Ultrafast ultrasound offers a unique route to cross-scale neurovascular phenotyping by integrating functional ultrasound (fUS), ultrasound localization microscopy (ULM), and functional ULM (fULM). Yet the baseline variability, longitudinal stability, and biological safety of such multimodal imaging in awake animals remain insufficiently defined, limiting its use for detecting subtle disease-associated neurovascular changes. Here, an awake longitudinal fUS-ULM-fULM framework is established and validated in mice over five months. Structural vascularity, microvascular flow velocity, mesoscale hemodynamic responses, and microvascular functional responses are repeatedly quantified in the same animals during monthly imaging sessions. Across all metrics, no significant longitudinal drift is detected (p > 0.60). Structural and flow-derived measures are markedly more reproducible than functional readouts, with within-subject coefficients of variation of 5.1% for mean flow velocity and 7.3% for vascularity, compared with 25.0% for fUS-derived cerebral blood volume responses and 53.2% for fULM-derived microvascular functional responses. Mean flow velocity shows the strongest longitudinal consistency (ICC = 0.70) and the lowest detection threshold. Behavioral testing and GFAP/Iba1 staining further reveal no memory impairment or chronic neuroinflammation. This study defines quantitative baselines, reproducibility limits, and safety evidence for awake cross-scale ultrasound imaging, providing a reference framework for longitudinal neurovascular phenotyping in preclinical disease models.

Brain-wide functional neuroimaging at single-vessel resolution in naturally behaving animals has been challenging to realize. Functional ultrasound localization microscopy (fULM) offers brain-wide hemodynamic imaging at microscopic resolution but has remained restricted to head-fixed preparations. Here we present a platform for fULM in freely moving rats. The system integrates a magnetic probe-clamping interface, a counterbalanced pulley-based tether, chronic jugular venous access for on-demand microbubble delivery, and a motion-correction processing pipeline tailored to freely moving ULM data. Using visual stimulation, we first show that the platform reliably captures functional hemodynamic responses and supports super-resolved vascular reconstruction across deep brain regions. We then demonstrate that freely moving fULM resolves stimulus-evoked vessel-specific changes in both diameter and flow velocity, revealing microvascular heterogeneity that cannot be recovered with conventional methods. Finally, we apply the platform to image brain responses induced by an experimental biased μ opioid agonist (SR-17018) in rats, revealing transient, region-dependent cerebrovascular responses, with flow-velocity changes of 20-30% that vary in magnitude and temporal profile across individual vessel segments in cortex and periaqueductal gray in free-moving rats. This work establishes freely moving fULM as a practical platform for whole-brain microvascular imaging under naturalistic behavioral conditions.

Functional ultrasound localization microscopy (fULM) enables brain-wide mapping of neural activity at micron-scale resolution but suffers from limited sensitivity due to sparse and noisy microbubble (MB) detections. Extending fULM into three dimensions (3D) further exacerbates these challenges because of low-frequency matrix arrays, reduced localization efficiency, and severe data sparsity. To address these limitations, we developed a statistical framework that models MB arrivals in 3D as a Poisson process accounting for localization efficiency, detection probability, and backscattered amplitude. This analysis predicts that integrating amplitude with count-based fULM improves functional sensitivity, particularly under high MB concentrations where localization saturates. Three-dimensional MB advection simulations confirmed these predictions, showing that backscattering fULM (B-fULM) maintains sensitivity at higher MB concentrations where ' conventional fULM fails. In rat brain experiments, B-fULM yielded stronger and more robust stimulus-evoked responses, with SNR gains of 18% in the somatosensory cortex and 61% in the thalamus, while preserving super-resolved spatial detail (33.4 μm for B-fULM vs 35.7 μm for fULM). These results establish B-fULM as a practical and sensitive approach for super-resolved 3D functional neuroimaging.

Functional neuroimaging with ultrafast ultrasound is an emerging neuroimaging tool for studying neural activities in the rodent brain. Existing methods, however, are challenged by the compromise between functional imaging sensitivity (i.e., sensitivity in detecting neural responses) and spatial resolution. For example, functional ultrasound (fUS) uses native red blood cells (RBCs) as imaging targets, which offers high functional imaging sensitivity but limited spatial resolution that is confined by the diffraction limit of ultrasound. On the other hand, functional ultrasound localization microscopy (fULM) employs intravenously injected microbubble (MB) as contrast agent to achieve super-resolved spatial resolution but at the cost of functional imaging sensitivity. This study aims to address this challenge by developing a novel, MB track-based hemodynamic activity estimation method to enhance the functional imaging sensitivity of fULM. Our approach involves conducting functional correlation analysis using the MB signals acquired from the entire MB movement track rather than individual MB centroid locations, which overcomes the signal sparsity issue in fULM. To further boost the functional sensitivity of fULM, we developed a novel approach based on indwelling jugular vein catheters to achieve fULM imaging in awake mice. The in vivo imaging results demonstrate that the proposed techniques successfully enhanced the functional imaging sensitivity of fULM without compromising its high spatial resolution. In the whisker stimulation experiments, the proposed technique enabled detection of significantly activated brain regions within fewer than five stimulation cycles (5 minutes of acquisition), reducing the required time by over 50% compared to conventional fULM.

3-D ultrasound localization microscopy (ULM) enables comprehensive mapping of microvascular networks by providing micrometer-scale spatial resolution while avoiding projection errors inherent to 2-D ULM imaging. Current 3-D ULM techniques are based on linear pulse sequences combined with spatiotemporal filtering to distinguish microbubble flow from tissue signals. However, singular-value decomposition (SVD)-based filtering demonstrates poor performance in highly mobile organs, suppressing small vessels with slow blood flow along with tissue signals. While imaging based on nonlinear multipulse sequences can isolate microbubble signals regardless of tissue motion, achieving the high-volume acquisition rates required for 3-D ULM remains technically challenging. Here, we present Fast3D-amplitude modulation (AM) imaging, a 3-D nonlinear imaging sequence that achieves a high-volume acquisition rate (225 Hz) using a single 256-channel ultrasound system with a multiplexed 2-D matrix array. We also introduce a motion rejection algorithm that leverages localized microbubble positions to reject respiratory-induced motion artifacts. Fast3D-AM imaging achieved a superior contrast-to-tissue ratio (CTR) than Fast3D, exhibiting a 6.66-dB improvement in phantom studies. In an in vivo rat study, Fast3D-AM demonstrated higher CTR across all SVD cutoffs compared to Fast3D and preserved both major and microvascular structures in whole-organ kidney imaging.

Ultrasound localization microscopy (ULM) enabled high-accuracy measurements of microvessel flow beyond the resolution limit of conventional ultrasound imaging by utilizing contrast microbubbles (MBs) as point targets. Robust tracking of MBs is an essential task for fast and high-quality ULM image reconstruction. Existing MB tracking methods suffer from challenging imaging scenarios such as high-density MB distributions, fast blood flow, and complex flow dynamics. Here we present a deep learning-based MB pairing and tracking method based on a bi-directional long short-term memory neural network for ULM. The proposed method integrates multiparametric MB characteristics to facilitate more robust and accurate MB pairing and tracking. The method was validated on a simulation data set, a tissue-mimicking flow phantom, and in vivo on a mouse and rat brain.

Ultrasound localization microscopy is a super-resolution vascular imaging technique which has garnered substantial interest as a tool for small animal neuroimaging, neuroscience research, and the characterization of vascular pathologies. In the context of small animal neurovascular imaging, we posit that increasing the ultrasound imaging frequency is a straightforward approach to enable higher concentrations of microbubble contrast agents, thus increasing the likelihood of microvascular mapping and decreasing the imaging duration. To test this hypothesis, we compared ULM imaging resolution of mouse brain vasculature for three transducers with different center transmit frequencies (15 MHz, 23 MHz, and 31 MHz) under conditions of low and high MB concentration. We demonstrate that higher frequency imaging resulted in more efficient microbubble localization due to a smaller microbubble point-spread function that is easier to localize, and which can achieve a higher localizable concentration within the same unit volume of tissue. We found that increasing the imaging frequency had a minor impact on ULM spatial resolution, as measured by Fourier ring correlation, under the low MB concentration case, but a substantial impact in the high MB concentration case. High-frequency ULM yielded a spatial resolution of 6.9 μm, as measured by Fourier ring correlation, throughout the entire depth of the brain. This highlights the potential of this technology as a highly relevant tool for neuroimaging research, which has substantial implications for neuroscientists investigating microvascular function in disease states, regulation, and brain development.

Ultrasound localization microscopy (ULM) is an emerging imaging modality that resolves microvasculature in deep tissues with high spatial resolution. However, existing preclinical ULM applications are largely constrained to anesthetized animals, introducing confounding vascular effects such as vasodilation and altered hemodynamics. As such, ULM quantifications (e.g., vessel diameter, density, and flow velocity) may be confounded by the use of anesthesia, undermining the usefulness of ULM in practice. Here we introduce a method to address this limitation and achieve ULM imaging in awake mouse brain. Pupillary monitoring was used to support the presence of the awake state during ULM imaging. Vasodilation induced by isoflurane was observed by ULM. Upon recovery to the awake state, reductions in vessel density and flow velocity were observed across different brain regions. In the cortex, the effects induced by isoflurane are more pronounced on venous flow than on arterial flow. In addition, serial in vivo imaging of the same animal brain at weekly intervals demonstrated the highly robust longitudinal imaging capability of the proposed technique. The consistency was further verified through quantitative analysis on individual vessels, cortical regions of arteries and veins, and subcortical regions. This study demonstrates longitudinal ULM imaging in the awake mouse brain, which is crucial for many ULM brain applications that require awake and behaving animals.

Objective Advanced imaging methods are crucial for understanding stroke mechanisms and discovering effective treatments to reduce bleeding and enhance recovery. In pre-clinical in vivo stroke imaging, MRI, CT and optical imaging are commonly used to evaluate stroke outcomes in rodent models. However, MRI and CT have limited spatial resolution for rodent brains, and optical imaging is hindered by limited imaging depth of penetration. Here we introduce a novel contrast-enhanced ultrasound imaging method to overcome these challenges and characterize intracerebral hemorrhage with unique insights. Methods We combined microbubble-based ultrasound localization microscopy (ULM) and nanodrop (ND)-based vessel leakage imaging to achieve simultaneous microvascular imaging and hemorrhage detection. ULM maps brain-wide cerebral vasculature with high spatial resolution and identifies microvascular impairments around hemorrhagic areas. NDs are sub-micron liquid-core particles that can extravasate due to blood-brain barrier breakdown, serving as positive contrast agents to detect hemorrhage sites. Results Our findings demonstrate that NDs could effectively accumulate in the hemorrhagic site and reveal the location of the bleeding areas upon activation by focused ultrasound beams. ULM further reveals the microvascular damage manifested in the form of reduced vascularity and decreased blood flow velocity across areas affected by the hemorrhagic stroke. Conclusion The results demonstrate that sequential ULM combined with ND imaging is a useful imaging tool for basic in vivo research in stroke with rodent models where brain-wide detection of active bleeding and microvascular impairment are essential.

Photoacoustic computed tomography (PACT) is a proven technology for imaging hemodynamics in deep brain of small animal models. PACT is inherently compatible with ultrasound (US) imaging, providing complementary contrast mechanisms. While PACT can quantify the brain's oxygen saturation of hemoglobin (sO2), US imaging can probe the blood flow based on the Doppler effect. Further, by tracking gas-filled microbubbles, ultrasound localization microscopy (ULM) can map the blood flow velocity with sub-diffraction spatial resolution. In this work, we present a 3D deep-brain imaging system that seamlessly integrates PACT and ULM into a single device, 3D-PAULM. Using a low ultrasound frequency of 4 MHz, 3D-PAULM is capable of imaging the whole-brain hemodynamic functions with intact scalp and skull in a totally non-invasive manner. Using 3D-PAULM, we studied the mouse brain functions with ischemic stroke. Multi-spectral PACT, US B-mode imaging, microbubble-enhanced power Doppler (PD), and ULM were performed on the same mouse brain with intrinsic image co-registration. From the multi-modality measurements, we future quantified blood perfusion, sO2, vessel density, and flow velocity of the mouse brain, showing stroke-induced ischemia, hypoxia, and reduced blood flow. We expect that 3D-PAULM can find broad applications in studying deep brain functions on small animal models.

Super-resolution ultrasound (SRUS) imaging through localizing and tracking microbubbles (MBs), also known as ultrasound localization microscopy (ULM), has achieved unprecedented resolution in deep tissue in vivo. In this review, we will focus on the key technical steps of ULM, including data acquisition and tissue clutter removal, motion correction, localization, tracking, and final image visualization, as well as offering the authors' perspectives of the techniques. In each of the technical steps, we review what has been done and the state of the art and describe the key factors and parameters that influence each step, existing issues, and considerations when choosing the parameters. Finally, methods for evaluation of ULM image quality with or without ground truth are also reviewed.

Functional ultrasound localization microscopy (fULM), which utilizes the neurovascular coupling effect, has become a critical tool for investigating neural activities in the rodent brain. This technique relies on intravenously injected microbubbles (MBs) as contrast agents, enabling exceptional spatial resolution. However, prior studies have predominantly applied fULM in anesthetized animals, a limitation that markedly reduces sensitivity to neural activity. Recent advancements in functional ultrasound imaging of freely moving rodents have demonstrated not only enhanced sensitivity but also an expanded application to behavioral studies, which is unattainable in anesthetized or head-fixed awake imaging setups. Nevertheless, the application of ULM in freely moving animals remains unexplored. In this study, we introduce a novel fULM imaging approach on freely moving rats. By utilizing indwelling jugular vein catheterization and a miniaturized ultrasound probe, this method achieves high spatial resolution and precise mapping of dynamic neural processes in vivo. We validate the system by visualizing cerebral blood flow and microvascular changes during visual stimulation, providing new insights into neurovascular coupling. This platform addresses the traditional limitations of immobilized and anesthetized imaging, offering a transformative tool for neuroscience research in naturalistic settings.

Ultrasound localization microscopy (ULM) enables deep tissue microvascular imaging by localizing and tracking intravenously injected microbubbles circulating in the bloodstream. However, conventional localization techniques require spatially isolated microbubbles, resulting in prolonged imaging time to obtain detailed microvascular maps. Here, we introduce LOcalization with Context Awareness (LOCA)-ULM, a deep learning-based microbubble simulation and localization pipeline designed to enhance localization performance in high microbubble concentrations. In silico, LOCA-ULM enhanced microbubble detection accuracy to 97.8% and reduced the missing rate to 23.8%, outperforming conventional and deep learning-based localization methods up to 17.4% in accuracy and 37.6% in missing rate reduction. In in vivo rat brain imaging, LOCA-ULM revealed dense cerebrovascular networks and spatially adjacent microvessels undetected by conventional ULM. We further demonstrate the superior localization performance of LOCA-ULM in functional ULM (fULM) where LOCA-ULM significantly increased the functional imaging sensitivity of fULM to hemodynamic responses invoked by whisker stimulations in the rat brain. Ultrasound localisation microscopy enables deep tissue microvascular imaging. Here, authors introduce LOCA-ULM, a deep learning pipeline enhancing localisation accuracy in high microbubble concentrations. LOCA-ULM reveals dense cerebrovascular networks and enhances the sensitivity of functional ULM.

Increasing evidence has suggested a link between cerebrovascular disease and the cognitive impairment of patients with Alzheimer’s disease. However, cerebrovascular disease and Alzheimer’s disease share several risk factors making it unclear whether cerebrovascular deficiency and Alzheimer’s disease pathology have additive effects on cognition or if cerebrovascular impairment merely exacerbates existing Alzheimer’s disease-associated cognitive decline. Additionally, early-stage Alzheimer’s disease typically involves hippocampal atrophy, complicating most efforts to elucidate the interplay between cerebral microvascular function and Alzheimer’s disease progression due to the necessity of probing deep-brain structures. The purpose of this study was to demonstrate the use of ultrasound localization microscopy on the 5xFAD mouse model of Alzheimer’s disease (3-month and 6-month-old cohorts) in comparison to age-matched wild-type controls, revealing microvascular scale reconstructions throughout the whole brain depth, to visualize and quantify Alzheimer’s disease-associated vascular impairments. We found that functional decreases in hippocampal and entorhinal flow velocity preceded structural derangements in regional vascular density. In addition to providing global vascular quantifications of deep brain structures with a high local resolution, this technology also permitted hierarchical analysis of individual vessels and, in some cases, potentially allowed for decoupling of arteriole and venous flow contributions. Co-registered histological sectioning confirmed the regionalized hypo-perfusion deficits seen on ultrasound imaging, which were co-localized with amyloid beta plaque deposition. Significance statement The study of the impact of cerebrovascular disease on Alzheimer’s disease pathology is complicated by the need to image deep-brain structures with high vascular fidelity. We demonstrate that ultrasound localization microscopy, a super-resolution acoustic imaging technique, is capable of imaging cerebrovasculature throughout the entire depth of the brain at a microvascular scale. This technology was applied to the 5xFAD mouse model of Alzheimer’s disease, where it was found that 5xFAD animals have significant impairments in vascular function in the entorhinal cortex and hippocampal region in comparison to age matched controls at the 3-month timepoint. Structural derangements in cerebrovasculature were only observed in the 6-month-old animal cohorts, with a maintained impairment in vascular function.

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.

Ultrasound localization microscopy is a super-resolution vascular imaging technique which has garnered substantial interest as a tool for small animal neuroimaging, neuroscience research, and the characterization of vascular pathologies. In the pursuit of increasingly high-fidelity reconstructions of microvasculature, there remains several outstanding questions concerning this sub-diffraction imaging technology, including the accurate reconstruction of microvessels approaching the capillary scale and the pragmatic challenges associated with long data acquisition times. In the context of small animal neurovascular imaging, we posit that increasing the ultrasound imaging frequency is a straightforward approach to enable higher concentrations of microbubble contrast agents, thus increasing the likelihood of microvascular/capillary mapping and decreasing the imaging duration. We demonstrate that higher frequency imaging results in improved ULM fidelity and more efficient microbubble localization due to a smaller microbubble point-spread function that is easier to localize, and which can achieve a higher localizable concentration within the same unit volume of tissue. A select example of in vivo capillary-level vascular reconstruction is demonstrated for the highest frequency imaging probe, which has substantial implications for neuroscientists investigating microvascular function in disease states, regulation, and brain development. High frequency ULM yielding a spatial resolution of 7.1μm, as measured by Fourier ring correlation, throughout the entire depth of the brain, highlighting this technology as a highly relevant tool for neuroimaging research.

Acoustic radiation force (ARF)-based shear wave elastography (SWE) is a clinically available ultrasound imaging mode that noninvasively and quantitatively measures tissue stiffness. Current implementations of ARF-SWE are largely limited to 2-D imaging, which does not provide robust estimation of heterogeneous tissue mechanical properties. Existing 3-D ARF-SWE solutions that are clinically available are based on wobbler probes, which cannot provide true 3-D shear wave motion detection. Although 3-D ARF-SWE based on 2-D matrix arrays have been previously demonstrated, they do not provide a practical solution because of the need for a high channel-count ultrasound system (e.g., 1024-channel) to provide adequate volume rates and the delicate circuitries (e.g., multiplexers) that are vulnerable to the long-duration “push” pulses. To address these issues, here we propose a new 3-D ARF-SWE method based on the 2-D row-column addressing (RCA) array which has a much lower element count (e.g., 256), provides an ultrafast imaging volume rate (e.g., 2000 Hz), and can withstand the push pulses. In this study, we combined the comb-push shear elastography (CUSE) technique with 2-D RCA for enhanced SWE imaging field-of-view. In vitro phantom studies demonstrated that the proposed method had robust 3-D SWE performance in both homogenous and inclusion phantoms. An in vivo study on a breast cancer patient showed that the proposed method could reconstruct 3-D elasticity maps of the breast lesion, which was validated using a commercial ultrasound scanner. These results demonstrate strong potential for the proposed method to provide a viable and practical solution for clinical 3-D ARF-SWE.

To improve the spatial resolution of power Doppler (PD) imaging, we explored null subtraction imaging (NSI) as an alternative beamforming technique to delay-and-sum (DAS). NSI is a nonlinear beamforming approach that uses three different apodizations on receive and incoherently sums the beamformed envelopes. NSI uses a null in the beam pattern to improve the lateral resolution, which we apply here for improving PD spatial resolution both with and without contrast microbubbles. In this study, we used NSI with singular value decomposition (SVD)-based clutter filtering and noise equalization to generate high-resolution PD images. An element sensitivity correction scheme was also performed to further improve the image quality of PD images using NSI. First, a microbubble trace experiment was performed to quantitatively evaluate the performance of NSI based PD. Then, both contrast-enhanced and contrast free ultrasound data were collected from a rat brain. Higher spatial resolution and image quality were observed from the NSI-based PD microvessel images compared to microvessel images generated by traditional DAS-based beamforming.

Functional ultrasound localization microscopy (fULM) is a new technique that combines the principles of ULM and functional ultrasound (fUS) to achieve brain-wide and micrometer-scale mapping of brain neural activities based on neurovascular coupling. The unique combination of high imaging spatial resolution, large imaging field-of-view, and deep imaging depth of penetration makes fULM a potentially transformative technology for numerous neuroscience applications where activities from both global neural networks and local neurocircuits need to be recorded simultaneously and continuously. At present, however, fULM suffers from many technical and pragmatic challenges, including low sensitivity and specificity to neural activities, the need of long data acquisition with continuous infusion of microbubbles and repeated simulations, and the lack of viable 3D imaging solutions that are essential for neuroscience research. In this presentation, I will first introduce the principles and technical challenges of fULM, followed by recent advances achieved by our group including (1) enhanced microbubble localization, tracking, and other post-processing techniques to boost fULM’s sensitivity to neural activities; (2) 3D fULM based on 2D matrix arrays that are compatible with mainstream 256-channel ultrasound systems; and (3) an awake fULM imaging platform for mice and rats that allows whole-brain, microscopic-scale recording of functional neural activities in awake animals.