Ultrafast Plane Wave Research Articles

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

Versatile Ultrasound-Compatible Microfluidic Platform for In Vitro Microvasculature Flow Research and Imaging Optimization.

Ultrasound localization microscopy (ULM) enables the creation of super-resolved images and velocity maps by localizing and tracking microbubble contrast agents through a vascular network over thousands of frames of ultrafast plane wave images. However, a significant challenge lies in developing ultrasound-compatible microvasculature phantoms to investigate microbubble flow and distribution in controlled environments. In this study, we introduce a new class of gelatin-based microfluidic-inspired phantoms uniquely tailored for ULM studies. These devices allow for the creation of complex and reproducible microvascular networks featuring channel diameters as small as 100 μm. Our experiments focused on microbubble behavior under ULM conditions within bifurcating and converging vessel phantoms. We evaluated the impact of bifurcation angles (25, 45, and 55°) and flow rates (0.01, 0.02, and 0.03 mL/min) on the acquisition time of branching channels. Additionally, we explored the saturation time effect of narrow channels branching off larger ones. Significantly longer acquisition times were observed for the narrow vessels, with an average increase of 72% when a 100 μm channel branched off from a 300 μm channel and an average increase of 90% for a 200 μm channel branching off from a 500 μm channel. The robustness of our fabrication method is demonstrated through the creation of two trifurcating microfluidic phantoms, including one that converges back into a single channel, a configuration that cannot be achieved through traditional methods. This new class of ULM phantoms serves as a versatile platform for noninvasively studying complex flow patterns using ultrasound imaging, unlocking new possibilities for in vitro microvasculature research and imaging optimization.

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.

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.

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.

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.

Comparison of Phase-Screen and Geometry-Based Phase Aberration Correction Techniques for Real-Time Transcranial Ultrasound Imaging

While transcranial ultrasound imaging is a promising diagnostic modality, it is still hindered due to phase aberration and multiple scattering caused by the skull. In this paper, we compare near-field phase-screen modeling (PS) to a geometry-based phase aberration correction technique (GB) when an ultrafast imaging sequence (five plane waves tilted from −15 to +15 degrees in the cutaneous tissue layer) is used for data acquisition. With simulation data, the aberration profile (AP) of two aberrator models (flat and realistic temporal bone) was estimated in five isoplanatic patches, while the wave-speed of the brain tissue surrounding the point targets was either modeled homogeneously (ideal) or slightly heterogeneously to generate speckle (for mimicking a more realistic brain tissue). For the experiment, a phased array P4-1 transducer was used to image a wire phantom; a 4.2-mm-thick bone-mimicking plate was placed in front of the probe. The AP of the plate was estimated in three isoplanatic patches. The numerical results indicate that, while all the scatterers are detectable in the image reconstructed by the GB method, many scatterers are not detected with the PS method when the dataset used for AP estimation is generated with a realistic bone model and heterogeneous brain tissue. The experimental results show that the GB method increases the signal-to-clutter ratio (SCR) by 7.5 dB and 6.5 dB compared to the PS and conventional reconstruction methods, respectively. The GB method reduces the axial/lateral localization error by 1.97/0.66 mm and 2.08/0.7 mm compared to the PS method and conventional reconstruction, respectively. The lateral spatial resolution (full-width-half-maximum) is also improved by 0.1 mm and 1.06 mm compared to the PS method and conventional reconstruction, respectively. Our comparison study suggests that GB aberration correction outperforms the PS method when an ultrafast multi-angle plane wave sequence is used for transcranial imaging with a single transducer.

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.

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 (∼10ms) than the conventional SR method (∼1-5mins), 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 75PWs in reconstruction of in-vivo images of human carotid arteries.

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.