinical treatment of liver tumors.

A New Plane Wave Compounding Scheme Using Phase Compensation for Motion Detection

Plane wave (PW) transmission has enabled multiple new applications, such as shear wave elastography, ultrafast Doppler imaging, and functional ultrasound imaging. PW compounding (PWC), which coherently sums the echo signals from multiple PW transmits with different angles, is widely used to improve B-mode image quality. When the motion between two speckle images is estimated, PWC suffers from an inherent displacement estimation error. This is derived theoretically and experimentally demonstrated in this work. We show that the phase difference between the acquired data with PW emissions with different angles is related to this error. When the absolute value of the phase difference is larger than π /2, the displacement estimation error occurs. A new scheme, named initial-phase-compensated PWC (IPCPWC), is proposed, which compensates the phase of echo signals from each PW transmit and maintains the absolute value of the phase difference smaller than π /2. The increased signal-to-noise ratio and reduced jitter of IPCPWC in motion data are demonstrated using tissue mimicking phantoms compared with PWC.

Shear wave imaging and classification using extended Kalman filter and decision tree algorithm

Shear wave ultrasound elastography is a quantitative imaging approach in soft tissues based on viscosity-elastic properties. Complex shear modulus (CSM) estimation is an effective solution to analyze tissues' physical properties for elasticity and viscosity based on the wavenumber and attenuation coefficient. CSM offers a way to detect and classify some types of soft tissues. However, CSM-based elastography inherits some obstacles, such as estimation precision and calculation complexity. This work proposes an approach for two-dimensional CSM estimation and soft tissue classification using the Extended Kalman Filter (EKF) and Decision Tree (DT) algorithm, named the EKF-DT approach. CSM estimation is obtained by applying EKF to exploit shear wave propagation at each spatial point. Afterward, the classification of tissues is done by a direct and efficient decision tree algorithm categorizing three types of normal, cirrhosis, and fibrosis liver tissues. Numerical simulation scenarios have been employed to illustrate the recovered quality and practicality of the proposed method's liver tissue classification. With the EKF, the estimated wave number and attenuation coefficient are close to the ideal values, especially the estimated wave number. The states of three liver tissue types were automatically classified by applying the DT coupled with two proposed thresholds of elasticity and viscosity: (2.310 kPa, 1.885 Pa.s) and (3.620 kPa 3.146 Pa.s), respectively. The proposed method shows the feasibility of CSM estimation based on the wavenumber and attenuation coefficient by applying the EKF. Moreover, the DT can automate the classification of liver tissue conditions by proposing two thresholds. The proposed EKF-DT method can be developed by 3D image reconstruction and empirical data before applying it in medical practice.

Time-Aligned Plane Wave Compounding Methods for High-Frame-Rate Shear Wave Elastography: Experimental Validation and Performance Assessment on Tissue Phantoms

Shear wave elastography (SWE) is an ultrasonic technique able to quantitatively assess the mechanical properties of tissues by combining acoustic radiation force and ultrafast imaging. While utilizing coherent plane wave compounding enhances echo and shear wave motion signal-to-noise ratio (SNR), it also reduces the effective pulse repetition frequency (PRF_e), affecting the accuracy of the measurements of motion and, consequently, of material properties. It is important to maintain both high-motion SNR and PRF_e, particularly for the characterization of (material and/or geometrical) dispersive tissues such as arteries. This work proposes a method for SWE measurements with high SNR, while maintaining a high PRF_e, using conventional clinical ultrasound scanners. A time alignment process is applied after acquiring data from plane wave transmissions at different angles. The time alignment uses interpolation to obtain data points at higher frame rates, and the time-aligned data are compounded to increase the SNR. The method is used for SWE in tissue-mimicking phantoms of different stiffness and is compared with traditional plane wave compounding. Increases of 58% and 36% in spatial and temporal bandwidth compared with conventional plane wave compounding, respectively, can be achieved for SWE measurements of representative arterial stiffness values. Improvements in phase velocity accuracy and bandwidth in an arterial phantom are also described, to emphasize the beneficial advantage in dispersive cases.

3D Cell Culture: Recent Development in Materials with Tunable Stiffness

It is widely accepted that three-dimensional cell culture systems simulate physiological conditions better than traditional 2D systems. Although extracellular matrix components strongly modulate cell behavior, several studies underlined the importance of mechanosensing in the control of different cell functions such as growth, proliferation, differentiation, and migration. Human tissues are characterized by different degrees of stiffness, and various pathologies (e.g., tumor or fibrosis) cause changes in the mechanical properties through the alteration of the extracellular matrix structure. Additionally, these modifications have an impact on disease progression and on therapy response. Hence, the development of platforms whose stiffness could be modulated may improve our knowledge of cell behavior under different mechanical stress stimuli. In this review, we have analyzed the mechanical diversity of healthy and diseased tissues, and we have summarized recently developed materials with a wide range of stiffness.

Radial Motion Estimation of Myocardium in Rats with Myocardial Infarction: A Hybrid Method of FNCCGLAM and Polar Transformation

Ultrasound elastography is a novel approach of evaluating regional myocardial systolic function and detecting infarcted area. This study aims to evaluate the radial motion of myocardial infarction (MI) area in left ventricular parasternal short axis (PSAX) view using a hybrid method of fast normalized cross-correlation and global analytic minimization (FNCCGLAM) and polar transformation. Fifteen rats were randomly selected for sham group, MI group and ischemia-reperfusion (IR) group (N = 5 for each group). The ultrasound radiofrequency data of the PSAX view of rat heart were acquired. After polar transformation of the data, the infarcted myocardium with the change of mechanical property was tracked over one myocardial systolic phase by the proposed method in comparison with fast normalized cross-correlation (FNCC) and dynamic programming analytic minimization (DPAM). To obtain a clear visualization of the myocardium, the inverse polar transformation was performed. The results indicated that the use of FNCCGLAM refined the myocardial displacements to obtain high-quality myocardial elastographic map with a higher contrast-to-noise ratio and dynamically tracked the infarcted myocardial segment with a higher success rate in comparison with FNCC and DPAM. It was found that the radial systolic motion of the infarcted anterior segment in the MI group reduced significantly (p < 0.05) in comparison with the sham group, while the systolic function of that myocardial segment in the IR group recovered at some extent. The results in this study suggest that FNCCGLAM is superior to FNCC and DPAM with the improved accuracy and robustness of motion estimation and has potentials as displacement estimator in ultrasound elastography.

4D Functional Imaging of the Rat Brain Using a Large Aperture Row-Column Array

Functional ultrasound imaging (fUS) recently emerged as a promising neuroimaging modality to image and monitor brain activity based on cerebral blood volume response (CBV) and neurovascular coupling. fUS offers very good spatial and temporal resolutions compared to fMRI gold standard as well as simplicity and portability. It was recently extended to 4D fUS imaging in preclinical settings although this approach remains limited and complex. Indeed 4D fUS requires a 2D matrix probe and specific hardware able to drive the N² elements of the probe with thousands of electronic channels. Several under-sampling approaches are currently investigated to limit the channel count and spread ultrasound 4D modalities. Among them, the Row Column Addressing (RCA) approach combined with ultrafast imaging is a compelling alternative using only N + N channels. We present a large field of view RCA probe prototype of 128 + 128 channels and 15 MHz central frequency adapted for preclinical imaging. Based on the Orthogonal Plane Wave compounding scheme, we were able to perform 4D vascular brain acquisitions at high volume rate. Doppler volumes of the whole rat brain were obtained in vivo at high rates (23 dB CNR at 156 Hz and 19 dB CNR at 313 Hz). Visual and whiskers stimulations were performed and the corresponding CBV increases were reconstructed in 3D with successful functional activation detected in the superior colliculus and somato-sensorial cortex respectively. This proof of concept study demonstrates for the first time the use of a low-channel count RCA array for in vivo 4D fUS imaging in the whole rat brain.

Sonoelastography for the comparative assessment of cervical maturation after different approaches to cervical preparation ahead of labor induction

Aim: To compare the efficacy of different approaches to cervical preparation to labor induction using the ultrasound cervical elastography.Materials and methods: This prospective open-label study included 200 pregnant women aged between 23 and 38 years eligible for labor pre-induction. Patients were divided into four groups (n = 50 per group). In Group I, four osmotic Dilapan-S cervical dilators combined with two doses of oral mifepristone (200 mg each) 24 h apart were used. The dilators were inserted for up to 12 h. In Group II, only the Dipalan-S dilators were used. In Group III, a Foley catheter was positioned intracervically for 12 h. In Group IV, we used two doses of intracervical prostaglandin E₂ gel (0.5 mg each) 6 h apart. Cervical maturation was assessed using the Bishop scoring system and the ultrasound cervicometry with the color mapping and calculation of SR ratio. At baseline, all participants were also divided into three subgroups depending on the Bishop score before the pre-induction. Subgroup А (n = 66) included patients with the Bishop score between 0‒2 points, subgroup B (n = 69) between 3-4 points, and subgroup С (n = 65) between 4-6 points.Results: Our study showed that the efficacy of Dilapan-S combined with mifepristone for cervical preparation to labor induction was higher than Dilapan-S, Foley catheter and intracervical prostaglandin E₂ gel. In this group, the Bishop score after the pre-induction was the highest (11.4 (0.21) points versus 10.2 (0.2), 9.4 (0.3) и 9.67 (0.25) in Groups II, III and IV respectively (p < .05 for all). The lowest SR values were also observed among the patients receiving the combination of Dilapan-S and mifepristone: 1.23 (0.04) versus 1.63 (0.07), 1.7 (0.08) and 1.83 (0.1) in Groups II, III and IV respectively (p < .05 for all). The sonoelastographic SR values in subgroups B and C were statistically lower compared with subgroup A across all groups studied. Ultrasound elastography of the cervix allowed to perform a more objective assessment of cervical maturation compared with the Bishop scoring.Conclusion: Dilapan-S combined with mifepristone had higher efficacy for cervical preparation to labor induction compared with other approaches investigated.

Optimization of transmission and reconstruction parameters in angular displacement compounding using plane wave ultrasound

In ultrasound elastography, plane-wave acquisitions and angular displacement compounding (ADC) are often used and combined to allow high frame rates and to improve accuracy of lateral displacement estimates, respectively. This study investigates the performance of displacement and strain estimation for ADC as a function of; the main-to-grating-lobe-amplitude ratio which decreases as a function of steering angle; plane-wave acquisition and Delay-and-Sum (DaS)-related parameters; and grating-lobe filter cut-off frequency. Three experiments were conducted with a block phantom to test ADC performance for displacement fields of varying complexity: a lateral transducer shift, phantom rotation and phantom deformation. Experiments were repeated for four linear array transducers (pitch-to-lambda ratios between 0.6 and 1.4). Best ADC performance was found for steering angles that resulted in a theoretically derived main-to-grating-lobe-amplitude ratio of 1.7 dB for pure lateral translation and 6 dB for predominately lateral strain or rotation. Temporal filtering to reduce grating lobe signal or shifting of the receive aperture to receive angles below or above the optimal angle, as dictated by the main-to-grating-lobe-amplitude ratio, did not improve results. The accuracy of lateral displacement and strain estimates was improved by apodization in transmission and a dedicated F-number in DaS (0.75) allowing incidence angles within ± 33° in the active aperture. ADC with the optimized settings as found in this study improves the accuracy of displacements and strain estimates up to 80.7% compared to non-ADC. Compared to ADC settings described in current literature, our optimization improved the accuracy by 11.9% to 75.3% for lateral displacement and strain, and by 89.3% to 96.2% for rotation. The accuracy of ADC in rotation seemed to depend highly on plane-wave and DaS-related parameters which may explain the major improvement compared to settings in current literature. The overall improvement by optimized ADC was statistically significant compared to non-ADC (p = 0.003) and literature (p = 0.002).

Physics-guided machine learning for 3-D quantitative quasi-static elasticity imaging

We present a 3D extension of the Autoprogressive Method (AutoP) for quantitative quasi-static ultrasonic elastography (QUSE) based on sparse sampling of force-displacement measurements. Compared to current model-based inverse methods, our approach requires neither geometric nor constitutive model assumptions. We build upon our previous report for 2D QUSE and demonstrate the feasibility of recovering the 3D linear-elastic material property distribution of gelatin phantoms under compressive loads. Measurements of boundary geometry, applied surface forces, and axial displacements enter into AutoP where a Cartesian neural network constitutive model (CaNNCM) interacts with finite element analyses to learn physically consistent material properties with no prior constitutive model assumption. We introduce a new regularization term uniquely suited to AutoP that improves the ability of CaNNCMs to extract information about spatial stress distributions from measurement data. Results of our study demonstrate that acquiring multiple sets of force-displacement measurements by moving the US probe to different locations on the phantom surface not only provides AutoP with the necessary information for a CaNNCM to learn the 3D material property distribution, but may significantly improve the accuracy of the Young's modulus estimates. Furthermore, we investigate the trade-offs of decreasing the contact area between the US transducer and phantom surface in an effort to increase sensitivity to surface force variations without additional instrumentation. Each of these modifications improves the ability of CaNNCMs trained in AutoP to learn the spatial distribution of Young's modulus from force-displacement measurements.

3D normalized cross-correlation for estimation of the displacement field in ultrasound elastography

This paper introduces a novel technique to estimate tissue displacement in quasi-static elastography. A major challenge in elastography is estimation of displacement (also referred to time-delay estimation) between pre-compressed and post-compressed ultrasound data. Maximizing normalized cross correlation (NCC) of ultrasound radio-frequency (RF) data of the pre- and post-compressed images is a popular technique for strain estimation due to its simplicity and computational efficiency. Several papers have been published to increase the accuracy and quality of displacement estimation based on NCC. All of these methods use 2D spatial windows in RF data to estimate NCC, wherein displacement is assumed to be constant within each window. In this work, we extend this assumption along the third dimension. Two approaches are proposed to get third dimension. In the first approach, we use temporal domain to exploit neighboring samples in both spatial and temporal directions. Considering temporal information is important since traditional and ultrafast ultrasound machines are, respectively, capable of imaging at more than 30 frame per second (fps) and 1000 fps. Another approach is to use time-delayed pre-beam formed data (channel data) instead of RF data. In this method information of all channels that are recorded as pre-beam formed data of each RF line will be considered as 3^rd dimension. We call these methods as spatial temporal normalized cross correlation (STNCC) and channel data normalized cross correlation (CNCC) and show that they substantially outperforms NCC using simulation, phantom and in-vivo experiments. Given substantial improvements of results in addition to the relative simplicity of implementing STNCC and CNCC, the proposed approaches can potentially have a large impact in both academic and commercial work on ultrasound elastography.

Combining Total Variation Regularization with Window-Based Time Delay Estimation in Ultrasound Elastography

A major challenge of free-hand palpation ultrasound elastography (USE) is estimating the displacement of RF samples between pre- and post-compressed RF data. The problem of displacement estimation is ill-posed since the displacement of one sample by itself cannot be uniquely calculated. To resolve this problem, two categories of methods have emerged. The first category assumes that the displacement of samples within a small window surrounding the reference sample is constant. The second class imposes smoothness regularization and optimizes an energy function. Herein, we propose a novel method that combines both approaches, and as such, is more robust to noise. The second contribution of this work is the introduction of the L1 norm as the regularization term in our cost function, which is often referred to as the total variation (TV) regularization. Compared to previous work that used the L2 norm regularization, optimization of the new cost function is more challenging. However, the advantages of using the L1 norm are twofold. First, it leads to substantial improvement in the sharpness of displacement estimates. Second, to optimize the cost function with the L1 norm regularization, we use an iterative method that further increases the robustness. We name our proposed method tOtal Variation Regularization and WINDow-based time delay estimation (OVERWIND) and show that it is robust to signal decorrelation and generates sharp displacement and strain maps for simulated, experimental phantom and in-vivo data. In particular, OVERWIND improves strain contrast-to-noise ratio (CNR) by 27.26%, 144.05%, and 49.90% on average in simulation, phantom, and in-vivo data, respectively, compared to our recent Global Ultrasound Elastography (GLUE) method.

A kernel smoothing algorithm for ablation visualization in ultrasound elastography

Three-dimensional visualization of tumor ablation procedures have significant clinical value because the ability to accurately visualize ablated volumes can help clinicians gauge the extent of ablated tissue necrosis and plan future treatment steps. Better control over ablation volume can prevent recurrence of tumors treated using ablative procedures. This paper presents a kernel based smoothing algorithm called MatérnSmooth to reconstruct shear wave velocity maps from data acquired through ultrasound electrode vibration elastography. Shear wave velocity estimates are acquired on several intersecting imaging planes that share a common axis of intersection collinear with the ablation needle. An objective method of choosing smoothing parameters from underlying data is outlined through simulations. Experimental validation was performed on data acquired from a tissue mimicking phantom. Volume estimates were found to be within 20% of the true value.

4D simultaneous tissue and blood flow Doppler imaging: revisiting cardiac Doppler index with single heart beat 4D ultrafast echocardiography

The goal of this study was to demonstrate the feasibility of semi-automatic evaluation of cardiac Doppler indices in a single heartbeat in human hearts by performing 4D ultrafast echocardiography with a dedicated sequence of 4D simultaneous tissue and blood flow Doppler imaging. 4D echocardiography has the potential to improve the quantification of major cardiac indices by providing more reproducible and less user dependent measurements such as the quantification of left ventricle (LV) volume. The evaluation of Doppler indices, however, did not benefit yet from 4D echocardiography because of limited volume rates achieved in conventional volumetric color Doppler imaging but also because spectral Doppler estimation is still restricted to a single location. High volume rate (5200 volume s^-1) transthoracic simultaneous tissue and blood flow Doppler acquisitions of three human LV were performed using a 4D ultrafast echocardiography scanner prototype during a single heartbeat. 4D color flow, 4D tissue Doppler cineloops and spectral Doppler at each voxel were computed. LV outflow tract, mitral inflow and basal inferoseptal locations were automatically detected. Doppler indices were derived at these locations and were compared against clinical 2D echocardiography. Blood flow Doppler indices E (early filling), A (atrial filling), E/A ratio, S (systolic ejection) and cardiac output were assessed on the three volunteers. Simultaneous tissue Doppler indices e' (mitral annular velocity peak), a' (late velocity peak), e'/a' ratio, s' (systolic annular velocity peak), E/e' ratio were also estimated. Standard deviations on three independent acquisitions were averaged over the indices and was found to be inferior to 4% and 8.5% for Doppler flow and tissue Doppler indices, respectively. Comparison against clinical 2D echocardiography gave a p  value larger than 0.05 in average indicating no significant differences. 4D ultrafast echocardiography can quantify the major cardiac Doppler indices in a single heart beat acquisition.

Compressed sensing reconstruction of synthetic transmit aperture dataset for volumetric diverging wave imaging

A high volume rate and high performance ultrasound imaging method based on a matrix array is proposed by using compressed sensing (CS) to reconstruct the complete dataset of synthetic transmit aperture (STA) from three-dimensional (3D) diverging wave transmissions (i.e. 3D CS-STA). Hereto, a series of apodized 3D diverging waves are transmitted from a fixed virtual source, with the ith row of a Hadamard matrix taken as the apodization coefficients in the ith transmit event. Then CS is used to reconstruct the complete dataset, based on the linear relationship between the backscattered echoes and the complete dataset of 3D STA. Finally, standard STA beamforming is applied on the reconstructed complete dataset to obtain the volumetric image. Four layouts of element numbering for apodizations and transmit numbers of 16, 32 and 64 are investigated through computer simulations and phantom experiments. Furthermore, the proposed 3D CS-STA setups are compared with 3D single-line-transmit (SLT) and 3D diverging wave compounding (DWC). The results show that, (i) 3D CS-STA has competitive lateral resolutions to 3D STA, and their contrast ratios (CRs) and contrast-to-noise ratios (CNRs) approach to those of 3D STA as the number of transmit events increases in noise-free condition. (ii) the tested 3D CS-STA setups show good robustness in complete dataset reconstruction in the presence of different levels of noise. (iii) 3D CS-STA outperforms 3D SLT and 3D DWC. More specifically, the 3D CS-STA setup with 64 transmit events and the Random layout achieves ~31% improvement in lateral resolution, ~14% improvement in ratio of the estimated-to-true cystic areas, a higher volume rate, and competitive CR/CNR when compared with 3D DWC. The results demonstrate that 3D CS-STA has great potential of providing high quality volumetric image with a higher volume rate.

Electromagnetic tracking-based freehand 3D quasi-static elastography with 1D linear array: a phantom study

Recent developments in hardware and scanning protocols have advanced conventional 2D quasi-static elastography to 3D level, which provides an intuitive visualization of lesions. A 2D linear array or scanning mechanism is typically required for 3D quasi-static elastography, requiring expensive and specifically designed hardware. In this study, we propose a novel method based on a commercial electromagnetic tracking system for freehand 3D quasi-static elastography with 1D linear array. Phantom experiments are performed to validate the feasibility of the proposed method. During data acquisition, the probe contacts the surface of an elasticity phantom and moves in the elevational direction, while applying sinusoidal-like axial compression to the phantom. For each frame of ultrasound data, the 3D coordinates and orientations of the probe are obtained from an electromagnetic tracking system. A correlation-based algorithm is adopted to obtain a series of axial strain images. Volumetric strain data are reconstructed by using the recorded 3D coordinates and orientations of the probe corresponding to each strain image. The diameters of inclusions are then obtained from the slice plots of the volumetric strain data. The volumes of inclusions are estimated from the isosurface plots. The experimental result shows that the volume estimation of the inclusions has good accuracy, with errors within 2%, while the diameters of the inclusions estimated from three orthogonal planes have larger errors up to 18%. In conclusion, the present framework would promise a reliable and effective solution for freehand 3D quasi-static elastography with 1D linear array.

Robust Reconstruction of Elasticity Using Ultrasound Imaging and Multi-Frequency Excitations

Biomedical parameters of tissue can be important indicators for clinical diagnosis. One such parameter that reflects tissue stiffness is elasticity, the imaging of which is called elastography. In this paper, we use displacements from harmonic excitations to solve the inverse problem of elasticity based on a finite-element method (FEM) formulation. This leads to iterative solution of nonlinear and nonconvex problems. In this paper, we show the importance and selection of viable initializations in numerical simulation studies and propose techniques for the fusion of multiple initializations for ideal reconstructions of unknown tissue as well as combining information from excitations at multiple frequencies. Results show that our method leads up to 76% decrease in root-mean-squared error (RMSE) and 9.9 dB increase in contrast-to-noise ratio (CNR) in simulations with noise, when compared to conventional iterative FEM without multiple initializations and frequencies. As the wave patterns in individually selected frequencies may introduce artifacts, a joint inverse-problem solution of multi-frequency excitations is introduced as a robust solution, where CNR improvements of up to 11.9 dB are observed. We also present the methods on a tissue-mimicking gelatin phantom study using mechanical excitation and ultrafast plane-wave ultrasound imaging, where the RMSE was improved by up to 51%. An experiment of ablation via heating an ex-vivo bovine liver shows that reconstruction artifacts are reduced with our proposed method.

High Spatial-Temporal Resolution Reconstruction of Plane-Wave Ultrasound Images With a Multichannel Multiscale Convolutional Neural Network

In recent years, plane-wave imaging (PWI) has attracted considerable attention because of its high temporal resolution. However, the low spatial resolution of PWI limits its clinical applications, which has inspired various studies on the high spatial resolution reconstruction of PW ultrasound images. Although compounding methods and traditional high spatial resolution reconstruction approaches can improve the image quality, these techniques decrease the temporal resolution. Since learning methods can fully reserve the high temporal resolution of PW ultrasounds, a novel convolutional neural network (CNN) model for the high spatial-temporal resolution reconstruction of PW ultrasound images is proposed in this paper. Considering the multiangle form of PW data, a multichannel model is introduced to produce balanced training. To combine local and contextual information, the multiscale model is adopted. These two innovations constitute our multichannel and multiscale CNN (MMCNN) model. Compared with traditional CNN methods, the proposed model uses a two-stage structure in which a cascading wavelet postprocessing stage is combined with the trained MMCNN model. Cascading wavelet postprocessing aims to preserve speckle information. Furthermore, a feedback system is appended to the iteration process of the network training to solve the overfitting problem and help produce convergence. Based on these improvements, an end-to-end mapping is established between a single-angle B-mode PW image and its corresponding multiangle compounded, high-resolution image. The experiments were conducted on simulated, phantom, and real human data. The advantages of our proposed method were compared with a coherent PW compounding method, a conventional maximum a posteriori-based high spatial resolution reconstruction method, and a 2-D CNN compounding method, and the results verified that our approach is capable of attaining a better temporal resolution and comparable spatial resolution. In clinical usage, the proposed method is equipped to satisfy with many ultrafast imaging applications, which require high spatial-temporal resolution. i.

Robust Estimation of Displacement in Real-Time Freehand Ultrasound Strain Imaging

We present a novel and efficient approach for robust estimation of displacement in real-time strain imaging for freehand ultrasound elastography by utilizing pre- and post-deformation ultrasound images. We define a quality factor for image lines and find the line with the highest value of quality factor to serve as the seed line for generating the displacement map. We also develop an analytical framework for coarse-to-fine displacement estimation, obtain an initial estimate of the seed line's displacement with subsample precision, and propagate it to the entire image to obtain a high quality strain image. Our fast strategy for estimating the seed line's displacement enables us to enhance the robustness without sacrificing the speed by identifying a new seed line when the quality falls below a given threshold. This is more efficient than the existing approaches that utilize multiple seed lines to improve robustness. Simulations, phantom experiments, and clinical studies show high signal-to-noise-ratio and contrast-to-noise-ratio values in our method for a wide range of average strain levels (1%-10%). Phantom experiments also demonstrate that our method is robust against corrupt and decorrelated data. Our method is superior to the existing real-time methods as it can produce high-quality strain images for up to 10% average strain levels at the rate of 20 frames/s on conventional CPUs.

Ultrafast Ultrasound Imaging With Cascaded Dual-Polarity Waves

Ultrafast ultrasound imaging using plane or diverging waves, instead of focused beams, has advanced greatly the development of novel ultrasound imaging methods for evaluating tissue functions beyond anatomical information. However, the sonographic signal-to-noise ratio (SNR) of ultrafast imaging remains limited due to the lack of transmission focusing, and thus insufficient acoustic energy delivery. We hereby propose a new ultrafast ultrasound imaging methodology with cascaded dual-polarity waves (CDWs), which consists of a pulse train with positive and negative polarities. A new coding scheme and a corresponding linear decoding process were thereby designed to obtain the recovered signals with increased amplitude, thus increasing the SNR without sacrificing the frame rate. The newly designed CDW ultrafast ultrasound imaging technique achieved higher quality B-mode images than coherent plane-wave compounding (CPWC) and multiplane wave (MW) imaging in a calibration phantom, ex vivo pork belly, and in vivo human back muscle. CDW imaging shows a significant improvement in the SNR (10.71 dB versus CPWC and 7.62 dB versus MW), penetration depth (36.94% versus CPWC and 35.14% versus MW), and contrast ratio in deep regions (5.97 dB versus CPWC and 5.05 dB versus MW) without compromising other image quality metrics, such as spatial resolution and frame rate. The enhanced image qualities and ultrafast frame rates offered by CDW imaging beget great potential for various novel imaging applications.

Cardiac Lesion Mapping In Vivo Using Intracardiac Myocardial Elastography

Radio frequency (RF) ablation of the myocardium is used to treat various cardiac arrhythmias. The size, spacing, and transmurality of lesions have been shown to affect the success of the ablation procedure; however, there is currently no method to directly image the size and formation of ablation lesions in real time. Intracardiac myocardial elastography (ME) has been previously used to image the decrease in cardiac strain during systole in the ablated region as a result of the lesion formation. However, the feasibility of imaging multiple lesions and identifying the presence of gaps between lesions has not yet been investigated. In this paper, RF ablation lesions ( ) were generated in the left ventricular epicardium in three anesthetized canines. Two sets of two lesions each were created in close proximity to one another with small gaps (1.5 and 4 cm), while one set of two lesions was created directly next to each other with no gap. A clinical intracardiac echocardiography system was programmed to transmit a custom diverging beam sequence at 600 Hz and used to image the ablation site before and after the induction of ablation lesions. Cumulative strains were estimated over systole using a normalized cross-correlational displacement algorithm and a least-squares strain kernel. Afterward, lesions were excised and subjected to tetrazolium chloride staining. Results indicate that intracardiac ME was capable of imaging the reduction in systolic strain associated with the formation of an ablation lesion. Furthermore, lesion sets containing gaps were able to be distinguished from lesion sets created with no gaps. These results indicate that the end-systolic strain measured using intracardiac ME may be used to image the formation of lesions induced during an RF ablation procedure, in order to provide critical assessment of lesion viability during the interventional procedure.

Reproducibility and Angle Independence of Electromechanical Wave Imaging for the Measurement of Electromechanical Activation during Sinus Rhythm in Healthy Humans

Electromechanical wave imaging (EWI) is an ultrasound-based technique that can non-invasively map the transmural electromechanical activation in all four cardiac chambers in vivo. The objective of this study was to determine the reproducibility and angle independence of EWI for the assessment of electromechanical activation during normal sinus rhythm (NSR) in healthy humans. Acquisitions were performed transthoracically at 2000 frames/s on seven healthy human hearts in parasternal long-axis, apical four- and two-chamber views. EWI data was collected twice successively in each view in all subjects, while four successive acquisitions were obtained in one case. Activation maps were generated and compared (i) within the same acquisition across consecutive cardiac cycles; (ii) within same view across successive acquisitions; and (iii) within equivalent left-ventricular regions across different views. EWI was capable of characterizing electromechanical activation during NSR and of reliably obtaining similar patterns of activation. For consecutive heart cycles, the average 2-D correlation coefficient between the two isochrones across the seven subjects was 0.9893, with a mean average activation time fluctuation in LV wall segments across acquisitions of 6.19%. A mean activation time variability of 12% was obtained across different views with a measurement bias of only 3.2 ms. These findings indicate that EWI can map the electromechanical activation during NSR in human hearts in transthoracic echocardiography in vivo and results in reproducible and angle-independent activation maps.

Feasibility and Validation of 4-D Pulse Wave Imaging in Phantoms and In Vivo

Pulse wave imaging (PWI) is a noninvasive technique for tracking the propagation of the pulse wave along the arterial wall. The 3-D ultrasound imaging would aid in objectively estimating the pulse wave velocity (PWV) vector. This paper aims to introduce a novel PWV estimation method along the propagation direction, validate it in phantoms, and test its feasibility in vivo. A silicone vessel phantom consisting of a stiff and a soft segment along the longitudinal axis and a silicone vessel with a plaque were constructed. A 2-D array with a center frequency of 2.5 MHz was used. Propagation was successfully visualized in 3-D in each phantom and in vivo in six healthy subjects. In three of the healthy subjects, results were compared against conventional PWI using a linear array. PWVs were estimated in the stiff (3.42 ± 0.23 m [Formula: see text]) and soft (2.41 ± 0.07 m [Formula: see text]) phantom segments. Good agreement was found with the corresponding static testing values (stiff: 3.41 m [Formula: see text] and soft: 2.48 m [Formula: see text]). PWI-derived vessel compliance values were validated with dynamic testing. Comprehensive views of pulse propagation in the plaque phantom were generated and compared against conventional PWI acquisitions. Good agreement was found in vivo between the results of 4-D PWI (4.80 ± 1.32 m [Formula: see text]) and conventional PWI (4.28±1.20 m [Formula: see text]) ( n=3 ). PWVs derived for all of the healthy subjects ( n = 6 ) were within the physiological range. Thus, the 4-D PWI was successfully validated in phantoms and used to image the pulse wave propagation in normal human subjects in vivo.

3D Myocardial Elastography In Vivo

Strain evaluation is of major interest in clinical cardiology as it can quantify the cardiac function. Myocardial elastography, a radio-frequency (RF)-based cross-correlation method, has been developed to evaluate the local strain distribution in the heart in vivo. However, inhomogeneities such as RF ablation lesions or infarction require a three-dimensional approach to be measured accurately. In addition, acquisitions at high volume rate are essential to evaluate the cardiac strain in three dimensions. Conventional focused transmit schemes using 2D matrix arrays, trade off sufficient volume rate for beam density or sector size to image rapid moving structure such as the heart, which lowers accuracy and precision in the strain estimation. In this study, we developed 3D myocardial elastography at high volume rates using diverging wave transmits to evaluate the local axial strain distribution in three dimensions in three open-chest canines before and after radio-frequency ablation. Acquisitions were performed with a 2.5 MHz 2D matrix array fully programmable used to emit 2000 diverging waves at 2000 volumes/s. Incremental displacements and strains enabled the visualization of rapid events during the QRS complex along with the different phases of the cardiac cycle in entire volumes. Cumulative displacement and strain volumes depict high contrast between non-ablated and ablated myocardium at the lesion location, mapping the tissue coagulation. 3D myocardial strain elastography could thus become an important technique to measure the regional strain distribution in three dimensions in humans.