Improved Sensitivity in Ultrasound Molecular Imaging With Coherence-Based Beamforming

Spatial Coherence in Medical Ultrasound: A Review

Traditional pulse-echo ultrasound imaging heavily relies on the discernment of signals based on their relative magnitudes but is limited in its ability to mitigate sources of image degradation, the most prevalent of which is acoustic clutter. Advances in computing power and data storage have made it possible for echo data to be alternatively analyzed through the lens of spatial coherence, a measure of the similarity of these signals received across an array. Spatial coherence is not currently explicitly calculated on diagnostic ultrasound scanners but a large number of studies indicate that it can be employed to describe image quality, to adaptively select system parameters and to improve imaging and target detection. With the additional insights provided by spatial coherence, it is poised to play a significant role in the future of medical ultrasound. This review details the theory of spatial coherence in pulse-echo ultrasound and key advances made over the last few decades since its introduction in the 1980s.

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.

Phospholipid-coated targeted microbubbles for ultrasound molecular imaging and therapy

Phospholipid-coated microbubbles are ultrasound contrast agents that, when functionalized, adhere to specific biomarkers on cells. In this concise review, we highlight recent developments in strategies for targeting the microbubbles and their use for ultrasound molecular imaging (UMI) and therapy. Recently developed novel targeting strategies include magnetic functionalization, triple targeting, and the use of several new ligands. UMI is a powerful technique for studying disease progression, diagnostic imaging, and monitoring of therapeutic responses. Targeted microbubbles (tMBs) have been used for the treatment of cardiovascular diseases and cancer, with therapeutics either coadministered or loaded onto the tMBs. Regardless of which disease was treated, the use of tMBs always resulted in a better therapeutic outcome than non-tMBs when compared in vitro or in vivo.

Therapeutic Ultrasound Parameter Optimization for Drug Delivery Applied to a Murine Model of Hepatocellular Carcinoma

Ultrasound and microbubble (USMB)-mediated drug delivery is a valuable tool for increasing the efficiency of the delivery of therapeutic agents to cancer while maintaining low systemic toxicity. Typically, selection of USMB drug delivery parameters used in current research settings are either based on previous studies described in the literature or optimized using tissue-mimicking phantoms. However, phantoms rarely mimic in vivo tumor environments, and the selection of parameters should be based on the application or experiment. In the following study, we optimized the therapeutic parameters of the ultrasound drug delivery system to achieve the most efficient in vivo drug delivery using fluorescent semiconducting polymer nanoparticles as a model nanocarrier. We illustrate that voltage, pulse repetition frequency and treatment time (i.e., number of ultrasound pulses per therapy area) delivered to the tumor can successfully be optimized in vivo to ensure effective delivery of the semiconducting polymer nanoparticles to models of hepatocellular carcinoma. The optimal in vivo parameters for USMB drug delivery in this study were 70 V (peak negative pressure = 3.4 MPa, mechanical index = 1.22), 1-Hz pulse repetition frequency and 100-s therapy time. USMB-mediated drug delivery using in vivo optimized ultrasound parameters caused an up to 2.2-fold (p < 0.01) increase in drug delivery to solid tumors compared with that using phantom-optimized ultrasound parameters.

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.

Nondestructive Detection of Targeted Microbubbles Using Dual-Mode Data and Deep Learning for Real-Time Ultrasound Molecular Imaging

Ultrasound molecular imaging (UMI) is enabled by targeted microbubbles (MBs), which are highly reflective ultrasound contrast agents that bind to specific biomarkers. Distinguishing between adherent MBs and background signals can be challenging in vivo. The preferred preclinical technique is differential targeted enhancement (DTE), wherein a strong acoustic pulse is used to destroy MBs to verify their locations. However, DTE intrinsically cannot be used for real-time imaging and may cause undesirable bioeffects. In this work, we propose a simple 4-layer convolutional neural network to nondestructively detect adherent MB signatures. We investigated several types of input data to the network: "anatomy-mode" (fundamental frequency), "contrast-mode" (pulse-inversion harmonic frequency), or both, i.e., "dual-mode", using IQ channel signals, the channel sum, or the channel sum magnitude. Training and evaluation were performed on in vivo mouse tumor data and microvessel phantoms. The dual-mode channel signals yielded optimal performance, achieving a soft Dice coefficient of 0.45 and AUC of 0.91 in two test images. In a volumetric acquisition, the network best detected a breast cancer tumor, resulting in a generalized contrast-to-noise ratio (GCNR) of 0.93 and Kolmogorov-Smirnov statistic (KSS) of 0.86, outperforming both regular contrast mode imaging (GCNR = 0.76, KSS = 0.53) and DTE imaging (GCNR = 0.81, KSS = 0.62). Further development of the methodology is necessary to distinguish free from adherent MBs. These results demonstrate that neural networks can be trained to detect targeted MBs with DTE-like quality using nondestructive dual-mode data, and can be used to facilitate the safe and real-time translation of UMI to clinical applications.

Broadband Generalized Sidelobe Canceler Beamforming Applied to Ultrasonic Imaging

A broadband generalized sidelobe canceler (Broadband-GSC) application for near-field beamforming is proposed. This approach is implemented in the wavelet domain. Broadband-GSC provides a set of complex, adapted apodization weights for each wavelet subband. The proposed method constrains interference and noise signal to improve the lateral resolution with only one single emission. Performance of the proposed beamforming is tested on simulated data obtained with Field II. Experiments have proved that the new beamforming can significantly increase the image quality compared with delay-and-sum (DAS) and synthetic aperture (SA). Imaging of scattering points show that Broadband-GSC improves the lateral resolution by 43.2% and 58.0% compared with SA and DAS, respectively. Meanwhile，Broadband-GSC reduces the peak sidelobe level by 11.6 dB and 26.4 dB compared with SA and DAS, respectively. Plane wave emission experiment indicates that Broadband-GSC can improve the lateral resolution by 44.2% compared with DAS. Furthermore, the new beamforming introduces the possibility for higher frame-rate and higher investigation depth with increased lateral resolution.

Improved Visualization in Difficult-to-Image Stress Echocardiography Patients Using Real-Time Harmonic Spatial Coherence Imaging

Stress echocardiography is used to detect myocardial ischemia by evaluating cardiovascular function both at rest and at elevated heart rates. Stress echocardiography requires excellent visualization of the left ventricle (LV) throughout the cardiac cycle. However, LV endocardial border visualization is often negatively impacted by high levels of clutter associated with patient obesity, which has risen dramatically worldwide in recent decades. Short-lag spatial coherence (SLSC) imaging has demonstrated reduced clutter in several applications. In this work, a computationally efficient formulation of SLSC was implemented into an object-oriented graphics processing unit-based software beamformer, enabling real-time (>30 frames per second) SLSC echocardiography on a research ultrasound scanner. The system was then used to image 15 difficult-to-image stress echocardiography patients in a comparison study of tissue harmonic imaging (THI) and harmonic spatial coherence imaging (HSCI). Video clips of four standard stress echocardiography views acquired with either THI or HSCI were provided in random shuffled order to three experienced readers. Each reader rated the visibility of 17 LV segments as "invisible," "suboptimally visualized," or "well visualized," with the first two categories indicating a need for contrast agent. In a symmetry test unadjusted for patientwise clustering, HSCI demonstrated a clear superiority over THI ( ). When measured on a per-patient basis, the median total score significantly favored HSCI with . When collapsing the ratings to a two-level scale ("needs contrast" versus "well visualized"), HSCI once again showed an overall superiority over THI, with by McNemar test adjusted for clustering.

Local speed of sound estimation in tissue using pulse-echo ultrasound: Model-based approach

A model and method to accurately estimate the local speed of sound in tissue from pulse-echo ultrasound data is presented. The model relates the local speeds of sound along a wave propagation path to the average speed of sound over the path, and allows one to avoid bias in the sound-speed estimates that can result from overlying layers of subcutaneous fat and muscle tissue. Herein, the average speed of sound using the approach by Anderson and Trahey is measured, and then the authors solve the proposed model for the local sound-speed via gradient descent. The sound-speed estimator was tested in a series of simulation and ex vivo phantom experiments using two-layer media as a simple model of abdominal tissue. The bias of the local sound-speed estimates from the bottom layers is less than 6.2 m/s, while the bias of the matched Anderson's estimates is as high as 66 m/s. The local speed-of-sound estimates have higher standard deviation than the Anderson's estimates. When the mean local estimate is computed over a 5-by-5 mm region of interest, its standard deviation is reduced to less than 7 m/s.