Systematic Performance Evaluation of a Cross-Correlation-Based Ultrasound Strain Imaging Method

Near-Field Clutter Mitigation in Speckle Tracking Echocardiography

OBJECTIVE

Near-field (NF) clutter filters are critical for unveiling true myocardial structure and dynamics. Randomized singular value decomposition (rSVD) stands out for its proven computational efficiency and robustness. This study investigates the effect of rSVD-based NF clutter filtering on myocardial motion estimation.

METHODS

In silico, material points and their displacements in a homogeneous medium under uniaxial compressions (0.5% - 9% axial strains at 0.5% increments) were simulated in finite-element models. They were exported to the k-Wave toolbox for simulations of pre- and post-deformed ultrasound images with/ without a realistic phase aberrating layer in a high-contrast diverging wave compounding scheme. In vivo, echocardiograms of 20 normal human hearts were acquired using a coded diverging wave compounding imaging method at 3200 frames/second in the transthoracic apical four-chamber view. Morphological component analysis (MCA), which is also a sparse representation method but computationally intensive, was used for comparison with rSVD. Both rSVD- and MCA-based filters were applied to beamformed ultrasound radio-frequency (RF) data before cross-correlation-based speckle tracking. Contrast-to-noise ratios (CNRs) and root-mean-square deviations (RMSDs) were computed from regions of interest to evaluate NF clutter filtering performance of rSVD and MCA.

RESULTS

In silico, 2-D displacements estimated from rSVD-based clutter-reduced image data showed strong agreement with ground truth (R2 of 0.95). In vivo, CNR improvements ranged from 1.02 dB to 17.68 dB, consistently enhancing image quality across all subjects. An improvement of ∼4.9 dB in the apical segments was observed in 80% of cases. Mean RMSDs were below 5.0% for all rSVD-based NF clutter-reduced data. While both rSVD and MCA effectively filtered NF clutter, rSVD was significantly more practical.

CONCLUSION

Our findings confirm the reliability, accuracy, and efficiency of rSVD-based clutter filtering in speckle tracking echocardiography. This underscores the feasibility of matrix decomposition-based methods, exemplified by rSVD, in NF clutter filtering for myocardial motion estimation.

Validation of Muscle Ultrasound Speckle Tracking and the Effect of Nordic Hamstring Exercise on Biceps Femoris Displacement

OBJECTIVE

This study aimed to validate the ultrasound speckle tracking (UST) algorithm, determine the optimal probe location by comparing normalized cross-correlation (NCC) values of muscle displacement at two locations (proximal vs. middle) of the biceps femoris long head (BFlh) using the UST, and investigate the effects of Nordic hamstring curl exercise (NHE) training on BFlh displacement.

METHODS

UST efficacy was verified with ex vivo uniaxial testing of porcine leg muscles. Ten participants (mean age 23.4 y) were recruited for comparison of NCC values between the proximal and middle BFlh during maximal knee flexor eccentric contraction using an ultrasound device and isokinetic dynamometer. Using the above devices, electromyography and shear wave elastography, the effects of an 8-wk NHE program on the morphomechanical profiles, displacement and activation of the middle BFlh and eccentric torque of the knee flexor were investigated in 20 males (mean age 23.5 y).

RESULTS

The validity of UST was confirmed by comparing UST and ex vivo test results (r = 0.99). The NCC values of the middle BFlh were greater than those of the proximal BFlh. The caudal-direction displacements of the BFlh in the dominant leg were reduced after the NHE training (from 3.98 ± 3.84 to 1.50 ± 4.17 mm, p < 0.05). The magnitude of reduction was associated with improved eccentric strength of the knee flexor muscle in the dominant leg (r = 0.63).

CONCLUSIONS

UST is a validated tool for measuring muscle displacement. NHE training decreased caudal-direction muscle displacement in the BFlh and increased eccentric strength.

An Optimization Approach for Creating Application-specific Ultrasound Speckle Tracking Algorithms

OBJECTIVE

Ultrasound speckle tracking enables in vivo measurement of soft tissue deformation or strain, providing a non-invasive diagnostic tool to quantify tissue health. However, adoption into new fields is challenging since algorithms need to be tuned with gold-standard reference data that are expensive or impractical to acquire. Here, we present a novel optimization approach that only requires repeated measurements, which can be acquired for new applications where reference data might not be readily available or difficult to get hold of.

METHODS

Soft tissue motion was captured using ultrasound for the medial collateral ligament (MCL) of three quasi-statically loaded porcine stifle joints, and medial ligamentous structures of a dynamically loaded human cadaveric knee joint. Using a training subset, custom speckle tracking algorithms were created for the porcine and human ligaments using surrogate optimization, which aimed to maximize repeatability by minimizing the normalized standard deviation of calculated strain maps for repeat measurements. An unseen test subset was then used to validate the tuned algorithms by comparing the ultrasound strains to digital image correlation (DIC) surface strains (porcine specimens) and length change values of the optically tracked ligament attachments (human specimens).

RESULTS

After 1500 iterations, the optimization routine based on the porcine and human training data converged to similar values of normalized standard deviations of repeat strain maps (porcine: 0.19, human: 0.26). Ultrasound strains calculated for the independent test sets using the tuned algorithms closely matched the DIC measurements for the porcine quasi-static measurements (R > 0.99, RMSE < 0.59%) and the length change between the tracked ligament attachments for the dynamic human dataset (RMSE < 6.28%). Furthermore, strains in the medial ligamentous structures of the human specimen during flexion showed a strong correlation with anterior/posterior position on the ligaments (R > 0.91).

CONCLUSION

Adjusting ultrasound speckle tracking algorithms using an optimization routine based on repeatability led to robust and reliable results with low RMSE for the medial ligamentous structures of the knee. This tool may be equally beneficial in other soft-tissue displacement or strain measurement applications and can assist in the development of novel ultrasonic diagnostic tools to assess soft tissue biomechanics.

Row Transmission for High Volume-Rate Ultrasound Imaging With a Matrix Array

The widely used Vermon 1024-element matrix array for 3-D ultrasound imaging has three blank rows in the elevational direction, which breaks the elevation periodicity, thus degrading volumetric image quality. To bypass the blank rows in elevation while maintaining the steering capability in azimuth, we proposed a row-transmission (RT) scheme to improve 3-D spatial resolution. Specifically, we divided the full array into four apertures, each with multiple rows along the elevation. Each multirow aperture (MRA) was further divided into subapertures to transmit diverging waves (DWs) sequentially. Coherent DW compounding (CDWC) was realized in azimuth, while the elevation was multielement synthetic aperture (M-SA) imaging by regarding each row as an array of dashed line elements. An in-house spatiotemporal coding strategy, cascaded synthetic aperture (CaSA), was incorporated into the RT scheme as RT-CaSA to increase the signal-to-noise ratio (SNR). We compared the proposed RT with conventional bank-by-bank transmission-reception (Bank) and sparse-random-aperture compounding (SRAC) in a wire phantom and the in vivo human abdominal aorta (AA) to assess the performance of anatomical imaging and aortic wall motion estimation. Phantom results demonstrated superior lateral resolution achieved by our RT scheme (+19.52% and +16.88% versus Bank, +15.32% and +19.72% versus SRAC, in the azimuth-depth and elevation-depth planes, respectively). Our RT-CaSA showed excellent contrast ratios (CRs) (+8.19 and +8.08 dB versus Bank, +6.81 and +5.85 dB versus SRAC, +0.99 and +0.90 dB versus RT) and the highest in vivo aortic wall motion estimation accuracy. The RT scheme was demonstrated to have potential for various matrix array-based 3-D imaging research.

Enabling strain imaging in realistic Eulerian ultrasound simulation methods

Cardiovascular strain imaging is continually improving due to ongoing advances in ultrasound acquisition and data processing techniques. The phantoms used for validation of new methods are often burdensome to make and lack flexibility to vary mechanical and acoustic properties. Simulations of US imaging provide an alternative with the required flexibility and ground truth strain data. However, the current Lagrangian US strain imaging models cannot simulate heterogeneous speed of sound distributions and higher-order scattering, which limits the realism of the simulations. More realistic Eulerian modelling techniques exist but have so far not been used for strain imaging. In this research, a novel sampling scheme was developed based on a band-limited interpolation of the medium, which enables accurate strain simulation in Eulerian methods. The scheme was validated in k-Wave using various numerical phantoms and by a comparison with Field II. The method allows for simulations with a large range in strain values and was accurate with errors smaller than -60 dB. Furthermore, an excellent agreement with the Fourier theory of US scattering was found. The ability to perform simulations with heterogeneous speed of sound distributions was demonstrated using a pulsating artery model. The developed sampling scheme contributes to more realistic strain imaging simulations, in which the effect of heterogenous acoustic properties can be taken into account.

Validation of the Efficacy of Ultrasound Speckle Tracking in Measuring Tendon Gliding After Finger Flexor Tendon Repair

OBJECTIVE

Restricted tendon gliding is commonly observed in patients after finger flexor tendon (FFT) repair. The study described here was aimed at quantifying the amount of FFT gliding to evaluate the recovery of post-operative tendons using a 2-D radiofrequency (RF)-based ultrasound speckle tracking algorithm (UST).

METHODS

Ex vivo uniaxial tensile testing of porcine flexor tendons and in vivo isometric testing of human FFT were implemented to verify the efficacy of UST beforehand. The verified UST was then applied to the patients after FFT repair to compare tendon gliding between affected and healthy sides and to investigate its correlation with the joint range of motion (ROM).

RESULTS

Excellent validity was confirmed with the average R2 value of 0.98, mean absolute error of 0.15 ± 0.08 mm and mean absolute percentage error of 5.19 ± 2.43% between results from UST and ex vivo testing. The test-retest reliability was verified with good agreement of ICC (0.90). The affected side exhibited less gliding (p = 0.001) and smaller active ROM (p = 0.002) than the healthy side. Meanwhile, a significant correlation between tendon gliding and passive ROM was found only on the healthy side (ρ = 0.711, p = 0.009).

CONCLUSION

The present study provides a promising protocol to evaluate post-operative tendon recovery by quantifying the amount of FFT gliding with a validated UST. FFT gliding in patients with different levels of ROM restriction should be further explored for categorizing the severity of tendon adhesion.

Segmental and transmural motion of the rat myocardium estimated using quantitative ultrasound with new strategies for infarct detection

Introduction: The estimation of myocardial motion abnormalities has great potential for the early diagnosis of myocardial infarction (MI). This study aims to quantitatively analyze the segmental and transmural myocardial motion in MI rats by incorporating two novel strategies of algorithm parameter optimization and transmural motion index (TMI) calculation. Methods: Twenty-one rats were randomly divided into three groups (n = 7 per group): sham, MI, and ischemia-reperfusion (IR) groups. Ultrasound radio-frequency (RF) signals were acquired from each rat heart at 1 day and 28 days after animal model establishment; thus, a total of six datasets were represented as Sham1, Sham28, MI1, MI28, IR1, and IR28. The systolic cumulative displacement was calculated using our previously proposed vectorized normalized cross-correlation (VNCC) method. A semiautomatic regional and layer-specific myocardium segmentation framework was proposed for transmural and segmental myocardial motion estimation. Two novel strategies were proposed: the displacement-compensated cross-correlation coefficient (DCCCC) for algorithm parameter optimization and the transmural motion index (TMI) for quantitative estimation of the cross-wall transmural motion gradient. Results: The results showed that an overlap value of 80% used in VNCC guaranteed a more accurate displacement calculation. Compared to the Sham1 group, the systolic myocardial motion reductions were significantly detected (p < 0.05) in the middle anteroseptal (M-ANT-SEP), basal anteroseptal (B-ANT-SEP), apical lateral (A-LAT), middle inferolateral (M-INF-LAT), and basal inferolateral (B-INF-LAT) walls as well as a significant TMI drop (p < 0.05) in the M-ANT-SEP wall in the MI1 rats; significant motion reductions (p < 0.05) were also detected in the B-ANT-SEP and A-LAT walls in the IR1 group. The motion improvements (p < 0.05) were detected in the M-INF-LAT wall in the MI28 group and the apical septal (A-SEP) wall in the IR28 group compared to the MI1 and IR1 groups, respectively. Discussion: Our results show that the MI-induced reductions and reperfusion-induced recovery in systolic myocardial contractility could be successfully evaluated using our method, and most post-MI myocardial segments could recover systolic function to various extents in the remodeling phase. In conclusion, the ultrasound-based quantitative estimation framework for estimating segmental and transmural motion of the myocardium proposed in our study has great potential for non-invasive, novel, and early MI detection.

Fast and Robust Clutter Filtering in Ultrafast Echocardiography

Singular value decomposition (SVD)-based filters have become the norm for clutter filtering in ultrasound blood flow applications but are computationally expensive and susceptible to large and fast tissue motion. Randomized SVD (rSVD) has later been shown to successfully accelerate filtering of in vivo stationary tissues. However, little is known about its performance on ultrafast echocardiography, which produces thousands of frames to assess complex myocardial deformation and blood dynamics. Neither has its inherently robust randomized scheme been proven in any ultrasound blood flow imaging methods. This study thus proposed to employ rSVD as a fast and robust clutter filter for ultrafast echocardiograms prior to power Doppler analysis. Ultrafast echocardiograms of nine normal human hearts were acquired in vivo by our cascaded synthetic aperture imaging method. One subject was additionally scanned under four different sonographic signal-to-noise ratio (SNR) levels. Contrast ratio (CR) and contrast-to-noise ratio (CNR) of in vivo power Doppler images obtained from filtered ultrafast echocardiograms were calculated, and their mean and standard deviation within a cardiac cycle represented temporal average and variation of contrast resolution, respectively. Our in vivo results showed that rSVD accelerated clutter filtering by 12-fold and provided significantly better local contrast (mean CNR values: p < 0.001) while being equally effective (mean CR values: p = 0.20) compared with full-SVD. rSVD yielded smaller standard deviations of CR (1.32 dB vs. 5.49 dB) and CNR (1.27 dB vs. 5.49 dB) than full-SVD in the lowest SNR scenario, thus substantiating its superior robustness. Our findings suggest using rSVD in ultrafast echocardiographic blood dynamics analysis.

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.

Four-quadrant fast compressive tracking of breast ultrasound videos for computer-aided response evaluation of neoadjuvant chemotherapy in mice

BACKGROUND AND OBJECTIVE

Neoadjuvant chemotherapy (NAC) is a valuable treatment approach for locally advanced breast cancer. Contrast-enhanced ultrasound (CEUS) potentially enables the assessment of therapeutic response to NAC. In order to evaluate the response accurately, quantitatively and objectively, a method that can effectively compensate motions of breast cancer in CEUS videos is urgently needed.

METHODS

We proposed the four-quadrant fast compressive tracking (FQFCT) approach to automatically perform CEUS video tracking and compensation for mice undergoing NAC. The FQFCT divided a tracking window into four smaller windows at four quadrants of a breast lesion and formulated the tracking at each quadrant as a binary classification task. After the FQFCT of breast cancer videos, the quantitative features of CEUS including the mean transit time (MTT) were computed. All mice showed a pathological response to NAC. The features between pre- (day 1) and post-treatment (day 3 and day 5) in these responders were statistically compared.

RESULTS

When we tracked the CEUS videos of mice with the FQFCT, the average tracking error of FQFCT was 0.65 mm, reduced by 46.72% compared with the classic fast compressive tracking method (1.22 mm). After compensation with the FQFCT, the MTT on day 5 of the NAC was significantly different from the MTT before NAC (day 1) (p = 0.013).

CONCLUSIONS

The FQFCT improves the accuracy of CEUS video tracking and contributes to the computer-aided response evaluation of NAC for breast cancer in mice.

Noninvasive Assessment of In Vivo Passive Skeletal Muscle Mechanics as a Composite Material Using Biomedical Ultrasound

OBJECTIVE

This study develops a biomedical ultrasound imaging method to infer microstructural information (i.e., tissue level) from imaging mechanical behavior of skeletal muscle (i.e., organ level).

METHODS

We first reviewed the constitutive model of skeletal muscle by regarding it as a transversely isotropic (TI) hyperelastic composite material, for which a theoretical formula was established among shear wave speed, deformation, and material parameters (MPs) using the acoustoelasticity theory. The formula was evaluated by finite element (FE) simulations and experimentally examined using ultrasound shear wave imaging (SWI) and strain imaging (SI) on in vivo passive biceps brachii muscles of two healthy volunteers. The imaging sequence included 1) generation of SW in multiple propagation directions while resting the muscle at an elbow angle of 90; 2) generation of SW propagating along the myofiber direction during continuous uniaxial muscle extension by passively changing the elbow angle from 90 to 120. Ultrasound-quantified SW speeds and muscle deformations were fitted by the theoretical formula to estimate MPs of in vivo passive muscle.

RESULTS

Estimated myofiber stiffness, stiffness ratio of myofiber to extracellular matrix (ECM), ECM volume ratio all agreed with literature findings.

CONCLUSION

The proposed mathematical formula together with our in-house ultrasound imaging method enabled assessing microstructural material properties of in vivo passive skeletal muscle from organ-level mechanical behavior in an entirely noninvasive way.

SIGNIFICANCE

Noninvasive assessment of both micro and macro properties of in vivo skeletal muscle will advance our understanding of complex muscle dynamics and facilitate treatment and rehabilitation planning.

A Novel 2-D Speckle Tracking Method for High-Frame-Rate Echocardiography

Speckle tracking echocardiography (STE) is a clinical tool to noninvasively assess regional myocardial function through the quantification of regional motion and deformation. Even if the time resolution of STE can be improved by high-frame-rate (HFR) imaging, dedicated HFR STE algorithms have to be developed to detect very small interframe motions. Therefore, in this article, we propose a novel 2-D STE method, purposely developed for HFR echocardiography. The 2-D motion estimator consists of a two-step algorithm based on the 1-D cross correlations to separately estimate the axial and lateral displacements. The method was first optimized and validated on simulated data giving an accuracy of ~3.3% and ~10.5% for the axial and lateral estimates, respectively. Then, it was preliminarily tested in vivo on ten healthy volunteers showing its clinical applicability and feasibility. Moreover, the extracted clinical markers were in the same range as those reported in the literature. Also, the estimated peak global longitudinal strain was compared with that measured with a clinical scanner showing good correlation and negligible differences (-20.94% versus -20.31%, p -value = 0.44). In conclusion, a novel algorithm for STE was developed: the radio frequency (RF) signals were preferred for the axial motion estimation, while envelope data were preferred for the lateral motion. Furthermore, using 2-D kernels, even for 1-D cross correlation, makes the method less sensitive to noise.

Locally optimized correlation-guided Bayesian adaptive regularization for ultrasound strain imaging

Ultrasound strain imaging utilizes radio-frequency (RF) ultrasound echo signals to estimate the relative elasticity of tissue under deformation. Due to the diagnostic value inherent in tissue elasticity, ultrasound strain imaging has found widespread clinical and preclinical applications. Accurate displacement estimation using pre and post-deformation RF signals is a crucial first step to derive high quality strain tensor images. Incorporating regularization into the displacement estimation framework is a commonly employed strategy to improve estimation accuracy and precision. In this work, we propose an adaptive variation of the iterative Bayesian regularization scheme utilizing RF similarity metric signal-to-noise ratio previously proposed by our group. The regularization scheme is incorporated into a 2D multi-level block matching (BM) algorithm for motion estimation. Adaptive nature of our algorithm is attributed to the dynamic variation of iteration number based on the normalized cross-correlation (NCC) function quality and a similarity measure between pre-deformation and motion compensated post-deformation RF signals. The proposed method is validated for either quasi-static and cardiac elastography or strain imaging applications using uniform and inclusion phantoms and canine cardiac deformation simulation models. Performance of adaptive Bayesian regularization was compared to conventional NCC and Bayesian regularization with fixed number of iterations. Results from uniform phantom simulation study show significant improvement in lateral displacement and strain estimation accuracy. For instance, at 1.5% lateral strain in a uniform phantom, Bayesian regularization with five iterations incurred a lateral strain error of 104.49%, which was significantly reduced using our adaptive approach to 27.51% (p   <  0.001). Contrast-to-noise (CNR _e ) ratios obtained from inclusion phantom indicate improved lesion detectability for both axial and lateral strain images. For instance, at 1.5% lateral strain, Bayesian regularization with five iterations had lateral CNR _e of  -0.31 dB which was significantly increased using the adaptive approach to 7.42 dB (p   <  0.001). Similar results are seen with cardiac deformation modelling with improvement in myocardial strain images. In vivo feasibility was also demonstrated using data from a healthy murine heart. Overall, the proposed method makes Bayesian regularization robust for clinical and preclinical applications.

Hierarchical Motion Estimation With Bayesian Regularization in Cardiac Elastography: Simulation and In Vivo Validation

Cardiac elastography (CE) is an ultrasound-based technique utilizing radio-frequency (RF) signals for assessing global and regional myocardial function. In this work, a complete strain estimation pipeline for incorporating a Bayesian regularization-based hierarchical block-matching algorithm, with Lagrangian motion description and myocardial polar strain estimation is presented. The proposed regularization approach is validated using finite-element analysis (FEA) simulations of a canine cardiac deformation model that is incorporated into an ultrasound simulation program. Interframe displacements are initially estimated using a hierarchical motion estimation framework. Incremental displacements are then accumulated under a Lagrangian description of cardiac motion from end-diastole (ED) to end-systole (ES). In-plane Lagrangian finite strain tensors are then derived from the accumulated displacements. Cartesian to cardiac coordinate transformation is utilized to calculate radial and longitudinal strains for ease of interpretation. Benefits of regularization are demonstrated by comparing the same hierarchical block-matching algorithm with and without regularization. Application of Bayesian regularization in the canine FEA model provided improved ES radial and longitudinal strain estimation with statistically significant ( ) error reduction of 48.88% and 50.16%, respectively. Bayesian regularization also improved the quality of temporal radial and longitudinal strain curves with error reductions of 78.38% and 86.67% ( ), respectively. Qualitative and quantitative improvements were also visualized for in vivo results on a healthy murine model after Bayesian regularization. Radial strain elastographic signal-to-noise ratio (SNR_e) increased from 3.83 to 4.76 dB, while longitudinal strain SNR_e increased from 2.29 to 4.58 dB with regularization.

Imaging Heart Dynamics With Ultrafast Cascaded-Wave Ultrasound

The heart is an organ with highly dynamic complexity, including cyclic fast electrical activation, muscle kinematics, and blood dynamics. Although ultrafast cardiac imaging techniques based on pulsed-wave ultrasound (PUS) have rapidly emerged to permit mapping of heart dynamics, they suffer from limited sonographic signal-to-noise ratio (SNR) and penetration due to insufficient energy delivery and inevitable attenuation through the chest wall. We hereby propose ultrafast cascaded-wave ultrasound (uCUS) imaging to depict heart dynamics in higher SNR and larger penetration than conventional ultrafast PUS. To solve the known tradeoff between the length of transmitted ultrasound signals and spatial resolution while achieving ultrafast frame rates (>1000 Hz), we develop a cascaded synthetic aperture (CaSA) imaging method. In CaSA, an array probe is divided into subapertures; each subaperture transmits a train of diverging waves. These diverging waves are weighted in both the aperture (i.e., spatial) and range (i.e., temporal) directions with a coding matrix containing only +1 and -1 polarity coefficients. A corresponding spatiotemporal decoding matrix is designed to recover backscattered signals. The decoded signals are thereafter beamformed and coherently compounded to obtain one high-SNR beamformed image frame. For CaSA with M subapertures and N cascaded diverging waves, sonographic SNR is increased by 10× log ₁₀ (N ×M) (dB) compared with conventional synthetic aperture (SA) imaging. The proposed uCUS with CaSA was evaluated with conventional SA and Hadamard-encoded SA (H-SA) methods in a calibration phantom for B-mode image quality and an in vivo human heart in a transthoracic setting for the quality assessment of anatomical, myocardial motion, and chamber blood power Doppler images. Our results demonstrated that the proposed uCUS with CaSA (4 subapertures, 32 cascaded waves) improved SNR (+20.46 dB versus SA, +14.83 dB versus H-SA) and contrast ratio (+8.44 dB versus SA, +7.81 dB versus H-SA) with comparable spatial resolutions to and at the same frame rates as benchmarks.

Bidirectional Ultrasound Elastographic Imaging Framework for Non-invasive Assessment of the Non-linear Behavior of a Physiologically Pressurized Artery

Studies of non-destructive bidirectional ultrasound assessment of non-linear mechanical behavior of the artery are scarce in the literature. We hereby propose derivation of a strain-shear modulus relationship as a new graphical diagnostic index using an ultrasound elastographic imaging framework, which encompasses our in-house bidirectional vascular guided wave imaging (VGWI) and ultrasound strain imaging (USI). This framework is used to assess arterial non-linearity in two orthogonal (i.e., longitudinal and circumferential) directions in the absence of non-invasive pressure measurement. Bidirectional VGWI estimates longitudinal (μ_L) and transverse (μ_T) shear moduli, whereas USI estimates radial strain (ɛ_r). Vessel-mimicking phantoms (with and without longitudinal pre-stretch) and in vitro porcine aortas under static and/or dynamic physiologic intraluminal pressure loads were examined. ɛ_r was found to be a suitable alternative to intraluminal pressure for representation of cyclic loading on the artery wall. Results revealed that μ_T values of all samples examined increased non-linearly with ε_r magnitude and more drastically than μ_L, whereas μ_L values of only the pre-stretched phantoms and aortas increased with ɛ_r magnitude. As a new graphical representation of arterial non-linearity and function, strain-shear modulus loops derived by the proposed framework over two consecutive dynamic loading cycles differentiated sample pre-conditions and corroborated direction-dependent non-linear mechanical behaviors of the aorta with high estimation repeatability.

Spatial Angular Compounding With Affine-Model-Based Optical Flow for Improvement of Motion Estimation

Tissue motion estimation is an essential step for ultrasound elastography. Our previous study has shown that the affine-model-based optical flow (OF) method outperforms the normalized cross-correlation-based block matching (BM) method in motion estimation. However, the quality of lateral estimation using OF is still low due to inherent limitation of ultrasound imaging. BM-based spatial angular compounding (SAC) has been developed to obtain better motion estimation. In this paper, OF-based SAC (OF-SAC) is proposed to further improve the performance of lateral (and axial) estimation, and it is compared with BM-based SAC (BM-SAC). Plane wave as well as focused wave is transmitted in both simulations and phantom experiments on a linear array. In order to compare the performance quantitatively, the root-mean-square error (RMSE) of axial/lateral displacement and strain, and signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of axial/lateral strain are used as the evaluation criteria in the simulations. In the phantom experiments, the SNR and CNR are used to assess the quality of axial/lateral strain. The results show that for both OF and BM, SAC improves the performance of motion estimation, regardless of using plane or focused wave transmission. More importantly, OF-SAC is shown to outperform BM-SAC with lower RMSE, higher SNR, and higher CNR. In addition, preliminary in vivo experiments on the carotid artery of a healthy human subject also prove the superiority of OF-SAC. These results suggest that OF-SAC is preferred for both axial and lateral motion estimation to BM-SAC.

Two-dimensional affine model-based estimators for principal strain vascular ultrasound elastography with compound plane wave and transverse oscillation beamforming

Polar strain (radial and circumferential) estimations can suffer from artifacts because the center of a nonsymmetrical carotid atherosclerotic artery, defining the coordinate system in cross-sectional view, can be misregistered. Principal strains are able to remove coordinate dependency to visualize vascular strain components (i.e., axial and lateral strains and shears). This paper presents two affine model-based estimators, the affine phase-based estimator (APBE) developed in the framework of transverse oscillation (TO) beamforming, and the Lagrangian speckle model estimator (LSME). These estimators solve simultaneously the translation (axial and lateral displacements) and deformation (axial and lateral strains and shears) components that were then used to compute principal strains. To improve performance, the implemented APBE was also tested by introducing a time-ensemble estimation approach. Both APBE and LSME were tested with and without the plane strain incompressibility assumption. These algorithms were evaluated on coherent plane wave compounded (CPWC) images considering TO. LSME without TO but implemented with the time-ensemble and incompressibility constraint (Porée et al., 2015) served as benchmark comparisons. The APBE provided better principal strain estimations with the time-ensemble and incompressibility constraint, for both simulations and in vitro experiments. With a few exceptions, TO did not improve principal strain estimates for the LSME. With simulations, the smallest errors compared with ground true measures were obtained with the LSME considering time-ensemble and the incompressibility constraint. This latter estimator also provided the highest elastogram signal-to-noise ratios (SNRs) for in vitro experiments on a homogeneous vascular phantom without any inclusion, for applied strains varying from 0.07% to 4.5%. It also allowed the highest contrast-to-noise ratios (CNRs) for a heterogeneous vascular phantom with a soft inclusion, at applied strains from 0.07% to 3.6%. In summary, the LSME outperformed the implemented APBE, and the incompressibility constraint improved performances of both estimators.

In silico simulation of liver crack detection using ultrasonic shear wave imaging

Background

Liver trauma is an important source of morbidity and mortality worldwide. A timely detection and precise evaluation of traumatic liver injury and the bleeding site is necessary. There is a need to develop better imaging modalities of hepatic injuries to increase the sensitivity of ultrasonic imaging techniques for sites of hemorrhage caused by cracks. In this study, we conduct an in silico simulation of liver crack detection and delineation using an ultrasonic shear wave imaging (USWI) based method.

Methods

We simulate the generation and propagation of the shear wave in a liver tissue medium having a crack using COMSOL. Ultrasound radio frequency (RF) signal synthesis and the two-dimensional speckle tracking algorithm are applied to simulate USWI in a medium with randomly distributed scatterers. Crack detection is performed using the directional filter and the edge detection algorithm rather than the conventional inversion algorithm. Cracks with varied sizes and locations are studied with our method and the crack localization results are compared with the given crack.

Results

Our pilot simulation study shows that, by using USWI combined with a directional filter cum edge detection technique, the near-end edge of the crack can be detected in all the three cracks that we studied. The detection errors are within 5%. For a crack of 1.6 mm thickness, little shear wave can pass through it and the far-end edge of the crack cannot be detected. The detected crack lengths using USWI are all slightly shorter than the actual crack length. The robustness of our method in detecting a straight crack, a curved crack and a subtle crack of 0.5 mm thickness is demonstrated.

Conclusions

In this paper, we simulate the use of a USWI based method for the detection and delineation of the crack in liver. The in silico simulation helps to improve understanding and interpretation of USWI measurements in a physical scattered liver medium with a crack. This pilot study provides a basis for improved insights in future crack detection studies in a tissue phantom or liver.

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.

Ultrafast Ultrasound Imaging Using Combined Transmissions With Cross-Coherence-Based Reconstruction

Plane-wave-based ultrafast imaging has become the prevalent technique for non-conventional ultrasound imaging. The image quality, especially in terms of the suppression of artifacts, is generally compromised by reducing the number of transmissions for a higher frame rate. We hereby propose a new ultrafast imaging framework that reduces not only the side lobe artifacts but also the axial lobe artifacts using combined transmissions with a new coherence-based factor. The results from simulations, in vitro wire phantoms, the ex vivo porcine artery, and the in vivo porcine heart show that our proposed methodology greatly reduced the axial lobe artifact by 25±5 dB compared with coherent plane-wave compounding (CPWC), which was considered as the ultrafast imaging standard, and suppressed side lobe artifacts by 15 ± 5 dB compared with CPWC and coherent spherical-wave compounding. The reduction of artifacts in our proposed ultrafast imaging framework led to a better boundary delineation of soft tissues than CPWC.

A Systematic Investigation of Lateral Estimation Using Various Interpolation Approaches in Conventional Ultrasound Imaging

Accurate lateral displacement and strain estimation is critical for some applications of elasticity imaging. Typically, motion estimation in the lateral direction is challenging because of low sampling frequency and lack of phase information in conventional ultrasound imaging. Several approaches have been proposed to improve the performance of lateral estimation, such as lateral interpolation on the radio frequency (RF) signals (Interp_RF), lateral interpolation on the cross-correlation function (Interp_CCF), and lateral interpolation on both the RF signals and cross-correlation function (Interp_Both). In this paper, the estimation performances of the above-mentioned three approaches are compared systematically in simulations and phantom experiments. In the simulations, the root-mean-square error (RMSE) of axial/lateral displacement and strain is utilized to assess the accuracy of motion estimation. In the phantom experiments, the displacement quality metric (DQM), defined as the normalized cross-correlation between the motion-compensated reference frame and the comparison frame, and the contrast-to-noise ratio (CNR) of axial/lateral strain are used as the evaluation criteria. The results show that the three approaches have similar performance in axial estimation. For lateral estimation, if the line density of ultrasound imaging is relatively high (i.e., >4.2 lines/mm), Interp_CCF is comparable to Interp_Both, and Interp_RF performs the worst. However, if the line density is relatively low (i.e., <2.8 lines/mm), Interp_Both performs the best as indicated by the lowest RMSEs or highest DQMs and CNRs in lateral estimation. The trend is consistent at different window sizes, applied strains, and sonographic signal-to-noise ratios (>20 dB). Besides, Interp_Both with a small interpolation factor (e.g., 3-5) is found to obtain the best tradeoff between the estimation accuracy and the computational cost, and thus is suggested for lateral motion estimation in the case of a low line density (i.e., <2.8 lines/mm).