It is a common desire to break traditional limits of sampling, circumventing Nyquist requirements using advanced statistical algorithms. In cardiac ultrasound imaging, reducing the number of transmissions per frame, thereby breaking spatial sampling restrictions, enables capturing faster moving structures or larger fields of view. However, the spatial and temporal image properties that may enable such acceleration have been underexplored in the ultrasound literature. This work provides a fundamental study of the structure of ultrasound images using simulations, phantoms, and in vivo cardiac data to quantify tensor rank and spatial/temporal roughness and explores the implications for tensor completion algorithms. Although low-rank reconstruction is a powerful approach that has been previously applied in this context, these data do not appear to be sufficiently low-rank for high-quality reconstructions. Two methods relying on local information—inverse distance-weighted (IDW) interpolation and the fast multiway delay-embedding transform—demonstrate significantly more accurate reconstruction (e.g., structured similarity index measure 0.76 vs 0.67 at 25% sampling and 0.63 vs 0.38 at 10% sampling for IDW versus low-rank reconstruction). Roughness in both space and time is shown to inversely correlate with tensor completion success. Motion compensation is shown to reduce both temporal roughness and rank, improving tensor completion.

Acquiring ultrasound images with high temporal resolution is essential for capturing motion in dynamic environments such as the heart. Conventional high-frame-rate approaches accelerate acquisition but often compromise image quality, reducing resolution, signal-to-noise ratio, and increasing motion artifacts. Multi-line transmit (MLT) imaging offers faster acquisition by generating multiple focused beams simultaneously. However, MLT images are degraded by crosstalk artifacts due to the interference between the simultaneous multiple beams. We introduce Multi-Line Transmit Incorporating Phase Linear Encoding with Synthetic Aperture decoding (MuLTIPLE-SA) to suppress crosstalk artifacts inherent to MLT, resulting in image quality comparable to that of standard single-line transmission (SLT) at accelerated acquisition rates. Our spatiotemporal encoding scheme uses Hadamard-based polarity or delay encoding across simultaneous beams. Synthetic aperture techniques are then used to combine multiple transmissions while decoding the echo signals to separate the contributions of each beam. MuLTIPLE-SA was evaluated in simulations, tissue-mimicking phantoms, and in vivo cardiac imaging. The combination of phase based encoding and synthetic aperture decoding reduced crosstalk artifacts, shown through reduced clutter and improved spatial coherence, and improved resolution due to synthetic focusing. Conventional MLT exhibited strong off-axis crosstalk, whereas MuLTIPLE-SA suppressed crosstalk by up to 27 dB on point targets, restoring image quality comparable to SLT while maintaining MLT's high frame-rate benefits. In a representative cardiac experiment, MuLTIPLE-SA improved generalized contrast-to-noise ratio (gCNR) in the right ventricle from 0.31 (conventional MLT) to 0.52, fully recovering SLT-level contrast by suppressing receive crosstalk. These findings demonstrate that MuLTIPLE-SA enables high temporal resolution without sacrificing image quality.

Cardiac ultrasound requires high frame rates to capture the dynamic motion of tissues. Developing high frame rate imaging sequences necessitates the reduction of sampling requirements, specifically reducing the number of pulse echo events to decrease the capture time of each frame (each event governed by the round-trip time of flight). It has been previously demonstrated that spatial and temporal similarities in the echo data can be exploited to intentionally undersample the data (missing up to 75% of beams) and robustly reconstruct missing beams using matrix-based tensor completion, an optimization based on rank minimization. We believe that this approach may miss the full multidimensional information contained in a multi-frame image tensor, especially local information. In this work, we evaluate the matrix-based low rank completion approach versus alternative tensor completion methods for cardiac data missing up to 87.5% of beams, an 8x acceleration for data acquisition. We also perform initial investigation into the rank and smoothness properties of the data that may impact the ability to perform tensor completion. We demonstrate that motion compensation is one possible post-processing approach to improve these properties and correspondingly improve tensor completion.

Achieving higher resolution for deeper tissue structures remains a significant challenge in ultrasound (US) imaging due to the inherent limitations of diffraction. Swept synthetic aperture (SSA) techniques, which utilize the motion of a single transducer to effectively increase the imaging aperture, offer a promising solution. Building on SSA, we propose that freehand SSA provides a flexible approach with real-time adaptability to varying patient anatomies. This article introduces the optically tracked SSA (OT-SSA) platform, an approach that integrates external tracking to ensure accurate transducer positioning during freehand sweeps. Key sources of image degradation, such as spatial calibration error, tracking precision, and out-of-plane motion were directly analyzed and addressed within the system. In in vivo quadriceps imaging, OT-SSA reduced average lateral speckle autocorrelation size from 2.33 to 0.49 mm compared to a stationary aperture, demonstrating substantial resolution gains. The results establish OT-SSA as a robust and adaptable approach for high-resolution imaging.

Multi-line transmit (MLT) imaging enables the acquisition of high frame rate (HFR) data in ultrasound imaging, especially in echocardiography where capturing rapid events associated with heart motion can provide valuable information for disease diagnosis. MLT beams are generated by simultaneously transmitting multiple focused beams in different spatial directions within a single pulse-echo event. The main drawback of MLT imaging is the generation of crosstalk artifacts due to the interferences between multiple beams and targets, which will in turn decorrelate the backscattered echoes and will reduce the spatial coherence significantly, leading to poor image quality. In this study, we have investigated the effects of synthetic focusing on the overall coherence of the received signals. We have shown that achieving more accurate focusing due to the implementation of synthetic aperture beamformers could be less susceptible to the artifacts introduced with MLT, and this will in turn improve the coherence of the backscattered signals, resulting in an improved image quality. Simulation, phantom, and in-vivo experiments have been conducted to demonstrate that spatial coherence enhances as a result of synthetic focusing in MLT imaging (especially away from the transmit focus). Furthermore, we have implemented synthetic aperture methods together with coherence-based techniques to investigate their synergistic performance in further suppressing the incoherent backscattered echoes and improving target detectability. The results demonstrate that this provides considerable benefits in rejecting MLT crosstalk artifacts compared to the conventional dynamic receive focusing.

Achieving higher frame rates in ultrasound imaging using traditional transmission methods often involves trade-offs, including reduced resolution and compromised signal-to-noise ratio (SNR). As a promising alternative, multi-line transmit (MLT) imaging has been introduced, where multiple focused beams are generated and insonified simultaneously in various directions, facilitating high frame rate data acquisition. Despite maintaining high SNR and spatial resolution, MLT is known to be susceptible to significant interference between the multiple beams, leading to crosstalk artifacts in the backscattered echoes and consequently degrading the overall image quality. The main objective of this study is to effectively remove these artifacts rather than merely suppressing them by employing spatiotemporal encoding techniques, thereby enhancing the image quality in high-frame rate ultrasound imaging. Specifically, we have presented two encoding methods for separating MLT beams: polarity-encoded MLT and delay-encoded MLT. Both encoding schemes are designed around a Hadamard matrix framework, with the former applying polarity apodization to the simultaneous beams and the latter implementing a zero or half-period time delay. The coding schemes were paired with a linear decoding process to eliminate crosstalk artifacts, and hence improving image quality without compromising the frame rate. We demonstrate that applying encoding schemes in combination with synthetic aperture focusing methods leads to significant improvements in resolution and overall coherence in the point target simulations and in vivo cardiac images, respectively.

The rapid advancement in the field of medical imaging presents a challenge in keeping up to date with the necessary objective evaluations and optimizations for safe and effective use in clinical settings. These evaluations are traditionally done using clinical imaging trials, which while effective, pose several limitations including high costs, ethical considerations for repetitive experiments, time constraints, and lack of ground truth. To tackle these issues, virtual trials (aka in silico trials) have emerged as a promising alternative, using computational models of human subjects and imaging devices, and observer models/analysis to carry out experiments. To facilitate the widespread use of virtual trials within the medical imaging research community, a major need is to establish a common consensus framework that all can use. Based on the ongoing efforts of an AAPM Task Group (TG387), this article provides a comprehensive overview of the requirements for establishing virtual imaging trial frameworks, paving the way toward their widespread use within the medical imaging research community. These requirements include credibility, reproducibility, and accessibility. Credibility assessment involves verification, validation, uncertainty quantification, and sensitivity analysis, ensuring the accuracy and realism of computational models. A proper credibility assessment requires a clear context of use and the questions that the study is intended to objectively answer. For reproducibility and accessibility, this article highlights the need for detailed documentation, user-friendly software packages, and standard input/output formats. Challenges in data and software sharing, including proprietary data and inconsistent file formats, are discussed. Recommended solutions to enhance accessibility include containerized environments and data-sharing hubs, along with following standards such as CDISC (Clinical Data Interchange Standards Consortium). By addressing challenges associated with credibility, reproducibility, and accessibility, virtual imaging trials can be positioned as a powerful and inclusive resource, advancing medical imaging innovation and regulatory science.

Objective: The transmit encoding model for synthetic aperture imaging is a robust and flexible framework for understanding the effects of acoustic transmission on ultrasound image reconstruction. Our objective is to use machine learning (ML) to construct scanning sequences, parameterized by time delays and apodization weights, that produce high-quality B-mode images. Approach: We use a custom ML model in PyTorch with simulated RF data from Field II to probe the space of possible encoding sequences for those that minimize a loss function that describes image quality. This approach is made computationally feasible by a novel formulation of the derivative for delay-and-sum beamforming. Main Results: When trained for a specified experimental setting (imaging domain, hardware restrictions, etc.), our ML model produces optimized encoding sequences that, when deployed in the REFoCUS imaging framework, improve a number of standard quality metrics over conventional sequences including resolution, field of view, and contrast. We demonstrate these results experimentally on both wire targets and a tissue-mimicking phantom. Significance: This work demonstrates that the set of commonly used encoding schemes represent only a narrow subset of those available. Additionally, it demonstrates the value for ML tasks in synthetic transmit aperture imaging to consider the beamformer within the model, instead of purely as a post-processing step.

Cardiac ultrasound seeks to image the most dynamic environment in the body-the moving heart. Many modern ultrasound imaging techniques address the tradeoff between spatial and temporal resolution using either narrow focused beams or with broad beam, synthetic aperture (SA) sequences that have been shown to suffer from motion artifacts. Retrospective encoding for conventional ultrasound sequences (REFoCUS) unifies the processing of these various geometric sequences, but the motion sensitivity of this approach has yet to be investigated. We hypothesize that a "mixed sequence" enabled by the REFoCUS method incorporating several beam geometries may better resolve cardiac motion over a wide field of view (FOV) and at a high frame rate. First, the motion sensitivity of REFoCUS was evaluated in simulation for several focused and broad transmit profiles. Focused transmissions resolve both lateral and axial motion much more effectively than broad transmissions, with performance similar to conventional beamforming techniques. Second, a mixed sequence was designed that insonifies the full field-of-view with plane wave (PW) transmissions and key moving targets with focused transmissions. This mixed sequence was tested in simulation and in vivo and was used to image the heart as well as the liver, a low-motion control. By combining a sparse PW sequence ( n=60 ) with a small group of targeted focused transmissions ( n = 10), the anterior mitral valve leaflet (AML) at its peak observed velocity was better resolved. We believe that mixed sequences have strong potential to resolve cardiac motion at clinically relevant frame rates.

Ultrasound imaging, crucial for clinical diagnostics, is limited by diffraction, affecting resolution at depth. Swept Synthetic Aperture (SSA), counters this issue by simulating a larger aperture through lateral transducer sweeping. Incorporating an innovative calibration optimization, this study presents Optically-Tracked SSA (OT-SSA), as an unconstrained approach shown to significantly improve lateral resolution and target detectability. The paper outlines the OT-SSA frame-work, showcases image quality improvements, and discusses its role as a benchmark for future SSA technologies, including untracked methods. Specifically, we introduce a 3D printed portable motorized translation stage that facilitates data-based motion estimation using optical tracking for accuracy assessment. It signifies a step towards adaptable, clinically integrated SSA ultrasound technology.

The rapid advancement in the field of medical imaging presents a challenge in keeping up to date with the necessary objective evaluations and optimizations for safe and effective use in clinical settings. These evaluations are traditionally done using clinical imaging trials, which while effective, pose several limitations including high costs, ethical considerations for repetitive experiments, time constraints, and lack of ground truth. To tackle these issues, virtual trials (aka in silico trials) have emerged as a promising alternative, using computational models of human subjects and imaging devices, and observer models/analysis to carry out experiments. To facilitate the widespread use of virtual trials within the medical imaging research community, a major need is to establish a common consensus framework that all can use. Based on the ongoing efforts of an AAPM Task Group (TG387), this article provides a comprehensive overview of the requirements for establishing virtual imaging trial frameworks, paving the way toward their widespread use within the medical imaging research community. These requirements include credibility, reproducibility, and accessibility. Credibility assessment involves verification, validation, uncertainty quantification, and sensitivity analysis, ensuring the accuracy and realism of computational models. A proper credibility assessment requires a clear context of use and the questions that the study is intended to objectively answer. For reproducibility and accessibility, this article highlights the need for detailed documentation, user-friendly software packages, and standard input/output formats. Challenges in data and software sharing, including proprietary data and inconsistent file formats, are discussed. Recommended solutions to enhance accessibility include containerized environments and data-sharing hubs, along with following standards such as CDISC (Clinical Data Interchange Standards Consortium). By addressing challenges associated with credibility, reproducibility, and accessibility, virtual imaging trials can be positioned as a powerful and inclusive resource, advancing medical imaging innovation and regulatory science.

Ultrasound imaging is valued for its affordability, non-invasiveness, and ease of use but is fundamentally limited in lateral resolution by diffraction, especially at depth. Previously, we addressed this limitation using freehand swept synthetic aperture (SSA) imaging with optical tracking (OT-SSA), which relies on a calibration matrix to transform optical tracking data into the transducer’s coordinate system for accurate beamforming. Here, we focus on optimizing the calibration matrix to enhance image quality. We propose a differentiable beamforming approach utilizing PyTorch’s automatic differentiation to refine the calibration matrix parameters. Our optimization process improves the definition of targets throughout the field of view and demonstrates repeatability for relevant degrees of freedom.

Ultrasound pulse sequencing and receive signal focusing work hand-in-hand to determine image quality. These are commonly linked by geometry, for example, using focused beams or plane waves in transmission paired with appropriate time-of-flight calculations for focusing. Spatial encoding allows a broader class of array transmissions but requires decoding of the recorded echoes before geometric focusing can be applied. Recent work has expanded spatial encoding to include not only element apodizations, but also element time delays. This powerful technique allows for a unified beamforming strategy across different pulse sequences and increased flexibility in array signal processing giving access to estimates of individual transmit element signals, but tradeoffs in image quality between these encodings have not been previously studied. We evaluate in simulation several commonly used time delay and amplitude encodings and investigate the optimization of the parameter space for each. Using the signal-to-noise ratio (SNR), point resolution, and lesion detectability, we found tradeoffs between focused beams, plane waves, and Hadamard weight encodings. Beams with broader geometries maintained a wider field of view after decoding at the cost of the SNR and lesion detectability. Focused beams and plane waves showed slightly reduced resolution compared to Hadamard weights in some cases, especially close to the array. We also found overall degraded image quality using random weight or random delay encodings. We validate these findings with experimental phantom imaging for select cases. We believe that these findings provide a starting point for sequence optimization and improved image quality using the spatial encoding approach for imaging.

Resolution and target detectability in ultrasound imaging are directly tied to the size of the imaging array. This is particularly important for imaging at depth, such as in the detection and diagnosis of hepatocellular carcinoma and other lesions in the liver. Swept synthetic aperture (SSA) imaging has shown promise for building large effective apertures from small physical arrays using motion but has required bulky fixtures and external motion tracking for precise positioning. This study presents an approach that constrains the transducer motion with a simple linear sliding fixture and estimates motion from the ultrasound data itself using either speckle tracking or channel correlation. This work demonstrates, through simulation and phantom experiments, the ability of both techniques to accurately estimate lateral transducer motion and form SSA images with improved resolution and target detectability. In simulation, errors were observed under 83 μm across a 50 mm sweep, and improvements were found of up to 61% in resolution and up to 33% in lesion detectability experimentally even imaging through ex vivo tissue layers. This approach will increase the accessibility of SSA imaging and allow researchers to test its use in clinical settings.

Ultrasound imaging is a non-invasive, low-cost option for real time screening and diagnosis across several areas of healthcare. However, the use of ultrasound is often limited by low image quality of deep targets which can necessitate more expensive and invasive imaging modalities. Resolution at depth can be improved by increasing the physical dimensions of the imaging array, but this approach is restricted by system complexity. The Swept Synthetic Aperture (SSA) technique bypasses this obstacle by using the position and orientation of the ultrasound array as it is swept over a target to generate an extended effective array. Our goal is to demonstrate the feasibility of using optical tracking to record the motion of a swept transducer with sufficient accuracy and precision to improve deep target detectability. This method eliminates the need for complex and constrictive physical fixture setups, thereby offering an improved level of practicality and adaptability to the SSA technique. Optically tracked SSA images showed a significant improvement in resolution and target detectability compared to a reference image from a stationary aperture. We expect that this method will improve resolution and penetration for deep targets, especially when using smaller ultrasonic systems with limited aperture size.

Achieving higher frame rates in ultrasound imaging is of great importance, especially in echocardiography where capturing rapid events associated with heart dynamics can provide valuable information in terms of disease diagnosis. Several approaches have been proposed to acquire higher frame rate cardiac images, however almost all of them suffer from degradation in image quality mainly in terms of spatial resolution, contrast and signal-to-noise ratio (SNR). Multi-line transmit (MLT) imaging, which sends focused beams in different spatial directions within a single transmit event, is one of the proposed approaches to improve the frame rates in cardiac imaging. While MLT has the potential to preserve spatial resolution and signal-to-noise ratio, the main drawback of the technique is the generation of crosstalk artifacts between simultaneous MLT beams. In this work we have explored synthetic aperture beamforming techniques that more accurately characterize the overlapping transmitted waves and hence are able to suppress the artifacts associated with MLT due to the improved focusing. It has been shown that synthetic focusing methods could improve cystic contrast and lower side lobe levels up to 80% for a simulated point target. Furthermore, the experimental phantom results demonstrated up to 12.8% improvement in the generalized contrast-to-noise ratio when applying synthetic aperture methods in comparison to dynamic receive focusing.

Remotely powered microrobots are proposed as next-generation vehicles for drug delivery. However, most microrobots swim with linear trajectories and lack the capacity to robustly adhere to soft tissues. This limits their ability to navigate complex biological environments and sustainably release drugs at target sites. In this work, bubble-based microrobots with complex geometries are shown to efficiently swim with non-linear trajectories in a mouse bladder, robustly pin to the epithelium, and slowly release therapeutic drugs. The asymmetric fins on the exterior bodies of the microrobots induce a rapid rotational component to their swimming motions of up to ≈150 body lengths per second. Due to their fast speeds and sharp fins, the microrobots can mechanically pin themselves to the bladder epithelium and endure shear stresses commensurate with urination. Dexamethasone, a small molecule drug used for inflammatory diseases, is encapsulated within the polymeric bodies of the microrobots. The sustained release of the drug is shown to temper inflammation in a manner that surpasses the performance of free drug controls. This system provides a potential strategy to use microrobots to efficiently navigate large volumes, pin at soft tissue boundaries, and release drugs over several days for a range of diseases.

In the context of ultrasonic hepatic shear wave elasticity imaging (SWEI), measurement success has been determined to increase when using elevated acoustic output pressures. As SWEI sequences consist of two distinct operations (pushing and tracking), acquisition failures could be attributed to (i) insufficient acoustic radiation force generation resulting in inadequate shear wave amplitude and/or (ii) distorted ultrasonic tissue motion tracking. In the study described here, an opposing window experimental setup that isolated body wall effects separately between the push and track SWEI operations was implemented. A commonly employed commercial track configuration was used, harmonic multiple-track-location SWEI. The effects of imaging through body walls on the pushing and tracking operations of SWEI as a function of mechanical index (MI), spanning 5 different push beam MIs and 10 track beam MIs, were independently assessed using porcine body walls. Shear wave speed yield was found to increase with both increasing push and track MI. Although not consistent across all samples, measurements in a subset of body walls were found to be signal limited during tracking and to increase yield by up to 35% when increasing electronic signal-to-noise ratio by increasing harmonic track transmit pressure.

The conventional view of ultrasound pulse-echo data—focused sound sent in a direction and bounced back towards the transducer—does not capture the rich information available. REFoCUS beamforming abandons this limitation, combining the ideas of spatially coded excitation and synthetic aperture imaging. Each transmission is an encoding of elements with various weights and time delays, and the multistatic data set (all transmit/receive element pairs) is estimated from the received data. We can, therefore, apply a single focusing operation across different choices of transmit pulse sequencing and ask questions about how to best optimize that sequence.The multistatic data set is a useful mathematical model since it is tied to individual array elements. Several works have used such raw echo data in optimization problems, for instance training neural networks to improve data quality from limited transmissions. However, we have found that the image formation process (e.g., focusing, beamforming) can change the appearance of errors in the data set. Even small errors in the raw data can result in significant image artifacts due to the inherent ill-conditioning of the beamforming operation. We demonstrate improvements in optimization using loss functions defined in the image domain compared to the raw multistatic data.