Noninvasive Vascular Elastography With Plane Strain Incompressibility Assumption Using Ultrafast Coherent Compound Plane Wave Imaging

Polyvinyl Alcohol Phantoms With Heterogeneous Plaques: Estimation of Pulse Wave Velocity at the Stenotic Region Using Pulse Wave Imaging

OBJECTIVE

Plaque characterization is essential for stroke prevention. In the study reported herein, we describe a heterogeneous phantom manufacturing technique with varying plaque compositions of different stiffness using polyvinyl alcohol (PVA) to emulate stenotic arteries and evaluated the use of pulse wave imaging (PWI) to assess plaque stiffness by comparing derived pulse wave velocities, with the goal of assessing plaque vulnerability and identifying high-risk patients for stroke.

METHODS

Five stenotic phantoms (50% stenosis) were fabricated by pouring PVA solutions into 3-D-printed molds. Two of the phantoms had heterogeneous plaque compositions of soft (E0 = 13 kPa) and intermediate (E0 = 40 kPa) materials and of stiff (E0 = 54 kPa) and intermediate materials. Ultrasound sequences were acquired as the arterial phantoms were connected to a pulsating pump, and PWI was performed on the ultrasound acquisition using normalized cross-correlation to track the pulse-induced phantom wall distension propagations. Pulse wave velocities were estimated by fitting a linear regression line between the arrival time of the peak acceleration of the wall distension waveform and the corresponding location.

RESULTS

Arterial phantoms with heterogeneous plaque stiffness were successfully fabricated. Pulse wave velocities of 2.06, 2.21, 2.49, 2.67 and 3.31 m/s were found in the phantom experiments using PWI for homogeneous soft plaque, the heterogeneous soft and intermediate plaque, homogeneous intermediate plaque, the heterogeneous stiff and intermediate plaque and homogeneous stiff plaque, respectively.

CONCLUSION

A novel arterial phantom building technique was reported with varying heterogenous plaque compositions of different stiffness. The feasibility of using PWI to evaluate plaque stiffness in stenotic arteries was determined and found that PWI can distinguish between plaques of distinct stiffness and composition.

Characterizing atherosclerotic tissues: in silico analysis of mechanical properties using intravascular ultrasound and inverse finite element methods

Atherosclerosis is a prevalent cause of acute coronary syndromes that consists of lipid deposition inside the artery wall, creating an atherosclerotic plaque. Early detection may prevent the risk of plaque rupture. Nowadays, intravascular ultrasound (IVUS) is the most common medical imaging technology for atherosclerotic plaque detection. It provides an image of the section of the coronary wall and, in combination with new techniques, can estimate the displacement or strain fields. From these magnitudes and by inverse analysis, it is possible to estimate the mechanical properties of the plaque tissues and their stress distribution. In this paper, we presented a methodology based on two approaches to characterize the mechanical properties of atherosclerotic tissues. The first approach estimated the linear behavior under particular pressure. In contrast, the second technique yielded the non-linear hyperelastic material curves for the fibrotic tissues across the complete physiological pressure range. To establish and validate this method, the theoretical framework employed in silico models to simulate atherosclerotic plaques and their IVUS data. We analyzed different materials and real geometries with finite element (FE) models. After the segmentation of the fibrotic, calcification, and lipid tissues, an inverse FE analysis was performed to estimate the mechanical response of the tissues. Both approaches employed an optimization process to obtain the mechanical properties by minimizing the error between the radial strains obtained from the simulated IVUS and those achieved in each iteration. The second methodology was successfully applied to five distinct real geometries and four different fibrotic tissues, getting median R 2 of 0.97 and 0.92, respectively, when comparing the real and estimated behavior curves. In addition, the last technique reduced errors in the estimated plaque strain field by more than 20% during the optimization process, compared to the former approach. The findings enabled the estimation of the stress field over the hyperelastic plaque tissues, providing valuable insights into its risk of rupture.

Frame rate improvement in ultrafast coherent plane wave compounding

Coherent plane wave compounding (CPWC), as an ultrafast ultrasound imaging technique, makes a significant breakthrough in frame rate enhancement. However, there exists a compromise between the quality of the final image and the frame rate in CPWC. In this paper, we propose an efficient method to minimize the number of required emissions, and consequently, improve the frame rate, while maintaining the image quality. To this end, we down-sample the angle interval using two specific sampling factors. More precisely, we construct two different subsets, each of which consists of a few numbers of emissions. The optimal values of the angle intervals are achieved based on the beampattern that corresponds to the reference case (that is, the case where all plane waves are used). Finally, in order to keep the image quality comparable with the reference case, we apply some modifications to the image reconstruction procedure. In the proposed algorithm, the Delay-and-Sum beamformed images of two considered subsets are convolved to achieve the final reconstructed image. The obtained results confirm the efficiency of the proposed method in terms of frame rate improvement compared to the reference case. In particular, by using the proposed method, the required emissions in PICMUS data reduce to 16, which is 4.6 times smaller compared to the reference case. Also, the gCNR values of the proposed method and the reference case are obtained as 0.98 and 0.97, respectively, for in-vivo dataset. This demonstrates that the proposed method successfully preserves the quality of the reconstructed image by using much fewer emissions.

Unsupervised deep learning-based displacement estimation for vascular elasticity imaging applications

Objective. Arterial wall stiffness can provide valuable information on the proper function of the cardiovascular system. Ultrasound elasticity imaging techniques have shown great promise as a low-cost and non-invasive tool to enable localized maps of arterial wall stiffness. Such techniques rely upon motion detection algorithms that provide arterial wall displacement estimation.Approach. In this study, we propose an unsupervised deep learning-based approach, originally proposed for image registration, in order to enable improved quality arterial wall displacement estimation at high temporal and spatial resolutions. The performance of the proposed network was assessed through phantom experiments, where various models were trained by using ultrasound RF signals, or B-mode images, as well as different loss functions.Main results. Using the mean square error (MSE) for the training process provided the highest signal-to-noise ratio when training on the B-modes images (30.36 ± 1.14 dB) and highest contrast-to-noise ratio when training on the RF signals (32.84 ± 1.89 dB). In addition, training the model on RF signals demonstrated the capability of providing accurate localized pulse wave velocity (PWV) maps, with a mean relative error (MREPWV) of 3.32 ± 1.80% and anR2 of 0.97 ± 0.03. Finally, the developed model was tested in human common carotid arteriesin vivo, providing accurate tracking of the distension pulse wave propagation, with an MREPWV= 3.86 ± 2.69% andR2 = 0.95 ± 0.03.Significance. In conclusion, a novel displacement estimation approach was presented, showing promise in improving vascular elasticity imaging techniques.

Imaging the subcellular viscoelastic properties of mouse oocytes

In recent years, cellular biomechanical properties have been investigated as an alternative to morphological assessments for oocyte selection in reproductive science. Despite the high relevance of cell viscoelasticity characterization, the reconstruction of spatially distributed viscoelastic parameter images in such materials remains a major challenge. Here, a framework for mapping viscoelasticity at the subcellular scale is proposed and applied to live mouse oocytes. The strategy relies on the principles of optical microelastography for imaging in combination with the overlapping subzone nonlinear inversion technique for complex-valued shear modulus reconstruction. The three-dimensional nature of the viscoelasticity equations was accommodated by applying an oocyte geometry-based 3D mechanical motion model to the measured wave field. Five domains-nucleolus, nucleus, cytoplasm, perivitelline space, and zona pellucida-could be visually differentiated in both oocyte storage and loss modulus maps, and statistically significant differences were observed between most of these domains in either property reconstruction. The method proposed herein presents excellent potential for biomechanical-based monitoring of oocyte health and complex transformations across lifespan. It also shows appreciable latitude for generalization to cells of arbitrary shape using conventional microscopy equipment.

Ultrafast Myocardial Principal Strain Ultrasound Elastography During Stress Tests: In Vitro Validation and In Vivo Feasibility

Objective myocardial contractility assessment during stress tests aims to improve the diagnosis of myocardial ischemia. Tissue Doppler imaging (TDI) or optical flow (OF) speckle tracking echocardiography (STE) has been used to quantify myocardial contractility at rest. However, this is more challenging during stress tests due to image decorrelation at high heart rates. Moreover, stress tests imply a high frame rate which leads to a limited lateral field of view. Therefore, a large lateral field-of-view robust ultrafast myocardial regularized OF-TDI principal strain estimator has been developed for high-frame-rate echocardiography of coherently compounded transmitted diverging waves. The feasibility and accuracy of the proposed estimator were validated in vitro (using sonomicrometry as the gold standard) and in vivo stress experiments. Compared with OF strain imaging, the proposed estimator improved the accuracy of principal major and minor strains during stress tests, with an average contrast-to-noise ratio improvement of 4.4 ± 2.7 dB ( p -value < 0.01). Moreover, there was a significant correlation and a very close agreement between the proposed estimator and sonomicrometry for tested heart rates between 60 and 180 beats per minute (bpm). The averages ± standard deviations (STD) of R² and biases ± STD between them were 0.96 ± 0.04 ( p -value < 0.01) and 0.01 ± 0.03% in the axial direction, respectively; and 0.94 ± 0.02 ( p -value < 0.01) and 0.04 ± 0.06% in the lateral direction, respectively. These results suggest that the proposed estimator could be useful clinically to provide an accurate and quantitative 2-D large lateral field-of-view myocardial strain assessment at high heart rates during stress echocardiography.

Deep learning in ultrasound elastography imaging: A review

It is known that changes in the mechanical properties of tissues are associated with the onset and progression of certain diseases. Ultrasound elastography is a technique to characterize tissue stiffness using ultrasound imaging either by measuring tissue strain using quasi-static elastography or natural organ pulsation elastography, or by tracing a propagated shear wave induced by a source or a natural vibration using dynamic elastography. In recent years, deep learning has begun to emerge in ultrasound elastography research. In this review, several common deep learning frameworks in the computer vision community, such as multilayer perceptron, convolutional neural network, and recurrent neural network are described. Then, recent advances in ultrasound elastography using such deep learning techniques are revisited in terms of algorithm development and clinical diagnosis. Finally, the current challenges and future developments of deep learning in ultrasound elastography are prospected. This article is protected by copyright. All rights reserved.

SIMUS: An open-source simulator for medical ultrasound imaging. Part I: Theory & examples

BACKGROUND AND OBJECTIVE

Computational ultrasound imaging has become a well-established methodology in the ultrasound community. Simulations of ultrasound sequences and images allow the study of innovative techniques in terms of emission strategy, beamforming, and probe design. There is a wide spectrum of software dedicated to ultrasound imaging, each having its specificities in its applications and the numerical method.

METHODS

We describe in this two-part paper a new ultrasound simulator (SIMUS) for MATLAB, which belongs to the MATLAB UltraSound Toolbox (MUST). The SIMUS software simulates acoustic pressure fields and radiofrequency RF signals for uniform linear or convex probes. SIMUS is an open-source software whose features are 1) ease of use, 2) time-harmonic analysis, 3) pedagogy. The main goal was to offer a comprehensive turnkey tool, along with a detailed theory for pedagogical and research purposes.

RESULTS

This article describes in detail the underlying linear theory of SIMUS and provides examples of simulated acoustic fields and ultrasound images. The accompanying article (part II) is devoted to the comparison of SIMUS with several software packages: Field II, k-Wave, FOCUS, and the Verasonics simulator. The MATLAB open codes for the simulator SIMUS are distributed under the terms of the GNU Lesser General Public License, and can be downloaded from https://www.biomecardio.com/MUST.

CONCLUSIONS

The simulations described in this part and in the accompanying paper (Part II) show that SIMUS can be used for realistic simulations in medical ultrasound imaging.

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

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

Deformability of ascending thoracic aorta aneurysms assessed using ultrafast ultrasound and a principal strain estimator: In vitro evaluation and in vivo feasibility

BACKGROUND

Noninvasive vascular strain imaging under conventional line-by-line scanning has a low frame rate and lateral resolution, and depends on the coordinate system. It is thus affected by high deformations due to image decorrelation between frames.

PURPOSE

To develop an ultrafast time-ensemble regularized tissue-Doppler optical-flow principal strain estimator for aorta deformability assessment in a long-axis view.

METHODS

This approach alleviated the impact of lateral resolution using image compounding and that of the coordinate system dependency using principal strain. Accuracy and feasibility were evaluated in two aorta-mimicking phantoms first, and then in four age-matched individuals with either a normal aorta or a pathological ascending thoracic aorta aneurysm (TAA).

RESULTS

Instantaneous aortic maximum and minimum principal strain maps and regional accumulated strains during each cardiac cycle were estimated at systolic and diastolic phases to characterize the normal aorta and TAA. In vitro, principal strain results matched sonomicrometry measurements. In vivo, a significant decrease in maximum and minimum principal strains was observed in TAA cases, whose range was respectively 7.9 ± 6.4% and 8.2 ± 2.6% smaller than in normal aortas.

CONCLUSIONS

The proposed principal strain estimator showed an ability to potentially assess TAA deformability, which may provide an individualized and reliable evaluation method for TAA rupture risk assessment. This article is protected by copyright. All rights reserved.

An unsupervised learning approach to ultrasound strain elastography with spatio-temporal consistency

Quasi-static ultrasound elastography (USE) is an imaging modality that measures deformation (i.e. strain) of tissue in response to an applied mechanical force. In USE, the strain modulus is traditionally obtained by deriving the displacement field estimated between a pair of radio-frequency data. In this work we propose a recurrent network architecture with convolutional long-short-term memory decoder blocks to improve displacement estimation and spatio-temporal continuity between time series ultrasound frames. The network is trained in an unsupervised way, by optimising a similarity metric between the reference and compressed image. Our training loss is also composed of a regularisation term that preserves displacement continuity by directly optimising the strain smoothness, and a temporal continuity term that enforces consistency between successive strain predictions. In addition, we propose an open-access in vivo database for quasi-static USE, which consists of radio-frequency data sequences captured on the arm of a human volunteer. Our results from numerical simulation and in vivo data suggest that our recurrent neural network can account for larger deformations, as compared with two other feed-forward neural networks. In all experiments, our recurrent network outperformed the state-of-the-art for both learning-based and optimisation-based methods, in terms of elastographic signal-to-noise ratio, strain consistency, and image similarity. Finally, our open-source code provides a 3D-slicer visualisation module that can be used to process ultrasound RF frames in real-time, at a rate of up to 20 frames per second, using a standard GPU.

Pulse Wave Imaging Coupled With Vector Flow Mapping: A Phantom, Simulation, and In Vivo Study

Pulse wave imaging (PWI) is an ultrasound imaging modality that estimates the wall stiffness of an imaged arterial segment by tracking the pulse wave propagation. The aim of the present study is to integrate PWI with vector flow imaging, enabling simultaneous and co-localized mapping of vessel wall mechanical properties and 2-D flow patterns. Two vector flow imaging techniques were implemented using the PWI acquisition sequence: 1) multiangle vector Doppler and 2) a cross-correlation-based vector flow imaging (CC VFI) method. The two vector flow imaging techniques were evaluated in vitro using a vessel phantom with an embedded plaque, along with spatially registered fluid structure interaction (FSI) simulations with the same geometry and inlet flow as the phantom setup. The flow magnitude and vector direction obtained through simulations and phantom experiments were compared in a prestenotic and stenotic segment of the phantom and at five different time frames. In most comparisons, CC VFI provided significantly lower bias or precision than the vector Doppler method ( ) indicating better performance. In addition, the proposed technique was applied to the carotid arteries of nonatherosclerotic subjects of different ages to investigate the relationship between PWI-derived compliance of the arterial wall and flow velocity in vivo. Spearman's rank-order test revealed positive correlation between compliance and peak flow velocity magnitude ( rs = 0.90 and ), while significantly lower compliance ( ) and lower peak flow velocity magnitude ( ) were determined in older (54-73 y.o.) compared with young (24-32 y.o.) subjects. Finally, initial feasibility was shown in an atherosclerotic common carotid artery in vivo. The proposed imaging modality successfully provided information on blood flow patterns and arterial wall stiffness and is expected to provide additional insight in studying carotid artery biomechanics, as well as aid in carotid artery disease diagnosis and monitoring.

CNN-Based Ultrasound Image Reconstruction for Ultrafast Displacement Tracking

Thanks to its capability of acquiring full-view frames at multiple kilohertz, ultrafast ultrasound imaging unlocked the analysis of rapidly changing physical phenomena in the human body, with pioneering applications such as ultrasensitive flow imaging in the cardiovascular system or shear-wave elastography. The accuracy achievable with these motion estimation techniques is strongly contingent upon two contradictory requirements: a high quality of consecutive frames and a high frame rate. Indeed, the image quality can usually be improved by increasing the number of steered ultrafast acquisitions, but at the expense of a reduced frame rate and possible motion artifacts. To achieve accurate motion estimation at uncompromised frame rates and immune to motion artifacts, the proposed approach relies on single ultrafast acquisitions to reconstruct high-quality frames and on only two consecutive frames to obtain 2-D displacement estimates. To this end, we deployed a convolutional neural network-based image reconstruction method combined with a speckle tracking algorithm based on cross-correlation. Numerical and in vivo experiments, conducted in the context of plane-wave imaging, demonstrate that the proposed approach is capable of estimating displacements in regions where the presence of side lobe and grating lobe artifacts prevents any displacement estimation with a state-of-the-art technique that relies on conventional delay-and-sum beamforming. The proposed approach may therefore unlock the full potential of ultrafast ultrasound, in applications such as ultrasensitive cardiovascular motion and flow analysis or shear-wave elastography.

Ultrasound image reconstruction from plane wave radio-frequency data by self-supervised deep neural network

Image reconstruction from radio-frequency (RF) data is crucial for ultrafast plane wave ultrasound (PWUS) imaging. Compared with the traditional delay-and-sum (DAS) method based on relatively imprecise assumptions, sparse regularization (SR) method directly solves the inverse problem of image reconstruction and has presented significant improvement in the image quality when the frame rate remains high. However, the computational complexity of SR is too high for practical implementation, which is inherently associated with its iterative process. In this work, a deep neural network (DNN), which is trained with an incorporated loss function including sparse regularization terms, is proposed to reconstruct PWUS images from RF data with significantly reduced computational time. It is remarkable that, a self-supervised learning scheme, in which the RF data are utilized as both the inputs and the labels during the training process, is employed to overcome the lack of the "ideal" ultrasound images as the labels for DNN. In addition, it has been also verified that the trained network can be used on the RF data obtained with steered plane waves (PWs), and thus the image quality can be further improved with coherent compounding. Using simulation data, the proposed method has significantly shorter reconstruction time (∼10 ms) than the conventional SR method (∼1-5 mins), with comparable spatial resolution and 1.5-dB higher contrast-to-noise ratio (CNR). Besides, the proposed method with single PW can achieve higher CNR than DAS with 75 PWs in reconstruction of in-vivo images of human carotid arteries.

Parameterized Strain Estimation for Vascular Ultrasound Elastography With Sparse Representation

Ultrasound vascular strain imaging has shown its potential to interrogate the motion of the vessel wall induced by the cardiac pulsation for predicting plaque instability. In this study, a sparse model strain estimator (SMSE) is proposed to reconstruct a dense strain field at a high resolution, with no spatial derivatives, and a high computation efficiency. This sparse model utilizes the highly-compacted property of discrete cosine transform (DCT) coefficients, thereby allowing to parameterize displacement and strain fields with truncated DCT coefficients. The derivation of affine strain components (axial and lateral strains and shears) was reformulated into solving truncated DCT coefficients and then reconstructed with them. Moreover, an analytical solution was derived to reduce estimation time. With simulations, the SMSE reduced estimation errors by up to 50% compared with the state-of-the-art window-based Lagrangian speckle model estimator (LSME). The SMSE was also proven to be more robust than the LSME against global and local noise. For in vitro and in vivo tests, residual strains assessing cumulated errors with the SMSE were 2 to 3 times lower than with the LSME. Regarding computation efficiency, the processing time of the SMSE was reduced by 4 to 25 times compared with the LSME, according to simulations, in vitro and in vivo results. Finally, phantom studies demonstrated the enhanced spatial resolution of the proposed SMSE algorithm against LSME.

A comparison between unfocused and focused transmit strategies in cardiac strain imaging

Unfocused ultrasound imaging, particularly coherent compounding with diverging waves, is a commonly employed high-frame rate transmit strategy in cardiac strain imaging. However, the accuracy and precision of diverging wave imaging compared to focused-beam transmit approaches in human subjects is unknown. Three transmit strategies-coherent compounding imaging, composite focused imaging with ECG gating and narrow-beams, and focused imaging with wide-beams-were compared in simulation and in transthoracic imaging of healthy human subjects (n  =  7). The focused narrow-beam sequence estimated radial end-systolic cumulative strains of a simulated left ventricular deformation with 26%  ±  1.5% and 34%  ±  1.5% greater accuracy compared with compounding and wide-beam imaging, respectively. Strain estimation precision in transthoracic imaging was then assessed with the Strain Filter on cumulative end-systolic radial strains. Within the strain values where statistically significant differences in precision (E(SNR_e|ε)) were found between transmit strategies, the narrow-beam sequence estimated radial strain 13%  ±  0.71% and 34%  ±  8.9% more precisely on average compared to compounding or wide-beam imaging, respectively.

Adaptive Pulse Wave Imaging: Automated Spatial Vessel Wall Inhomogeneity Detection in Phantoms and in-Vivo

Imaging arterial mechanical properties may improve vascular disease diagnosis. Pulse wave velocity (PWV) is a marker of arterial stiffness linked to cardio-vascular mortality. Pulse wave imaging (PWI) is a technique for imaging the pulse wave propagation at high spatial and temporal resolution. In this paper, we introduce adaptive PWI, a technique for the automated partition of heterogeneous arteries into individual segments characterized by most homogeneous pulse wave propagation, allowing for more robust PWV estimation. This technique was validated in a silicone phantom with a soft-stiff interface. The mean detection error of the interface was 4.67 ± 0.73 mm and 3.64 ± 0.14 mm in the stiff-to-soft and soft-to-stiff pulse wave transmission direction, respectively. This technique was tested in monitoring the progression of atherosclerosis in mouse aortas in vivo ( n = 11 ). The PWV was found to already increase at the early stage of 10 weeks of high-fat diet (3.17 ± 0.67 m/sec compared to baseline 2.55 ± 0.47 m/sec, ) and further increase after 20 weeks of high-fat diet (3.76±1.20 m/sec). The number of detected segments of the imaged aortas monotonically increased with the duration of high-fat diet indicating an increase in arterial wall property inhomogeneity. The performance of adaptive PWI was also tested in aneurysmal mouse aortas in vivo. Aneurysmal boundaries were detected with a mean error of 0.68±0.44 mm. Finally, initial feasibility was shown in the carotid arteries of healthy and atherosclerotic human subjects in vivo ( n = 3 each). Consequently, adaptive PWI was successful in detecting stiffness inhomogeneity at its early onset and monitoring atherosclerosis progression in vivo.

An adaptive imaging method for ultrasound coherent plane-wave compounding based on the subarray zero-cross factor

Coherent plane-wave compounding (CPWC) has the ability to generate high quality image using the backscattered signals from plane wave emitting at different steer angles. To improve the image quality of CPWC, adaptive weighting techniques have been introduced in the compounding procedure. This paper proposes subarray zeros-cross factor (SZF) for CPWC, and it is used as an adaptive weighting factor to improve image quality. The SZF is calculated based on polarity of plane-wave imaging results with adjacent steering angle to estimate the coherence of plane wave emitting events. It is effective to suppress noise and maintain background speckle pattern. Simulations and experiments were conducted to evaluate the performance of the proposed method. Results demonstrate that the SZF can achieve better performance on contrast ratio (CR) and resolution than traditional CPWC. For simulated cysts, a maximal CR improvement of 125.4% is achieved. For experimental cysts, the maximal CR improvement is 197.9%. Compared with coherence factor (CF) and generalized coherence factor (GCF), SZF can obtain improvements in contrast-to-noise ratio and speckle signal-to-noise ratio at near field and increase CR at far field. In addition, when subarray length L is in the range of [10,12], SZF can obtain satisfying comprehensive performance.

Simultaneous transmission and reception on all elements of an array: binary code excitation

Pulse-echo arrays are used in radar, sonar, seismic, medical and non-destructive evaluation. There is a trend to produce arrays with an ever-increasing number of elements. This trend presents two major challenges: (i) often the size of the elements is reduced resulting in a lower signal-to-noise ratio (SNR) and (ii) the time required to record all of the signals that correspond to every transmit-receive path increases. Coded sequences with good autocorrelation properties can increase the SNR while orthogonal sets can be used to simultaneously acquire all of the signals that correspond to every transmit-receive path. However, a central problem of conventional coded sequences is that they cannot achieve good autocorrelation and orthogonality properties simultaneously due to their length being limited by the location of the closest reflectors. In this paper, a solution to this problem is presented by using coded sequences that have receive intervals. The proposed approach can be more than one order of magnitude faster than conventional methods. In addition, binary excitation and quantization can be employed, which reduces the data throughput by roughly an order of magnitude and allows for higher sampling rates. While this concept is generally applicable to any field, a 16-element system was built to experimentally demonstrate this principle for the first time using a conventional medical ultrasound probe.

In vivo carotid strain imaging using principal strains in longitudinal view

Carotid plaque rupture can result in stroke or transient ischemic attack that can be devastating for patients. Ultrasound strain imaging provides a noninvasive method to identify unstable plaque likely to rupture. Axial, lateral and shear strains in carotid plaque have been shown to be linked to carotid plaque instability. Recently, there has been interest in using principal strains, which do not depend on angle of insonification of the carotid artery for quantifying instability in plaque along the longitudinal view. In this work relationships between angle dependent axial, lateral and shear strain along with axis independent principal strains are compared. Three strain indices were defined, 1) Average Mean Strain (AMS), 2) Maximum Mean Strain (MMS) and 3) Mean Standard Deviation (MSD) to identify relationships between these five strain image types in a group of 76 in vivo patients. The maximum principal strain demonstrated the highest strain values when compared to axial strain for all patients with a linear regression slope of 1.6 and a y intercept of 2.4 percent strain for AMS. The maximum shear strain when compared to shear strain had a slope of 1.15 and a y intercept of 0.21 percent for AMS. Next, the effect of insonification angle, which is the angle subtended by the artery at the location of plaque was studied. Patients were divided into three sub groups, i.e. less than 5 degrees (n = 31), between 5 and 10 degrees (n = 24) and above 10 degrees (n = 21). The angle of insonification did not make a significant difference between the three angle groups when comparing the relationship between the angle dependent and independent strain values.

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.

Assessment of Mechanical Properties of Tissue in Breast Cancer-Related Lymphedema Using Ultrasound Elastography

Breast cancer-related lymphedema is a consequence of a malfunctioning lymphatic drainage system resulting from surgery or some other form of treatment. In the initial stages, minor and reversible increases in the fluid volume of the arm are evident. As the stages progress over time, the underlying pathophysiology dramatically changes with an irreversible increase in arm volume most likely due to a chronic local inflammation leading to adipose tissue hypertrophy and fibrosis. Clinicians have subjective ways to stage the degree and severity such as the pitting test which entails manually comparing the elasticity of the affected and unaffected arms. Several imaging modalities can be used but ultrasound appears to be the most preferred because it is affordable, safe, and portable. Unfortunately, ultrasonography is not typically used for staging lymphedema, because the appearance of the affected and unaffected arms is similar in B-mode ultrasound images. However, novel ultrasound techniques have emerged, such as elastography, which may be able to identify changes in mechanical properties of the tissue related to detection and staging of lymphedema. This paper presents a novel technique to compare the mechanical properties of the affected and unaffected arms using quasi-static ultrasound elastography to provide an objective alternative to the current subjective assessment. Elastography is based on time delay estimation (TDE) from ultrasound images to infer displacement and mechanical properties of the tissue. We further introduce a novel method for TDE by incorporating higher order derivatives of the ultrasound data into a cost function and propose a novel optimization approach to efficiently minimize the cost function. This method works reliably with our challenging patient data. We collected radio frequency ultrasound data from both arms of seven patients with stage 2 lymphedema, at six different locations in each arm. The ratio of strain in skin, subcutaneous fat, and skeletal muscle divided by strain in the standoff gel pad was calculated in the unaffected and affected arms. The p -values using a Wilcoxon sign-rank test for the skin, subcutaneous fat, and skeletal muscle were 1.24×10^-5 , 1.77×10^-8 , and 8.11×10^-7 respectively, showing differences between the unaffected and affected arms with a very high level of significance.

Pulse Wave Imaging in Carotid Artery Stenosis Human Patients in Vivo

Carotid stenosis involves narrowing of the lumen in the carotid artery potentially leading to a stroke, which is the third leading cause of death in the United States. Several recent investigations have found that plaque structure and composition may represent a more direct biomarker of plaque rupture risk compared with the degree of stenosis. In this study, pulse wave imaging was applied in 111 (n = 11, N = 13 plaques) patients diagnosed with moderate (>50%) to severe (>80%) carotid artery stenosis to investigate the feasibility of characterizing plaque properties based on the pulse wave-induced arterial wall dynamics captured by pulse wave imaging. Five (n = 5 patients, N = 20 measurements) healthy volunteers were also imaged as a control group. Both conventional and high-frame-rate plane wave radiofrequency imaging sequences were used to generate piecewise maps of the pulse wave velocity (PWV) at a single depth along stenotic carotid segments, as well as intra-plaque PWV mapping at multiple depths. Intra-plaque cumulative displacement and strain maps were also calculated for each plaque region. The Bramwell-Hill equation was used to estimate the compliance of the plaque regions based on the PWV and diameter. Qualitatively, wave convergence, elevated PWV and decreased cumulative displacement around and/or within regions of atherosclerotic plaque were observed and may serve as biomarkers for plaque characterization. Intra-plaque mapping revealed the potential to capture wave reflections between calcified inclusions and differentiate stable (i.e., calcified) from vulnerable (i.e., lipid) plaque components based on the intra-plaque PWV and cumulative strain. Quantitatively, one-way analysis of variance indicated that the pulse wave-induced cumulative strain was significantly lower (p < 0.01) in the moderately and severely calcified plaques compared with the normal controls. As expected, compliance was also significantly lower in the severely calcified plaques regions compared with the normal controls (p < 0.01). The results from this pilot study indicated the potential of pulse wave imaging coupled with strain imaging to differentiate plaques of varying stiffness, location and composition. Such findings may serve as valuable information to compensate for the limitations of currently used methods for the assessment of stroke risk.

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.

Investigation of out-of-plane motion artifacts in 2D noninvasive vascular ultrasound elastography

Ultrasound noninvasive vascular elastography (NIVE) has shown its potential to measure strains of carotid arteries to predict plaque instability. When two-dimensional (2D) strain estimation is performed, either in longitudinal or cross-sectional view, only in-plane motions are considered. The motions in elevation direction (i.e. perpendicular to the imaging plane), can induce estimation artifacts affecting the accuracy of 2D NIVE. The influence of such out-of-plane motions on the performance of axial strain and axial shear strain estimations has been evaluated in this study. For this purpose, we designed a diseased carotid bifurcation phantom with a 70% stenosis and an in vitro experimental setup to simulate orthogonal out-of-plane motions of 1 mm, 2 mm and 3 mm. The Lagrangian speckle model estimator (LSME) was used to estimate axial strains and shears under pulsatile conditions. As anticipated, in vitro results showed more strain estimation artifacts with increasing magnitudes of motions in elevation. However, even with an out-of-plane motion of 2.0 mm, strain and shear estimations having inter-frame correlation coefficients higher than 0.85 were obtained. To verify findings of in vitro experiments, a clinical LSME dataset obtained from 18 participants with carotid artery stenosis was used. Deduced out-of-plane motions (ranging from 0.25 mm to 1.04 mm) of the clinical dataset were classified into three groups: small, moderate and large elevational motions. Clinical results showed that pulsatile time-varying strains and shears remained reproducible for all motion categories since inter-frame correlation coefficients were higher than 0.70, and normalized cross-correlations (NCC) between radiofrequency (RF) images were above 0.93. In summary, the performance of LSME axial strain and shear estimations appeared robust in the presence of out-of-plane motions (<2 mm) as encountered during clinical ultrasound imaging.

Carotid Plaque Vulnerability Assessment Using Ultrasound Elastography and Echogenicity Analysis

OBJECTIVE

The purpose of this study was to evaluate ultrasound elastography and echogenicity analysis to discriminate between carotid plaques in patients with symptomatic internal carotid artery (ICA) stenosis versus patients with asymptomatic stenosis.

SUBJECTS AND METHODS

Patients with symptomatic and asymptomatic ICA stenosis of more than 50% were recruited for the study. After both carotid arteries were scanned, plaque translation and elastography and echogenicity features were assessed. Parameters of index stenosis (i.e., symptomatic or more severe stenosis) were compared between populations. For further validation, parameters of index stenosis were also compared with those of the contralateral artery for segments with plaque. Segments without plaque on the index side were also evaluated between populations. ROC curve analyses were performed using a cross-validation method with bootstrapping to calculate sensitivity and specificity.

RESULTS

Sixty-six patients with symptomatic (n = 26) or asymptomatic (n = 40) carotid stenoses were included. The maximum axial strain (p < 0.001), maximum axial shear strain magnitude (p = 0.03), and percentage of low-intensity of gray level (p = 0.01) of the index ICA were lower for patients with symptoms than for those without symptoms. In both groups, the contralateral ICA had translation and elastography and echogenicity parameters similar to those of the index ICA in patients with asymptomatic stenosis. The ROC curve for the detection of vulnerable plaques in patients with symptomatic stenosis was higher when ultrasound elastography and ultrasound echogenicity were used in combination than when each method was used alone (p < 0.001); a sensitivity of 71.6% and a specificity of 79.3% were obtained.

CONCLUSION

This pilot study establishes the usefulness of combining elastography with echogenicity analysis to discriminate plaques in patients with symptomatic ICA stenosis versus asymptomatic stenosis.

Visualizing Angle-Independent Principal Strains in the Longitudinal View of the Carotid Artery: Phantom and In Vivo Evaluation

Non-invasive vascular elastography can evaluate the stiffness of the carotid artery by visualizing the vascular strain distribution. Axial strain estimates of the longitudinal cross section of the carotid artery are sensitive to the angle between the artery and the transducer. Anatomical variations in branching and arching of the carotid artery can affect the assessment of arterial stiffness. In this study, we hypothesized that principal strain elastograms computed using compounded plane wave imaging can reliably visualize the strain distribution in the carotid artery, independent of the transducer angle. We corroborated this hypothesis by conducting phantom and in vivo studies using a commercial ultrasound scanner (Sonix RP, Ultrasonix Medical Corp., Richmond, BC, Canada). The phantom studies were conducted using a homogeneous cryogel vessel phantom. The goal of the phantom study was to assess the feasibility of visualizing the radial deformation in the longitudinal plane of the vessel phantom, independent of the transducer angle (±30°, ±20°, ±10° and 0°). The in vivo studies were conducted on 20 healthy human volunteers in the age group 50-60 y. All echo imaging was performed at a transmit frequency of 5 MHz and sampling frequency of 40 MHz. The elastograms obtained from the phantom study revealed that for straight vessels, which had their lumen parallel to the transducer, principal strains were similar to axial strains. At non-parallel configurations (angles ±30°, ±20° and ±10°), the magnitudes of the mean principal strains were within 2.5% of the parallel configuration (0° angle) estimates and, thus, were observed to be relatively unaffected by change in angle. However, in comparison, the magnitude of the axial strain decreased with increase in angle because of coordinate dependency. Further, the pilot in vivo study indicated that the principal and axial strain elastograms were similar for subjects with relatively straight arteries. However, for arteries with arched geometry, axial strains were significantly lower (p <0.01) than the corresponding principal vascular strains, which was consistent with the results obtained from the phantom study. In conclusion, the results of the phantom and in vivo studies revealed that principal strain elastograms computed using CPW imaging could reliably visualize angle-independent vascular strains in the longitudinal plane of the carotid artery.

Optimization of Transmit Parameters in Cardiac Strain Imaging With Full and Partial Aperture Coherent Compounding

Coherent compounding methods using the full or partial transmit aperture have been investigated as a possible means of increasing strain measurement accuracy in cardiac strain imaging; however, the optimal transmit parameters in either compounding approach have yet to be determined. The relationship between strain estimation accuracy and transmit parameters-specifically the subaperture, angular aperture, tilt angle, number of virtual sources, and frame rate-in partial aperture (subaperture compounding) and full aperture (steered compounding) fundamental mode cardiac imaging was thus investigated and compared. Field II simulation of a 3-D cylindrical annulus undergoing deformation and twist was developed to evaluate accuracy of 2-D strain estimation in cross-sectional views. The tradeoff between frame rate and number of virtual sources was then investigated via transthoracic imaging in the parasternal short-axis view of five healthy human subjects, using the strain filter to quantify estimation precision. Finally, the optimized subaperture compounding sequence (25-element subperture, 90° angular aperture, 10 virtual sources, 300-Hz frame rate) was compared to the optimized steered compounding sequence (60° angular aperture, 15° tilt, 10 virtual sources, 300-Hz frame rate) via transthoracic imaging of five healthy subjects. Both approaches were determined to estimate cumulative radial strain with statistically equivalent precision (subaperture compounding E(SNRe %) = 3.56, and steered compounding E(SNRe %) = 4.26).

Ultrafast imaging of cell elasticity with optical microelastography

In wave physics, and especially seismology, uncorrelated vibrations could be exploited using “noise correlation” tools to reconstruct images of a medium. By using a high-frequency vibration, a high-speed tracking device, and a reconstruction technique based on temporal correlations of travelling waves we conceptualized an optical microelastography technique to map elasticity of internal cellular structures. This technique, unlike other methods, can provide an elasticity image in less than a millisecond, thus opening the possibility of studying dynamic cellular processes and elucidating new mechanocellular properties. We call this proposed technique “cell quake elastography.”

Elasticity is a fundamental cellular property that is related to the anatomy, functionality, and pathological state of cells and tissues. However, current techniques based on cell deformation, atomic force microscopy, or Brillouin scattering are rather slow and do not always accurately represent cell elasticity. Here, we have developed an alternative technique by applying shear wave elastography to the micrometer scale. Elastic waves were mechanically induced in live mammalian oocytes using a vibrating micropipette. These audible frequency waves were observed optically at 200,000 frames per second and tracked with an optical flow algorithm. Whole-cell elasticity was then mapped using an elastography method inspired by the seismology field. Using this approach we show that the elasticity of mouse oocytes is decreased when the oocyte cytoskeleton is disrupted with cytochalasin B. The technique is fast (less than 1 ms for data acquisition), precise (spatial resolution of a few micrometers), able to map internal cell structures, and robust and thus represents a tractable option for interrogating biomechanical properties of diverse cell types.

Noninvasive Vascular Modulography Method for Imaging the Local Elasticity of Atherosclerotic Plaques: Simulation and In Vitro Vessel Phantom Study

Mechanical and morphological characterization of atherosclerotic lesions in carotid arteries remains an essential step for the evaluation of rupture prone plaques and the prevention of strokes. In this paper, we propose a noninvasive vascular imaging modulography (NIV-iMod) method, which is capable of reconstructing a heterogeneous Young's modulus distribution of a carotid plaque from the Von Mises strain elastogram. Elastograms were computed with noninvasive ultrasound images using the Lagrangian speckle model estimator and a dynamic segmentation-optimization procedure to highlight mechanical heterogeneities. This methodology, based on continuum mechanics, was validated in silico with finite-element model strain fields and ultrasound simulations, and in vitro with polyvinyl alcohol cryogel phantoms based on magnetic resonance imaging geometries of carotid plaques. In silico, our results show that the NiV-iMod method: 1) successfully detected and quantified necrotic core inclusions with high positive predictive value (PPV) and sensitivity value (SV) of 81±10% and 91±6%; 2) quantified Young's moduli of necrotic cores, fibrous tissues, and calcium inclusions with mean values of 32±23, 515±30, and 3160±218 kPa (ground true values are 10, 600, and 5000 kPa); and 3) overestimated the cap thickness by . In vitro, the PPV and SV for detecting soft inclusions were 60±21% and 88±9%, and Young's modulus mean values of mimicking lipid, fibrosis, and calcium were 34±19, 193±14, and 649±118 kPa (ground true values are 25±3, 182±21, and 757±87 kPa).

Revisiting the Cramér Rao Lower Bound for Elastography: Predicting the Performance of Axial, Lateral and Polar Strain Elastograms

We derived the Cramér Rao lower bound for 2-D estimators employed in quasi-static elastography. To illustrate the theory, we modeled the 2-D point spread function as a sinc-modulated sine pulse in the axial direction and as a sinc function in the lateral direction. We compared theoretical predictions of the variance incurred in displacements and strains when quasi-static elastography was performed under varying conditions (different scanning methods, different configuration of conventional linear array imaging and different-size kernels) with those measured from simulated or experimentally acquired data. We performed studies to illustrate the application of the derived expressions when performing vascular elastography with plane wave and compounded plane wave imaging. Standard deviations in lateral displacements were an order higher than those in axial. Additionally, the derived expressions predicted that peak performance should occur when 2% strain is applied, the same order of magnitude as observed in simulations (1%) and experiments (1%-2%). We assessed how different configurations of conventional linear array imaging (number of active reception and transmission elements) influenced the quality of axial and lateral strain elastograms. The theoretical expressions predicted that 2-D echo tracking should be performed with wide kernels, but the length of the kernels should be selected using knowledge of the magnitude of the applied strain: specifically, longer kernels for small strains (<5%) and shorter kernels for larger strains. Although the general trends of theoretical predictions and experimental observations were similar, biases incurred during beamforming and subsample displacement estimation produced noticeable differences.

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).

Cardiac Strain Imaging With Coherent Compounding of Diverging Waves

Current methods of cardiac strain imaging at high frame rate suffer from motion matching artifacts or poor lateral resolution. Coherent compounding has been shown to improve echocardiographic image quality while maintaining a high frame rate, but has never been used to image cardiac strain. However, myocardial velocity can have an impact on coherent compounding due to displacements between frames. The objective of this paper was to investigate the feasibility and performance of coherent compounding for cardiac strain imaging at a low and a high myocardial velocity. Left-ventricular contraction in short-axis view was modeled as an annulus with radial thickening and circumferential rotation. Simulated radio-frequency channel data with a cardiac phased array were obtained using three different beamforming methods: single diverging wave, coherent compounding of diverging waves, and conventional focusing. Axial and lateral displacements and strains as well as radial strains were estimated and compared to their true value. In vivo feasibility of cardiac strain imaging with coherent compounding was performed and compared to single diverging wave imaging. At low myocardial velocities, the axial, lateral, and radial strain relative error for nine compounded waves (16.3%, 40.4%, and 18.9%) were significantly lower than those obtained with single diverging wave imaging (19.9%, 80.3%, and 30.6%) and closer to that obtained with conventional focusing (16.7%, 43.7%, and 16%). In vivo left-ventricular radial strains exhibited higher quality with nine compounded waves than with single diverging wave imaging. These results indicate that cardiac strain can be imaged using coherent compounding of diverging waves with a better performance than with single diverging wave imaging while maintaining a high frame rate, and therefore, has the potential to improve diagnosis of myocardial strain-based cardiac diseases.

Noninvasive carotid artery elastography using multielement synthetic aperture imaging: Phantom and in vivo evaluation

PURPOSE

Vascular elastography can visualize the strain distribution in the carotid artery, which could be useful in assessing the propensity of advanced plaques to rupture. In our previous studies, we demonstrated that sparse synthetic aperture (SA) imaging can produce high quality vascular strain elastograms. However, the low output power of SA imaging may hamper its clinical utility. In this study, we hypothesize that multi-element defocused emissions can overcome this limitation and improve the quality of the vascular strain elastograms.

METHODS

To assess the impact of attenuation on the elastographic performance of SA and (multi-element synthetic aperture) MSA imaging, we conducted experiments using heterogeneous vessel phantoms with ideal (0.1 dB cm^-1 MHz^-1 ) and realistic (0.75 dB cm^-1 MHz^-1 ) attenuation. Further, we validated the results of the phantom study in vivo, on a healthy male volunteer. All echo imaging was performed at a transmit frequency of 5 MHz, using a commercially available ultrasound scanner (Sonix RP, Ultrasonix Medical Corp., Richmond, BC, Canada).

RESULTS

The results from the phantom results demonstrated that plaques were visible in all strain elastograms, but those produced using MSA imaging had less artifacts. MSA imaging improved the elastographic contrast to noise ratio (CNRe) of the vascular elastograms by 14.58 dB relative to SA imaging, and 9.1 dB relative to compounded plane wave (CPW) imaging. Further, the results demonstrated that the elastographic performance of MSA imaging improved with increase in (a) the number of transmit-receive events and (b) the size of the transmit sub-aperture, up to 13 elements. Using larger sub-apertures degraded the elastographic performance. The results from the in vivo study were in good agreement with the phantom results. Specifically, using a defocused multi-element transmit sub-aperture for SA imaging improved the performance of vascular elastography.

CONCLUSIONS

The results suggested that MSA imaging can produce reliable vascular stain elastograms. Future studies will involve using coded excitations to improve the CNRe and frame-rate of the proposed technique for vascular elastography.

Feasibility and relevance of compound strain imaging in non-stenotic arteries: comparison between individuals with cardiovascular diseases and healthy controls

BACKGROUND

Compound strain imaging is a novel method to noninvasively evaluate arterial wall deformation which has recently shown to enable differentiation between fibrous and (fibro-)atheromatous plaques in patients with severe stenosis. We tested the hypothesis that compound strain imaging is feasible in non-stenotic arteries and provides incremental discriminative power to traditional measures of vascular health (i.e., distensibility coefficient (DC), central pulse wave velocity [cPWV], and intima-media thickness [IMT]) for differentiating between participants with and without a history of cardiovascular diseases (CVD).

METHODS

Seventy two participants (60 ± 7 years) with non-stenotic arteries (IMT < 1.1 mm) were categorized in healthy participants (CON, n = 36) and CVD patients (n = 36) based on CVD history. Participants underwent standardised ultrasound-based assessment (DC, cPWV, and IMT) and compound strain imaging (radial [RS] and circumferential [CS] strain) in left common carotid artery. Area under receiver operating characteristics (AROC)-curve was used to determine the discriminatory power between CVD and CON of the various measures.

RESULTS

CON had a significantly (P < 0.05) smaller carotid IMT (0.68 [0.58 to 0.76] mm) than CVD patients (0.76 [0.68 to 0.80] mm). DC, cPWV, RS, and CS did not significantly differ between groups (P > 0.05). A higher CS or RS was associated with a higher DC (CS: r = -0.32;p < 0.05 and RS: r = 0.24;p < 0.05) and lower cPWV (CS: r = 0.24;p < 0.05 and RS: r = -0.25;p < 0.05). IMT could identify CVD (AROC: 0.66, 95%-CI: 0.53 to 0.79), whilst the other measurements, alone or in combination, did not significantly increase the discriminatory power compared to IMT.

CONCLUSIONS

In non-stenotic arteries, compound strain imaging is feasible, but does not seem to provide incremental discriminative power to traditional measures of vascular health for differentiation between individuals with and without a history of CVD.

Principal Strain Vascular Elastography: Simulation and Preliminary Clinical Evaluation

It is difficult to produce reliable polar strain elastograms (radial and circumferential) because the center of the carotid artery is typically unknown. Principal strain imaging can overcome this limitation, but suboptimal lateral displacement estimates make this an impractical approach for visualizing mechanical properties within the carotid artery. We hypothesized that compounded plane wave imaging can minimize this problem. To test this hypothesis, we performed (i) simulations with vessels of varying morphology and mechanical behavior (i.e., isotropic and transversely isotropic), and (ii) a pilot study with 10 healthy volunteers. The accuracy of principal and polar strain (computed using knowledge of the precise vessel center) elastograms varied between 7% and 17%. In both types of elastograms, strain concentrated at the junction between the fibrous cap and the vessel wall, and the strain magnitude decreased with increasing fibrous cap thickness. Elastograms of healthy volunteers were consistent with those of transversely isotropic homogeneous vessels; they were spatially asymmetric, a trend that was common to both principal and polar strains. No significant differences were observed in the mean strain recovered from principal and polar strains (p > 0.05). This investigation indicates that principal strain elastograms measured with compounding plane wave imaging overcome the problems incurred when polar strain elastograms are computed with imprecise estimates of the vessel center.

Performance optimization of lateral displacement estimation with spatial angular compounding

Elastography provides tissue mechanical information to differentiate normal and disease states. Nowadays, axial displacement and strain are usually estimated in clinical practice whereas lateral estimation is rarely used given that its accuracy is typically one order of magnitude worse than that of axial estimation. To improve the performance of lateral estimation, spatial angular compounding of multiple axial displacements along ultrasound beams transmitting in different steering angles was previously proposed. However, few studies have been conducted to evaluate the influence of key factors such as grating lobe noise (GLN), the number of steering angles (NSA) and maximum steering angle (MSA) in terms of performance optimization. The aim of this study was thus to investigate the effects of these factors through both computer simulations and phantom experiments. Only lateral rigid motion was considered in this study to separate its effects from those of axial and lateral strains on lateral displacement estimation. The performance as indicated by the root mean square error (RMSE) and standard deviation (SD) of the estimated lateral displacements validates the capability of spatial angular compounding in improving the performance of lateral estimation. It is necessary to filter the GLN for better estimation, and better performance is associated with a larger NSA and bigger MSA in both simulations and experiments, which is in agreement with the theoretical analysis. As indicated by the RMSE and SD, two steering angles with a larger steering angle are recommended. These results could provide insights into the performance optimization of lateral displacement estimation with spatial angular compounding.

Pulse wave imaging using coherent compounding in a phantom and in vivo

Pulse wave velocity (PWV) is a surrogate marker of arterial stiffness linked to cardiovascular morbidity. Pulse wave imaging (PWI) is a technique developed by our group for imaging the pulse wave propagation in vivo. PWI requires high temporal and spatial resolution, which conventional ultrasonic imaging is unable to simultaneously provide. Coherent compounding is known to address this tradeoff and provides full aperture images at high frame rates. This study aims to implement PWI using coherent compounding within a GPU-accelerated framework. The results of the implemented method were validated using a silicone phantom against static mechanical testing. Reproducibility of the measured PWVs was assessed in the right common carotid of six healthy subjects (n  =  6) approximately 10-15 mm before the bifurcation during two cardiac cycles over the course of 1-3 d. Good agreement of the measured PWVs (3.97  ±  1.21 m s^-1, 4.08  ±  1.15 m s^-1, p  =  0.74) was obtained. The effects of frame rate, transmission angle and number of compounded plane waves on PWI performance were investigated in the six healthy volunteers. Performance metrics such as the reproducibility of the PWVs, the coefficient of determination (r ²), the SNR of the PWI axial wall velocities ([Formula: see text]) and the percentage of lateral positions where the pulse wave appears to arrive at the same time-point, indicating inadequacy of the temporal resolution (i.e. temporal resolution misses) were used to evaluate the effect of each parameter. Compounding plane waves transmitted at 1° increments with a linear array yielded optimal performance, generating significantly higher r ² and [Formula: see text] values (p  ⩽  0.05). Higher frame rates (⩾1667 Hz) produced improvements with significant gains in the r ² coefficient (p  ⩽  0.05) and significant increase in both r ² and [Formula: see text] from single plane wave imaging to 3-plane wave compounding (p  ⩽  0.05). Optimal performance was established at 2778 Hz with 3 plane waves and at 1667 Hz with 5 plane waves.

Ultrasound Vector Flow Imaging-Part I: Sequential Systems

This paper gives a review of the most important methods for blood velocity vector flow imaging (VFI) for conventional sequential data acquisition. This includes multibeam methods, speckle tracking, transverse oscillation, color flow mapping derived VFI, directional beamforming, and variants of these. The review covers both 2-D and 3-D velocity estimation and gives a historical perspective on the development along with a summary of various vector flow visualization algorithms. The current state of the art is explained along with an overview of clinical studies conducted and methods for presenting and using VFI. A number of examples of VFI images are presented, and the current limitations and potential solutions are discussed.

High-Frame-Rate Echocardiography Using Coherent Compounding With Doppler-Based Motion-Compensation

High-frame-rate ultrasonography based on coherent compounding of unfocused beams can potentially transform the assessment of cardiac function. As it requires successive waves to be combined coherently, this approach is sensitive to high-velocity tissue motion. We investigated coherent compounding of tilted diverging waves, emitted from a 2.5 MHz clinical phased array transducer. To cope with high myocardial velocities, a triangle transmit sequence of diverging waves is proposed, combined with tissue Doppler imaging to perform motion compensation (MoCo). The compound sequence with integrated MoCo was adjusted from simulations and was tested in vitro and in vivo. Realistic myocardial velocities were analyzed in an in vitro spinning disk with anechoic cysts. While a 8 dB decrease (no motion versus high motion) was observed without MoCo, the contrast-to-noise ratio of the cysts was preserved with the MoCo approach. With this method, we could provide high-quality in vivo B-mode cardiac images with tissue Doppler at 250 frames per second. Although the septum and the anterior mitral leaflet were poorly apparent without MoCo, they became well perceptible and well contrasted with MoCo. The septal and lateral mitral annulus velocities determined by tissue Doppler were concordant with those measured by pulsed-wave Doppler with a clinical scanner (r(2)=0.7,y=0.9 x+0.5,N=60) . To conclude, high-contrast echo cardiographic B-mode and tissue Doppler images can be obtained with diverging beams when motion compensation is integrated in the coherent compounding process.

Ultrasound-Based Carotid Elastography for Detection of Vulnerable Atherosclerotic Plaques Validated by Magnetic Resonance Imaging

Ultrasound-based carotid elastography has been developed to estimate the mechanical properties of atherosclerotic plaques. The objective of this study was to evaluate the in vivo capability of carotid elastography in vulnerable plaque detection using high-resolution magnetic resonance imaging as reference. Ultrasound radiofrequency data of 46 carotid plaques from 29 patients (74 ± 5 y old) were acquired and inter-frame axial strain was estimated with an optical flow method. The maximum value of absolute strain rate for each plaque was derived as an indicator for plaque classification. Magnetic resonance imaging of carotid arteries was performed on the same patients to classify the plaques into stable and vulnerable groups for carotid elastography validation. The maximum value of absolute strain rate was found to be significantly higher in vulnerable plaques (2.15 ± 0.79 s(-1), n = 27) than in stable plaques (1.21 ± 0.37 s(-1), n = 19) (p < 0.0001). Receiver operating characteristic curve analysis was performed, and the area under the curve was 0.848. Therefore, the in vivo capability of carotid elastography to detect vulnerable plaques, validated by magnetic resonance imaging, was proven, revealing the potential of carotid elastography as an important tool in atherosclerosis assessment and stroke prevention.