Volumetric ultrasound imaging of blood flow with microbubbles enables 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, 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.
Contrast-enhanced ultrasound is a diagnostic tool used to visualize blood flow in the cardiovascular system. The use of ultrasound contrast agent (microbubbles) in combination with contrast pulsing scheme (CPS) improves the sensitivity and specificity of ultrasound flow imaging by enhancing the signal in the blood compartment. The commonly used CPS are pulse inversion (PI), amplitude modulation (AM), and amplitude-modulated pulse inversion (AMPI). Using differences in phase or amplitude of multiple pulses, the linear tissue clutter signal can be suppressed. However, this process can be degraded by motion or non-linear propagation of the ultrasound wave. These effects cause the cancellation of linear clutter signal to be ineffective We propose using higher-order singular value decomposition (HOSVD) with spatial, temporal, and pulsing dimensions as the input to improve clutter suppression under the conditions of motion and non-linear propagation. We performed systematic in-vitro- experiment emulating these conditions, as well as in-vivo cardiac measurements. The results showed that HOSVD increases the clutter suppression of all the 3 CPS compared to the conventional linear processing. The improvement of clutter reduction could be beneficial to various cardiac evaluation like myocardial perfusion or intra ventricular flow assessment.
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is an established minimally-invasive method for assessment of extravascular leakage, hemodynamics, and tissue viability. However, differences in acquisition protocols, variety of pharmacokinetic models, and uncertainty on physical sources of MR signal hamper the reliability and widespread use of DCE-MRI in clinical practice. Measurements performed in a controlled in vitro setup could be used as a basis for standardization of the acquisition procedure, as well as objective evaluation and comparison of pharmacokinetic models. In this paper, we present a novel flow phantom that mimics a two-compartmental (blood plasma and extravascular extracellular space/EES) vascular bed, enabling systemic validation of acquisition protocols. The phantom consisted of a hemodialysis filter with two compartments, separated by hollow fiber membranes. The aim of this phantom was to vary the extravasation rate by adjusting the flow in the two compartments. Contrast agent transport kinetics within the phantom was interpreted using two-compartmental pharmacokinetic models. Boluses of gadolinium-based contrast-agent were injected in a tube network connected to the hollow fiber phantom; time-intensity curves (TICs) were obtained from image series, acquired using a T1-weighted DCE-MRI sequence. Under the assumption of a linear dilution system, the TICs obtained from the input and output of the system were then analyzed by a system identification approach to estimate the trans-membrane extravasation rates in different flow conditions. To this end, model-based deconvolution was employed to determine (identify) the impulse response of the investigated dilution system. The flow rates in the EES compartment significantly and consistently influenced the estimated extravasation rates, in line with the expected trends based on simulation results. The proposed phantom can therefore be used to model a two-compartmental vascular bed and can be employed to test and optimize DCE-MRI acquisition sequences in order to determine a standardized acquisition procedure leading to consistent quantification 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 frame rate 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 which 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.
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