Combining Slow Flow Techniques With Adaptive Demodulation for Improved Perfusion Ultrasound Imaging Without Contrast

Large Scale in vivo Acquisition, Segmentation and 3D Reconstruction of Cortical Vasculature using μ Doppler Ultrasound Imaging

The brain is composed of a dense and ramified vascular network of arteries, veins and capillaries of various sizes. One way to assess the risk of cerebrovascular pathologies is to use computational models to predict the physiological effects of reduced blood supply and correlate these responses with observations of brain damage. Therefore, it is crucial to establish a detailed 3D organization of the brain vasculature, which could be used to develop more accurate in silico models. To this end, we have adapted our functional ultrasound imaging platform, previously designed for recording large scale activity, to enable rapid and reproducible acquisition, segmentation and reconstruction of the cortical vasculature. For the first time, it allows us to digitize the cortical ∼ 100 - μ m3 spatial resolution. Unlike most available strategies, our approach can be performed in vivo within minutes. Moreover, it is easy to implement since it requires neither exogenous contrast agents nor long post-processing time. Therefore, we performed a cortex-wide reconstruction of the vasculature and its quantitative analysis, including i) classification of descending arteries versus ascending veins in more than 1500 vessels/animal and ii) rapid estimation of their length. Importantly, we confirmed the relevance of our approach in a model of cortical stroke, which allows rapid visualization of the ischemic lesion. This development contributes to extending the capabilities of ultrasound neuroimaging to better understand cerebrovascular pathologies such as stroke, vascular cognitive impairment and brain tumors, and is highly scalable for the clinic.

Correlations between ultrafast power Doppler perfusion imaging variables and clinical disease activity in rheumatoid arthritis: potential applications for diagnosing and treating patients in deep clinical remission

PURPOSE

This study aimed to evaluate the ability of ultrafast power Doppler (PD) to assess disease activity in rheumatoid arthritis (RA) by examining the correlations between variables from ultrafast PD perfusion imaging and clinical measures of disease activity.

METHODS

Thirty-three RA patients underwent clinical assessments of disease activity and ultrasound scans of bilateral wrists using both ultrafast and conventional PD systems. A spatial singular value decomposition filter was applied to the ultrafast PD imaging. Singular vectors representing perfusion and fast flows were selected to produce perfusion images. All images were quantitatively analyzed with computer assistance and scored semiquantitatively (0-3) by a physician for synovial vascularity. The Pearson correlation coefficients between image variables and clinical indices were calculated.

RESULTS

The correlation coefficients ranged from weakly to moderately positive between ultrafast PD variables and clinical indices (r=0.221-0.374, all P<0.05). The strongest correlations were observed for synovial PD brightness with the 28-joint Disease Activity Score based on C-Reactive Protein (DAS28-CRP) and the Simplified Disease Activity Index (SDAI). In patients within the deep clinical remission (dCR) subgroup, synovial PD brightness showed stronger correlations with DAS28-CRP, the Clinical Disease Activity Index, and SDAI (r=0.578-0.641, all P<0.001). The correlation coefficients between conventional PD variables and clinical indices were similar to those observed with ultrafast PD variables.

CONCLUSION

Ultrafast PD imaging effectively extracts capillary blood signals and generates perfusion images. In the RA population, ultrafast PD variables exhibit weak-to-moderate correlations with clinical indices, with these correlations being notably stronger in dCR patients.

A Coded Excitation Framework for High SNR Transcranial Ultrasound Imaging

Robust transcranial ultrasound imaging is difficult due to poor image quality. In particular, low signal-to-noise ratio (SNR) limits sensitivity to blood flow and has hindered clinical translation of transcranial functional ultrasound neuroimaging thus far. In this work, we present a coded excitation framework to increase SNR in transcranial ultrasound without negatively impacting frame rate or image quality. We applied this coded excitation framework in phantom imaging and showed SNR gains as large as 24.78 dB and signal-to-clutter ratio gains as high as 10.66 dB with a 65 bit code. We also analyzed how imaging sequence parameters can impact image quality and showed how coded excitation sequences can be designed to maximize image quality for a given application. In particular, we show that considering the number of active transmit elements and the transmit voltage is critical for coded excitation with long codes. Finally, we applied our coded excitation technique in transcranial imaging of ten adult subjects and showed an average SNR gain of 17.91 ± 0.96 dB without a significant increase in clutter using a 65 bit code. We also performed transcranial power Doppler imaging in three adult subjects and showed contrast and contrast-to-noise ratio improvements of 27.32 ± 8.08 dB and 7.25 ± 1.61 dB, respectively with a 65 bit code. These results show that transcranial functional ultrasound neuroimaging may be possible using coded excitation.

Microvascular Flow Imaging: A State-of-the-Art Review of Clinical Use and Promise

Vascular imaging with color and power Doppler is a useful tool in the assessment of various disease processes. Assessment of blood flow, from infarction and ischemia to hyperemia, in organs, neoplasms, and vessels, is used in nearly every US investigation. Recent developments in this area are sensitive to small-vessel low velocity flow without use of intravenous contrast agents, known as microvascular flow imaging (MVFI). MVFI is more sensitive in detection of small vessels than color, power, and spectral Doppler, reducing the need for follow-up contrast-enhanced US (CEUS), CT, and MRI, except when arterial and venous wash-in and washout characteristics would be helpful in diagnosis. Varying clinical applications of MVFI are reviewed in adult and pediatric populations, including its technical underpinnings. MVFI shows promise in assessment of several conditions including benign and malignant lesions in the liver and kidney, acute pathologic abnormalities in the gallbladder and testes, and superficial lymph nodes. Future potential of MVFI in different conditions (eg, endovascular repair) is discussed. Finally, clinical cases in which MVFI correlated and potentially obviated additional CEUS, CT, or MRI are shown.

Assessment of uterine receptivity by endometrial and sub-endometrial blood flow using SlowflowHD in hormone prepared frozen embryo transfer cycles: a pilot study

PURPOSE

Utilizing SlowflowHD as a measurement of endometrial and sub-endometrial blood flow in women with infertility undergoing frozen embryo transfer (FET) cycles and correlation with pregnancy outcomes.

METHODS

A prospective pilot study of 99 women undergoing hormone replacement FET cycles. Ultrasounds were performed with Voluson E8 at 3-time points: day 15, day of transfer, and 11 days post transfer (T + 11). SlowflowHD Doppler blood flow indices in the endometrium and sub-endometrium were compared in women who achieved pregnancy with those who did not.

RESULTS

Using SlowflowHD, both pregnant and non-pregnant women had similar trends with decreased endometrial blood flow day of transfer compared with day 15. However, there was a borderline significantly lower mean percentage decrease of endometrial blood flow in women achieving a pregnancy (28.3% vs 42.9%). Significantly higher numbers of pregnant women had a 20% or less decrease in blood flow (21 vs 9) with increases in mean percentage blood flow on T + 11 (pregnant 39.59% vs non-pregnant 25.20%). The RI and S/D ratio in the spiral arteries was also significantly higher on transfer day in women who had a live birth RI (0.68 vs 0.65) and S/D (3.91 vs 3.17).

CONCLUSION

There are blood flow changes both in pregnant and non-pregnant patients with decreases in blood flow after progesterone replacement. Pregnancy and live births were associated with a lower mean percentage drop in blood flow from day 15 to the day of transfer and elevated RI and S/D ratio on transfer day.

Ultrafast Power Doppler Imaging Using Frame-Multiply-and-Sum-Based Nonlinear Compounding

Ultrafast power Doppler imaging based on coherent compounding (UPDI-CC) has become a promising technique for microvascular imaging due to its high sensitivity to slow blood flows. However, since this method utilizes a limited number of plane-wave or diverging-wave transmissions for high-frame-rate imaging, it suffers from degraded image quality because of the low contrast resolution. In this article, an ultrafast power Doppler imaging method based on a nonlinear compounding framework, called frame-multiply-and-sum (UPDI-FMAS), is proposed to improve contrast resolution. In UPDI-FMAS, unlike conventional channel-domain delay-multiply-and-sum (DMAS) beamforming, the signal coherence is estimated based on autocorrelation function over plane-wave angle frames. To avoid phase distortion of blood flow signals during the autocorrelation process, clutter filtering is preferentially applied to individual beamformed plane-wave data set. Therefore, only coherent blood flow signals are emphasized, while incoherent background noise is suppressed. The performance of the UPDI-FMAS was evaluated with simulation, phantom, and in vivo studies. For the simulation and phantom studies with a constant laminar flow, the UPDI-FMAS showed improvements in the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) to those of UPDI-CC, i.e., over 10 and 7 dB for 13 plane waves, respectively, and the performances were improved as the number of plane waves increased. Moreover, the enhancement of the image quality due to the increased SNR and CNR in UPDI-FMAS was more clearly depicted with the in vivo study, in which a human kidney and a tumor-bearing mouse were evaluated. These results indicate that the FMAS compounding can improve the image quality of UPDI for microvascular imaging without loss of temporal resolution.

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.

Independent Component-Based Spatiotemporal Clutter Filtering for Slow Flow Ultrasound

Effective tissue clutter filtering is critical for non-contrast ultrasound imaging of slow blood flow in small vessels. Independent component analysis (ICA) has been considered by other groups for ultrasound clutter filtering in the past and was shown to be superior to principal component analysis (PCA)-based methods. However, it has not been considered specifically for slow flow applications or revisited since the onset of other slow flow-focused advancements in beamforming and tissue filtering, namely angled plane wave beamforming and full spatiotemporal singular value decomposition (SVD) (i.e., PCA-based) tissue filtering. In this work, we aim to develop a full spatiotemporal ICA-based tissue filtering technique facilitated by plane wave applications and compare it to SVD filtering. We compare ICA and SVD filtering in terms of optimal image quality in simulations and phantoms as well as in terms of optimal correlation to ground truth blood signal in simulations. Additionally, we propose an adaptive blood independent component sorting and selection method. We show that optimal and adaptive ICA can consistently separate blood from tissue better than principal component analysis (PCA)-based methods using simulations and phantoms. Additionally we demonstrate initial in vivo feasibility in ultrasound data of a liver tumor.

A Spatial Coherence Beamformer Design for Power Doppler Imaging

Acoustic clutter is a primary source of image degradation in ultrasound imaging. In the context of flow imaging, tissue and acoustic clutter signals are often much larger in magnitude than the blood signal, which limits the sensitivity of conventional power Doppler in SNR-limited environments. This has motivated the development of coherence-based beamformers, including Coherent Flow Power Doppler (CFPD), which have demonstrated efficacy in mitigating sources of diffuse clutter. However, CFPD uses a measure of normalized coherence, which incurs a non-linear relationship between image intensity and the magnitude of the blood echo. As a result, CFPD is not a robust approach to study gradation of blood signal energy, which depicts the fractional moving blood volume. We propose the application of mutual intensity, rather than normalized coherence, to retain the clutter suppression capability inherent in coherence beamforming, while preserving the underlying signal energy. Feasibility of this approach was shown via Field II simulations, phantoms, and in vivo human liver data. In addition, we derive an adaptive statistical threshold for the suppression of residual noise signals. Overall, this beamformer design shows promise as an alternative technique to depict flow volume gradation in cluttered imaging environments.

Non-contrast power Doppler ultrasound imaging for early assessment of trans-arterial chemoembolization of liver tumors

Trans-arterial chemoembolization (TACE) is an important yet variably effective treatment for management of hepatic malignancies. Lack of response can be in part due to inability to assess treatment adequacy in real-time. Gold-standard contrast enhanced computed tomography and magnetic resonance imaging, although effective, suffer from treatment-induced artifacts that prevent early treatment evaluation. Non-contrast ultrasound is a potential solution but has historically been ineffective at detecting treatment response. Here, we propose non-contrast ultrasound with recent perfusion-focused advancements as a tool for immediate evaluation of TACE. We demonstrate initial feasibility in an 11-subject pilot study. Treatment-induced changes in tumor perfusion are detected best when combining adaptive demodulation (AD) and singular value decomposition (SVD) techniques. Using a 0.5 s (300-sample) ensemble size, AD + SVD resulted in a 7.42 dB median decrease in tumor power after TACE compared to only a 0.06 dB median decrease with conventional methods.