Doppler Ensemble Research Articles

Dynamic Mode Decomposition for Transient Cavitation Bubbles Imaging in Pulsed High-Intensity Focused Ultrasound Therapy.

Pulsed high-intensity focused ultrasound (pHIFU) can induce sparse de novo inertial cavitation without the introduction of exogenous contrast agents, promoting mild mechanical disruption in targeted tissue. Because the bubbles are small and rapidly dissolve after each HIFU pulse, mapping transient bubbles and obtaining real-time quantitative metrics correlated with tissue damage are challenging. Prior work introduced Bubble Doppler, an ultrafast power Doppler imaging method as a sensitive means to map cavitation bubbles. The main limitation of that method was its reliance on conventional wall filters used in Doppler imaging and its optimization for imaging blood flow rather than transient scatterers. This study explores Bubble Doppler enhancement using dynamic mode decomposition (DMD) of a matrix created from a Doppler ensemble for mapping and extracting the characteristics of transient cavitation bubbles. DMD was first tested in silico with a numerical dataset mimicking the spatiotemporal characteristics of backscattered signal from tissue and bubbles. The performance of DMD filter was compared to other widely used Doppler wall filter-singular value decomposition (SVD) and infinite impulse response (IIR) high-pass filter. DMD was then applied to an ex vivo tissue dataset where each HIFU pulse was immediately followed by a plane wave Doppler ensemble. In silico DMD outperformed SVD and IIR high-pass filter and ex vivo provided physically interpretable images of the modes associated with bubbles and their corresponding temporal decay rates. These DMD modes can be trackable over the duration of pHIFU treatment using k-means clustering method, resulting in quantitative indicators of treatment progression.

Active Doppler monitoring of de novo cavitation induced by a dual-mode pulsed high-intensity focused ultrasound array

Pulsed high-intensity focused ultrasound (pHIFU) is capable of inducing inertial cavitation in tissues without the need for microbubbles or other ultrasound contrast agents, thereby permeabilizing the tissue to enhance passive diffusion of systemically administered therapeutic agents. Here, we report on the use of ultrafast, synchronous power Doppler imaging to spatially map cavitation activity and resulting tissue disruption in ex vivo and invivo porcine tissues using a dual-mode imaging-therapy linear pHIFU array. The array (64 elements, aperture 51.2 mm × 14 mm, frequency 1.0MHz, 40% bandwidth) was driven by a power-enhanced Verasonics V1 system to deliver a series of 1 ms pulses at a 1% duty cycle while electronically scanning the pHIFU focus over an azimuthal range of ±1 cm. Plane wave Doppler ensembles were captured immediately after each pHIFU pulse to map the distribution and characteristics of the remnants of cavitation bubbles. The degree of resulting tissue disruption was assessed by histology and was correlated with cumulative Doppler power contours computed over the exposure region. The results show that ultrafast synchronous power Doppler is a promising approach for real-time quantitative monitoring of cavitational therapies. [Work supported by NIH R01EB023910 and T32DK007742.]

Ultrasound Ultrafast Power Doppler Imaging with High Signal-to-Noise Ratio by Temporal Multiply-and-Sum (TMAS) Autocorrelation.

Coherent plane wave compounding (CPWC) reconstructs transmit focusing by coherently summing several low-resolution plane-wave (PW) images from different transmit angles to improve its image resolution and quality. The high frame rate of CPWC imaging enables a much larger number of Doppler ensembles such that the Doppler estimation of blood flow becomes more reliable. Due to the unfocused PW transmission, however, one major limitation of the Doppler estimation in CPWC imaging is the relatively low signal-to-noise ratio (SNR). Conventionally, the Doppler power is estimated by a zero-lag autocorrelation which reduces the noise variance, but not the noise level. A higher-lag autocorrelation method such as the first-lag (R(1)) power Doppler image has been developed to take advantage of the signal coherence in the temporal direction for suppressing uncorrelated random noises. In this paper, we propose a novel Temporal Multiply-and-Sum (TMAS) power Doppler detection method to further improve the noise suppression of the higher-lag method by modulating the signal coherence among the temporal correlation pairs in the higher-lag autocorrelation with a tunable pt value. Unlike the adaptive beamforming methods which demand for either receive-channel-domain or transmit-domain processing to exploit the spatial coherence of the blood flow signal, the proposed TMAS power Doppler can share the routine beamforming architecture with CPWC imaging. The simulated results show that when it is compared to the original R(1) counterpart, the TMAS power Doppler image with the pt value of 2.5 significantly improves the SNR by 8 dB for the cross-view flow velocity within the Nyquist rate. The TMAS power Doppler, however, suffers from the signal decorrelation of the blood flow, and thus, it relies on not only the pt value and the flow velocity, but also the flow direction relative to the geometry of acoustic beam. The experimental results in the flow phantom and in vivo dataset also agree with the simulations.

Passive and active Doppler methods and metrics to quantify inertial cavitation induced by pulsed focused ultrasound

Inertial cavitation induced by pulses of nonlinearly distorted focused ultrasound (FUS) at moderate intensity can result in mild mechanical disruption of tissue, short of its complete mechanical disintegration—histotripsy. This effect can be used to enhance diffusion of subsequently systemically administered drugs or biologics. Previously, single-element passive cavitation detection (PCD) of broadband noise emissions was successfully used to quantify tissue disruption and enhancement in drug concentration. This metric, however, has limitations: minimal spatial resolution and challenges with calibration when used at large depths in acoustically variable tissue. To address this, we developed a combination of passive and active Doppler-based methods that relied on relative, rather than absolute signal metrics. Specifically, destructive cavitation behaviors were previously linked to substantial motion of the bubbles during the FUS pulse due to acoustic radiation force and shock scattering. This was reflected in the backscattered FUS harmonics as Doppler shift and measurable from PCD. The bubbles were observed to dissolve within milliseconds following each FUS pulse, thus their distribution could be visualized as an area of rapid change via fast plane wave Doppler ensemble following the FUS pulse. The Doppler power distribution was spatially correlated with the area of tissue disruption in the in vivo experiments. [Work supported by NIH R01CA154451, R01EB025187, and R01EB23910.]

Quantitative assessment of ensemble coherency in contrast‐free ultrasound microvasculature imaging

PurposeContrast‐free visualization of microvascular blood flow (MBF) using ultrasound can play a valuable role in diagnosis and detection of diseases. In this study, we demonstrate the importance of quantifying ensemble coherence for robust MBF imaging. We propose a novel approach to quantify ensemble coherence by estimating the local spatiotemporal correlation (LSTC) image, and evaluate its efficacy through simulation and in vivo studies.MethodsThe in vivo patient studies included three volunteers with a suspicious breast tumor, 15 volunteers with a suspicious thyroid tumor, and two healthy volunteers for renal MBF imaging. The breast data displayed negligible prior motion and were used for simulation analysis involving synthetically induced motion, to assess its impact on ensemble coherency and motion artifacts in MBF images. The in vivo thyroid data involved complex physiological motion due to its proximity to the pulsating carotid artery, which was used to assess the in vivo efficacy of the proposed technique. Further, in vivo renal MBF images demonstrated the feasibility of using the proposed ensemble coherence metric for curved array‐based MBF imaging involving phase conversion. All ultrasound data were acquired at high imaging frame rates and the tissue signal was suppressed using spatiotemporal clutter filtering. Thyroid tissue motion was estimated using two‐dimensional normalized cross correlation‐based speckle tracking, which was subsequently used for ensemble motion correction. The coherence of the MBF image was quantified based on Casorati correlation of the Doppler ensemble.ResultsThe simulation results demonstrated that an increase in ensemble motion corresponded with a decrease in ensemble coherency, which reciprocally degraded the MBF images. Further the data acquired from breast tumors demonstrated higher ensemble coherency than that from thyroid tumors. Motion correction improved the coherence of the thyroid MBF images, which substantially improved its visualization. The proposed coherence metrics were also useful in assessing the ensemble coherence for renal MBF imaging. The results also demonstrated that the proposed coherence metric can be reliably estimated from downsampled ensembles (by up to 90%), thus allowing improved computational efficiency for potential applications in real‐time MBF imaging.ConclusionsThis pilot study demonstrates the importance of assessing ensemble coherency in contrast‐free MBF imaging. The proposed LSTC image quantified coherence of the Doppler ensemble for robust MBF imaging. The results obtained from this pilot study are promising, and warrant further development and in vivo validation.

Blood Flow Imaging in the Neonatal Brain Using Angular Coherence Power Doppler.

Using ultrasound to image small vessels in the neonatal brain can be difficult in the presence of strong clutter from the surrounding tissue and with a neonate motion during the scan. We propose a coherence-based beamforming method, namely the short-lag angular coherence (SLAC) beamforming that suppresses incoherent noise and motion artifacts in Ultrafast data, and we demonstrate its applicability to improve detection of blood flow in the neonatal brain. Instead of estimating spatial coherence across the receive elements, SLAC utilizes the principle of acoustic reciprocity to estimate angular coherence from the beamsummed signals from different plane-wave transmits, which makes it computationally efficient and amenable to advanced beamforming techniques, such as f-k migration. The SLAC images of a simulated speckle phantom show similar edge resolution and texture size as the matching B-mode images, and reduced random noise in the background. We apply SLAC power Doppler (PD) to free-hand imaging of neonatal brain vasculature with long Doppler ensembles and show that: 1) it improves visualization of small vessels in the cortex compared to conventional PD and 2) it can be used for tracking of blood flow in the brain over time, meaning it could potentially improve the quality of free-hand functional ultrasound.

Impact of imaging cross-section on visualization of thyroid microvessels using ultrasound: Pilot study

Non-invasive, contrast-free microvascular imaging of human thyroids can be potentially beneficial in reducing the large number of benign biopsies of suspicious nodules. However, motion incurred by thyroid due to its proximity to the pulsating carotid artery significantly impacts the visualization of blood flow in small vessels. Singular value based spatiotemporal clutter filtering (SVD-STF) improves the performance of tissue rejection in the presence of motion. However, despite effective clutter filtering, motion in thyroid imaging can impact coherent integration of the Doppler ensemble and degrade the visualization of the underlying vasculature. Recently studies have demonstrated that motion correction using 2D normalized cross-correlation based speckle tracking can address this issue, however, only in-plane motion can be tracked and corrected. Given the natural anatomical orientation of the rigid trachea, thyroid and the pulsating carotid artery, we hypothesize that imaging of thyroid microvessels may be more reliable in the longitudinal view than in the transverse. Specifically, distal presence of rigid trachea can limit out-of-plane motion in the longitudinal view. We tested this hypothesis on 48 acquisitions obtained from 24 thyroid patients having at least one suspicious nodule. In each patient, ultrasound images of the thyroid were acquired in both longitudinal and transverse views. Compounded plane-wave imaging was used to acquire the ultrasound images at high frame-rate, which is important for contrast-free small vessel blood flow imaging. Thyroid motion was tracked using 2D normalized cross-correlation based speckle tracking. Tissue clutter was rejected using singular value decomposition based spatiotemporal clutter filtering. The clutter-filtered Doppler ensemble was motion corrected prior to slow-time power Doppler integration. Signal-to-noise and contrast-to-noise ratios were computed to assess the improvement in quality of the power Doppler images. Out-of-plane motion was detected by estimating normalized ensemble cross-correlation coefficient. The results demonstrated that motion associated with the thyroid due to the carotid artery was primarily in the lateral direction, which could be estimated and corrected using 2D speckle tracking. However, the motion in the transverse view displayed increased speckle decorrelation. The average ensemble cross-correlation coefficient of the thyroid ultrasound images were significantly higher (p < 0.05) in the longitudinal view than in the transverse view. The largest improvement in SNR and CNR of the estimated PD images upon motion correction was observed in the longitudinal view (12.95 ± 3.76 dB and 16.48 ± 4.6 dB) than in the transverse view (3.72 ± 0.894 dB and 6.217 ± 1.689 dB). These preliminary results show that motion encountered by the thyroid due to carotid pulsations can be effectively tracked and corrected in the longitudinal view relative to transverse, which is important for reliably visualizing the underlying blood flow.

Adaptive background noise bias suppression in contrast-free ultrasound microvascular imaging

Non-invasive, contrast-free imaging of small vessel blood flow is diagnostically invaluable for detection, diagnosis and monitoring of disease. Recent advances in ultrafast imaging and tissue clutter-filtering have considerably improved the sensitivity of power Doppler (PD) imaging in detecting small vessel blood flow. However, suppression of tissue clutter exposes the depth-dependent time-gain compensated noise bias that noticeably degrades the PD image. We hypothesized that background suppression of PD images based on noise bias estimated from the entire clutter-filtered singular value spectrum can considerably improve flow signal visualization compared to currently existing techniques.To test our hypothesis, in vivo experiments were conducted on suspicious breast lesions in 10 subjects and deep-seated hepatic and renal microvasculatures in four healthy volunteers. Ultrasound PD images were acquired using a clinical ultrasound scanner, implemented with compounded plane wave imaging. The time gain compensated noise field was computed from the clutter-filtered Doppler ensemble (CFDE) based on its local spatio-temporal correlation, combined with low-rank signal estimation. Subsequently, the background bias in the PD images was suppressed by subtracting the estimated noise field.Background-suppressed PD images obtained using the proposed technique substantially improved visualization of the blood flow signal. The background bias in the noise suppressed PD images varied <0.6 dB, independent of depth, which otherwise increased up to 13.8 dB. Further, the results demonstrated that the proposed technique efficaciously suppressed the background noise bias associated with smaller Doppler ensembles, which are challenging due to increased overlap between blood flow and noise components in the singular value spectrum.These preliminary results demonstrate the utility of the proposed technique to improve the visualization of small vessel blood flow in contrast-free PD images. The results of this feasibility study were encouraging, and warrant further development and additional in vivo validation.

Suppression of in vivo flow artifacts in power Doppler through spatial and angular coherence beamforming

Power Doppler imaging is traditionally the flow imaging technique utilized clinically in the task of flow detection. Due to the relatively low pulse repetition frequencies used, power Doppler ensemble sizes are small to allow real-time imaging. The small ensemble size, however, makes power Doppler imaging subject to the so-called flash artifact due to limited stationary clutter filtering capabilities. In addition, with the increasing population of overweight and obese individuals, power Doppler imaging is subject to higher amounts of thermal noise and reverberation artifact that pass through the stationary clutter filters. We present coherence beamforming techniques, applied to in vivo human imaging, to demonstrate their ability to reduce flow artifacts and noise in power Doppler imaging. Using coherence beamforming techniques in Coherent Flow Power Doppler (CFPD), we show that artifacts due to reverberation and thermal noise are reduced, corresponding to an increase of 7.5 dB in signal-to-noise ratio, in liver imaging of overweight and obese individuals. Similarly, we demonstrate coherence beamforming techniques in CFPD to reduce flash artifacts in videos of the neonatal brain.

Non-invasive Small Vessel Imaging of Human Thyroid Using Motion-Corrected Spatiotemporal Clutter Filtering

Reliable assessment of small vessel blood flow in the thyroid, without using any contrast agents, can be challenging because of increased physiological motion resulting from its proximity to the pulsating carotid artery. In this study, we hypothesized that correction of tissue motion prior to singular value decomposition (SVD)-based clutter filtering can improve the coherency of the tissue components and, thus, may allow better clutter suppression and visualization of small vessels in the thyroid. We corroborated this hypothesis by conducting phantom and in vivo studies using a clinical ultrasound scanner implemented with compounded plane wave imaging. The phantom studies were conducted using a homogeneous tissue-mimicking phantom to study the impact of motion on the covariance of the spatiotemporal Doppler data, in the absence of blood activity. The non-invasive in vivo study was conducted on a 74-y-old woman with a thyroid nodule suspicious of malignancy. A rigid body-based motion correction was performed using tissue displacements obtained from 2-D normalized cross-correlation–based speckle tracking. Subsequently, the power Doppler images were computed using SVD-based spatiotemporal clutter filtering. The results from the phantom study revealed that motion can considerably reduce the covariance of the spatiotemporal data and, thus, increase the rank of the tissue components. When the phantom was subjected to a total translation displacement of 6 pixels over the entire ensemble, in each direction (axial and lateral), the covariance dropped by more than 25%. The results obtained from the non-invasive in vivo study indicated that visualization of small vessel blood flow improved with motion correction of the power Doppler ensemble. The contrast-to-noise ratio of the blood signal in motion-corrected power Doppler images was considerably higher (8.17 and 8.32 dB), compared with that obtained using the standard SVD approach at an optimal threshold (0.87 and 4.33 dB) and a lower singular value threshold (1.92 and 3.05 dB). Further, the covariance of the in vivo thyroid spatiotemporal data increased by approximately 10% with motion correction. These preliminary results indicate that motion correction can be used to improve the visualization of small vessel blood flow in the thyroid, without using any contrast agents. The results of this feasibility study were encouraging, and warrant further development and more in vivo validation in moving tissues and organs.

Non-contrast agent based small vessel imaging of human thyroid using motion corrected power Doppler imaging

Singular value based spatiotemporal clutter filtering (SVD-STF) can significantly improve the sensitivity of blood flow imaging in small vessels without using contrast agents. However, despite effective clutter filtering, large physiological motion in thyroid imaging can impact coherent integration of the Doppler signal and degrade the visualization of the underlying vasculature. In this study, we hypothesize that motion correction of the clutter filtered Doppler ensemble, prior to the power Doppler estimation, can considerably improve the visualization of smalls vessels in suspicious thyroid nodules. We corroborated this hypothesis by conducting in vivo experiments on 10 female patients in the age group 44–82 yrs, with at least one thyroid nodule suspicious of malignancy, with recommendation for fine needle aspiration biopsy. Ultrasound images were acquired using a clinical ultrasound scanner, implemented with compounded plane wave imaging. Axial and lateral displacements associated with the thyroid nodules were estimated using 2D normalized cross-correlation. Subsequently, the tissue clutter associated with the Doppler ensemble was suppressed using SVD-STF. Motion correction of the clutter-filtered Doppler ensemble was achieved using a spline based sub-pixel interpolation. The results demonstrated that power Doppler images of thyroid nodules were noticeably degraded due to large physiological motion of the pulsating carotid artery in the proximity. The resultant power Doppler images were corrupted with signal distortion, motion blurring and occurrence of artificial shadow vessels and displayed visibly low signal-to-background contrast. In contrast, the power Doppler images obtained from the motion corrected ultrasound data addressed the issue and considerabley improved the visualization of blood flow. The signal-to-noise ratio and the contrast-to-noise ratio increased by up to 15.2 dB and 12.1 dB, respectively. Across the ten subjects, the highest improvement was observed for the nodule with the largest motion. These preliminary results show the ability of using motion correction to improve the visualization of small vessel blood flow in thyroid, without using any contrast agents. The results of this feasibility study were encouraging, and warrant further development and more in vivo validation in moving tissues and organs.

3-D Perfusion Imaging Using Principal Curvature Detection Rendering.

Three-dimensional contrast-enhanced ultrasound (CEUS) imaging presents a clear advantage over its 2-D counterpart in detecting and characterizing suspicious lesions as it properly surveys the inherent heterogeneity of tumors. However, 3-D CEUS is also slow compared to 2-D CEUS and tends to undersample the microbubble wash-in. This makes it difficult to resolve the feeding vessels, an important oncogenic marker, from the background perfusion cloud. Contrast-enhanced Doppler is helpful in isolating this conduit flow, but requires too many pulses in conventional line-by-line beamforming design. Recent breakthroughs in plane-wave imaging have greatly accelerated the volumetric imaging frame rate, but volumetric Doppler angiography still remains challenging when considering real-time limitations on the Doppler ensemble length. In this work, we demonstrate the feasibility of volumetric CEUS angiography subjected to real-time imaging constraints. Namely, we show how principal curvature detection can significantly improve 3-D rendering of relatively noisy ultrasound angiograms without degrading the spatial resolution while subjected to a reasonable Doppler ensemble size. Singular value decomposition is also shown to be capable of identifying the quasi-stationary capillary perfusion.

Multi-resolution rank analysis for non-contrast ultrasound imaging of slow flow

While conventional filtering techniques can effectively exclude tissue-related Doppler shifts from those resulting from blood motions in large vessels (flow rates ~ cm/s), significant spectral overlap can hinder proper clutter filtering in imaging slow flows (flow rates ~ mm/s or tenths of mm/s). Recently, several groups have proposed clutter filtering via processing of echo ensembles in the rank space instead of frequency domain. Though significant Doppler content can result from fast moving tissues, global coherence of the induced variations enables a low rank representation. In this talk, we first provide a brief overview of the low rank clutter removal methods. We then present a new framework for the analysis of Doppler ensembles using multi-linear decomposition of a tensor comprising Doppler ensembles at different rates. The model results in a high dimensional tensor from which, after proper rank selection, images of flow at different speeds can be extracted along different fibers. Using simulation models, we demonstrate the superior performance of the proposed method over singular value clutter filtering in imaging small vessels embedded in moving tissue undergoing both translational and shearing motions. We also present in vivo examples where the proposed method provides significant blood to clutter + noise ratio enhancement compared to singular value clutter filtering.

Enhanced sensitivity of flow detection in small vessels with slow flow by coherent-flow power Doppler

Power Doppler imaging is a commonly used method for the detection of flow. However, the sensitivity of power Doppler in small vessel detection is limited in clinical ultraound scanners by a combination of factors, including the small-diameter of vessels, slow flow through the vessels, the size of the Doppler ensemble, the presence of motion, the presence of noise, and the type of filter used. We have developed an alternative power Doppler imaging technique that enhances flow detection of small vessels and slow flow. This technique utilizes the same principles as power Doppler, but uses the coherence of backscattered blood signal rather than the backscattered signal power. We show that this technique, called coherent flow power Doppler (CFPD), is less sensitive to clutter-based signals and thermal noise and improves signal-to-noise ratio of the flow signal. We show through simulations, phantoms, and in vivo experimentation in human liver that this additional signal-to-noise ratio (7.5-12.5 dB) can be utilized to detect slower flow, improved frame rate (smaller Doppler ensemble), or improve the Doppler image profile. In addition, the technique demonstrates better signal-to-noise ratio for small-sized vessels (less than 2 mm).

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.

Noise Equalization for Ultrafast Plane Wave Microvessel Imaging.

Ultrafast plane wave microvessel imaging significantly improves ultrasound Doppler sensitivity by increasing the number of Doppler ensembles that can be collected within a short period of time. The rich spatiotemporal plane wave data also enable more robust clutter filtering based on singular value decomposition. However, due to the lack of transmit focusing, plane wave microvessel imaging is very susceptible to noise. This paper was designed to: 1) study the relationship between ultrasound system noise (primarily time gain compensation induced) and microvessel blood flow signal and 2) propose an adaptive and computationally cost-effective noise equalization method that is independent of hardware or software imaging settings to improve microvessel image quality.

Concepts and Tradeoffs in Velocity Estimation With Plane-Wave Contrast-Enhanced Doppler.

While long Doppler ensembles are, in principle, beneficial for velocity estimates, short acoustic pulses must be used in microbubble contrast-enhanced (CE) Doppler to mitigate microbubble destruction. This introduces inherent tradeoffs in velocity estimates with autocorrelators, which are studied here. A model of the autocorrelation function adapted to the microbubble Doppler signal accounting for transit time, the echo frequency uncertainty, and contrast-agent destruction is derived and validated in vitro. It is further demonstrated that a local measurement of the center frequency of the microbubble echo is essential in order to avoid significant bias in velocity estimates arising from the linear and nonlinear frequency-dependent scattering of microbubbles and compensate for the inherent speckle nature of the received echo frequency. For these reasons, broadband Doppler estimators (2-D autocorrelator and Radon projection) are better suited than simpler narrow-band estimators (1-D autocorrelator and 1-D Fourier transform) for CE flow assessment. A case study of perfusion in a VX-2 carcinoma using CE plane-wave Doppler is also shown. We demonstrate that even when considering all uncertainties associated with microbubble-related decorrelation (destruction, pulse bandwidth, transit time, and flow gradient) and the need for real-time imaging, a coefficient of variation of 4% on the axial velocity is achievable with plane-wave imaging.

Spread-Spectrum Beamforming and Clutter Filtering for Plane-Wave Color Doppler Imaging.

Plane-wave imaging is desirable for its ability to achieve high frame rates, allowing the capture of fast dynamic events and continuous Doppler data. In most implementations of plane-wave imaging, multiple low-resolution images from different plane wave tilt angles are compounded to form a single high-resolution image, thereby reducing the frame rate. Compounding improves the lateral beam profile in the high-resolution image, but it also acts as a low-pass filter in slow time that causes attenuation and aliasing of signals with high Doppler shifts. This paper introduces a spread-spectrum color Doppler imaging method that produces high-resolution images without the use of compounding, thereby eliminating the tradeoff between beam quality, maximum unaliased Doppler frequency, and frame rate. The method uses a long, random sequence of transmit angles rather than a linear sweep of plane wave directions. The random angle sequence randomizes the phase of off-focus (clutter) signals, thereby spreading the clutter power in the Doppler spectrum, while keeping the spectrum of the in-focus signal intact. The ensemble of randomly tilted low-resolution frames also acts as the Doppler ensemble, so it can be much longer than a conventional linear sweep, thereby improving beam formation while also making the slow-time Doppler sampling frequency equal to the pulse repetition frequency. Experiments performed using a carotid artery phantom with constant flow demonstrate that the spread-spectrum method more accurately measures the parabolic flow profile of the vessel and outperforms conventional plane-wave Doppler in both contrast resolution and estimation of high flow velocities. The spread-spectrum method is expected to be valuable for Doppler applications that require measurement of high velocities at high frame rates.

Pulsed Rydberg four-wave mixing with motion-induced dephasing in a thermal vapor.

We report on time-resolved pulsed four-wave mixing (FWM) signals in a thermal Rubidium vapor involving a Rydberg state. We observe FWM signals with dephasing times up to 7 ns, strongly dependent on the excitation bandwidth to the Rydberg state. The excitation to the Rydberg state is driven by a pulsed two-photon transition on ns timescales. Combined with a cw de-excitation laser, a strongly directional and collective emission is generated according to a combination of the phase matching effect and averaging over Doppler classes. In contrast to a previous report (Huber et al. in Phys Rev A 90: 053806, 2014) using off-resonant FWM, at a resonant FWM scheme we observe additional revivals of the signal shortly after the incident pulse has ended. We infer that this is a revival of motion-induced constructive interference between the coherent emissions of the thermal atoms. The resonant FWM scheme reveals a richer temporal structure of the signals, compared to similar, but off-resonant excitation schemes. A simple explanation lies in the selectivity of Doppler classes. Our numerical simulations based on a four-level model including a whole Doppler ensemble can qualitatively describe the data.

Visualizing the Tumor Microvasculature With a Nonlinear Plane-Wave Doppler Imaging Scheme Based on Amplitude Modulation

Imaging with ultrasonic plane waves enables the combination of Doppler and microbubble contrast-enhanced imaging without compromising the Doppler ensemble length, as is the case for conventional line-by-line imaging, thus maintaining flow sensitivity. This permits the separation of conduit flow in large vessels from the perfusion background and the presentation of velocity estimates in real-time. However, the ability to differentiate perfusion from the tissue signal is limited by the contrast-to-tissue (CTR) ratio achieved with the contrast-enhanced pulsing sequence, independently of the acquisition length. One way to improve the CTR is to use a Doppler sequence based on amplitude modulation instead of one based on pulse inversion. In this work, we discuss how amplitude modulation can be adapted to Doppler processing. We show that amplitude modulation Doppler, like pulse inversion Doppler, can separate the signal of moving tissue from that of moving microbubbles, while achieving a better contrast-to-tissue ratio than pulse inversion Doppler, both in vitro and in vivo. Both amplitude modulation Doppler and pulse inversion Doppler yield similar velocity estimates when the bandwidth of the RF echo is properly compensated. Finally, we demonstrate how amplitude modulation Doppler can be used to reveal both the conduit flow and the capillary perfusion at high frame rates in an in vivo tumor.