ULTRA-SR Challenge: Assessment of Ultrasound Localization and TRacking Algorithms for Super-Resolution Imaging.

With the widespread interest and uptake of super-resolution ultrasound (SRUS) through localization and tracking of microbubbles, also known as ultrasound localization microscopy (ULM), many localization and tracking algorithms have been developed. ULM can image many centimeters into tissue in-vivo and track microvascular flow non-invasively with sub-diffraction resolution. In a significant community effort, we organized a challenge, Ultrasound Localization and TRacking Algorithms for Super-Resolution (ULTRA-SR). The aims of this paper are threefold: to describe the challenge organization, data generation, and winning algorithms; to present the metrics and methods for evaluating challenge entrants; and to report results and findings of the evaluation. Realistic ultrasound datasets containing microvascular flow for different clinical ultrasound frequencies were simulated, using vascular flow physics, acoustic field simulation and nonlinear bubble dynamics simulation. Based on these datasets, 38 submissions from 24 research groups were evaluated against ground truth using an evaluation framework with six metrics, three for localization and three for tracking. In-vivo mouse brain and human lymph node data were also provided, and performance assessed by an expert panel. Winning algorithms are described and discussed. The publicly available data with ground truth and the defined metrics for both localization and tracking present a valuable resource for researchers to benchmark algorithms and software, identify optimized methods/software for their data, and provide insight into the current limits of the field. In conclusion, Ultra-SR challenge has provided benchmarking data and tools as well as direct comparison and insights for a number of the state-of-the art localization and tracking algorithms.

Individualized Ultrasound-Guided Intervention Phantom Development, Fabrication, and Proof of Concept.

Commercial ultrasound vascular phantoms lack the anatomic diversity required for robust pre-clinical interventional device testing. We fabricated individualized phantoms to test an artificial intelligence enabled ultrasound-guided surgical robotic system (AI-GUIDE) which allows novices to cannulate deep vessels. After segmenting vessels on computed tomography scans, vessel cores, bony anatomy, and a mold tailored to the skin contour were 3D-printed. Vessel cores were coated in silicone, surrounded in tissue-mimicking gel tailored for ultrasound and needle insertion, and dissolved with water. One upper arm and four inguinal phantoms were constructed. Operators used AI-GUIDE to deploy needles into phantom vessels. Two groin phantoms were tested due to imaging artifacts in the other two phantoms. Six operators (medical experience: none, 3; 1-5 years, 2; 5+ years, 1) inserted 27 inguinal needles with 81% (22/27) success in a median of 48 seconds. Seven operators performed 24 arm injections, without tuning the AI for arm anatomy, with 71% (17/24) success. After excluding failures due to motor malfunction and a defective needle, success rate was 100% (22/22) in the groin and 85% (17/20) in the arm. Individualized 3D-printed phantoms permit testing of surgical robotics across a large number of operators and different anatomic sites. AI-GUIDE operators rapidly and reliably inserted a needle into target vessels in the upper arm and groin, even without prior medical training. Virtual device trials in individualized 3-D printed phantoms may improve rigor of results and expedite translation.Clinical Relevance- Individualized phantoms enable rigorous and efficient evaluation of interventional devices and reduce the need for animal and human subject testing.

The Future Is Beyond Bright: The Evolving Role of Quantitative US for Fatty Liver Disease.

Nonalcoholic fatty liver disease (NAFLD) is a common cause of morbidity and mortality. Nonfocal liver biopsy is the historical reference standard for evaluating NAFLD, but it is limited by invasiveness, high cost, and sampling error. Imaging methods are ideally situated to provide quantifiable results and rule out other anatomic diseases of the liver. MRI and US have shown great promise for the noninvasive evaluation of NAFLD. US is particularly well suited to address the population-level problem of NAFLD because it is lower-cost, more available, and more tolerable to a broader range of patients than MRI. Noninvasive US methods to evaluate liver fibrosis are widely available, and US-based tools to evaluate steatosis and inflammation are gaining traction. US techniques including shear-wave elastography, Doppler spectral imaging, attenuation coefficient, hepatorenal index, speed of sound, and backscatter-based estimation have regulatory clearance and are in clinical use. New methods based on channel and radiofrequency data analysis approaches have shown promise but are mostly experimental. This review discusses the advantages and limitations of clinically available and experimental approaches to sonographic liver tissue characterization for NAFLD diagnosis as well as future applications and strategies to overcome current limitations.

Acoustic diffraction-resistant adaptive profile technology (ADAPT) for elasticity imaging.

Acoustic beam shaping with high degrees of freedom is critical for applications such as ultrasound imaging, acoustic manipulation, and stimulation. However, the ability to fully control the acoustic pressure profile over its propagation path has not yet been achieved. Here, we demonstrate an acoustic diffraction-resistant adaptive profile technology (ADAPT) that can generate a propagation-invariant beam with an arbitrarily desired profile. By leveraging wave number modulation and beam multiplexing, we develop a general framework for creating a highly flexible acoustic beam with a linear array ultrasonic transducer. The designed acoustic beam can also maintain the beam profile in lossy material by compensating for attenuation. We show that shear wave elasticity imaging is an important modality that can benefit from ADAPT for evaluating tissue mechanical properties. Together, ADAPT overcomes the existing limitation of acoustic beam shaping and can be applied to various fields, such as medicine, biology, and material science.

Memory-efficient low-compute segmentation algorithms for bladder-monitoring smart ultrasound devices.

Post-operative urinary retention is a medical condition where patients cannot urinate despite having a full bladder. Ultrasound imaging of the bladder is used to estimate urine volume for early diagnosis and management of urine retention. Moreover, the use of bladder ultrasound can reduce the need for an indwelling urinary catheter and the risk of catheter-associated urinary tract infection. Wearable ultrasound devices combined with machine-learning based bladder volume estimation algorithms reduce the burdens of nurses in hospital settings and improve outpatient care. However, existing algorithms are memory and computation intensive, thereby demanding the use of expensive GPUs. In this paper, we develop and validate a low-compute memory-efficient deep learning model for accurate bladder region segmentation and urine volume calculation. B-mode ultrasound bladder images of 360 patients were divided into training and validation sets; another 74 patients were used as the test dataset. Our 1-bit quantized models with 4-bits and 6-bits skip connections achieved an accuracy within [Formula: see text] and [Formula: see text], respectively, of a full precision state-of-the-art neural network (NN) without any floating-point operations and with an [Formula: see text] and [Formula: see text] reduction in memory requirements to fit under 150 kB. The means and standard deviations of the volume estimation errors, relative to estimates from ground-truth clinician annotations, were [Formula: see text] ml and [Formula: see text] ml, respectively. This lightweight NN can be easily integrated on the wearable ultrasound device for automated and continuous monitoring of urine volume. Our approach can potentially be extended to other clinical applications, such as monitoring blood pressure and fetal heart rate.

Ultrasonic Sound Speed Estimation for Liver Fat Quantification: A Review by the AIUM-RSNA QIBA Pulse-Echo Quantitative Ultrasound Initiative.

Non-alcoholic fatty liver disease (NAFLD) is a significant cause of diffuse liver disease, morbidity and mortality worldwide. Early and accurate diagnosis of NALFD is critical to identify patients at risk of disease progression. Liver biopsy is the current gold standard for diagnosis and prognosis. However, a non-invasive diagnostic tool is desired because of the high cost and risk of complications of tissue sampling. Medical ultrasound is a safe, inexpensive and widely available imaging tool for diagnosing NAFLD. Emerging sonographic tools to quantitatively estimate hepatic fat fraction, such as tissue sound speed estimation, are likely to improve diagnostic accuracy, precision and reproducibility compared with existing qualitative and semi-quantitative techniques. Various pulse-echo ultrasound speed of sound estimation methodologies have been investigated, and some have been recently commercialized. We review state-of-the-art in vivo speed of sound estimation techniques, including their advantages, limitations, technical sources of variability, biological confounders and existing commercial implementations. We report the expected range of hepatic speed of sound as a function of liver steatosis and fibrosis that may be encountered in clinical practice. Ongoing efforts seek to quantify sound speed measurement accuracy and precision to inform threshold development around meaningful differences in fat fraction and between sequential measurements.

Spatially targeted brain cancer immunotherapy with closed-loop controlled focused ultrasound and immune checkpoint blockade.

Despite the challenges in treating glioblastomas (GBMs) with immune adjuvants, increasing evidence suggests that targeting the immune cells within the tumor microenvironment (TME) can lead to improved responses. Here, we present a closed-loop controlled, microbubble-enhanced focused ultrasound (MB-FUS) system and test its abilities to safely and effectively treat GBMs using immune checkpoint blockade. The proposed system can fine-tune the exposure settings to promote MB acoustic emission-dependent expression of the proinflammatory marker ICAM-1 and delivery of anti-PD1 in a mouse model of GBM. In addition to enhanced interaction of proinflammatory macrophages within the PD1-expressing TME and significant improvement in survival (P < 0.05), the combined treatment induced long-lived memory T cell formation within the brain that supported tumor rejection in rechallenge experiments. Collectively, our findings demonstrate the ability of MB-FUS to augment the therapeutic impact of immune checkpoint blockade in GBMs and reinforce the notion of spatially tumor-targeted (loco-regional) brain cancer immunotherapy.

Experimental Demonstration of Trans-Skull Volumetric Passive Acoustic Mapping With the Heterogeneous Angular Spectrum Approach.

Real-time, 3-D, passive acoustic mapping (PAM) of microbubble dynamics during transcranial focused ultrasound (FUS) is essential for optimal treatment outcomes. The angular spectrum approach (ASA) potentially offers a very efficient method to perform PAM, as it can reconstruct specific frequency bands pertinent to microbubble dynamics and may be extended to correct aberrations caused by the skull. Here, we experimentally assess the abilities of heterogeneous ASA (HASA) to perform trans-skull PAM. Our experimental investigations demonstrate that the 3-D PAMs of a known 1-MHz source, constructed with HASA through an ex vivo human skull segment, reduced both the localization error (from 4.7 ± 2.3 to 2.3 ± 1.6 mm) and the number, size, and energy of spurious lobes caused by aberration, with the modest additional computational expense. While further improvements in the localization errors are expected with arrays with denser elements and larger aperture, our analysis revealed that experimental constraints associated with the array pitch and aperture (here, 1.8 mm and 2.5 cm, respectively) can be ameliorated by interpolation and peak finding techniques. Beyond the array characteristics, our analysis also indicated that errors in the registration (translation and rotation of ±5 mm and ±5°, respectively) of the skull segment to the array can lead to peak localization errors of the order of a few wavelengths. Interestingly, errors in the spatially dependent speed of sound in the skull (±20%) caused only subwavelength errors in the reconstructions, suggesting that registration is the most important determinant of point source localization accuracy. Collectively, our findings show that HASA can address source localization problems through the skull efficiently and accurately under realistic conditions, thereby creating unique opportunities for imaging and controlling the microbubble dynamics in the brain.

Towards controlled drug delivery in brain tumors with microbubble-enhanced focused ultrasound.

Brain tumors are particularly challenging malignancies, due to their location in a structurally and functionally distinct part of the human body - the central nervous system (CNS). The CNS is separated and protected by a unique system of brain and blood vessel cells which together prevent most bloodborne therapeutics from entering the brain tumor microenvironment (TME). Recently, great strides have been made through microbubble (MB) ultrasound contrast agents in conjunction with ultrasound energy to locally increase the permeability of brain vessels and modulate the brain TME. As we elaborate in this review, this physical method can effectively deliver a wide range of anticancer agents, including chemotherapeutics, antibodies, and nanoparticle drug conjugates across a range of preclinical brain tumors, including high grade glioma (glioblastoma), diffuse intrinsic pontine gliomas, and brain metastasis. Moreover, recent evidence suggests that this technology can promote the effective delivery of novel immunotherapeutic agents, including immune check-point inhibitors and chimeric antigen receptor T cells, among others. With early clinical studies demonstrating safety, and several Phase I/II trials testing the preclinical findings underway, this technology is making firm steps towards shaping the future treatments of primary and metastatic brain cancer. By elaborating on its key components, including ultrasound systems and MB technology, along with methods for closed-loop spatial and temporal control of MB activity, we highlight how this technology can be tuned to enable new, personalized treatment strategies for primary brain malignancies and brain metastases.

Morphological Reconstruction Improves Microvessel Mapping in Super-Resolution Ultrasound.

Generation of super-resolution (SR) ultrasound (US) images, created from the successive localization of individual microbubbles in the circulation, has enabled the visualization of microvascular structure and flow at a level of detail that was not possible previously. Despite rapid progress, tradeoffs between spatial and temporal resolution may challenge the translation of this promising technology to the clinic. To temper these tradeoffs, we propose a method based on morphological image reconstruction. This method can extract from ultrafast contrast-enhanced US (CEUS) images hundreds of microbubble peaks per image (312-by-180 pixels) with intensity values varying by an order of magnitude. Specifically, it offers a fourfold increase in the number of peaks detected per frame, requires on the order of 100 ms for processing, and is robust to additive electronic noise (down to 3.6-dB CNR in CEUS images). By integrating this method to an SR framework, we demonstrate a sixfold improvement in spatial resolution, when compared with CEUS, in imaging chicken embryo microvessels. This method that is computationally efficient and, thus, scalable to large data sets may augment the abilities of SR-US in imaging microvascular structure and function.

Acoustic source localization with the angular spectrum approach in continuously stratified media.

The angular spectrum approach (ASA)-a frequency domain method to calculate the acoustic field-enables highly efficient passive source localization and modeling forward propagation in homogeneous media. If the medium is continuously stratified, a first-order analytical solution may be obtained for the field at arbitrary depth. Simulations show that the proposed stratified ASA solution enables accurate source localization as compared to the uncorrected ASA (error from 1.2 ± 0.3 to 0.49 ± 0.3 wavelengths) at scalings relevant to biomedical, underwater, and atmospheric acoustic applications, and requiring milliseconds on nonspecialized hardware. The results suggest the proposed correction enables efficient and accurate localization in stratified environments.

Heterogeneous Angular Spectrum Method for Trans-Skull Imaging and Focusing.

Ultrasound, alone or in concert with circulating microbubble contrast agents, has emerged as a promising modality for therapy and imaging of brain diseases. While this has become possible due to advancements in aberration correction methods, a range of applications, including adaptive focusing and tracking of the microbubble dynamics through the human skull, may benefit from even more computationally efficient methods to account for skull aberrations. Here, we derive a general method for the angular spectrum approach (ASA) in a heterogeneous medium, based on a numerical marching scheme to approximate the full implicit solution. We then demonstrate its functionality with simulations for (human) skull-related aberration correction and trans-skull passive acoustic mapping. Our simulations show that the general solution provides accurate trans-skull focusing as compared to the uncorrected case (error in focal point location of 1.0 ± 0.4 mm vs 2.2 ± 0.7 mm) for clinically relevant frequencies (0.25-1.5MHz), apertures (50-100 mm), and targets, with peak focal pressures approximately 30 ± 17% of the free field case, with the effects of skull attenuation and amplitude shading included. In the case of source localization, our method leads to an average of 75% error reduction (from 2.9 ± 1.8 mm to 0.7 ± 0.5 mm) and 40-60% increase in peak intensity, evaluated over the range of frequencies (0.4-1.2 MHz), apertures (50-100 mm), and point source locations (40 mm by 50 mm grid) as compared to the homogeneous medium ASA. Overall, total computation times for both focusing and point source localization of the order milliseconds (166 ± 37 ms, compared with 44 ± 4 ms for the homogeneous ASA formulation) can be attained with this approach. Collectively our findings indicate that the proposed phase correction method based on the ASA could provide a computationally efficient and accurate method for trans-skull transmit focusing and imaging of point scatterers, potentially opening new possibilities for treatment and diagnosis of brain diseases.

Closed Loop Spatial and Temporal Control of Cavitation Activity with Passive Acoustic Mapping.

Ultrasonically actuated microbubble oscillations hold great promise for minimally invasive therapeutic interventions. While several preclinical studies have demonstrated the potential of this technology, real-time methods to control the amplitude and type of microbubble oscillations (stable vs inertial acoustic cavitation) and ensure that cavitation occurs within the targeted region are needed for their successful translation to the clinic. In this paper, we propose a real-time nonlinear state controller that uses specific frequency bands of the microbubble acoustic emissions (harmonic, ultra-harmonic, etc.) to control cavitation activity (observer states). To attain both spatial and temporal control of cavitation activity with high signal to noise ratio, we implement a controller using fast frequency-selective passive acoustic mapping (PAM) based on the angular spectrum approach. The controller includes safety states based on the recorded broadband signal level and is able to reduce sensing inaccuracies with the inclusion of multiple frequency bands. In its simplest implementation the controller uses the peak intensity of the passive acoustic maps, reconstructed using the 3rd harmonic (4.896 × 0.019 MHz) of the excitation frequency. Our results show that the proposed real-time nonlinear state controller based on PAM is able to reach the targeted level of observer state (harmonic emissions) in less than 6 seconds and remain within 10 % of tolerance for the duration of the experiment (45 seconds). Similar response was observed using the acoustic emissions from single element passive cavitation detection, albeit with higher susceptibility to background noise and lack of spatial information. Importantly, the proposed PAM-based controller was able to control cavitation activity with spatial selectivity when cavitation existed simultaneously in multiple regions. The robustness of the controller is demonstrated using a range of controller parameters, multiple observer states concurrently (harmonic, ultra-harmonic, and broadband), noise levels (°6 to 12 dB SNR), and bubble concentrations (0.3 to 180 × 103 bubbles per microliter). More research in this direction under preclinical and clinical conditions is warranted.