Higher-order Singular Value Decomposition Filter for Contrast Echocardiography

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 could not provide adequate image quality. The contrast agent’s visibility in the myocardium is generally poor, impaired by motion and non-linear propagation artifacts. The established multi-pulse contrast schemes (MPCS) and the more experimental singular value decomposition (SVD) filter also fall short to solve these issues. Here, we propose a scheme to process AM/AMPI echoes with higher-order singular value decomposition (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 10dB and 14dB, respectively. In vivo porcine heart results also demonstrate that, compared to AM, HOSVD improves CBR in open-chest acquisition (up to 19dB) and contrast ratio in closed-chest acquisition (3dB)

High-Frame-Rate Volumetric Porcine Renal Vasculature Imaging

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.</p

High-frame-rate contrast-enhanced echography for myocardial perfusion assessment

Cardiovascular disease remains a significant global burden, standing as the leading cause of death. Annually, millions of people are diagnosed with angina and myocardial infarction (MI) worlwide, with over 3 million cases reported in the European Union alone. Acute MI, particularly ST-segment elevation MI (STEMI) is associated with substantial morbidity and mortality. Prompt primary percutaneous intervention (PPCI) is the preferred treatment, reopening occluded vessels with a high success rate. Despite this, the no-reflow (NR) phenomenon, characterized by microvascular obstruction, can lead to inadequate myocardial perfusion even after successful epicardial flow restoration, thereby increasing the risk of adverse outcomes post-MI.Current diagnostic methods used to assess myocardial perfusion and diagnose NR have certain limitations, including varying levels of accuracy and potential harm if performed repeatedly due to the presence of ionizing radiation. Echocardiography emerges as a promising option due to its accessibility, cost-effectiveness, and absence of ionizing radiation. The adoption of gas-filled coated bubbles with the size of few micrometers (microbubbles) as ultrasound contrast agents (UCAs) has improved echocardiography sensitivity to detect blood flow. However, challenges remain in producing reliable perfusion images due to noise, image artifacts, variability, and operator dependence despite the use of UCAs.This thesis addresses these challenges by developing contrast imaging techniques that improve contrast-enhanced ultrasound (CEUS) image quality and contrast detection compared to the standard imaging methods. It could lead to CEUS becoming a reliable method for assessing myocardial perfusion and monitoring NR. This would have significant clinical implications, improving decision-making in patient treatment and understanding NR mechanism.First, in Chapter 2 we explored the capabilities and limitations of the spatiotemporal implementation of SVD as a clutter filter to separate microbubble and tissue signals. We conducted an in vitro experiment and found that SVD is ineffective in detecting slow flow during tissue motion, which is the condition of myocardial perfusion. Thus, we introduced Independent Component Analysis (ICA) as a post-processing technique to improve contrast detection by exploiting the distinct statistical distributions of microbuble and tissue signal. Our in vitro results show that ICA improves SVD detection by 7-10 dB during motion.Next, we incorporated the nonlinear response of microbubbles to enhance contrast detection. The standard technique to exploit this property is the Multi-Pulse Contrast Scheme (MPCS), including techniques like pulse inversion (PI), amplitude modulation (AM), and their combination (AMPI). On top of the motion artifacts, the nonlinear propagation through the microbubble cloud also reduces contrast detection when using the MPCS technique. In Chapter 3, we developed a contrast detection technique using higher-order singular value decomposition (HOSVD), a generalization of SVD that works on high-order tensors. HOSVD is applied to a beamformed IQ image series, with spatial, temporal, and pulsing sequence as the input dimensions. We conducted both in vitro and in vivo experiments to evaluate the efficacy of this technique in comparison to the current standard methods. in vitro results, particularly in scenarios involving motion, demonstrated that HOSVD outperformed the existing standard contrast detection schemes by over 10 dB. We also validated the viability of HOSVD implementation in a more realistic in vivo experiment utilizing a cardiac porcine model. HOSVD showed the superior capability to detect microbubble signal within the myocardium, surpassing the AM contrast-to-background ratio by up to 19 dB. On Chapter 4, we furthered our investigation with the porcine cardiac model to visualize coronary vascular dynamics and identify perfusion deficits by inducing occlusion in the left anterior descending (LAD) artery. We successfully differentiated between fast and slow coronary flows, assumed to represent flow in larger vessels and perfusion. This distinction enhanced our confidence in evaluating myocardial perfusion. Moreover, we accurately visualized the affected area in the myocardium caused by the LAD occlusion.To improve reproducibility and errors due to out-of-plane motion, we explored the implementation of 3D ultrasound imaging. The 3D part of the thesis begins with Chapter 5. We developed an image reconstruction technique for data acquired with the in-house developed spiral array probe. We adjusted the "lags" on the spatial coherence (SC) beamforming and show it capabilities to improve image quality compared to traditional Delay and Sum (DAS) technique. Our in vitro and in vivo experiments, employing a chicken embryo model results showed that SC outperformed conventional DAS beamforming by up to 25 dB. In chapter 6, the focus shifts to in vivo studies using big animal model. We utilize porcine kidney model to visualize renal cortex microcirculation and measure Doppler velocity in vessels. The results are validated against commercial Doppler and contrast-enhanced imaging. Super-resolution imaging is introduced to enhance the visualization of microvascular structures. Chapter 7 builds upon the previous techniques by implementing HOSVD on high-frame-rate volumetric images, beamformed with SC technique. In vitro and in vivo experiments demonstrate the improved contrast detection capabilities of this approach. The chapter concludes with successful visualization of the coronary artery using HOSVD and SC on a porcine model.Lastly, in Chapter 8, we presented the key findings, challenges, and limitations of this thesis. We also shared some technical insights based on unpublished results and provided technical suggestions and clinical implications for future research.<br/

In vitro pharmacokinetic phantom for two-compartment modeling in DCE-MRI

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

In vitro pharmacokinetic phantom for two-compartment modeling in DCE-MRI

\u3cp\u3eDynamic 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.\u3c/p\u3

High Frame Rate Volumetric Imaging of Microbubbles Using a Sparse Array and Spatial Coherence Beamforming

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. </p