Objective: Assessing myocardial perfusion in acute myocardial infarction is important for guiding clinicians in choosing appropriate treatment strategies. Echocardiography can be used due to its direct feedback and bedside nature, but it currently faces image quality issues and an inability to differentiate coronary macro- from micro-circulation. We previously developed an imaging scheme using high frame-rate contrast-enhanced ultrasound (HFR CEUS) with higher order singular value decomposition (HOSVD) that provides dynamic perfusion and vascular flow visualization. In this study, we aim to show the ability of this technique to image perfusion deficits and investigate the potential occurrence of false-positive contrast detection. Methods: We used a porcine model comprising occlusion and release of the left anterior descending coronary artery. During slow contrast agent infusion, the afore-mentioned imaging scheme was used to capture and process the data offline using HOSVD. Results: Fast and slow coronary flow was successfully differentiated, presumably representing the different compartments of the micro-circulation. Low perfusion was seen in the area that was affected, as expected by vascular occlusion. Furthermore, we also imaged coronary flow dynamics before, during and after release of the occlusion, the latter showing hyperemia as expected. A contrast agent destruction test showed that the processed images contained actual contrast signal in the cardiac phases with minimal motion. With larger tissue motion, tissue signal leaked into the contrast-enhanced images. Conclusion: Our results demonstrate the feasibility of HFR CEUS with HOSVD as a viable option for assessing myocardial perfusion. Flow dynamics were resolved, which potentially helped to directly evaluate coronary flow deficits.

Assessing the coronary circulation with contrast-enhanced echocardiography has high clinical relevance. However, it is not being routinely performed in clinical practice because the current clinical tools generally cannot provide adequate image quality. The contrast agent's visibility in the myocardium is generally poor, impaired by motion and nonlinear propagation artifacts. The established multipulse contrast schemes (MPCSs) and the more experimental singular value decomposition (SVD) filter also fall short to solve these issues. Here, we propose a scheme to process amplitude modulation/amplitude-modulated pulse inversion (AM/AMPI) echoes with higher order SVD (HOSVD) instead of conventionally summing the complementary pulses. The echoes from the complementary pulses form a separate dimension in the HOSVD algorithm. Then, removing the ranks in that dimension with dominant coherent signals coming from tissue scattering would provide the contrast detection. We performed both in vitro and in vivo experiments to assess the performance of our proposed method in comparison with the current standard methods. A flow phantom study shows that HOSVD on AM pulsing exceeds the contrast-to-background ratio (CBR) of conventional AM and an SVD filter by 10 and 14 dB, respectively. In vivo porcine heart results also demonstrate that, compared to AM, HOSVD improves CBR in open-chest acquisition (up to 19 dB) and contrast ratio (CR) in closed-chest acquisition (3 dB).

Objective: The aim of this study was to assess the feasibility and imaging options of contrast-enhanced volumetric ultrasound kidney vasculature imaging in a porcine model using a prototype sparse spiral array. Methods: Transcutaneous freehand in vivo imaging of two healthy porcine kidneys was performed according to three protocols with different microbubble concentrations and transmission sequences. Combining high-frame-rate transmission sequences with our previously described spatial coherence beamformer, we determined the ability to produce detailed volumetric images of the vasculature. We also determined power, color and spectral Doppler, as well as super-resolved microvasculature in a volume. The results were compared against a clinical 2-D ultrasound machine. Results: Three-dimensional visualization of the kidney vasculature structure and blood flow was possible with our method. Good structural agreement was found between the visualized vasculature structure and the 2-D reference. Microvasculature patterns in the kidney cortex were visible with super-resolution processing. Blood flow velocity estimations were within a physiological range and pattern, also in agreement with the 2-D reference results. Conclusion: Volumetric imaging of the kidney vasculature was possible using a prototype sparse spiral array. Reliable structural and temporal information could be extracted from these imaging results.

Suppressing tissue clutter is an essential step in blood flow estimation and visualization, even when using ultrasound contrast agents. Blind source separation (BSS)-based clutter filter for high-framerate ultrasound imaging has been reported to perform better in tissue clutter suppression than the conventional frequency-based wall filter and nonlinear contrast pulsing schemes. The most notable BSS technique, singular value decomposition (SVD) has shown compelling results in cases of slow tissue motion. However, its performance degrades when the tissue motion is faster than the blood flow speed, conditions that are likely to occur when imaging the small vessels, such as in the myocardium. Independent component analysis (ICA) is another BSS technique that has been implemented as a clutter filter in the spatiotemporal domain. Instead, we propose to implement ICA in the spatial domain where motion should have less impact. In this work, we propose a clutter filter with the combination of SVD and ICA to improve the contrast-to-background ratio (CBR) in cases where tissue velocity is significantly faster than the flow speed. In an in vitro study, the range of fast tissue motion velocity was 5-25 mm/s and the range of flow speed was 1-12 mm/s. Our results show that the combination of ICA and SVD yields 7-10 dB higher CBR than SVD alone, especially in the tissue high-velocity range. The improvement is crucial for cardiac imaging where relatively fast myocardial motions are expected.

3-D contrast enhanced ultrasound enables better visualization of inherently 3-D vascular geometries compared to an intersecting plane. Additionally, it would allow the application of motion correction techniques for all directions. Both contrast detection and motion correction work better on high-frame rate data. However high-frame rate 3-D ultrasound imaging with dense matrix arrays is challenging to realize. Sparse arrays alleviate some of the limitations in cable count and data rate that fully populated arrays encounter, but their increased level of secondary lobes negatively impacts image contrast. Meanwhile the use of unfocused transmit beams needed to achieve high-frame rates negatively impacts resolution. Here we propose to use adaptive beamforming by deep learning (ABLE) to improve the image quality of contrast enhanced ultrasound images acquired with a sparse spiral array. We train the neural network on simulated data and evaluate simulated images and in vivo images of an ex ovo chicken embryo. ABLE improved resolution compared to delay-and-sum (DAS) and spatial coherence (SC) beamforming on the simulated and in vivo data. The qualitative improvements persist after histogram matching, indicating that the image quality improvement of the ABLE images was not purely due to dynamic range stretching.

Two-dimensional (2-D) arrays offer volumetric imaging capabilities without the need for probe translation or rotation. A sparse array with elements seeded in a tapering spiral pattern enables one-to-one connection to an ultrasound machine, thus allowing flexible transmission and reception strategies. To test the concept of sparse spiral array imaging, we have designed, realized, and characterized two prototype probes designed at 2.5-MHz low-frequency (LF) and 5-MHz high-frequency (HF) center frequencies. Both probes share the same electronic design, based on piezoelectric ceramics and rapid prototyping with printed circuit board substrates to wire the elements to external connectors. Different center frequencies were achieved by adjusting the piezoelectric layer thickness. The LF and HF prototype probes had 88% and 95% of working elements, producing peak pressures of 21 and 96 kPa/V when focused at 5 and 3 cm, respectively. The one-way -3-dB bandwidths were 26% and 32%. These results, together with experimental tests on tissue-mimicking phantoms, show that the probes are viable for volumetric imaging.

Volumetric ultrasound imaging of blood flow with microbubbles enables a more complete visualization of the microvasculature. Sparse arrays are ideal candidates to perform volumetric imaging at reduced manufacturing complexity and cable count. However, due to the small number of transducer elements, sparse arrays often come with high clutter levels, especially when wide beams are transmitted to increase the frame rate. In this study, we demonstrate with a prototype sparse array probe and a diverging wave transmission strategy, that a uniform transmission field can be achieved. With the implementation of a spatial coherence beamformer, the background clutter signal can be effectively suppressed, leading to a signal to background ratio improvement of 25 dB. With this approach, we demonstrate the volumetric visualization of single microbubbles in a tissue-mimicking phantom as well as vasculature mapping in a live chicken embryo chorioallantoic membrane.