Sub-sample displacement estimation from digitized ultrasound RF signals using multi-dimensional polynomial fitting of the cross-correlation function

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.

3-D Ultrafast Shear Wave Absolute Vibro-Elastography Using a Matrix Array Transducer

Real-time ultrasound imaging plays an important role in ultrasound-guided interventions. The 3-D imaging provides more spatial information compared to conventional 2-D frames by considering the volumes of data. One of the main bottlenecks of 3-D imaging is the long data acquisition time, which reduces practicality and can introduce artifacts from unwanted patient or sonographer motion. This article introduces the first shear wave absolute vibro-elastography (S-WAVE) method with real-time volumetric acquisition using a matrix array transducer. In S-WAVE, an external vibration source generates mechanical vibrations inside the tissue. The tissue motion is then estimated and used in solving a wave equation inverse problem to provide the tissue elasticity. A matrix array transducer is used with a Verasonics ultrasound machine and a frame rate of 2000 volumes/s to acquire 100 radio frequency (RF) volumes in 0.05 s. Using plane wave (PW) and compounded diverging wave (CDW) imaging methods, we estimate axial, lateral, and elevational displacements over 3-D volumes. The curl of the displacements is used with local frequency estimation to estimate elasticity in the acquired volumes. Ultrafast acquisition extends substantially the possible S-WAVE excitation frequency range, now up to 800 Hz, enabling new tissue modeling and characterization. The method was validated on three homogeneous liver fibrosis phantoms and on four different inclusions within a heterogeneous phantom. The homogeneous phantom results show less than 8% (PW) and 5% (CDW) difference between the manufacturer values and the corresponding estimated values over a frequency range of 80-800 Hz. The estimated elasticity values for the heterogeneous phantom at 400-Hz excitation frequency show the average errors of 9% (PW) and 6% (CDW) compared to the provided average values by magnetic resonance elastography (MRE). Furthermore, both imaging methods were able to detect the inclusions within the elasticity volumes. An ex vivo study on a bovine liver sample shows less than 11% (PW) and 9% (CDW) difference between the estimated elasticity ranges by the proposed method and the elasticity ranges provided by MRE and acoustic radiation force impulse (ARFI).

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.

Analytical estimation of beamforming speed-of-sound using transmission geometry

Most ultrasound imaging techniques necessitate the fundamental step of converting temporal signals received from transducer elements into a spatial echogenecity map. This beamforming (BF) step requires the knowledge of speed-of-sound (SoS) value in the imaged medium. An incorrect assumption of BF SoS leads to aberration artifacts, not only deteriorating the quality and resolution of conventional brightness mode (B-mode) images, hence limiting their clinical usability, but also impairing other ultrasound modalities such as elastography and spatial SoS reconstructions, which rely on faithfully beamformed images as their input. In this work, we propose an analytical method for estimating BF SoS. We show that pixel-wise relative shifts between frames beamformed with an assumed SoS is a function of geometric disparities of the transmission paths and the error in such SoS assumption. Using this relation, we devise an analytical model, the closed form solution of which yields the difference between the assumed and the true SoS in the medium. Based on this, we correct the BF SoS, which can also be applied iteratively. Both in simulations and experiments, lateral B-mode resolution is shown to be improved by ≈25% compared to that with an initial SoS assumption error of 3.3% (50m/s), while localization artifacts from beamforming are also corrected. After 5 iterations, our method achieves BF SoS errors of under 0.6m/s in simulations. Residual time-delay errors in beamforming 32 numerical phantoms are shown to reduce down to 0.07μs, with average improvements of up to 21 folds compared to initial inaccurate assumptions. We additionally show the utility of the proposed method in imaging local SoS maps, where using our correction method reduces reconstruction root-mean-square errors substantially, down to their lower-bound with actual BF SoS.

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.

Optimum Speckle Tracking Based on Ultrafast Ultrasound for Improving Blood Flow Velocimetry

Speckle tracking using optimum comparison frames (STO) is proposed to improve the blood flow velocity profile (BFVP) estimation based on ultrafast ultrasound with coherent plane-wave compounding. The optimum comparison frames are as far as possible from the reference frame image while possessing a speckle correlation above a given threshold. The correlation thresholds for different kernel sizes are determined via an experiment based on a vascular-mimicking phantom. In in vitro experiments with different peak velocities of the flow ranging from 0.38 to 1.18 m/s, the proposed STO method with three kernel sizes ( 0.46 × 0.46 , 0.31 × 0.69 , and 0.92 × 0.92 mm²) is used for the BFVP estimations. The normalized root mean square errors (NRMSEs) between the estimated and theoretical BFVPs are calculated and compared with the results based on the speckle tracking using adjacent-frame images. For the three kernel sizes, the mean relative decrements in the STO-based NRMSEs are 46.6%, 44.7%, and 52.9%, and the standard deviations are 36.8%, 37.6%, and 35.9%, respectively. The STO method is also validated by in vivo experiments using rabbit iliac arteries with contrast agents. With parabolic curves fitting to the mean velocity estimates, the average relative increments for the STO-based R² (coefficients of determination) are 7.22% and 6.25% for kernel sizes of 0.46 × 0.46 and 0.31 × 0.69 mm², respectively. In conclusion, the STO method improves the BFVP measurement accuracy, whereby accurate diagnosis information can be acquired for clinical applications.

Ultrasound-based speckle-tracking in tendons: a critical analysis for the technician and the clinician

Ultrasound has risen to the forefront as one of the primary tools in tendon research, with benefits including its relatively low cost, ease of use, and high safety. Moreover, it has been shown that cine ultrasound can be used to evaluate tendon deformation by tracking the motion of anatomical landmarks during physical movement. Estimates from landmark tracking, however, are typically limited to global tissue properties, such that clinically relevant regional nonuniformities may be missed. Fortunately, advancements in ultrasound scanning have led to the development of speckle-tracking algorithms, which enable the noninvasive measurement of in vivo local deformation patterns. Despite the successes in other fields, the adaptation of speckle-tracking to tendon research has presented some unique challenges as a result of tissue anisotropy and microstructural changes under load. With no generally accepted standards for its use, current methodological approaches vary substantially between studies and research groups. Therefore, the goal of this paper is to provide a summative review of the technical complexities and variations of speckle-tracking approaches being used and the impact these decisions may have on measured results and their interpretation. Variations in these approaches currently being used with relevant technical aspects are discussed first (for the technician), followed by a discussion of the more clinical considerations (for the clinician). Finally, a summary table of common challenges encountered when implementing speckle-tracking is provided, with suggested recommendations for minimizing the impact of such potential sources of error.

Ultrasound Imaging of Injections in Masseter Muscle without Contrast Agent Using Strain Elastography and a Novel B-Mode Spatiotemporal Filter

Botulinum toxin type A (BTX-A) injections in masseter muscle can alleviate muscle tightness and aching pain caused by idiopathic masticatory myalgia, a subform of the myofascial pain syndrome. Yet the injection procedure (number, amount) is currently empirical. In this ex vivo study, we determined the feasibility of using contrast-free ultrasound imaging to visualize the short-term injectate propagation. Ultrasound annotations of BTX-A injectate spread in N = 12 porcine masseter muscles were compared with the histopathology of the excised masseter. BTX-A presence was automatically detected in the ultrasound cine by: compensating tissue motion and deformation during injection with a novel spatiotemporal filtering (SF) algorithm, and by imaging tissue swelling strains with strain elastography (SE). BTX-A injectate introduced 6.5% (standard deviation = 5.0%) echogenicity contrast and 13.9% (standard deviation = 3.7%) tissue swelling strain. Muscle fasciae were a border for BTX-A distribution. The SF algorithm achieved significantly higher noise rejection (contrast-to-noise ratio = 4.63) than SE (2.56, p = 0.01), and state-of-the-art 2-D digital image correlation (1.81, p < 0.001) and direct image subtraction (1.29, p < 0.001) methods. Histopathology agreed well with ultrasound (Dice coefficient = 0.48), with deviations mainly explained by the three-dimensional inhomogeneous distribution of BTX-A. Preliminary in vivo patient results indicated that SF and SE discard artifactual BTX-A detection outside the injection region. The proposed methods contribute to objectivize ultrasound-guided injections, with additional applications, for instance, to monitor injectate spread of local anesthetics.

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

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

Long-Duration Tracking of Cervical-Spine Kinematics With Ultrasound

Cervical-spine (C-spine) pathoanatomy is commonly evaluated by plane radiographs, computed tomography (CT), or magnetic resonance imaging (MRI); however, these modalities are unable to directly measure the dynamic mechanical properties of the functional spinal units (FSU) comprising the C-spine that account for its functional performance. We have developed an ultrasound-based technique that provides a non-invasive, real-time, quantitative, in vivo assessment of C-spine kinematics and FSU viscoelastic properties. The fidelity of the derived measurements is predicated on accurate tracking of vertebral motion over a prolonged time duration. The purpose of this work was to present a bundle adjustment method that enables accurate tracking of the relative motion of contiguous cervical vertebrae from ultrasound radio-frequency data. The tracking method was validated using both a plastic anatomical model of a cervical vertebra undergoing prescribed displacements and also human cadaveric C-spine specimens subjected to physiologically relevant loading configurations. While the velocity of motion and thickness of the surrounding soft tissue envelope affected accuracy, using the bundle adjustment method, B-mode ultrasound was capable of accurately tracking vertebral motion under clinically relevant physiologic conditions. Therefore, B-mode ultrasound can be used to evaluate in vivo real-time C-spine kinematics and FSU mechanical properties in environments where radiographs, CT, or MRI cannot be used.

Accelerating 3-D GPU-based Motion Tracking for Ultrasound Strain Elastography Using Sum-Tables: Analysis and Initial Results

Now, with the availability of 3-D ultrasound data, a lot of research efforts are being devoted to developing 3-D ultrasound strain elastography (USE) systems. Because 3-D motion tracking, a core component in any 3-D USE system, is computationally intensive, a lot of efforts are under way to accelerate 3-D motion tracking. In the literature, the concept of Sum-Table has been used in a serial computing environment to reduce the burden of computing signal correlation, which is the single most computationally intensive component in 3-D motion tracking. In this study, parallel programming using graphics processing units (GPU) is used in conjunction with the concept of Sum-Table to improve the computational efficiency of 3-D motion tracking. To our knowledge, sum-tables have not been used in a GPU environment for 3-D motion tracking. Our main objective here is to investigate the feasibility of using sum-table-based normalized correlation coefficient (ST-NCC) method for the above-mentioned GPU-accelerated 3-D USE. More specifically, two different implementations of ST-NCC methods proposed by Lewis et al. and Luo-Konofagou are compared against each other. During the performance comparison, the conventional method for calculating the normalized correlation coefficient (NCC) was used as the baseline. All three methods were implemented using compute unified device architecture (CUDA; Version 9.0, Nvidia Inc., CA, USA) and tested on a professional GeForce GTX TITAN X card (Nvidia Inc., CA, USA). Using 3-D ultrasound data acquired during a tissue-mimicking phantom experiment, both displacement tracking accuracy and computational efficiency were evaluated for the above-mentioned three different methods. Based on data investigated, we found that under the GPU platform, Lou-Konofaguo method can still improve the computational efficiency (17–46%), as compared to the classic NCC method implemented into the same GPU platform. However, the Lewis method does not improve the computational efficiency in some configuration or improves the computational efficiency at a lower rate (7–23%) under the GPU parallel computing environment. Comparable displacement tracking accuracy was obtained by both methods.

Biplanar ultrasound investigation of in vivo Achilles tendon displacement non-uniformity

The Achilles tendon is a common tendon for the medial and lateral gastrocnemius and soleus muscles. Non-uniform Achilles tendon regional displacements have been observed in vivo which may result from non-uniform muscle loading and intra-tendinous shearing. However, prior observations are limited to the sagittal plane. This study investigated Achilles tendon tissue displacement patterns during isometric plantarflexor contractions in the coronal and sagittal planes. Fourteen subjects (5 female, 9 male, 26±3 yr) performed maximal isometric plantarflexor contractions with the knee in full extension and flexed to 110°. An ultrasound transducer positioned over the free Achilles tendon collected beam formed radio frequency (RF) data at 70 frames/s. Localized tissue displacements were analyzed using a speckle tracking algorithm. We observed non-uniform Achilles tendon tissue displacements in both imaging planes. Knee joint posture had no significant effect on tissue displacement patterns in either imaging plane. The non-uniform Achilles tendon tissue displacements during loading may arise from the anatomical organization of the sub-tendons associated with the three heads of the triceps surae. The biplanar investigation suggests that greatest displacements are localized to tissue likely to belong to soleus sub-tendon. This study adds novel information with possible implications for muscle coordination, function and muscle-tendon injury mechanisms.

Comparison of Displacement Tracking Algorithms for in Vivo Electrode Displacement Elastography

Hepatocellular carcinoma and liver metastases are common hepatic malignancies presenting with high mortality rates. Minimally invasive microwave ablation (MWA) yields high success rates similar to surgical resection. However, MWA procedures require accurate image guidance during the procedure and for post-procedure assessments. Ultrasound electrode displacement elastography (EDE) has demonstrated utility for non-ionizing imaging of regions of thermal necrosis created with MWA in the ablation suite. Three strategies for displacement vector tracking and strain tensor estimation, namely coupled subsample displacement estimation (CSDE), a multilevel 2-D normalized cross-correlation method, and quality-guided displacement tracking (QGDT) have previously shown accurate estimations for EDE. This paper reports on a qualitative and quantitative comparison of these three algorithms over 79 patients after an MWA procedure. Qualitatively, CSDE presents sharply delineated, clean ablated regions with low noise except for the distal boundary of the ablated region. Multilevel and QGDT contain more visible noise artifacts, but delineation is seen over the entire ablated region. Quantitative comparison indicates CSDE with more consistent mean and standard deviations of region of interest within the mass of strain tensor magnitudes and higher contrast, while Multilevel and QGDT provide higher CNR. This fact along with highest success rates of 89% and 79% on axial and lateral strain tensor images for visualization of thermal necrosis using the Multilevel approach leads to it being the best choice in a clinical setting. All methods, however, provide consistent and reproducible delineation for EDE in the ablation suite.

Spatial domain reconstruction for imaging speed-of-sound with pulse-echo ultrasound: simulation and in vivo study

Despite many uses of ultrasound, some pathologies such as breast cancer still cannot reliably be diagnosed in either conventional B-mode ultrasound imaging nor with more recent ultrasound elastography methods. Speed-of-sound (SoS) is a quantitative imaging biomarker, which is sensitive to structural changes due to pathology, and hence could facilitate diagnosis. Full-angle ultrasound computed tomography (USCT) was proposed to obtain spatially-resolved SoS images, however, its water-bath setup involves practical limitations. To increase clinical utility and for widespread use, recently, a limited-angle Fourier-domain SoS reconstruction was proposed, however, it suffers from significant image reconstruction artifacts. In this work, we present a SoS reconstruction strategy, where the forward problem is formulated using differential time-of-flight measurements based on apparent displacements along different ultrasound wave propagation paths, and the inverse problem is solved in spatial-domain using a proposed total-variation scheme with spatially-varying anisotropic weighting to compensate for geometric bias from limited angle imaging setup. This is shown to be robust to missing displacement data and easily allow for incorporating any prior geometric information. In numerical simulations, SoS values in inclusions are accurately reconstructed with 90% accuracy up to a noise level of 50%. With respect to Fourier-domain reconstruction, our proposed method improved contrast ratio from 0.37 to 0.67 for even high noise levels such as 50%. Numerical full-wave simulation and our preliminary in vivo results illustrate the clinical applicability of our method in a breast cancer imaging setting. Our proposed method requires single-sided access to the tissue and can be implemented as an add-on to conventional ultrasound equipment, applicable to a range of transducers and applications.

3-D Single Breath-Hold Shear Strain Estimation for Improved Breast Lesion Detection and Classification in Automated Volumetric Ultrasound Scanners

Automated breast volume scanner (ABVS) is an ultrasound imaging modality used in breast cancer screening. It has high sensitivity but limited specificity as it is hard to discriminate between benign and malignant lesions by echogenic properties. Specificity might be improved by shear strain imaging as malignant lesions, firmly bonded to its host tissue, show different shear patterns compared to benign lesions, often loosely bonded. Therefore, 3-D quasi-static elastography was implemented in an ABVS-like system. Plane wave instead of conventional focused transmissions were used to reduce scan times within a single breath hold. A 3-D strain tensor was obtained and shear strains were reconstructed in phantoms containing firmly and loosely bonded lesions. Experiments were also simulated in finite-element models (FEMs). Experimental results, confirmed by FEM-results, indicated that loosely bonded lesions showed increased maximal shear strains (~2.5%) and different shear patterns compared to firmly bonded lesions (~0.9%). To conclude, we successfully implemented 3-D elastography in an ABVS-like system to assess lesion bonding by shear strain imaging.

Investigation of the interpolation method to improve the distributed strain measurement accuracy in optical frequency domain reflectometry systems

We use a spectrum interpolation technique to improve the distributed strain measurement accuracy in a Rayleigh-scatter-based optical frequency domain reflectometry sensing system. We demonstrate that strain accuracy is not limited by the "uncertainty principle" that exists in the time-frequency analysis. Different interpolation methods are investigated and used to improve the accuracy of peak position of the cross-correlation and, therefore, improve the accuracy of the strain. Interpolation implemented by padding zeros on one side of the windowed data in the spatial domain, before the inverse fast Fourier transform, is found to have the best accuracy. Using this method, the strain accuracy and resolution are both improved without decreasing the spatial resolution. The strain of 3 μϵ within the spatial resolution of 1 cm at the position of 21.4 m is distinguished, and the measurement uncertainty is 3.3 μϵ.

Nonuniform Deformation of the Patellar Tendon During Passive Knee Flexion

The purpose of this study was to evaluate localized patterns of patellar tendon deformation during passive knee flexion. Ultrasound radiofrequency data were collected from the patellar tendons of 20 healthy young adults during knee flexion over a range of motion of 50°-90° of flexion. A speckle tracking approach was used to compute proximal and distal tendon displacements and elongations. Nonuniform tissue displacements were visible in the proximal tendon (P < .001), with the deep tendon undergoing more distal displacement than the superficial tendon. In the distal tendon, more uniform tendon motion was observed. Spatial variations in percent elongation were also observed, but these varied along the length of the tendon (P < .002), with the proximal tendon remaining fairly isometric while the distal tendon underwent slight elongation. These results suggest that even during passive flexion the tendon undergoes complex patterns of deformation. Proximal tendon nonuniformity may arise from its complex anatomy where the deep tendon inserts onto the patella and the superficial tendon extends to the quadriceps tendon. Such heterogeneity is not captured in whole tendon average assessments, emphasizing the relevance of considering localized tendon mechanics, which may be key to understanding tendon behavior and precursors to injury and disease.

Low-Cost 3-D Flow Estimation of Blood With Clutter

Volumetric flow rate estimation is an important ultrasound medical imaging modality that is used for diagnosing cardiovascular diseases. Flow rates are obtained by integrating velocity estimates over a cross-sectional plane. Speckle tracking is a promising approach that overcomes the angle dependency of traditional Doppler methods, but suffers from poor lateral resolution. Recent work improves lateral velocity estimation accuracy by reconstructing a synthetic lateral phase (SLP) signal. However, the estimation accuracy of such approaches is compromised by the presence of clutter. Eigen-based clutter filtering has been shown to be effective in removing the clutter signal; but it is computationally expensive, precluding its use at high volume rates. In this paper, we propose low-complexity schemes for both velocity estimation and clutter filtering. We use a two-tiered motion estimation scheme to combine the low complexity sum-of-absolute-difference and SLP methods to achieve subpixel lateral accuracy. We reduce the complexity of eigen-based clutter filtering by processing in subgroups and replacing singular value decomposition with less compute-intensive power iteration and subspace iteration methods. Finally, to improve flow rate estimation accuracy, we use kernel power weighting when integrating the velocity estimates. We evaluate our method for fast- and slow-moving clutter for beam-to-flow angles of 90° and 60° using Field II simulations, demonstrating high estimation accuracy across scenarios. For instance, for a beam-to-flow angle of 90° and fast-moving clutter, our estimation method provides a bias of -8.8% and standard deviation of 3.1% relative to the actual flow rate.

A GPU-Accelerated 3-D Coupled Subsample Estimation Algorithm for Volumetric Breast Strain Elastography

Our primary objective of this paper was to extend a previously published 2-D coupled subsample tracking algorithm for 3-D speckle tracking in the framework of ultrasound breast strain elastography. In order to overcome heavy computational cost, we investigated the use of a graphic processing unit (GPU) to accelerate the 3-D coupled subsample speckle tracking method. The performance of the proposed GPU implementation was tested using a tissue-mimicking phantom and in vivo breast ultrasound data. The performance of this 3-D subsample tracking algorithm was compared with the conventional 3-D quadratic subsample estimation algorithm. On the basis of these evaluations, we concluded that the GPU implementation of this 3-D subsample estimation algorithm can provide high-quality strain data (i.e., high correlation between the predeformation and the motion-compensated postdeformation radio frequency echo data and high contrast-to-noise ratio strain images), as compared with the conventional 3-D quadratic subsample algorithm. Using the GPU implementation of the 3-D speckle tracking algorithm, volumetric strain data can be achieved relatively fast (approximately 20 s per volume [2.5 cm ×2.5 cm ×2.5 cm]).

A coupled subsample displacement estimation method for ultrasound-based strain elastography

Obtaining accurate displacement estimates along both axial (parallel to the acoustic beam) and lateral (perpendicular to the beam) directions is an important task for several clinical applications such as shear strain imaging, modulus reconstruction and temperature imaging, where a full description of the two or three-dimensional (2D/3D) deformation field is required. In this study we propose an improved speckle tracking algorithm where axial and lateral motion estimations are simultaneously performed to enhance motion tracking accuracy. More specifically, using conventional ultrasound echo data, this algorithm first finds an iso-contour in the vicinity of the peak correlation between two segments of the pre- and post-deformation ultrasound radiofrequency echo data. The algorithm then attempts to find the center of the iso-contour of the correlation function that corresponds to the unknown (sub-sample) motion vector between these two segments of echo data. This algorithm has been tested using computer-simulated data, studies with a tissue-mimicking phantom, and in vivo breast lesion data. Computer simulation results show that the method improves the accuracy of both lateral and axial tracking. Such improvements are more significant when the deformation is small or along the lateral direction. Results from the tissue-mimicking phantom study are consistent with findings observed in computer simulations. Using in vivo breast lesion data we found that, compared to the 2D quadratic subsample displacement estimation methods, higher quality axial strain and shear strain images (e.g. 18.6% improvement in contrast-to-noise ratio for shear strain images) can be obtained for large deformations (up to 5% frame-to-frame and 15% local strains) in a multi-compression technique. Our initial results demonstrated that this conceptually and computationally simple method could improve the image quality of ultrasound-based strain elastography with current clinical equipment.

Multiparametric 3D in vivo ultrasound vibroelastography imaging of prostate cancer: Preliminary results

PURPOSE

Ultrasound-based solutions for diagnosis and prognosis of prostate cancer are highly desirable. The authors have devised a method for detecting prostate cancer using a vibroelastography (VE) system developed in our group and a tissue classification approach based on texture analysis of VE images.

METHODS

The VE method applies wide-band mechanical vibrations to the tissue. Here, the authors report on the use of this system for cancer detection and show that the texture of VE images characterized by the first and the second order statistics of the pixel intensities form a promising set of features for tissue typing to detect prostate cancer. The system was used to image patients prior to radical surgery. The removed specimens were sectioned and studied by an experienced histopathologist. The authors registered the whole-mount histology sections to the ultrasound images using an automatic registration algorithm. This enabled the quantitative evaluation of the performance of the authors' imaging method in cancer detection in an unbiased manner. The authors used support vector machine (SVM) classification to measure the cancer detection performance of the VE method. Regions of tissue of size 5 × 5 mm, labeled as cancer and noncancer based on automatic registration to histology slides, were classified using SVM.

RESULTS

The authors report an area under ROC of 0.81 ± 0.10 in cancer detection on 1066 tissue regions from 203 images. All cancer tumors in all zones were included in this analysis and were classified versus the noncancer tissue in the peripheral zone. This outcome was obtained in leave-one-patient-out validation.

CONCLUSIONS

The developed 3D prostate vibroelastography system and the proposed multiparametric approach based on statistical texture parameters from the VE images result in a promising cancer detection method.

The use of 2D ultrasound elastography for measuring tendon motion and strain

The goal of the current study was to investigate the fidelity of a 2D ultrasound elastography method for the measurement of tendon motion and strain. Ultrasound phantoms and ex vivo porcine flexor tendons were cyclically stretched to 4% strain while cine ultrasound radiofrequency (RF) data and video data were simultaneously collected. 2D ultrasound elastography was used to estimate tissue motion and strain from RF data, and surface tissue motion and strain were separately estimated using digital image correlation (DIC). There were strong correlations (R(2)>0.97) between DIC and RF measurements of phantom displacement and strain, and good agreement in estimates of peak phantom strain (DIC: 3.5±0.2%; RF: 3.7±0.1%). For tendon, elastographic estimates of displacement profiles also correlated well with DIC measurements (R(2)>0.92), and exhibited similar estimated peak tendon strain (DIC: 2.6±1.4%; RF: 2.2±1.3%). Elastographic tracking with B-Mode images tended to under-predict peak strain for both the phantom and tendon. This study demonstrates the capacity to use quantitative elastographic techniques to measure tendon displacement and strain within an ultrasound image window. The approach may be extendible to in vivo use on humans, which would allow for the non-invasive analysis of tendon deformation in both normal and pathological states.

Normal and shear strain imaging using 2D deformation tracking on beam steered linear array datasets

PURPOSE

Previous publications have reported on the use of one-dimensional cross-correlation analysis with beam-steered echo signals. However, this approach fails to accurately track displacements at larger depths (>4.5 cm) due to lower signal-to-noise. In this paper, the authors present the use of adaptive parallelogram shaped two-dimensional processing blocks for deformation tracking.

METHODS

Beam-steered datasets were acquired using a VFX 9L4 linear array transducer operated at a 6 MHz center frequency for steered angles from -15 to 15° in increments of 1°, on both uniformly elastic and single-inclusion tissue-mimicking phantoms. Echo signals were acquired to a depth of 65 mm with the focus set at 40 mm corresponding to the center of phantom. Estimated angular displacements along and perpendicular to the beam direction are used to compute axial and lateral displacement vectors using a least-squares approach. Normal and shear strain tensor component are then estimated based on these displacement vectors.

RESULTS

Their results demonstrate that parallelogram shaped two-dimensional deformation tracking significantly improves spatial resolution (factor of 7.79 along the beam direction), signal-to-noise (5 dB improvement), and contrast-to-noise (8-14 dB improvement) associated with strain imaging using beam steering on linear array transducers.

CONCLUSIONS

Parallelogram shaped two-dimensional deformation tracking is demonstrated in beam-steered radiofrequency data, enabling its use in the estimation of normal and shear strain components.

Tendon motion and strain patterns evaluated with two-dimensional ultrasound elastography

The purpose of this study was to evaluate the use of 2D ultrasound elastography to assess tendon tissue motion and strain under axial loading conditions. Four porcine flexor tendons were cyclically loaded to 4% peak strain using a servo hydraulic test system. An ultrasound transducer was positioned to image a longitudinal cross-section of the tendon during loading. Ultrasound radiofrequency (RF) data were collected at 63 frames per second simultaneously with applied force and crosshead displacement. A grid of nodes was manually positioned on an ultrasound image of the unloaded tendon. Small kernels (2×1 mm) centered at each node were then cross-correlated with search regions centered at corresponding nodal locations in the subsequent frame. Frame-to-frame nodal displacements were defined as the values that maximized the normalized cross-correlations. This process was repeated across all frames in the loading cycle, providing a measurement of the 2D trajectories of tissue motion throughout the loading cycle. The high resolution displacement measures along the RF beam direction were spatially differentiated to estimate the transverse (relative to tendon fibers) tissue strains. The nodal displacements obtained using this method were very repeatable, with average along-fiber trajectories that were highly correlated (average r=0.99) with the prescribed crosshead displacements. The elastography transverse strains were also repeatable and were consistent with average transverse strains estimated via changes in tendon width. The apparent Poisson's ratios (0.82-1.64) exceeded the incompressibility limit, but are comparable to values found for tendon in prior experimental and computational studies. The results demonstrate that 2D ultrasound elastography is a promising approach for noninvasively assessing localized tissue motion and strain patterns.

Comparison between 2-D cross correlation with 2-D sub-sampling and 2-D tracking using beam steering

We have previously presented multi-dimensional sub-sample motion estimation techniques that use multi-dimensional polynomial fitting to the discrete cross-correlation function to jointly estimate the sub-sample motion in all three spatial directions. Previous simulation and experimental results showed that these estimators significantly improve the performance of the motion estimation in 2-D and 3-D. In this short communication, we present additional simulation results and compare these techniques to 2-D tracking using beam steering. The results show that beam steering technique performs better in estimating the motion vector especially the lateral component.