Ultrafast Plane Wave Imaging Research Articles

TOBE-Costas arrays for fast high-resolution 3D power Doppler imaging.

2D sparse arrays and row-column arrays are both alternatives to 2D fully-addressed arrays with lower channel counts. Row-column arrays have recently demonstrated fast 3D structural and flow imaging but commonly suffer from high grating lobes or require multiplexing to achieve better quality. 2D sparse arrays enable full-volume acquisitions for each to transmit event, but plane-wave transmissions with them usually lack quality in terms of uniformity of wavefronts. Here, we propose a novel architecture that combines both types of these arrays in one aperture, enabling imaging using row-column or sparse arrays alone or a hybrid imaging scheme where the row-column array is used in transmission and a 2D sparse array in reception. This hybrid imaging scheme can potentially solve the shortcomings of each of these approaches. The sparse array layout chosen is a Costas array, characterized by having only one element per row and column, facilitating its integration with row-column (TOBE) arrays. We simulate images acquired with TOBE-Costas arrays using the hybrid imaging scheme and compare them to row-column and sparse spiral arrays of equivalent aperture size (128λ×128λ at 7.5 MHz) in ultrafast plane-wave imaging of point targets and 3D power Doppler imaging of synthetic flow phantoms. Our simulation results show that TOBE-Costas arrays exhibit superior resolution and lower side lobe levels compared to plane-wave compounding with row-column arrays. Compared to density-tapered spiral arrays, they provide a larger field of view and finer resolution.

A Low-Complexity Compressive Sensing Algorithm for Point Target Detection Using Ultrafast Plane Wave Imaging

A Low-Complexity Compressive Sensing Algorithm for Point Target Detection Using Ultrafast Plane Wave Imaging

Ultrafast plane wave imaging of breast lesions

Ultrafast plane wave imaging has great potential for 3-D functional ultrasound imaging but also comes with decreased lateral resolution, contrast, and penetration depth with respect to conventional imaging (CI). By utilizing coherent plane-wave compound imaging (CPWCI) and different beam forming techniques (Delay and Sum (DAS), Stolt’s-fk, and Lu’s-fk), we have demonstrated to improve resolution, penetration, and contrast-to-noise ratio. In this work we evaluate this technique in patients. A Siemens Sequoia system equipped with an 18L6HD, 14L5, and 10L4 was used to acquire CI and CPWCI data in 77 patients suspected of breast cancer visiting our clinic. CI data was acquired at three angles (-11, 0, and 11 degrees) and beamformed in the Sequoia and incoherently compounded while CPWCI data was acquired for 33 angles (-16:1:16 degrees) and subsequently processed off-line. In total, 9 malignant lesions, 35 benign lesions, and 32 normal other structures were found. For all three transducers, improved penetration was observed with CPWCI compared to CI. Additionally, contrast to noise ratio was also improved by CPWCI, especially at larger imaging depths. Qualitatively, an improved resolution appeared to be present, probably also caused by the improved contrast. Currently, a reader study in which radiologists have to score CI and CPWCI images sight by side while blinded to the acquisition mode is being prepared to test the efficacy of CPWCI in clinical practice. In conclusion, CPWCI bears great promise for improved breast cancer detection.

Ultrafast Plane Wave Imaging Using Tensor Completion-Based Minimum Variance Algorithm.

Coherent plane wave compounding (CPWC) imaging is an efficient technique in high-frame-rate ultrasound imaging. To improve the image quality obtained from the CPWC, the adaptive minimum variance (MV) algorithm can be used. However, the high computational complexity of this algorithm negatively affects the frame rate. In other words, achieving a high frame rate and high-quality features simultaneously remains a challenge in medical ultrasound imaging. The aim of the work described here was to develop an algorithm to tackle this challenge and improve the frame rate while preserving the good quality of the resulting image. A tensor completion (TC)-based MV algorithm is proposed to simultaneously improve the frame rate and image quality in CPWC. In the proposed method, the MV algorithm is applied to a limited number of pixels in the beamforming grid. Then, the appropriate values are assigned to the remaining unprocessed pixels by using the TC algorithm. The proposed algorithm speeds up the beamforming process, and consequently, improves the frame rate. The computational complexity of the proposed TC-based MV algorithm is reduced compared with that of the conventional MV algorithm while the good quality of this algorithm is preserved. The results indicate that, in particular, by processing 40% of the beamforming grid using the MV beamformer followed by the TC algorithm, a reconstructed image comparable to that in the case in which the MV algorithm is performed on the full beamforming grid is obtained; the difference between the contrast-to-noise ratio evaluation metric between these two cases is about 0.16 dB for the experimental-resolution phantom. Also, the resulting images obtained from the MV algorithm and the TC-based MV method have the same resolution, indicating that the TC-based MV algorithm can successfully achieve the quality of the MV algorithm with a lower computational complexity. The TC-based MV algorithm is proposed in CPWC with the goal of improving frame rate and image quality. Qualitative and quantitative results reveal that by use of the proposed algorithm, the quality of the reconstructed image will be comparable to that of the conventional MV algorithm, and the frame rate will be improved.

High-Level Synthesis Design of Scalable Ultrafast Ultrasound Beamformer With Single FPGA.

Ultrafast ultrasound imaging is essential for advanced ultrasound imaging techniques such as ultrasound localization microscopy (ULM) and functional ultrasound (fUS). Current ultrafast ultrasound imaging is challenged by the ultrahigh data bandwidth associated with the radio frequency (RF) signal, and by the latency of the computationally expensive beamforming process. As such, continuous ultrafast data acquisition and beamforming remain elusive with existing software beamformers based on CPUs or GPUs. To address these challenges, the proposed work introduces a novel method of implementing an ultrafast ultrasound beamformer specifically for ultrafast plane wave imaging (PWI) on a field programmable gate array (FPGA) by using high-level synthesis. A parallelized implementation of the beamformer on a single FPGA was proposed by 1) utilizing a delay compression technique to reduce the delay profile size, which enables both run-time pre-calculated delay profile loading from external memory and delay reuse, 2) vectorizing channel data fetching which is enabled by delay reuse, and 3) using fixed summing networks to reduce consumption of logic resources. Our proposed method presents two unique advantages over current FPGA beamformers: 1) high scalability that allows fast adaptation to different FPGA resources and beamforming speed demands by using Xilinx High-Level Synthesis as the development tool, and 2) allow a compact form factor design by using a single FPGA to complete the beamforming instead of multiple FPGAs. Current Xilinx FPGAs provide the capabilities of connecting up to 1024 ultrasound channels with a single FPGA and the newest JESD204B interface analog front end (AFE). This channel count is much more than the channel count needed by current linear arrays, which normally have 128 or 256 channels. With the proposed method, a sustainable average beamforming rate of 4.83 G samples/second in terms of input raw RF sample was achieved. The resulting image quality of the proposed beamformer was compared with the software beamformer on the Verasonics Vantage system for both phantom imaging and in vivo imaging of a mouse brain. Multiple imaging schemes including B-mode, power Doppler and ULM were assessed to verify that the image quality was not compromised for speed.

Contrast analysis in ultrafast ultrasound blood flow imaging of jugular vein

PurposeThe contrasts of flowing blood in in vitro experiments using porcine blood and in vivo measurements of human jugular veins were analyzed to demonstrate that the hemorheological property was dependent on the shear rate.MethodsBlood samples (45% hematocrit) suspended in saline or plasma were compared with examine the difference in viscoelasticity. Ultrafast plane-wave imaging at an ultrasonic center frequency of 7.5 MHz was performed on different steady flows in a graphite-agar phantom. Also, in vivo measurement was performed in young, healthy subjects and patients with diabetes. A spatiotemporal matrix of beamformed radio-frequency data was used for the singular value decomposition (SVD) clutter filter. The clutter-filtered B-mode image was calculated as the amplitude envelope normalized at the first frame in the diastolic phase to evaluate contrast. The shear rate was estimated as the velocity gradient perpendicular to the lateral axis.ResultsAlthough nonaggregated erythrocytes at a high shear rate exhibited a low echogenicity, the echogenicity in the plasma sample overall increased due to erythrocyte aggregation at a low shear rate. In addition, the frequency of detection of specular components, defined as components beyond twice the standard deviation of a contrast map obtained from a clutter-filtered B-mode image, increased in the porcine blood at a high shear rate and the venous blood in healthy subjects versus patients with diabetes.ConclusionThe possibility of characterizing hemorheological properties dependent on the shear rate and diabetes condition was indicated using ultrafast plane-wave imaging with an SVD-based clutter filter.

In Vivo Comparison of Pulse Wave Velocity Estimation Based on Ultrafast Plane Wave Imaging and High-Frame-Rate Focused Transmissions.

Ultrasound-based local pulse wave velocity (PWV) estimation, as a measure of arterial stiffness, can be based on fast focused imaging (FFI) or plane wave imaging (PWI). This study was aimed at comparing the accuracy of in vivo PWV estimation using FFI and PWI. Ultrasound radiofrequency data of carotid arteries were acquired in 14 healthy volunteers (25-57 y) by executing the FFI (12 lines, 7200 Hz) and PWI (128 lines, 2000 Hz) methods consecutively. PWV was derived at two time-reference points, dicrotic notch (DN) and systolic foot (SF), for multiple pressure cycles by fitting a linear function through the positions of the peaks of low-pass filtered wall acceleration curves as a function of time. The accuracy of PWV estimation was determined for various cutoff frequencies (10-200 Hz). No statistically significant difference was observed between PWVs estimated by both approaches. The PWV and R2 at DN were higher, on average, than those at SF (PWV/R2: FFI SF 5.5/0.92, FFI DN 6.1/0.92; PWI SF 5.4/0.89, PWI DN 6.3/0.95). The use of cutoff frequencies between 40 and 80Hz provided the most accurate PWVs. Both methods seemed equally suitable for use in clinical practice, although we have a preference for the PWV at DN given the higher R2 values.

Super-Resolution Ultrasound Localization Microscopy for Visualization of the Ocular Blood Flow.

The ocular vascular system plays an important role in preserving the visual function. Alterations in either anatomy or hemodynamics of the eye may have adverse effects on vision. Thus, an imaging approach that can monitor alterations of ocular blood flow of the deep eye vasculature ranging from capillary-level vessels to large supporting vessels would be advantageous for detection of early stage retinal and optic nerve diseases. We propose a super-resolution ultrasound localization microscopy (ULM) technique that can assess both the microvessel and flow velocity of the deep eye with high resolution. Ultrafast plane wave imaging was acquired using an L22-14v linear array on a high frequency Verasonics Vantage system. A robust microbubble localization and tracking technique was applied to reconstruct ULM images. The experiment was first performed on pre-designed flow phantoms in vitro and then tested on a New Zealand white rabbit eye in vivo calibrated to various intraocular pressures (IOP) - 10 mmHg, 30 mmHg and 50 mmHg. We demonstrated that retinal/choroidal vessels, central retinal artery, posterior ciliary artery, and vortex vein were all visible at high resolution. In addition, reduction of vascular density and flow velocity were observed with elevated IOPs. These results indicate that super-resolution ULM is able to image the deep ocular tissue while maintaining high resolution that is comparable with optical coherence tomography angiography. Capability to detect subtle changes of blood flow may be clinically important in detecting and monitoring eye diseases such as glaucoma.

Improved Ultrafast Power Doppler Imaging by Using Spatiotemporal Non-Local Means Filtering.

The change of microvasculature is associated with the occurrence and development of many diseases. Ultrafast power Doppler imaging (uPDI) is an emerging technology for the visualization of microvessels due to the development of ultrafast plane wave (PW) imaging and advanced clutter filters. However, the low signal-to-noise ratio (SNR) caused by unfocused transmit of PW imaging deteriorates the subsequent imaging of microvasculature. Nonlocal means (NLM) filtering has been demonstrated to be effective in the denoising of both natural and medical images, including ultrasound power Doppler images. However, the feasibility and performance of applying an NLM filter on the ultrasound radio frequency (RF) data have not been investigated so far. In this study, we propose to apply an NLM filter on the spatiotemporal domain of clutter filtered blood flow RF data (St-NLM) to improve the quality of uPDI. Experiments were conducted to compare the proposed method with three different methods (under various similarity window sizes), including conventional uPDI without NLM filtering (Non-NLM), NLM filtering on the obtained power Doppler images (PD-NLM), and NLM filtering on the spatial domain of clutter filtered blood flow RF data (S-NLM). Phantom experiments, in vivo contrast-enhanced human spinal cord tumor experiments, and in vivo contrast-free human liver experiments were performed to demonstrate the superiority of the proposed St-NLM method over the other three methods. Qualitative and quantitative results show that the proposed St-NLM method can effectively suppress the background noise, improve the contrast between vessels and background, and preserve the details of small vessels at the same time. In the human liver study, the proposed St-NLM method achieves 31.05-, 24.49-, and 11.15-dB higher contrast-to-noise ratios (CNRs) and 36.86-, 36.86-, and 15.22-dB lower noise powers than Non-NLM, PD-NLM, and S-NLM, respectively. In the human spinal cord tumor, the full-width at half-maximums (FWHMs) of vessel cross Section are 76, 201, and [Formula: see text] for St-NLM, Non-NLM, and S-NLM, respectively. The proposed St-NLM method can enhance the microvascular visualization in uPDI and has the potential for the diagnosis of many microvessel-change-related diseases.

Noninvasive direct assessment of the skeletal muscle function during neuromuscular electrical stimulation

Neuromuscular electrical stimulation (NMES) artificially activates skeletal muscle contraction by sending electrical pulses either to nerves or muscle belly. NMES has been used in various applications in rehabilitation and sports medicine. However, muscle function assessment has been limited to electrical activity measurements by an electromyography, indirect mechanical measurements using a force sensor, or ultrasound imaging that only provides anatomy and structure. In this paper, dynamic contractility of the targeted muscle in response to the NMES stimulation on human subjects is assessed using ultrafast plane wave imaging and speckle tracking. The change of the strain in the targeted muscle due to the continued NMES, resulting in muscle fatigue, was continually measured. By correlating the transient muscle strain with the force measurement as the direct gait function, it has been shown that muscle strain as measure of muscle contractility obtained by ultrasound elastography can be used as surrogate biomarker of muscle fatigue due to NMES. This technology can be used in several applications including NMES integrated exoskeletal for those who lost gait function as feedback to the motion control and NMES dose and monitoring the muscle strength and functional gain by NMES induced muscle treatment and training.

Simultaneous Noise Suppression and Incoherent Artifact Reduction in Ultrafast Ultrasound Vascular Imaging.

Ultrasound vascular imaging based on ultrafast plane wave imaging and singular value decomposition (SVD) clutter filtering has demonstrated superior sensitivity in blood flow detection. However, ultrafast ultrasound vascular imaging is susceptible to electronic noise due to the weak penetration of unfocused waves, leading to a lower signal-to-noise ratio (SNR) at larger depths. In addition, incoherent clutter artifacts originating from strong and moving tissue scatterers that cannot be completely removed create a strong mask on top of the blood signal that obscures the vessels. Herein, a method that can simultaneously suppress the background noise and incoherent artifacts is proposed. The method divides the tilted plane or diverging waves into two subgroups. Coherent spatial compounding is performed within each subgroup, resulting in two compounded data sets. An SVD-based clutter filter is applied to each data set, followed by a correlation between the two data sets to produce a vascular image. Uncorrelated noise and incoherent artifacts can be effectively suppressed with the correlation process, while the coherent blood signal can be preserved. The method was evaluated in wire-target simulations and phantom, in which around 7-10-dB SNR improvement was shown. Consistent results were found in a flow channel phantom with improved SNR by the proposed method (39.9 ± 0.2 dB) against conventional power Doppler (29.1 ± 0.6 dB). Last, we demonstrated the effectiveness of the method combined with block-wise SVD clutter filtering in a human liver, breast tumor, and inflammatory bowel disease data sets. The improved blood flow visualization may facilitate more reliable small vessel imaging for a wide range of clinical applications, such as cancer and inflammatory diseases.

Ultrafast ultrasound imaging in acoustic microbubble trapping

The lack of actively targeted nanocarriers and a low drug concentration in lesions are two of the main problems in targeted therapy for clinical use. In this paper, an ultrasound-induced trapping and ultrafast imaging system for flowing microbubbles is proposed to increase the effective drug dose and achieve real-time positioning. A finite element method model is established to analyze microbubble tracing in a fluid flow model at 2.5 MHz, which demonstrates how the interaction of acoustic radiation force (ARF) and flowing drag force is able to trap microbubbles and move them to a specific location. This motion can be explicitly imaged and captured by ultrafast plane wave imaging with a 1D array ultrasound probe at 18 MHz. The use of this plane wave and ARF technique can be beneficial for fast localization, monitoring, and manipulation of drug delivery bubbles for targeted release at 10 mm depth in a noninvasive and feasible way. Therefore, this ultrasound technology can be a useful tool to increase the local drug concentration in an accurate location for clinical use.

Ultrafast ultrasound breast scanning for improved image quality and functional information in 3-D

With an automated breast volume scanner (ABVS), a volumetric breast image can be constructed. Clinical studies show high sensitivity but also high recall-rates due to the detection of many lesions of uncertain malignant potential. It is known that breast lesions have different mechanical properties with respect to its surrounding tissue. Consequently, imaging the biomechanics of a breast might improve diagnosis in this disease. First, we improved the image quality by taking full advantage of the ultrafast acquisition and by applying dedicated signal processing techniques. Next, by imaging biomechanics we increased the specificity since compared to benign lesions, malignant lesions are often stiffer, and more grown into the surrounding tissue (firmly bonded). We extended conventional 2-D strain imaging to full 3-D (shear) strain imaging by combining automated breast volume scanning with ultrafast plane wave imaging (10 000 frames/s). Validation studies in breast phantoms revealed that lesions could be differentiated based on strain and shear strain imaging. Decreased strain values were found in stiff lesions and firmly bonded lesions demonstrated low shear strain values. Initial acquisitions in patients demonstrated decreasing strain values with increasing severity of the disease. Additionally, we developed an ultrasensitive 3-D Doppler method to detect neo-vascularization that might be present around malignant lesions. In conclusion, imaging the biomechanical properties in 3-D improves diagnosis breast cancer.With an automated breast volume scanner (ABVS), a volumetric breast image can be constructed. Clinical studies show high sensitivity but also high recall-rates due to the detection of many lesions of uncertain malignant potential. It is known that breast lesions have different mechanical properties with respect to its surrounding tissue. Consequently, imaging the biomechanics of a breast might improve diagnosis in this disease. First, we improved the image quality by taking full advantage of the ultrafast acquisition and by applying dedicated signal processing techniques. Next, by imaging biomechanics we increased the specificity since compared to benign lesions, malignant lesions are often stiffer, and more grown into the surrounding tissue (firmly bonded). We extended conventional 2-D strain imaging to full 3-D (shear) strain imaging by combining automated breast volume scanning with ultrafast plane wave imaging (10 000 frames/s). Validation studies in breast phantoms revealed that lesions could be diff...

Debiasing-Based Noise Suppression for Ultrafast Ultrasound Microvessel Imaging.

Ultrasound microvessel imaging (UMI) based on the combination of singular value decomposition (SVD) clutter filtering and ultrafast plane wave imaging has recently demonstrated significantly improved Doppler sensitivity, especially to small vessels that are invisible to conventional Doppler imaging. Practical implementation of UMI is hindered by the high computational cost associated with SVD and low blood signal-to-noise ratio (SNR) in deep regions of the tissue due to the lack of transmit focusing of plane waves. Concerning the high computational cost, an accelerated SVD clutter filtering method based on randomized SVD (rSVD) and randomized spatial downsampling (rSD) was recently proposed by our group, which showed the feasibility of real-time implementation of UMI. Concerning the low blood flow SNR in deep imaging regions, here we propose a noise suppression method based on noise debiasing that can be easily applied to the accelerated SVD method to bridge the gap between real-time implementation and high imaging quality. The proposed method experimentally measures the noise-induced bias by collecting the noise signal using the identical imaging sequence as regular UMI, but with the ultrasound transmission turned off. The estimated bias can then be subtracted from the original power Doppler (PD) image to obtain effective noise suppression. The feasibility of the proposed method was validated under different ultrasound imaging parameters [including transmitting voltages and time-gain compensation (TGC) settings] with a phantom experiment. The noise-debiased images showed an increase of up to 15.3 and 13.4 dB in SNR as compared to original PD images on the blood flow phantom and an in vivo human kidney data set, respectively. The proposed noise suppression method has negligible computational cost and can be conveniently combined with the previously proposed accelerated SVD clutter filtering technique to achieve high quality, real-time UMI imaging.

Initial phantom study on estimation of speed of sound in medium using coherence among received echo signals.

Ultrasound beamforming is required to obtain clinical ultrasound images. In the beamforming procedure, the distance between the receiving focal point and each transducer element is determined based on the assumed speed of sound in the tissue. However, the actual speed of sound in tissue is unknown and varies depending on the tissue type. To improve the performance of an ultrasonic beamformer by evaluating its focusing quality, the coherence factor (CF) was introduced in medical ultrasound imaging. The CF may be used to estimate the speed of sound in tissue because it can identify focusing errors in beamforming. In the present study, the feasibility of CF for estimating the speed of sound was examined through phantom experiments. To evaluate the dependency of CF on the assumed speed of sound in ultrasound beamforming, beamformed ultrasonic radio frequency (RF) signals and CFs were obtained at different assumed speeds of sound. CF is highest when the assumed speed of sound matches the true speed of sound in the medium. Therefore, the speed of sound in the medium was determined as the assumed speed of sound, which gives the highest CF. The proposed method was validated in a conventional line-by-line sequence with a focused transmit beam and ultrafast plane wave imaging. A homogeneous phantom (diffuse scattering medium) with a known speed of sound of 1540m/s was used for validating the proposed method. Beamformed ultrasonic RF signals and CFs were obtained at an assumed speed of sound from 1480 to 1600m/s varied at a pitch of 5m/s. In the line-by-line sequence, CF reached the maximum at an assumed speed of sound of 1525.0m/s (0.97% difference from the true value) when CFs at all spatial points in the region of interest (ROI) were averaged. On the other hand, the speed of sound was determined to be 1528.5m/s (0.75% difference) when CFs at spatial points with CF-weighted echo amplitudes were larger than 20% of the maximum value. In plane wave imaging, the speed of sound was estimated to be 1544.5m/s (0.29% difference) using CFs with CF-weighted echo amplitudes larger than 20% of the maximum value. The speed of sound of a homogeneous medium could be determined by the proposed method with errors of less than 1% using CFs obtained from ultrasonic echo signals selected based on the CF-weighted echo amplitudes, i.e., when echo signals with better signal-to-noise ratios (SNRs) were used.

Evaluation of Brain Tumor in Small Animals Using Plane Wave-Based Power Doppler Imaging

Precisely evaluating the characteristics of a glioma tumor in vivo is challenging when performing surgical resection clinically. The infiltration characteristics of a tumor make precise resection difficult because of uncertainties about the surrounding vasculature and the relationships with functional structures. Magnetic resonance imaging is routinely used to distinguish the area of a glioma, but it cannot resolve details of the vascular network around or inside the tumor. Ultrasound imaging is a real-time imaging modality that has been applied clinically in intra-operative surgery, and the sensitivity of flow measurements in the brain is improved by ultrafast plane wave imaging. This study applies a plane wave-based power Doppler imaging method to visualize the blood flow distribution in glioma models in vivo. This new imaging method makes it possible to delineate the flow structure of a glioma tumor in the brain of a small animal. The tumor can be distinguished from normal brain tissue, and different sections of the tumor contain different flow structures. The normalized blood flow intensities (mean ± standard deviation) within regions of interest were 0.33 ± 0.13, 0.72 ± 0.15, 0.36 ± 0.23 and 0.06 ± 0.07 for the type I normal rat, type I glioma rat, type II normal rat and type II glioma rat, respectively. Quantification analysis verified the feasibility of using this plane wave-based Doppler imaging method to evaluate brain tumors in small animals.

Simultaneous Vascular Strain and Blood Vector Velocity Imaging Using High-Frequency Versus Conventional-Frequency Plane Wave Ultrasound: A Phantom Study.

Plaque strain and blood vector velocity imaging of stenosed arteries are expected to aid in diagnosis and prevention of cerebrovascular disease. Ultrafast plane wave imaging enables simultaneous strain and velocity estimation. Multiple ultrasound vendors are introducing high-frequency ultrasound probes and systems. This paper investigates whether the use of high-frequency ultrafast ultrasound is beneficial for assessing blood velocities and strain in arteries. The performance of strain and blood flow velocity estimation was compared between a high-frequency transducer (MS250, fc = 21 MHz) and a clinically utilized transducer (L12-5, fc = 9 MHz). Quantitative analysis based on straight tube phantom experiments revealed that the MS250 outperformed the L12-5 in the superficial region: low velocities near the wall were more accurately estimated and wall strains were better resolved. At greater than 2-cm echo depth, the L12-5 performed better due to the high attenuation of the MS250 probe. Qualitative comparison using a perfused patient-specific carotid bifurcation phantom confirmed these findings. Thus, in conclusion, for strain and blood velocity estimation for depths up to ~2 cm, a high-frequency probe is recommended.

Phantom study of flow speed measurement using ultrafast ultrasound plane wave imaging

Color flow imaging is an ultrasound imaging technique widely used to image the blood movement through arteries and veins. Quantification of velocity is urgently demanding. The objective of this study is to use ultrafast plane wave imaging to measure the flow in speed in vitro. For the flow phantom, the diagonal vessel (2-mm inner diameter at 40° angle) was studied with injection of blood mimic fluid via syringe pump at various volume rates (15, 20, 25, and 30 ml/min). Verasonics Vantage system (Verasonics Inc., Kirkland, WA, USA) and a linear array transducer L11-4v (Verasonics Inc., Kirkland, WA, USA) were used for ultrasound acquisition, a 8-angle (−7° to 7°) plane wave compounding with effective pulse-repetition frequency (PRF) of 1000 Hz was used (central frequency = 6.42 MHz, number of transmit cycles = 4). A total of 600 ensembles were acquired. The frame rate was 1000/s.[XZ1] [BZ2] The ultrasound in-phase quadrature data size was 195 × 156 × 600 (axial x lateral x temporal) with data type of complex double. Singular value decomposition (SVD)-based ultrasound blood flow clutter filters was used for ultrafast plane wave imaging.[XZ3] [BZ4] Randomized SVD was utilized to filter noise and tissue motion. Power Doppler image was generated. The color flow images were generated by using the 2-D autocorrelation method. Results showed that color flow measurement can quantitatively evaluate the flow speed in the tube of the flow phantom.

Spatiotemporal clutter filtering methods for in vivo microvessel imaging

Ultrafast plane wave imaging enables acquisition and accumulation of a large number of Doppler ensembles in a short period of time, which substantially boosts ultrasound Doppler sensitivity by at least an order of magnitude. As a key component, spatiotemporal clutter filtering based on singular value decomposition (SVD) has recently demonstrated superior performance in tissue clutter suppression and microvessel signal extraction over conventional high-pass-filter-based clutter filtering techniques. This presentation introduces several novel SVD clutter filter techniques from our recent work, focusing on addressing the technical challenges (complex tissue motion, high computational cost, and noise) of SVD clutter filter during clinical translations of the ultrafast microvessel imaging technology for human imaging. We present a block-wise adaptive SVD filter method that can robustly threshold singular values on a local level, a real-time feasible SVD clutter filtering method based on partial SVD and randomized spatial downsampling, and a noise equalization and suppression method that can significantly improve microvessel imaging quality at a low cost. In vivo performance of these methods will be demonstrated in different organs.

Quasi-Static Elastography and Ultrasound Plane-Wave Imaging: The Effect of Beam-Forming Strategies on the Accuracy of Displacement Estimations

Quasi-static elastography is an ultrasound method which is widely used to assess displacements and strain in tissue by correlating ultrasound data at different levels of deformation. Ultrafast plane-wave imaging allows us to obtain ultrasound data at frame rates over 10 kHz, permitting the quantification and visualization of fast deformations. Currently, mainly three beam-forming strategies are used to reconstruct radio frequency (RF) data from plane-wave acquisitions: delay-and-sum (DaS), and Lu’s-fk and Stolt’s-fk operating in the temporal-spatial and Fourier spaces, respectively. However, the effect of these strategies on elastography is unknown. This study investigates the effect of these beam-forming strategies on the accuracy of displacement estimation in four transducers (L7-4, 12L4VF, L12-5, MS250) for various reconstruction line densities and apodization/filtering settings. A method was developed to assess the accuracy experimentally using displacement gradients obtained in a rotating phantom. A line density with multiple lines per pitch resulted in increased accuracy compared to one line per pitch for all transducers and strategies. The impact on displacement accuracy of apodization/filtering varied per transducer. Overall, Lu’s-fk beam-forming resulted in the most accurate displacement estimates. Although DaS in some cases provided similar results, Lu’s-fk is more computationally efficient, leading to the conclusion that Lu’s-fk is most optimal for plane wave ultrasound-based elastography.