Jaime Tierney

A model and regularization scheme for ultrasonic beamforming clutter reduction

Acoustic clutter produced by off-axis and multipath scattering is known to cause image degradation, and in some cases these sources may be the prime determinants of in vivo image quality. We have previously shown some success addressing these sources of image degradation by modeling the aperture domain signal from different sources of clutter, and then decomposing aperture domain data using the modeled sources. Our previous model had some shortcomings including model mismatch and failure to recover B-Mode speckle statistics. These shortcomings are addressed here by developing a better model and by using a general regularization approach appropriate for the model and data. We present results with L1 (lasso), L2 (ridge), and L1/L2 combined (elastic-net) regularization methods. We call our new method aperture domain model image reconstruction (ADMIRE). Our results demonstrate that ADMIRE with L1 regularization, or weighted toward L1 in the case of elastic-net regularization, have improved image quality. L1 by itself works well, but additional improvements are seen with elastic-net regularization over the pure L1 constraint. On in vivo example cases, L1 regularization showed mean contrast improvements of 4.6 and 6.8 dB on fundamental and harmonic images, respectively. Elastic net regularization (α = 0.9) showed mean contrast improvements of 17.8 dB on fundamental images and 11.8 dB on harmonic images. We also demonstrate that in uncluttered Field II simulations the de-cluttering algorithm produces the same contrast, contrast-to-noise ratio, and speckle SNR as normal B-mode imaging, demonstrating that ADMIRE preserves typical image features.

Perfusion imaging with non-contrast ultrasound

A Doppler ultrasound clutter filter that enables estimation of low velocity blood flow could considerably improve ultrasound as a tool for clinical diagnosis and monitoring, including for the evaluation of vascular diseases and tumor perfusion. Conventional Doppler ultrasound is currently used for visualizing and estimating blood flow. However, conventional Doppler is limited by frame rate and tissue clutter caused by involuntary movement of the patient or sonographer. Spectral broadening of the clutter due to tissue motion limits ultrasound’s ability to detect blood flow less than about 5mm/s at an 8MHz center frequency. We propose a clutter filtering technique that may increase the sensitivity of Doppler measurements to at least as low as 0.41mm/s. The proposed filter uses an adaptive demodulation scheme that decreases the bandwidth of the clutter. To test the performance of the adaptive demodulation method at removing sonographer hand motion, six volunteer subjects acquired data from a basic quality assurance phantom. Additionally, to test initial in vivo feasibility, an arterial occlusion reactive hyperemia study was performed to assess the efficiency of the proposed filter at preserving signals from blood velocities 2mm/s or greater. The hand motion study resulted in initial average bandwidths of 577Hz (28.5mm/s), which were decreased to 7.28Hz (0.36mm/s) at -60 dB at 3cm using our approach. The in vivo power Doppler study resulted in 15.2dB and 0.15dB dynamic ranges between the lowest and highest blood flow time points for the proposed filter and conventional 50Hz high pass filter, respectively.

Adaptive Clutter Demodulation for Non-Contrast Ultrasound Perfusion Imaging

Conventional Doppler ultrasound is useful for visualizing fast blood flow in large resolvable vessels. However, frame rate and tissue clutter caused by movement of the patient or sonographer make visualizing slow flow with ultrasound difficult. Patient and sonographer motion causes spectral broadening of the clutter signal, which limits ultrasound’s sensitivity to velocities greater than 5–10 mm/s for typical clinical imaging frequencies. To address this, we propose a clutter filtering technique that may increase the sensitivity of Doppler measurements to at least as low as 0.52 mm/s. The proposed technique uses plane wave imaging and an adaptive frequency and amplitude demodulation scheme to decrease the bandwidth of tissue clutter. To test the performance of the adaptive demodulation method at suppressing tissue clutter bandwidths due to sonographer hand motion alone, six volunteer subjects acquired data from a stationary phantom. Additionally, to test in vivo feasibility, arterial occlusion and muscle contraction studies were performed to assess the efficiency of the proposed filter at preserving signals from blood velocities 2 mm/s or greater at a 7.8 MHz center frequency. The hand motion study resulted in initial average bandwidths of 175 Hz (8.60mm/s), which were decreased to 10.5 Hz (0.52 mm/s) at −60 dB using our approach. The in vivo power Doppler studies resulted in 4.73 dB and 4.80 dB dynamic ranges of the blood flow with the proposed filter and 0.15 dB and 0.16 dB dynamic ranges of the blood flow with a conventional 50 Hz high-pass filter for the occlusion and contraction studies, respectively.

Plane wave perfusion ultrasound imaging without contrast

Perfusion imaging with conventional Doppler ultrasound is difficult due to frame rate and tissue clutter limitations. Consequently, conventional methods are only sensitive to velocities above 5-10mm/s for typical clinical imaging frequencies. To overcome this limitation and simultaneously address the frame rate and tissue clutter problems, we propose a technique that uses plane wave sequencing and an adaptive tissue clutter frequency and amplitude demodulation scheme. Suppression of tissue clutter due to sonographer hand motion was tested using phantoms and showed potential for increased Doppler sensitivity to at least as low as 1.17mm/s. Additionally, feasibility of the method is demonstrated in vivo using muscle contractions of a human calf, which resulted in 2.54dB and 0.12dB dynamic ranges of blood flow through slow-time for the proposed and conventional methods, respectively.

Feasibility of non-linear beamforming ultrasound methods to characterize and size kidney stones

Purpose Ultrasound methods for kidney stone imaging suffer from poor sensitivity and size overestimation. The study objective was to demonstrate feasibility of non-linear ultrasound beamforming methods for stone imaging, including plane wave synthetic focusing (PWSF), short-lag spatial coherence (SLSC) imaging, mid-lag spatial coherence (MLSC) imaging with incoherent compounding, and aperture domain model image reconstruction (ADMIRE). Materials and methods The ultrasound techniques were evaluated in an in vitro kidney stone model and in a pilot study of 5 human stone formers (n = 6 stones). Stone contrast, contrast-to-noise ratio (CNR), sizing, posterior shadow contrast, and shadow width sizing were compared among the different techniques and to B-mode. CT imaging within 60 days was considered the gold standard stone size. Paired t-tests using Bonferroni correction were performed to evaluate comparing each technique with B-mode. Results Mean CT measured stone size was 6.0mm (range 2.9–12.2mm) with mean skin-to-stone distance 10.2cm (range 5.4–16.3cm). Compared to B-mode, stone contrast was best with ADMIRE (mean +12.2dB), while SLSC and MLSC showed statistically improved CNR. Sizing was best with ADMIRE (mean +1.3mm error), however this was not significantly improved over B-mode (+2.4mm). PWSF performed similarly to B-mode for stone contrast, CNR, SNR, and stone sizing. In the in vitro model, the shadow contrast was highest with ADMIRE (mean 10.5 dB vs 3.1 dB with B-mode). Shadow sizing was best with SLSC (mean error +0.9mm ± 2.9), however the difference compared to B-mode was not significant. Conclusions The detection and sizing of stones are feasible with advanced beamforming methods with ultrasound. ADMIRE, SLSC, and MLSC hold promise for improving stone detection, shadow contrast, and sizing.

Combining adaptive demodulation with singular value decomposition filtering for improved non-contrast perfusion ultrasound imaging

Tissue clutter caused by patient and sonographer hand motion makes perfusion ultrasound imaging difficult. We previously introduced an adaptive frequency and amplitude demodulation scheme to address this challenge. Our initial implementation used a conventional high-pass infinite impulse response (IIR) filter to attenuate the tissue signal after applying adaptive demodulation. However, other groups have shown that singular value decomposition (SVD) filtering is superior to conventional frequency domain filters. Here we evaluate the SVD filter both in comparison and in conjunction with our proposed adaptive demodulation technique. Blood-to-background SNRs were compared using power Doppler images made from single small vessel simulations with realistic tissue clutter. Additionally, filtering methods were qualitatively assessed using power Doppler images of a cut-in-half perfusion-mimicking phantom. Furthermore, in vivo power Doppler images were compared before and after muscle contraction. SVD filtering with adaptive demodulation resulted in a 7dB increase in simulated blood-to-background SNR compared to a conventional IIR filter and a 54.6% increase in power after in vivo muscle contraction compared to a 1.74% increase using a conventional IIR filter.

Perfusion flow phantoms with randomly oriented microchannels

Interest in ultrasound perfusion imaging has grown with the development of more sensitive algorithms to detect slow blood flow. Unfortunately, there are not many phantoms that can be used to evaluate these techniques. Some have used small linear tubes, while others have adapted dialysis cartridges. Here we propose a technique using conventional gelatin cast around a sacrificial polymer network. Specifically, we form a gelatin phantom, doped with graphite scatterers to mimic the diffuse scattering in soft tissue, around a polymer resin. The resin structure can be dissolved leaving behind a network of small randomly oriented channels that are connected to a large channel which is connected to a pump to perfuse blood mimicking fluid through the phantom. The phantoms were qualitatively demonstrated to show perfusion through visual confirmation and the speckle SNR, and speed of sound were calculated.

Ultrasonic non-contrast perfusion imaging with adaptive demodulation

Ultrasonic non-contrast perfusion imaging remains challenging due to spectral broadening of the tissue clutter signal caused by patient and sonographer hand motion. Simply, the velocity of the slowest moving blood has similar spectral support to the moving tissue. To address this problem, we developed an adaptive demodulation (AD) scheme to suppress the bandwidth of tissue prior to high-pass filtering. The method works by directly estimating the modulation imposed by tissue motion, and then removing that motion from the signal. Our initial implementation used single plane wave power Doppler imaging sequence combined with a conventional high-pass IIR tissue filter. However, other recent advancements in beamforming and tissue filtering have been proposed for improved slow-flow imaging, including coherent flow power Doppler (CFPD) and singular value decomposition (SVD). Here, we aim to evaluate AD separately as well as in comparison and in conjunction with improvements in beamforming and filtering using simu...

Perfusion flow phantoms with many variably oriented micro channels

Ultrasound perfusion imaging with and without contrast agents continues to be an exciting pre-clinical and clinical problem as ultrasound systems and algorithms get more sensitive to slow blood flow. Unfortunately, there have been few phantoms to help develop these techniques. Some have used very small straight tubes, while others have adapted dialysis cartridges. Here, we form a gelatin phantom around a polymer resin template. Then, the resin structure is dissolved leaving behind a network of small randomly oriented channels. These small microchannels are connected to a large channel and then connected to a pump to perfuse blood-mimicking fluid through the phantom.

Non-linear beamforming approaches for sizing and detecting large calcifications

Standard B-mode imaging has poor sensitivity and specificity for detecting kidney stones and consistently overestimates stone size. Because of this, the acoustic shadow produced by the stone and twinkling artifacts seen with color Doppler have been used as substitutes for conventional imaging for stone sizing and detection. However, often neither a shadow nor a color Doppler artifact are present. In this study, the use of several non-linear beamforming strategies was investigated in conjunction with plane wave synthetic focusing (PWSF). These include aperture domain model image reconstruction (ADMIRE), short-lag spatial coherence (SLSC), and a new mid-lag spatial coherence (MLSC) method designed specifically for kidney stone detection but not sizing. Evaluations of all four methods were performed in vitro and ex vivo. For the in vitro evaluation, various sized kidney stones (n=8 with width 9.88±5.96mm) were placed on top of a gelatin phantom doped with graphite, which served as a platform and provided a diffuse scattering background for comparisons. The stones were imaged at a depth of 4 cm and 8 cm. An ex vivo evaluation was also performed where several stones were implanted into pig kidneys. The pig kidneys were immersed in water for imaging. The in vitro sizing errors for all stones at both depths for PWSF, ADMIRE, SLSC, and MLSC were 0.89±0.74mm, 0.57±0.69mm, 0.96±1.31mm, and −0.92±3.12mm, respectively. For sizing, ADMIRE performs best in vitro, but in the ex vivo study delineation of the border was unclear. For detection, the custom MLSC method was able to achieve excellent discrimination between the stones and the diffuse scattering media with a constant threshold across all sets.