Fast Acoustic Wave Sparsely Activated Localization Microscopy (fast-AWSALM): Ultrasound Super-Resolution using Plane-Wave Activation of Nanodroplets

Hepatic Portal Venous Perfusion Imaging Using Vessel-Labeling Super-Resolution Ultrasound

OBJECTIVE

Blood flow imaging and perfusion assessment of the hepatic portal vein are critical for the diagnosis of several liver diseases, including cirrhosis, primary and metastatic liver tumors. However, perfusion imaging of the portal vein is challenging due to the unique dual blood supply system of the liver.

METHODS

We developed a novel method for specific perfusion imaging of the portal vein and downstream vessels, which was validated on healthy mice (n = 4). The right lobe of the liver in healthy mice was sequentially imaged using ultrafast plane-wave Doppler imaging and vascular labeling. In each experiment, mice were first injected with phase-change nanodroplets (PCNDs), followed immediately by ultrafast Doppler imaging to determine the imaging section and locate portal vein branches. Through an interactive process, portal vein branches were selected by mouse click for data acquisition of vessel-labeling ultrasound (VLUS) based on PCNDs. Subsequent arrival time calculations and super-resolution ultrasound (SRUS) imaging were performed offline. To demonstrate the specificity of the proposed method for vascular imaging, one mouse was injected with Sonovue microbubbles for plane-wave ultrasound data acquisition and microbubble-based VLUS data acquisition. All imaging experiments were conducted on the Verasonics (Kirkland, WA, USA) Vantage 256 ultrasound system using an L22-8v linear array transducer with a center frequency of 15.625 MHz. The multi-angle coherent compounding plane-wave acquisition frame rate was 500 Hz.

RESULTS

Imaging results from healthy mice (n = 4) demonstrated that VLUS was able to label different branches of the hepatic portal vein and specifically image downstream vessels. Analysis of the in vivo results at different spatial scales showed that the brightness of the downstream perfusion area was significantly enhanced after labeling started, while there was no significant difference in image brightness before the labeling started and after it ended. By analyzing the acoustic field distribution at the focal point, the full width at half maximum in the x1 and z1 directions were 98.56 μm and 526.68 μm, respectively. Along the propagation path of the focused beam (outside the labeling area), no significant activation of the PCNDs was observed (p < 0.0001). Combined with SRUS technology, the resolution of the VLUS portal vein imaging results was further enhanced. The time-intensity curves of the downstream regions of interest indicated that VLUS provided a step input signal to the downstream vessels. Based on the arrival time of the step point in the time-intensity curves, the arrival time distribution map of the downstream vessels relative to the labeling point could be calculated.

CONCLUSION

We propose a novel method for hepatic portal vein perfusion imaging based on VLUS. In vivo experiments, simulation results and statistical analysis demonstrate that this method is able to accurately label portal vein vessels with millimeter-level precision, enabling specific high-resolution imaging and precise, non-invasive measurement of the downstream perfusion area. By combining VLUS with SRUS technology, the resolution of the portal vein imaging results can be further enhanced.

Achieving single cell acoustic localisation with deactivation super resolution

Photo-activated localization microscopy (PALM) has been a game-changer, breaking the diffraction limit in spatial resolution. This study presents the Deactivation Super Resolution (DSR) method, which utilises the deactivation of genetically encodable contrast agents, enabling us to super-resolve and pinpoint individual cells with ultrasound as they navigate through structures which cannot be resolved by conventional B-Mode imaging. DSR takes advantage of Gas Vesicles (GVs), which are air-filled sub-micron particles that have been expressed in genetically engineered bacterial and mammalian cells to produce acoustic contrast. Our experimental results show that DSR can distinguish sub-wavelength microstructures that standard B-mode ultrasound images fail to resolve by super-localising individual mammalian cells. This study provides a proof of concept for the potential of DSR to serve as a super-resolution ultrasound technique for individual cell localisation, opening new horizons in the field.

The impact of monodisperse microbubble size on contrast-enhanced ultrasound super-localization imaging

Contrast-enhanced ultrasound (CEUS) super-localization imaging has shown promise for the assessment of microvascular networks by localizing and tracking microbubbles. The size of the available microbubbles for clinical use is polydisperse, but size-tailorable monodisperse microbubbles are now being developed that present a narrow size distribution. Therefore, proper frequency and pressure tuning have the potential to improve the signal-to-noise ratio and resolution of CEUS acquisitions, which can be expected to increase the performance of CEUS super-localization imaging. In this work, the impact of monodisperse microbubble size on CEUS imaging quality and the efficacy of super-localization imaging was investigated by jointly tuning different frequencies and pressures for different monodisperse microbubble size when performing in vitro CEUS imaging of microbubbles flowing through a dedicated sugar-printed dual-bifurcation microvasculature phantom. The obtained CEUS acquisitions were then post-processed to generate a super-localization output using the Gaussian-centroid localization approach. Four metrics, including generalized contrast-to-noise ratio, full-width half-maximum, number of localization events, and localization F1-score, were employed to quantify the CEUS imaging quality and super-localization performance. In general, jointly optimizing the transmit frequency and pressure for monodisperse microbubbles with smaller size leads to improved CEUS imaging and better super-localization performance. Yet, the weaker backscatter of smaller microbubbles must also be considered.

ULM-MbCNRT: In Vivo Ultrafast Ultrasound Localization Microscopy by Combining Multibranch CNN and Recursive Transformer

Ultrasound localization microscopy (ULM) overcomes the acoustic diffraction limit by localizing tiny microbubbles (MBs), thus enabling the microvascular to be rendered at subwavelength resolution. Nevertheless, to obtain such superior spatial resolution, it is necessary to spend tens of seconds gathering numerous ultrasound (US) frames to accumulate the MB events required, resulting in ULM imaging still suffering from tradeoffs between imaging quality, data acquisition time, and data processing speed. In this article, we present a new deep learning (DL) framework combining multibranch convolutional neural network (CNN) and recursive transformer (RT), termed ULM-MbCNRT, that is capable of reconstructing a super-resolution (SR) image directly from a temporal mean low-resolution image generated by averaging much fewer raw US frames, i.e., implement an ultrafast ULM imaging. To evaluate the performance of ULM-MbCNRT, a series of numerical simulations and in vivo experiments are carried out. Numerical simulation results indicate that ULM-MbCNRT achieves high-quality ULM imaging with ~10-fold reduction in data acquisition time and ~130-fold reduction in computation time compared to the previous DL method (e.g., the modified subpixel CNN, ULM-mSPCN). For the in vivo experiments, when comparing to the ULM-mSPCN, ULM-MbCNRT allows ~37-fold reduction in data acquisition time (~0.8 s) and ~2134-fold reduction in computation time (~0.87 s) without sacrificing spatial resolution. It implies that ultrafast ULM imaging holds promise for observing rapid biological activity in vivo, potentially improving the diagnosis and monitoring of clinical conditions.

Transcutaneous Imaging of Rabbit Kidney Using 3-D Acoustic Wave Sparsely Activated Localization Microscopy With a Row-Column-Addressed Array

OBJECTIVE

Super-resolution ultrasound (SRUS) imaging through localizing and tracking microbubbles, also known as ultrasound localization microscopy (ULM), can produce sub-diffraction resolution images of micro-vessels. We have recently demonstrated 3-D selective SRUS with a matrix array and phase change contrast agents (PCCAs). However, this method is limited to a small field of view (FOV) and by the complex hardware required.

METHOD

This study proposed 3-D acoustic wave sparsely activated localization microscopy (AWSALM) using PCCAs and a 128+128 row-column-addressed (RCA) array, which offers ultrafast acquisition with over 6 times larger FOV and 4 times reduction in hardware complexity than a 1024-element matrix array. We first validated this method on an in-vitro microflow phantom and subsequently demonstrated non-invasively on a rabbit kidney in-vivo.

RESULTS

Our results show that 3-D AWSALM images of the phantom covering a mm volume can be generated under 5 seconds with an 8 times resolution improvement over the system point spread function. The full volume of the rabbit kidney can be covered to generate 3-D microvascular structure, flow speed and direction super-resolution maps under 15 seconds, combining the large FOV of RCA with the high resolution of SRUS. Additionally, 3-D AWSALM is selective and can visualize the microvasculature within the activation volume and downstream vessels in isolation. Sub-sets of the kidney microvasculature can be imaged through selective activation of PCCAs.

CONCLUSION

Our study demonstrates large FOV 3-D AWSALM using an RCA probe.

SIGNIFICANCE

3-D AWSALM offers an unique in-vivo imaging tool for fast, selective and large FOV vascular flow mapping.

Novel intravital approaches to quantify deep vascular structure and perfusion in the aging mouse brain using ultrasound localization microscopy (ULM)

Intra-vital visualization of deep cerebrovascular structures and blood flow in the aging brain has been a difficult challenge in the field of neurovascular research, especially when considering the key role played by the cerebrovasculature in the pathogenesis of both vascular cognitive impairment and dementia (VCID) and Alzheimer's disease (AD). Traditional imaging methods face difficulties with the thicker skull of older brains, making high-resolution imaging and cerebral blood flow (CBF) assessment challenging. However, functional ultrasound (fUS) imaging, an emerging non-invasive technique, provides real-time CBF insights with notable spatial-temporal resolution. This study introduces an enhanced longitudinal fUS method for aging brains. Using elderly (24-month C57BL/6) mice, we detail replacing the skull with a polymethylpentene window for consistent fUS imaging over extended periods. Ultrasound localization mapping (ULM), involving the injection of a microbubble (<<10 μm) suspension allows for recording of high-resolution microvascular vessels and flows. ULM relies on the localization and tracking of single circulating microbubbles in the blood flow. A FIJI-based analysis interprets these high-quality ULM visuals. Testing on older mouse brains, our method successfully unveils intricate vascular specifics even in-depth, showcasing its utility for longitudinal studies that require ongoing evaluations of CBF and vascular aspects in aging-focused research.

Achieving Single Cell Acoustic Localisation with Deactivation Super Resolution

Super-resolution optical microscopy enables optical imaging of cells, molecules and other biological structures beyond the diffraction limit. However, no similar method exists to super-resolve specific cells with ultrasound. Here we introduce Deactivation Super Resolution (DSR), an ultrasound imaging method that uses the acoustic deactivation of genetically encodable contrast agents to super-resolve individual cells with ultrasound as they navigate through structures that cannot be resolved by conventional imaging methods. DSR takes advantage of gas vesicles, which are air-filled sub-micron protein particles that can be expressed in genetically engineered cells to produce ultrasound contrast. Our experimental results show that DSR can distinguish sub-wavelength microstructures that standard B-mode ultrasound images fail to resolve by super- localizing individual mammalian cells. This study provides a proof of concept for the potential of DSR to serve as a super- resolution ultrasound technique for individual cell localization, opening new horizons in the field.

In vivo ultrasound localization microscopy for high-density microbubbles

Ultrasound Localization Microscopy (ULM) surpasses the constraints imposed by acoustic diffraction, achieving sub-wavelength resolution visualization of microvasculature through the precise localization of minute microbubbles (MBs). Nonetheless, the analysis of densely populated regions with overlapping MB point spread responses introduces significant localization errors, limiting the use of technique to low-concentration conditions. This raises a trade-off issue between localization efficiency and MB density. In this work, we present a new deep learning framework that combines Transformer and U-Net architectures, termed ULM-TransUNet. As a non-linear model, it is able to learn the complex data patterns of overlapping MBs in dense conditions for accurate localization. To evaluate the performance of ULM-TransUNet, a series of numerical simulations and in vivo experiments are carried out. Numerical simulation results indicate that ULM-TransUNet achieves high-quality ULM imaging, with improvements of 21.93 % in detection rate, 17.36 % in detection precision, and 20.53 % in detection sensitivity, compared to previous state-of-the-art deep learning (DL) method (e.g., ULM-UNet). For the in vivo experiments, ULM-TransUNet achieves the highest spatial resolution (9.4 μm) and rapid inference speed (26.04 ms/frame). Furthermore, it consistently detects more small vessels and resolves closely spaced vessels more effectively. The outcomes of this work imply that ULM-TransUNet can potentially enhance the microvascular imaging performance on high-density MB conditions.

Versatile Ultrasound-Compatible Microfluidic Platform for In Vitro Microvasculature Flow Research and Imaging Optimization

Ultrasound localization microscopy (ULM) enables the creation of super-resolved images and velocity maps by localizing and tracking microbubble contrast agents through a vascular network over thousands of frames of ultrafast plane wave images. However, a significant challenge lies in developing ultrasound-compatible microvasculature phantoms to investigate microbubble flow and distribution in controlled environments. In this study, we introduce a new class of gelatin-based microfluidic-inspired phantoms uniquely tailored for ULM studies. These devices allow for the creation of complex and reproducible microvascular networks featuring channel diameters as small as 100 μm. Our experiments focused on microbubble behavior under ULM conditions within bifurcating and converging vessel phantoms. We evaluated the impact of bifurcation angles (25, 45, and 55°) and flow rates (0.01, 0.02, and 0.03 mL/min) on the acquisition time of branching channels. Additionally, we explored the saturation time effect of narrow channels branching off larger ones. Significantly longer acquisition times were observed for the narrow vessels, with an average increase of 72% when a 100 μm channel branched off from a 300 μm channel and an average increase of 90% for a 200 μm channel branching off from a 500 μm channel. The robustness of our fabrication method is demonstrated through the creation of two trifurcating microfluidic phantoms, including one that converges back into a single channel, a configuration that cannot be achieved through traditional methods. This new class of ULM phantoms serves as a versatile platform for noninvasively studying complex flow patterns using ultrasound imaging, unlocking new possibilities for in vitro microvasculature research and imaging optimization.

Deep learning for fast super-resolution ultrasound microvessel imaging

Objective. Ultrasound localization microscopy (ULM) enables microvascular reconstruction by localizing microbubbles (MBs). Although ULM can obtain microvascular images that are beyond the ultimate resolution of the ultrasound (US) diffraction limit, it requires long data processing time, and the imaging accuracy is susceptible to the density of MBs. Deep learning (DL)-based ULM is proposed to alleviate these limitations, which simulated MBs at low-resolution and mapped them to coordinates at high-resolution by centroid localization. However, traditional DL-based ULMs are imprecise and computationally complex. Also, the performance of DL is highly dependent on the training datasets, which are difficult to realistically simulate.Approach. A novel architecture called adaptive matching network (AM-Net) and a dataset generation method named multi-mapping (MMP) was proposed to overcome the above challenges. The imaging performance and processing time of the AM-Net have been assessed by simulation andin vivoexperiments.Main results. Simulation results show that at high density (20 MBs/frame), when compared to other DL-based ULM, AM-Net achieves higher localization accuracy in the lateral/axial direction.In vivoexperiment results show that the AM-Net can reconstruct ∼24.3μm diameter micro-vessels and separate two ∼28.3μm diameter micro-vessels. Furthermore, when processing a 128 × 128 pixels image in simulation experiments and an 896 × 1280 pixels imagein vivoexperiment, the processing time of AM-Net is ∼13 s and ∼33 s, respectively, which are 0.3-0.4 orders of magnitude faster than other DL-based ULM.Significance. We proposes a promising solution for ULM with low computing costs and high imaging performance.

Three-dimensional super resolution ultrasound imaging with a multi-frequency hemispherical phased array

BACKGROUND

High resolution imaging of the microvasculature plays an important role in both diagnostic and therapeutic applications in the brain. However, ultrasound pulse-echo sonography imaging the brain vasculatures has been limited to narrow acoustic windows and low frequencies due to the distortion of the skull bone, which sacrifices axial resolution since it is pulse length dependent.

PURPOSE

To overcome the detect limit, a large aperture 256-module sparse hemispherical transmit/receive array was used to visualize the acoustic emissions of ultrasound-vaporized lipid-coated decafluorobutane nanodroplets flowing through tube phantoms and within rabbit cerebral vasculature in vivo via passive acoustic mapping and super resolution techniques.

METHODS

Nanodroplets were vaporized with 55 kHz burst-mode ultrasound (burst length = 145 μs, burst repetition frequency = 9-45 Hz, peak negative acoustic pressure = 0.10-0.22 MPa), which propagates through overlying tissues well without suffering from severe distortions. The resulting emissions were received at a higher frequency (612 or 1224 kHz subarray) to improve the resulting spatial resolution during passive beamforming. Normal resolution three-dimensional images were formed using a delay, sum, and integrate beamforming algorithm, and super-resolved images were extracted via Gaussian fitting of the estimated point-spread-function to the normal resolution data.

RESULTS

With super resolution techniques, the mean lateral (axial) full-width-at-half-maximum image intensity was 16 ± 3 (32 ± 6) μm, and 7 ± 1 (15 ± 2) μm corresponding to ∼1/67 of the normal resolution at 612 and 1224 kHz, respectively. The mean positional uncertainties were ∼1/350 (lateral) and ∼1/180 (axial) of the receive wavelength in water. In addition, a temporal correlation between nanodroplet vaporization and the transmit waveform shape was observed, which may provide the opportunity to enhance the signal-to-noise ratio in future studies.

CONCLUSIONS

Here, we demonstrate the feasibility of vaporizing nanodroplets via low frequency ultrasound and simultaneously performing spatial mapping via passive beamforming at higher frequencies to improve the resulting spatial resolution of super resolution imaging techniques. This method may enable complete four-dimensional vascular mapping in organs where a hemispherical array could be positioned to surround the target, such as the brain, breast, or testicles.

Nanodroplet-Based Super-Resolution Ultrasound Localization Microscopy

Over the past decade, super-resolution ultrasound localization microscopy (SR-ULM) has revolutionized ultrasound imaging with its capability to resolve the microvascular structures below the ultrasound diffraction limit. The introduction of this imaging technique enables the visualization, quantification, and characterization of tissue microvasculature. The early implementations of SR-ULM utilize microbubbles (MBs) that require a long image acquisition time due to the requirement of capturing sparsely isolated microbubble signals. The next-generation SR-ULM employs nanodroplets that have the potential to significantly reduce the image acquisition time without sacrificing the resolution. This review discusses various nanodroplet-based ultrasound localization microscopy techniques and their corresponding imaging mechanisms. A summary is given on the preclinical applications of SR-ULM with nanodroplets, and the challenges in the clinical translation of nanodroplet-based SR-ULM are presented while discussing the future perspectives. In conclusion, ultrasound localization microscopy is a promising microvasculature imaging technology that can provide new diagnostic and prognostic information for a wide range of pathologies, such as cancer, heart conditions, and autoimmune diseases, and enable personalized treatment monitoring at a microlevel.

Super-resolution ultrasound microvascular imaging: Is it ready for clinical use?

The field of super-resolution ultrasound microvascular imaging has been rapidly growing over the past decade. By leveraging contrast microbubbles as point targets for localization and tracking, super-resolution ultrasound pinpoints the location of microvessels and measures their blood flow velocity. Super-resolution ultrasound is the first in vivo imaging modality that can image micron-scale vessels at a clinically relevant imaging depth without tissue destruction. These unique capabilities of super-resolution ultrasound provide structural (vessel morphology) and functional (vessel blood flow) assessments of tissue microvasculature on a global and local scale, which opens new doors for many enticing preclinical and clinical applications that benefit from microvascular biomarkers. The goal of this short review is to provide an update on recent advancements in super-resolution ultrasound imaging, with a focus on summarizing existing applications and discussing the prospects of translating super-resolution imaging to clinical practice and research. In this review, we also provide brief introductions of how super-resolution ultrasound works, how does it compare with other imaging modalities, and what are the tradeoffs and limitations for an audience who is not familiar with the technology.

Fast and Selective Super-Resolution Ultrasound In Vivo With Acoustically Activated Nanodroplets

Perfusion by the microcirculation is key to the development, maintenance and pathology of tissue. Its measurement with high spatiotemporal resolution is consequently valuable but remains a challenge in deep tissue. Ultrasound Localization Microscopy (ULM) provides very high spatiotemporal resolution but the use of microbubbles requires low contrast agent concentrations, a long acquisition time, and gives little control over the spatial and temporal distribution of the microbubbles. The present study is the first to demonstrate Acoustic Wave Sparsely-Activated Localization Microscopy (AWSALM) and fast-AWSALM for in vivo super-resolution ultrasound imaging, offering contrast on demand and vascular selectivity. Three different formulations of acoustically activatable contrast agents were used. We demonstrate their use with ultrasound mechanical indices well within recommended safety limits to enable fast on-demand sparse activation and destruction at very high agent concentrations. We produce super-localization maps of the rabbit renal vasculature with acquisition times between 5.5 s and 0.25 s, and a 4-fold improvement in spatial resolution. We present the unique selectivity of AWSALM in visualizing specific vascular branches and downstream microvasculature, and we show super-localized kidney structures in systole (0.25 s) and diastole (0.25 s) with fast-AWSALM outperforming microbubble based ULM. In conclusion, we demonstrate the feasibility of fast and selective imaging of microvascular dynamics in vivo with subwavelength resolution using ultrasound and acoustically activatable nanodroplet contrast agents.

Analytic prediction of droplet vaporization events to estimate the precision of ultrasound-based proton range verification

BACKGROUND

The safety and efficacy of proton therapy is currently hampered by range uncertainties. The combination of ultrasound imaging with injectable radiation-sensitive superheated nanodroplets was recently proposed for in vivo range verification. The proton range can be estimated from the distribution of nanodroplet vaporization events, which is stochastically related to the stopping distribution of protons, as nanodroplets are vaporized by protons reaching their maximal LET at the end of their range.

PURPOSE

Here, we aim to estimate the range estimation precision of this technique. As for any stochastic measurement, the precision will increase with the sample size, that is, the number of detected vaporizations. Thus, we first develop and validate a model to predict the number of vaporizations, which is then applied to estimate the range verification precision for a set of conditions (droplet size, droplet concentration, and proton beam parameters).

METHODS

Starting from the thermal spike theory, we derived a model that predicts the expected number of droplet vaporizations in an irradiated sample as a function of the droplet size, concentration, and number of protons. The model was validated by irradiating phantoms consisting of size-sorted perfluorobutane droplets dispersed in an aqueous matrix. The number of protons was counted with an ionization chamber, and the droplet vaporizations were recorded and counted individually using high frame rate ultrasound imaging. After validation, the range estimate precision was determined for different conditions using a Monte Carlo algorithm.

RESULTS

A good agreement between theory and experiments was observed for the number of vaporizations, especially for large (5.8 ± 2.2 µm) and medium (3.5 ± 1.1 µm) sized droplets. The number of events was lower than expected in phantoms with small droplets (2.0 ± 0.7 µm), but still within the same order of magnitude. The inter-phantom variability was considerably larger (up to 30x) than predicted by the model. The validated model was then combined with Monte Carlo simulations, which predicted a theoretical range retrieval precision improving with the square-root of the number of vaporizations, and degrading at high beam energies due to range straggling. For single pencil beams with energies between 70 and 240 MeV, a range verification precision below 1% of the range required perfluorocarbon concentrations in the order of 0.3-2.4 µM.

CONCLUSION

We proposed and experimentally validated a model to provide a quick estimate of the number of vaporizations for a given set of conditions (droplet size, droplet concentration, and proton beam parameters). From this model, promising range verification performances were predicted for realistic perfluorocarbon concentrations. These findings are an incentive to move towards preclinical studies, which are critical to assess the achievable droplet distribution in and around the tumor, and hence the in vivo range verification precision.

Ultrafast Background-Free Ultrasound Imaging Using Blinking Nanoparticles

Localization-based ultrasound imaging methods that use microbubbles or nanodroplets offer high-resolution imaging with improved sensitivity and reduced background signal. However, these methods require long acquisition times (typically seconds to minutes), preventing their use for real-time imaging and, thus, limiting their clinical translational potential. Here, we present a new ultrafast localization method using blinking ultrasound-responsive nanoparticles (BNPs). When activated with high frame rate (1 kHz) plane wave ultrasound pulses with a mechanical index of 1.5, the BNPs incept growth of micrometer-sized bubbles, which in turn collapse and generate a blinking ultrasound signal. We showed that background-free ultrasound images could be obtained by localizing these blinking events using acquisition times as low as 11 ms. In addition, we demonstrated that BNPs enable in vivo background-free ultrasound imaging in mice. We envision that BNPs will facilitate the clinical translation of localization-based ultrasound imaging for more sensitive detection of cancer and other diseases.

Super-Resolution Ultrasound Localization Microscopy of Microvascular Structure and Flow for Distinguishing Metastatic Lymph Nodes - An Initial Human Study

PURPOSE

Detecting and distinguishing metastatic lymph nodes (LNs) from those with benign lymphadenopathy are crucial for cancer diagnosis and prognosis but remain a clinical challenge. A recent advance in super-resolution ultrasound (SRUS) through localizing individual microbubbles has broken the diffraction limit and tracking enabled in vivo noninvasive imaging of vascular morphology and flow dynamics at a microscopic level. In this study we hypothesize that SRUS enables quantitative markers to distinguish metastatic LNs from benign ones in patients with lymphadenopathy.

MATERIALS AND METHODS

Clinical contrast-enhanced ultrasound image sequences of LNs from 6 patients with lymph node metastasis and 4 with benign lymphadenopathy were acquired and motion-corrected. These were then used to generate super-resolution microvascular images and super-resolved velocity maps. From these SRUS images, morphological and functional measures were obtained including micro-vessel density, fractal dimension, mean flow speed, and Local Flow Direction Irregularity (LFDI) measuring the variance in local flow direction. These measures were compared between pathologically proven reactive and metastasis LNs.

RESULTS

Our initial results indicate that the difference in the indicator of flow irregularity (LFDI) derived from the SRUS images is statistically significant between the two groups. The LFDI is 60% higher in metastatic LNs compared with reactive nodes.

CONCLUSION

This pilot study demonstrates the feasibility of super-resolution ultrasound for clinical imaging of lymph nodes and the potential of using the irregularity of local blood flow directions afforded by SRUS for the characterization of LNs.

Ultrasound Molecular Imaging and Its Applications in Cancer Diagnosis and Therapy

Ultrasound imaging is regarded as a highly sensitive imaging modality used in routine clinical examinations. Over the last several decades, ultrasound contrast agents have been widely applied in ultrasound molecular cancer imaging to improve the detection, characterization, and quantification of tumors. To date, a few new potential preclinical and clinical applications regarding ultrasound molecular cancer imaging are being investigated. This review presents an overview of the various kinds of ultrasound contrast agents employed in ultrasound molecular imaging and advanced imaging techniques using these contrast agents. Additionally, we discuss the recent enormous development of ultrasound contrast agents in the relevant preclinical and clinical applications, highlight the recent challenges which need to be overcome to accelerate the clinical translation, and discuss the future perspective of ultrasound molecular cancer imaging using various contrast agents. As a highly promising and valuable tumor-specific imaging technique, it is believed that ultrasound molecular imaging will pave an accurate and efficient way for cancer diagnosis.

Ultrasound super-resolution imaging for the differential diagnosis of thyroid nodules: A pilot study

Objective

Ultrasound imaging provides a fast and safe examination of thyroid nodules. Recently, the introduction of super-resolution imaging technique shows the capability of breaking the Ultrasound diffraction limit in imaging the micro-vessels. The aim of this study was to evaluate its feasibility and value for the differentiation of thyroid nodules.

Methods

In this study, B-mode, contrast-enhanced ultrasound, and color Doppler flow imaging examinations were performed on thyroid nodules in 24 patients. Super-resolution imaging was performed to visualize the microvasculature with finer details. Microvascular flow rate (MFR) and micro-vessel density (MVD) within thyroid nodules were computed. The MFR and MVD were used to differentiate the benign and malignant thyroid nodules with pathological results as a gold standard.

Results

Super-resolution imaging (SRI) technique can be successfully applied on human thyroid nodules to visualize the microvasculature with finer details and obtain the useful clinical information MVD and MFR to help differential diagnosis. The results suggested that the mean value of the MFR within benign thyroid nodule was 16.76 ± 6.82 mm/s whereas that within malignant thyroid was 9.86 ± 4.54 mm/s. The mean value of the MVD within benign thyroid was 0.78 while the value for malignant thyroid region was 0.59. MFR and MVD within the benign thyroid nodules were significantly higher than those within the malignant thyroid nodules respectively (p < 0.01).

Conclusions

This study demonstrates the feasibility of ultrasound super-resolution imaging to show micro-vessels of human thyroid nodules via a clinical ultrasound platform. The important imaging markers, such as MVD and MFR, can be derived from SRI to provide more useful clinical information. It has the potential to be a new tool for aiding differential diagnosis of thyroid nodules.

Super-Resolution Ultrasound Through Sparsity-Based Deconvolution and Multi-Feature Tracking

Ultrasound super-resolution imaging through localisation and tracking of microbubbles can achieve sub-wave-diffraction resolution in mapping both micro-vascular structure and flow dynamics in deep tissue in vivo. Currently, it is still challenging to achieve high accuracy in localisation and tracking particularly with limited imaging frame rates and in the presence of high bubble concentrations. This study introduces microbubble image features into a Kalman tracking framework, and makes the framework compatible with sparsity-based deconvolution to address these key challenges. The performance of the method is evaluated on both simulations using individual bubble signals segmented from in vivo data and experiments on a mouse brain and a human lymph node. The simulation results show that the deconvolution not only significantly improves the accuracy of isolating overlapping bubbles, but also preserves some image features of the bubbles. The combination of such features with Kalman motion model can achieve a significant improvement in tracking precision at a low frame rate over that using the distance measure, while the improvement is not significant at the highest frame rate. The in vivo results show that the proposed framework generates SR images that are significantly different from the current methods with visual improvement, and is more robust to high bubble concentrations and low frame rates.

Functional ultrasound localization microscopy reveals brain-wide neurovascular activity on a microscopic scale

The advent of neuroimaging has increased our understanding of brain function. While most brain-wide functional imaging modalities exploit neurovascular coupling to map brain activity at millimeter resolutions, the recording of functional responses at microscopic scale in mammals remains the privilege of invasive electrophysiological or optical approaches, but is mostly restricted to either the cortical surface or the vicinity of implanted sensors. Ultrasound localization microscopy (ULM) has achieved transcranial imaging of cerebrovascular flow, up to micrometre scales, by localizing intravenously injected microbubbles; however, the long acquisition time required to detect microbubbles within microscopic vessels has so far restricted ULM application mainly to microvasculature structural imaging. Here we show how ULM can be modified to quantify functional hyperemia dynamically during brain activation reaching a 6.5-µm spatial and 1-s temporal resolution in deep regions of the rat brain.

Slow-Flow Ultrasound Localization Microscopy Using Recondensation of Perfluoropentane Nanodroplets

Ultrasound localization microscopy (ULM) is an emerging, super-resolution imaging technique for detailed mapping of the microvascular structure and flow velocity via subwavelength localization and tracking of microbubbles. Because microbubbles rely on blood flow for movement throughout the vascular space, acquisition times can be long in the smallest, low-flow microvessels. In addition, detection of microbubbles in low-flow regions can be difficult because of minimal separation of microbubble signal from tissue. Nanoscale, phase-change contrast agents (PCCAs) have emerged as a switchable, intermittent or persisting contrast agent for ULM via acoustic droplet vaporization (ADV). Here, the focus is on characterizing the spatiotemporal contrast properties of less volatile perfluoropentane (PFP) PCCAs. The results indicate that at physiological temperature, nanoscale PFP PCCAs with diameters less than 100 nm disappear within microseconds after ADV with high-frequency ultrasound (16 MHz, 5- to 6-MPa peak negative pressure) and that nanoscale PFP PCCAs have an inherent deactivation mechanism via immediate recondensation after ADV. This "blinking" on-and-off contrast signal allowed separation of flow in an in vitro flow phantom, regardless of flow conditions, although with a need for some replenishment at very low flow conditions to maintain count rate. This blinking behavior allows for rapid spatial mapping in areas of low or no flow with ULM, but limits velocity tracking because there is no stable bubble formation with nanoscale PFP PCCAs.

A Real-Time Dual-Mode High-Frequency Beamformer for Ultrafast and Focused Imaging

A firmware-based high-frequency beam- former implementing both conventional transmit focused B-mode imaging and diverging wave ultrafast (UF) imaging for Doppler overlay was developed. The beamformer can generate one transmit focused frame with four transmit focal zones (FZs), and 68 UF frames with 16 diverging waves each at a 10-Hz frame rate. The beamformer firmware stores the beamforming delays as a single bit, enabling efficient compression within the internal memory. The beamformer was characterized using a 30-MHz 64-element phased array endoscope. The hybrid system generates a 128 line by 768-pixel focused B-mode image spanning 1.2-12.6 mm axially over a ±32° range of steering angles. In addition, the system generates an UF image that is 64 lines by 384-pixels spanning 3.5-10.8 mm axially over a ±16° angle.

Deep Learning-Based Microbubble Localization for Ultrasound Localization Microscopy

Ultrasound localization microscopy (ULM) is an emerging vascular imaging technique that overcomes the resolution-penetration compromise of ultrasound imaging. Accurate and robust microbubble (MB) localization is essential for successful ULM. In this study, we present a deep learning (DL)-based localization technique that uses both Field-II simulation and in vivo chicken embryo chorioallantoic membrane (CAM) data for training. Both radio frequency (RF) and in-phase and quadrature (IQ) data were tested in this study. The simulation experiment shows that the proposed DL-based localization was able to reduce both missing MB localization rate and MB localization error. In general, RF data showed better performance than IQ. For the in vivo CAM study with high MB concentration, DL-based localization was able to reduce the vessel MB saturation time by more than 50% compared to conventional localization. In addition, we propose a DL-based framework for real-time visualization of the high-resolution microvasculature. The findings of this article support the use of DL for more robust and faster MB localization, especially under high MB concentrations. The results indicate that further improvement could be achieved by incorporating temporal information of the MB data.

Improved Ultrasound Localization Microscopy Based on Microbubble Uncoupling via Transmit Excitation

Ultrasound localization microscopy (ULM) demonstrates great potential for visualization of tissue microvasculature at depth with high spatial resolution. The success of ULM heavily depends on robust localization of isolated microbubbles (MBs), which can be challenging in vivo especially within larger vessels where MBs can overlap and cluster close together. While MB dilution alleviates the issue of MB overlap to a certain extent, it drastically increases the data acquisition time needed for MBs to populate the microvasculature, which is already on the order of several minutes using recommended MB concentrations. Inspired by optical super-resolution imaging based on stimulated emission depletion (STED), here we propose a novel ULM imaging sequence based on MB uncoupling via transmit excitation (MUTE). MUTE "silences" MB signals by creating acoustic nulls to facilitate MB separation, which leads to robust localization of MBs especially under high concentrations. The efficiency of localization accomplished via the proposed technique was first evaluated in simulation studies with conventional ULM as a benchmark. Then, an in-vivo study based on the chorioallantoic membrane (CAM) of chicken embryos showed that MUTE could reduce the data acquisition time by half, thanks to the enhanced MB separation and localization. Finally, the performance of MUTE was validated in an in vivo mouse brain study. These results demonstrate the high MB localization efficacy of MUTE-ULM, which contributes to a reduced data acquisition time and improved temporal resolution for ULM.

Arterial Labeling Ultrasound Subtraction Angiography (ALUSA) Based on Acoustic Phase-Change Nanodroplets

Biomedical imaging technology (like digital subtraction angiography (DSA)) based on contrast agents has been widely employed in the diagnosis of vascular-related diseases. While the DSA achieves the high-resolution observation of specified vessels and their downstream perfusion at the cost of invasive, radioactive operation and hepatorenal toxicity. To address those problems, this study develops arterial labeling ultrasound (US) subtraction angiography (ALUSA) based on a new perfluorobutane (PFB) nanodroplets with a lower vaporization threshold through spontaneous nucleation. The nanodroplets can be selectively vaporized to microbubbles, indicating a highly echogenic signal at B-mode images only using a diagnostic transducer. By labeling a single blood vessel for nanodroplets vaporization and tracking its downstream blood perfusion in segmental renal arteries at a frame rate of 500 Hz. The results demonstrate the color-coded super-resolution ALUSA image, exhibiting the downstream arcuate and interlobular arteries of each segmental renal artery with a resolution of 36 µm in a rabbit kidney. Furthermore, ALUSA could offer the vascular structures, blood flow velocity, and direction of their primary supply vessels in the mouse breast tumor. ALUSA fills the gap of noninvasive labeling angiography in US and opens a broad vista in the diagnosis and treatment of tumor and vascular-related diseases.

In Vivo Ultrasound Localization Microscopy Imaging of the Kidney's Microvasculature With Block-Matching 3-D Denoising

Structural abnormalities and functional changes of renal microvascular networks play a significant pathophysiologic role in the occurrence of kidney diseases. Super-resolution ultrasound imaging has been successfully utilized to visualize the microvascular network and provide valuable diagnostic information. To prevent the burst of microbubbles, a lower mechanical index (MI) is generally used in ultrasound localization microscopy (ULM) imaging. However, high noise levels lead to incorrect signal localizations in relatively low-MI settings and deep tissue. In this study, we implemented a block-matching 3-D (BM3D) image-denoising method, after the application of singular value decomposition filtering, to further suppress the noise at various depths. The in vitro flow-phantom results show that the BM3D method helps the significant reduction of the error localizations, thus improving the localization accuracy. In vivo rhesus macaque experiments help conclude that the BM3D method improves the resolution more than other image-based denoising techniques, such as the nonlocal means method. The obtained clutter-filtered images with fewer incorrect localizations can enable robust ULM imaging, thus helping in establishing an effective diagnostic tool.

Ultrasound contrast agents: microbubbles made simple for the pediatric radiologist

The ability to provide prompt, real-time, easily accessible and radiation-free diagnostic assessments makes ultrasound (US) one of the most versatile imaging modalities. The introduction and development of stable microbubble-based ultrasound contrast agents (UCAs) in the early 1990s improved visualization of complex vascular structures, overcoming some of the limitations of B-mode and Doppler imaging. UCAs have been used extensively in the adult population to visualize vasculature and to evaluate perfusion and blood flow dynamics in organs and lesions. Since the first observations that air bubbles within a liquid can generate a strong echogenic effect, to the early makeshift approaches with agitated saline, and later to the development of industrially produced and federally approved UCAs, these agents have evolved to become both clinically and commercially viable. Perhaps the most exciting potential of UCAs is being uncovered by current research that explores the use of these agents for molecular imaging and therapeutic applications. As contrast-enhanced ultrasound (CEUS) becomes more widely available, it is important for pediatric radiologists to understand the physics of the interaction between the US signal and the microbubbles in order to properly utilize them for the highest level of diagnostic imaging and interventions. In this article we introduce the composition of UCAs and the physics of their behavior in US, and we offer a brief history of their development over the last decades.

Ultrasound microvasculature imaging with entropy-based radiality super-resolution (ERSR)

Objective:Microvasculature is highly relevant to the occurrence and development of pathologies such as cancer and diabetes. Ultrasound localization microscopy (ULM) has bypassed the diffraction limit and demonstrated its great potential to provide new imaging modality and establish new diagnostic criteria in clinical application. However, sparse microbubble distribution can be a significant bottleneck for improving temporal resolution, even for further clinical translation. Other important challenges for ULM to tackle in clinic also include high microbubble concentration and low frame rate.Approach:As part of the efforts to facilitate clinical translation, this paper focused on the low frame rate and the high microbubble distribution issue and proposed a new super-resolution imaging strategy called entropy-based radiality super-resolution (ERSR). The feasibility of ERSR is validated with simulations, phantom experiment and contrast-enhanced ultrasound scan of rabbit sciatic nerve with clinical accessible ultrasound system.Main results:ERSR can achieve 10 times improvement in spatial resolution compared to conventional ultrasound imaging, higher temporal resolution (∼10 times higher) and contrast-to-noise ratio under high-density microbubbles, compared with ULM under low-density microbubbles.Significance:We conclude ERSR could be a valuable imaging tool with high spatio-temporal resolution for clinical diagnosis and assessment of diseases potentially.

Blinking Acoustic Nanodroplets Enable Fast Super-resolution Ultrasound Imaging

The advent of localization-based super-resolution ultrasound (SRUS) imaging creates a vista for precision vasculature and hemodynamic measurements in brain science, cardiovascular diseases, and cancer. As blinking fluorophores are crucial to super-resolution optical imaging, blinking acoustic contrast agents enabling ultrasound localization microscopy have been highly sought, but only with limited success. Here we report on the discovery and characterization of a type of blinking acoustic nanodroplets (BANDs) ideal for SRUS. BANDs of 200-500 nm diameters comprise a perfluorocarbon-filled core and a shell of DSPC, Pluronic F68, and DSPE-PEG2000. When driven by clinically safe acoustic pulses (MI < 1.9) provided by a diagnostic ultrasound transducer, BANDs underwent reversible vaporization and reliquefaction, manifesting as "blinks", at rates of up to 5 kHz. By sparse activation of perfluorohexane-filled BANDs-C₆ at high concentrations, only 100 frames of ultrasound imaging were sufficient to reconstruct super-resolution images of a no-flow tube through either cumulative localization or temporal radiality autocorrelation. Furthermore, the use of high-density BANDs-C_6-4 (1 × 10⁸/mL) with a 1:9 admixture of perfluorohexane and perfluorobutane supported the fast SRUS imaging of muscle vasculature in live animals, at 64 μm resolution requiring only 100 frames per layer. We anticipate that the BANDs developed here will greatly boost the application of SRUS in both basic science and clinical settings.

Ultrasonic technologies in imaging and drug delivery

Ultrasonic technologies show great promise for diagnostic imaging and drug delivery in theranostic applications. The development of functional and molecular ultrasound imaging is based on the technical breakthrough of high frame-rate ultrasound. The evolution of shear wave elastography, high-frequency ultrasound imaging, ultrasound contrast imaging, and super-resolution blood flow imaging are described in this review. Recently, the therapeutic potential of the interaction of ultrasound with microbubble cavitation or droplet vaporization has become recognized. Microbubbles and phase-change droplets not only provide effective contrast media, but also show great therapeutic potential. Interaction with ultrasound induces unique and distinguishable biophysical features in microbubbles and droplets that promote drug loading and delivery. In particular, this approach demonstrates potential for central nervous system applications. Here, we systemically review the technological developments of theranostic ultrasound including novel ultrasound imaging techniques, the synergetic use of ultrasound with microbubbles and droplets, and microbubble/droplet drug-loading strategies for anticancer applications and disease modulation. These advancements have transformed ultrasound from a purely diagnostic utility into a promising theranostic tool.

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.

Sparse channel sampling for ultrasound localization microscopy (SPARSE-ULM)

Ultrasound localization microscopy (ULM) has recently enabled the mapping of the cerebral vasculaturein vivowith a resolution ten times smaller than the wavelength used, down to ten microns. However, with frame rates up to 20000 frames per second, this method requires large amount of data to be acquired, transmitted, stored, and processed. The transfer rate is, as of today, one of the main limiting factors of this technology. Herein, we introduce a novel reconstruction framework to decrease this quantity of data to be acquired and the complexity of the required hardware by randomly subsampling the channels of a linear probe. Method performance evaluation as well as parameters optimization were conductedin silicousing the SIMUS simulation software in an anatomically realistic phantom and then compared toin vivoacquisitions in a rat brain after craniotomy. Results show that reducing the number of active elements deteriorates the signal-to-noise ratio and could lead to false microbubbles detections but has limited effect on localization accuracy. In simulation, the false positive rate on microbubble detection deteriorates from 3.7% for 128 channels in receive and 7 steered angles to 11% for 16 channels and 7 angles. The average localization accuracy ranges from 10.6μm and 9.93μm for 16 channels/3 angles and 128 channels/13 angles respectively. These results suggest that a compromise can be found between the number of channels and the quality of the reconstructed vascular network and demonstrate feasibility of performing ULM with a reduced number of channels in receive, paving the way for low-cost devices enabling high-resolution vascular mapping.

Super-resolution ultrasound localization microscopy based on a high frame-rate clinical ultrasound scanner: an in-human feasibility study

Non-invasive detection of microvascular alterations in deep tissuesin vivoprovides critical information for clinical diagnosis and evaluation of a broad-spectrum of pathologies. Recently, the emergence of super-resolution ultrasound localization microscopy (ULM) offers new possibilities for clinical imaging of microvasculature at capillary level. Currently, the clinical utility of ULM on clinical ultrasound scanners is hindered by the technical limitations, such as long data acquisition time, high microbubble (MB) concentration, and compromised tracking performance associated with low imaging frame-rate. Here we present a robust in-human ULM on a high frame-rate (HFR) clinical ultrasound scanner to achieve super-resolution microvessel imaging using a short acquisition time (<10 s). Ultrasound MB data were acquired from different human tissues, including a healthy liver and a diseased liver with acute-on-chronic liver failure, a kidney, a pancreatic tumor, and a breast mass using an HFR clinical scanner. By leveraging the HFR and advanced processing techniques including sub-pixel motion registration, MB signal separation, and Kalman filter-based tracking, MBs can be robustly localized and tracked for ULM under the circumstances of relatively high MB concentration associated with standard clinical MB administration and limited data acquisition time in humans. Subtle morphological and hemodynamic information in microvasculature were shown based on data acquired with single breath-hold and free-hand scanning. Compared with contrast-enhanced power Doppler generated based on the same MB dataset, ULM showed a 5.7-fold resolution improvement in a vessel based on a linear transducer, and provided a wide-range blood flow speed measurement that is Doppler angle-independent. Microvasculatures with complex hemodynamics can be well-differentiated at super-resolution in both normal and pathological tissues. This preliminary study implemented the ultrafast in-human ULM in various human tissues based on a clinical scanner that supports HFR imaging, indicating the potentials of the technique for various clinical applications. However, rigorous validation of the technique in imaging human microvasculature (especially for those tiny vessel structure), preferably with a gold standard, is still required.

Super-Resolution Ultrasound Localization Microscopy Through Deep Learning

Ultrasound localization microscopy has enabled super-resolution vascular imaging through precise localization of individual ultrasound contrast agents (microbubbles) across numerous imaging frames. However, analysis of high-density regions with significant overlaps among the microbubble point spread responses yields high localization errors, constraining the technique to low-concentration conditions. As such, long acquisition times are required to sufficiently cover the vascular bed. In this work, we present a fast and precise method for obtaining super-resolution vascular images from high-density contrast-enhanced ultrasound imaging data. This method, which we term Deep Ultrasound Localization Microscopy (Deep-ULM), exploits modern deep learning strategies and employs a convolutional neural network to perform localization microscopy in dense scenarios, learning the nonlinear image-domain implications of overlapping RF signals originating from such sets of closely spaced microbubbles. Deep-ULM is trained effectively using realistic on-line synthesized data, enabling robust inference in-vivo under a wide variety of imaging conditions. We show that deep learning attains super-resolution with challenging contrast-agent densities, both in-silico as well as in-vivo. Deep-ULM is suitable for real-time applications, resolving about 70 high-resolution patches ( 128×128 pixels) per second on a standard PC. Exploiting GPU computation, this number increases to 1250 patches per second.

Transient acoustic vaporization signatures unique to low boiling point phase change contrast agents enable super-resolution ultrasound imaging without spatiotemporal filtering

The unique activation signal of phase-change contrast agents (PCCAs or droplets) can be separated from the tissue signal and localized to generate super-resolution (SR) ultrasound (US) images. Lipid-shelled, perfluorocarbon PCCAs can be stochastically vaporized (activated) by a plane wave US transmission thereby enabling them to be used as separable targets for ultrasound localization microscopy. The unique signature of droplet vaporization imaging and the transient inherent nature of this signature increases signal contrast and therefore localization confidence, while the poor resolution of the low-frequency vaporization signal is overcome by the super-resolution result. Furthermore, our proposed PCCA SR technique does not require the use of user-dependent and flow-dependent spatio-temporal filtering via singular-value decomposition. Rather, matched filters selected by Fourier-domain analysis are able to identify and localize PCCA activations. Droplet SR was demonstrated in a crossed-microtube water phantom by localizing the activation signals of octafluoropropane nanodroplets (OFP, C₃F₈, -37 °C boiling point) to resolve 100 µm diameter fluorinated ethylene propylene tubes, which are ordinarily 35% smaller than the native diffraction-limited resolution of the imaging system utilized.

Assessing Vessel Reconstruction in Ultrasound Localization Microscopy by Maximum Likelihood Estimation of a Zero-Inflated Poisson Model

In clinical applications of super-resolution ultrasound imaging, it is often not possible to achieve a full reconstruction of the microvasculature within a limited measurement time. This makes the comparison of studies and quantitative parameters of vascular morphology and perfusion difficult. Therefore, saturation models were proposed to predict adequate measurement times and estimate the degree of vessel reconstruction. Here, we derive a statistical model for the microbubble counts in super-resolution voxels by a zero-inflated Poisson (ZIP) process. In this model, voxels either belong to vessels with probability P_v and count events with Poisson rate Λ , or they are empty and remain zero. In this model, P_v represents the vessel voxel density in the super-resolution image after infinite measurement time. For the parameters P_v and Λ , we give Cramér-Rao lower bounds (CRLBs) for the estimation variance and derive maximum likelihood estimators (MLEs) in a novel closed-form solution. These can be calculated with knowledge of only the counts at the end of the acquisition time. The estimators are applied to preclinical and clinical data and the MLE outperforms alternative estimators proposed before. The estimated degree of reconstruction lies between 38% and 74% after less than 90 s. Vessel probability P_v ranged from 4% to 20%. The rate parameter Λ was estimated in the range of 0.5-1.3 microbubbles/voxel. For these parameter ranges, the CRLB gives standard deviations of less than 2%, which supports that the parameters can be estimated with good precision already for limited acquisition times.

Imaging the Activation of Low-Boiling-Point Phase-Change Contrast Agents in the Presence of Tissue Motion Using Ultrafast Inter-frame Activation Ultrasound Imaging

Nanoscale phase-change contrast agents (PCCAs) have been found to have great potential in non-invasive extravascular imaging and therapeutic delivery. However, the contrast-to-tissue ratio (CTR) of PCCA images is usually limited because of either physiological motion or incomplete cancelation of tissue signal. Therefore, to improve the CTR of PCCA images in the presence of physiological motion, a new imaging technique, ultrafast inter-frame activation ultrasound (UIAU) imaging, is proposed and validated. Results of studies with controlled motion in tissue-mimicking phantoms indicate UIAU could provide significantly higher CTRs (maximum: 17.3 ± 0.9 dB) relative to conventional pulse inversion imaging (maximum CTR: 3.4 ± 1.4 dB). UIAU has CTRs up to 16.1 ± 1.0 dB relative to 3.9 ± 2.3 dB for differential imaging in the presence of physiological motion at 20 mm/s. In vivo imaging of PCCAs in the rat liver also reveals the ability of UIAU to enhance PCCA image contrast in the presence of physiological motion.

Short Acquisition Time Super-Resolution Ultrasound Microvessel Imaging via Microbubble Separation

Super-resolution ultrasound localization microscopy (ULM), based on localization and tracking of individual microbubbles (MBs), offers unprecedented microvascular imaging resolution at clinically relevant penetration depths. However, ULM is currently limited by the requirement of dilute MB concentrations to ensure spatially sparse MB events for accurate localization and tracking. The corresponding long imaging acquisition times (tens of seconds or several minutes) to accumulate sufficient isolated MB events for full reconstruction of microvasculature preclude the clinical translation of the technique. To break this fundamental tradeoff between acquisition time and MB concentration, in this paper we propose to separate spatially overlapping MB events into sub-populations, each with sparser MB concentration, based on spatiotemporal differences in the flow dynamics (flow speeds and directions). MB localization and tracking are performed for each sub-population separately, permitting more robust ULM imaging of high-concentration MB injections. The superiority of the proposed MB separation technique over conventional ULM processing is demonstrated in flow channel phantom data, and in the chorioallantoic membrane of chicken embryos with optical imaging as an in vivo reference standard. Substantial improvement of ULM is further demonstrated on a chicken embryo tumor xenograft model and a chicken brain, showing both morphological and functional microvasculature details at super-resolution within a short acquisition time (several seconds). The proposed technique allows more robust MB localization and tracking at relatively high MB concentrations, alleviating the need for dilute MB injections, and thereby shortening the acquisition time of ULM imaging and showing great potential for clinical translation.

Super-resolution Ultrasound Imaging

The majority of exchanges of oxygen and nutrients are performed around vessels smaller than 100 μm, allowing cells to thrive everywhere in the body. Pathologies such as cancer, diabetes and arteriosclerosis can profoundly alter the microvasculature. Unfortunately, medical imaging modalities only provide indirect observation at this scale. Inspired by optical microscopy, ultrasound localization microscopy has bypassed the classic compromise between penetration and resolution in ultrasonic imaging. By localization of individual injected microbubbles and tracking of their displacement with a subwavelength resolution, vascular and velocity maps can be produced at the scale of the micrometer. Super-resolution ultrasound has also been performed through signal fluctuations with the same type of contrast agents, or through switching on and off nano-sized phase-change contrast agents. These techniques are now being applied pre-clinically and clinically for imaging of the microvasculature of the brain, kidney, skin, tumors and lymph nodes.

In Vivo Visualization of Eye Vasculature Using Super-Resolution Ultrasound Microvessel Imaging

OBJECTIVE

The choroidal vessels, which supply oxygen and nutrient to the retina, may play a pivotal role in eye disease pathogenesis such as diabetic retinopathy and glaucoma. In addition, the retrobulbar circulation that feeds the choroid shows an important pathophysiologic role in myopia and degenerative myopia. Owing to the light-absorbing retinal pigment epithelium (RPE) and optically opaque sclera, choroidal and retrobulbar vasculature were difficult to be observed using clinically accepted optical coherence tomography angiography (OCT-A) technique. Here, we have developed super-resolution ultrasound microvessel imaging technique to visualize the deep ocular vasculature.

METHODS

An 18-MHz linear array transducer with compounding plane wave imaging technique and contrast agent - microbubble was implemented in this study. The centroid intensity of each microbubble was detected using image deconvolution algorithm with spatially variant point spread function, and then accumulated in successive frames in order to reconstruct microvasculature. The image deconvolution technique was first evaluated in a simulation study and experimental flow phantoms. The performance was then validated on normal rabbit eyes in vivo.

RESULTS

The image deconvolution based super-resolution ultrasound microvessel imaging technique shows good performance on either simulation study or flow phantoms. In vivo rabbit eye study indicated that the micron-level choroidal and retrobulbar vessels around the optic nerve head were successfully reconstructed in multiple 2D views and 3D volume imaging.

CONCLUSIONS

Our results demonstrate the capability of using super-resolution ultrasound microvessel imaging technique to image the microvasculature of the posterior pole of the eye. This efficient approach can potentially lead to a routinely performed diagnostic procedure in the field of ophthalmology.

3-D Super-Resolution Ultrasound Imaging With a 2-D Sparse Array

High-frame-rate 3-D ultrasound imaging technology combined with super-resolution processing method can visualize 3-D microvascular structures by overcoming the diffraction-limited resolution in every spatial direction. However, 3-D super-resolution ultrasound imaging using a full 2-D array requires a system with a large number of independent channels, the design of which might be impractical due to the high cost, complexity, and volume of data produced. In this study, a 2-D sparse array was designed and fabricated with 512 elements chosen from a density-tapered 2-D spiral layout. High-frame-rate volumetric imaging was performed using two synchronized ULA-OP 256 research scanners. Volumetric images were constructed by coherently compounding nine-angle plane waves acquired at a pulse repetition frequency of 4500 Hz. Localization-based 3-D super-resolution images of two touching subwavelength tubes were generated from 6000 volumes acquired in 12 s. Finally, this work demonstrates the feasibility of 3-D super-resolution imaging and super-resolved velocity mapping using a customized 2-D sparse array transducer.