Ultrasound Localization Microscopy and Super-Resolution: A State of the Art

An Early Progression Biomarker in Glioblastoma: Microcirculatory Heterogeneity on Ultrasound Localization Microscopy

OBJECTIVE

Microcirculatory heterogeneity plays an essential role in the initiation and progression of glioblastoma (GBM). This study employs super-resolution ultrasound imaging to visualize the microcirculatory heterogeneity in GBM, with the objective of illustrating its predictive value in histological assessments.

METHODS

This in vivo study explored the microvasculature in GBM models using 15 Sprague-Dawley rats, divided into three groups based on tumor growth stages (12, 18 and 24 d post-implantation). Ultrasound localization microscopy (ULM) was employed to assess microvascular morphology, hemodynamics and heterogeneity. Structural, functional and heterogeneity parameters at different tumor growth stages were quantified using Kruskal-Wallis H tests, or analysis of variance, followed by Bonferroni correction to characterize tumor progression. Linear correlations between these quantitative parameters and pathological indicators, including histological vascular density (VD-H), proliferation index and histological vascular maturity index (VMI-H), were evaluated. A stepwise linear regression model was constructed to assess the predictive performance in relation to histological parameters.

RESULTS

Compared to histology, ULM enabled the earlier detection of tumor progression. The quantitative parameters derived from ULM provided a more comprehensive assessment than conventional metrics such as tumor size and immunohistochemistry. Multivariate analysis exhibited significant correlations among curvature, blood flow orientation variance (OV) and VD-H. Additionally, curvature, blood flow and OV demonstrated significant correlations with the proliferation index, while blood flow and fractal dimension showed significant associations with VMI-H. Heterogeneity parameters exhibited superior predictive power for certain histological features compared to microvascular morphology and functional perfusion.

CONCLUSION

ULM provides a basis for early, non-invasive in vivo imaging and quantification of microvascular structures in rat GBM and demonstrates super-resolution predictive capability for histological parameters.

Commercially Available Ultrasound Contrast Agents: Factors Contributing to Favorable Outcomes With Ultrasound-Mediated Drug Delivery and Ultrasound Localization Microscopy Imaging

ABSTRACT

Ultrasound contrast agents (UCAs) are microbubbles comprising an inert gas core stabilized by an encapsulating shell, which serves to increase the signal-to-noise ratio of blood-to-tissue in diagnostic ultrasound imaging. More recently, research has investigated the use of UCAs to combine both diagnostics and therapeutic outcomes in an amalgamated approach, designated 'theranostics.' Two examples of theranostic based approaches include the use of super-resolution imaging with ultrasound localized microscopy (ULM) and ultrasound-mediated drug delivery (UMDD). Both ULM and UMDD have been shown to have the potential to improve both patient care and clinical outcomes. Currently, there are 4 commercially available global UCAs licensed for clinical use. The physico-chemical properties of each of these UCAs influence its potential theranostic efficacy. Because of differences in their composition and/or manufacturing processes, each UCA has different characteristics that contribute to different in vivo resonance behavior, which in turn influences their effective clinical applications. This review highlights the key physico-chemical characteristic differences of the 4 commercially available contrast agents, with specific emphasis on their gaseous core, shell composition, and microbubble volume distribution, while providing novel insights into their benefits for supporting emerging clinical technologies, specifically ULM and UMDD.

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.

Optimizingin vivodata acquisition for robust clinical microvascular imaging using ultrasound localization microscopy

Objective. Ultrasound localization microscopy (ULM) enables microvascular imaging at spatial resolutions beyond the acoustic diffraction limit, offering significant clinical potentials. However, ULM performance relies heavily on microbubble (MB) signal sparsity, the number of detected MBs, and signal-to-noise ratio (SNR), all of which vary in clinical scenarios involving bolus MB injections. These sources of variations underscore the need to optimize MB dosage, data acquisition timing, and imaging settings in order to standardize and optimize ULM of microvasculature. This pilot study aims to investigate the temporal changes in MB signals during bolus injections in both pig and human models to optimize data acquisition for clinical ULM.Approach.Quantitative indices, mainly including individual MB SNR, normalized cross-correlation (NCC) of the MB signal with the point-spread function, and the number of localizable MBs, were developed to evaluate MB signal quality and guide the selection of acquisition timing. The effects of transmitted voltage and dosage on signal quality for MB localization were also explored.Main results. In both pig and human studies, MB localization quality (primarily indicated by NCC) reached a minimum at peak MB concentration, then improved as MB counts decreased during the wash-out phase. An optimal acquisition window was identified by balancing localization quality (empirically, NCC > 0.57) and MB concentration. In the pig model, a relatively short time window (approximately 10 s) for optimal acquisition was identified during the rapid wash-out phase, highlighting the need for real-time MB signal monitoring during data acquisition. The slower wash-out phase in humans allowed for a more flexible imaging window of 1-2 min, while trade-offs were observed between localization quality and MB density (or acquisition length) at different wash-out phase timings. Guided by these findings, robust ULM imaging was achieved in both pig and human kidneys using a short period of data acquisition (3.6 s and 9.6 s of data), demonstrating its feasibility in clinical practice.Significance.This study provides insights into optimizing data acquisition for consistent and reproducible ULM, paving the way for its standardization and broader clinical applications.

Noninvasive optical monitoring of cerebral hemodynamics in a preclinical model of neonatal intraventricular hemorrhage

Intraventricular hemorrhage (IVH) is a common complication in premature infants and is associated with white matter injury and long-term neurodevelopmental disabilities. Standard diagnostic tools such as cranial ultrasound and MRI are widely used in both preclinical drug development and clinical practice to detect IVH. However, these methods are limited to endpoint assessments of blood accumulation and do not capture real-time changes in germinal matrix blood flow leading to IVH. This limitation could potentially result in missed opportunities to advance drug candidates that may have protective effects against IVH. In this pilot study, we aimed to develop a noninvasive optical approach using diffuse correlation spectroscopy (DCS) to monitor real-time hemodynamic changes associated with hemorrhagic events and pre-hemorrhagic blood flow in a preclinical rabbit model of IVH. DCS measurements were conducted during the experimental induction of IVH, and results were compared with ultrasound and histological analysis to validate findings. Significant changes in hemodynamics were detected in all animals subjected to IVH-inducing procedures, including those that did not show clear positive results on ultrasound 18 h later. The study revealed progressively elevated coefficients of variation in blood flow, largely driven by temporal fluctuations in the <0.25 Hz range. Our findings suggest that real-time optical monitoring with DCS can provide critical insights heralding pathological blood flow changes, offering a more sensitive and informative tool for evaluating potential therapeutics that may help avert the progression to IVH.

Full-Waveform Inversion Imaging of Cortical Bone Using Phased Array Tomography

Classic ultrasound bone imaging modalities usually demand either a prior knowledge or an advanced estimation on speed of sound (SoS), which not only renders to a burdensome imaging process but also supplies a limited resolution. To overcome these drawbacks, this article proposed a frequency-domain full-waveform inversion (FDFWI) modality using phased array tomography for high-accuracy cortical bone imaging. A transmission scenario of ultrasound wave in 2-D space was presented in the frequency domain to simulate the forward wavefield propagation. Iterations in the inversion process were performed by matching the simulation wavefield to the experimental one from low to high discrete frequency points. Moreover, the association between the maximum initial frequency and the initial SoS model was explored to prevent the occurrence of cycle-skipping phenomenon, which could lead to the outcomes being trapped in local minima. The feasibility and effectiveness of the proposed imaging scheme were testified by simulation, phantom, and ex-vivo studies, with mean relative errors of cortical part being 3.18%, 8.71%, and 9.36%, respectively. It is verified that the proposed FDFWI method is an effective way for parametric imaging of cortical bone without any prior knowledge of sound speed.

Improved Microbubble Tracking for Super-Resolution Ultrasound Localization Microscopy using a Bi-Directional Long Short-term Memory Neural Network

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.

Non-Invasive Deep-Brain Imaging With 3D Integrated Photoacoustic Tomography and Ultrasound Localization Microscopy (3D-PAULM)

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 (sO , 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 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 further 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.

A Tracking Prior to Localization Workflow for Ultrasound Localization Microscopy

Ultrasound Localization Microscopy (ULM) has proven effective in resolving microvascular structures and local mean velocities at sub-diffraction-limited scales, offering high-resolution imaging capabilities. Dynamic ULM (DULM) enables the creation of angiography or velocity movies throughout cardiac cycles. Currently, these techniques rely on a Localization-and-Tracking (LAT) workflow consisting in detecting microbubbles (MB) in the frames before pairing them to generate tracks. While conventional LAT methods perform well at low concentrations, they suffer from longer acquisition times and degraded localization and tracking accuracy at higher concentrations, leading to biased angiogram reconstruction and velocity estimation. In this study, we propose a novel approach to address these challenges by reversing the current workflow. The proposed method, Tracking-and-Localization (TAL), relies on first tracking the MB and then performing localization. Through comprehensive benchmarking using both in silico and in vivo experiments and employing various metrics to quantify ULM angiography and velocity maps, we demonstrate that the TAL method consistently outperforms the reference LAT workflow. Moreover, when applied to DULM, TAL successfully extracts velocity variations along the cardiac cycle with improved repeatability. The findings of this work highlight the effectiveness of the TAL approach in overcoming the limitations of conventional LAT methods, providing enhanced ULM angiography and velocity imaging.

Blind-label subwavelength ultrasound imaging

There is a long-existing trade-off between the imaging resolution and penetration depth in acoustic imaging caused by the diffraction limit. Most existing approaches addressing this trade-off require controlled "labels," i.e., metamaterials or contrast agents, to be deposited close to the objects and to either remain static or be tracked precisely during imaging. We propose a "blind-label" approach for acoustic subwavelength imaging. The blind labels are randomly distributed acoustic scatterers with deep-subwavelength sizes whose exact locations and trajectories are not necessary information in image reconstruction. The proposed method achieves the resolution of 0.24 wavelengths in ultrasound imaging experiments and 0.2 wavelengths in simulations, providing over 10 times improvement compared to the diffraction limit. We also elucidate the influence of scatterer size and concentration on imaging performance. The proposed "blind-label" approach relaxes the restrictions of existing acoustic subwavelength imaging technologies relying on controlled labels, therefore substantially improving the practicality of acoustic subwavelength imaging in biomedical ultrasound imaging, sonar, and nondestructive testing.

Microvascular blood flow ultrasound imaging with microbubble-based H-Scan technology

Ultrasound blood flow imaging plays a crucial role in the diagnosis of cardiovascular and cerebrovascular diseases. Conventional ultrafast ultrasound plane-wave imaging techniques have limited capabilities in microvascular imaging. To enhance the quality of blood flow imaging, this study proposes a microbubble-based H-Scan ultrasound imaging technique. This technique utilizes high-order H-Scan to detect the Rayleigh scattering contributed by blood flow and microbubbles at certain concentrations. The detected results are then processed in the B channel using methods such as clutter filtering based on Casorati matrix singular value decomposition (Casorati-SVD). Compared with the control group without H-Scan, the signal-to-noise ratio (SNR) of the experimental group using the microbubble-based H-Scan ultrasound imaging technique was increased by 38.61% on average and the contrast signal-to-noise ratio (CNR) was increased by 39.5% on average. The improved image quality of microvascular flow imaging was visibly enhanced. This method demonstrates significant advantages in enhancing the sensitivity and accuracy of ultrasound blood flow imaging, indicating considerable potential for clinical applications.

Ultrasound localization microscopy in the diagnosis of breast tumors and prediction of relevant histologic biomarkers associated with prognosis in humans: the protocol for a prospective, multicenter study

BACKGROUND

Benign and malignant breast tumors differ in their microvasculature morphology and distribution. Histologic biomarkers of malignant breast tumors are also correlated with the microvasculature. There is a lack of imaging technology for evaluating the microvasculature. Ultrasound localization microscopy (ULM) can provide detailed microvascular architecture at super-resolution. The objective of this trial is to explore the role of ULM in distinguishing benign from malignant breast tumors and to explore the correlations between ULM qualitative and quantitative parameters and histologic biomarkers in malignant breast tumors.

METHODS/DESIGN

This prospective and multicenter study will include 83 patients with breast tumors that will undergo ULM. 55 patients will be assigned to the malignant group, and 28 patients will be assigned to the benign group. The primary outcome is the differences in the qualitative parameters (microvasculature morphology, distribution, and flow direction) between benign and malignant breast tumors on ULM. Secondary outcomes include (1) differences in the quantitative parameters (microvasculature density, tortuosity, diameter, and flow velocity) between benign and malignant breast tumors based on ULM; (2) diagnostic performance of the qualitative parameters in distinguishing benign and malignant breast tumors; (3) diagnostic performance of the quantitative parameters in distinguishing benign and malignant breast tumors; (4) relationships between the qualitative parameters and histologic biomarkers in malignant breast tumors; (5) relationships between the quantitative parameters and histologic biomarkers in malignant breast tumors; and (6) the evaluation of inter-reader and intra-reader reproducibility.

DISCUSSION

Detecting vascularity in breast tumors is of great significance to differentiate benign from malignant tumors and to predict histologic biomarkers. These histologic biomarkers, such as ER, PR, HER2 and Ki67, are closely related to prognosis evaluation. This trial will provide maximum information about the microvasculature of breast tumors and thereby will help with the formulation of subsequent differential diagnosis and the prediction of histologic biomarkers.

TRIAL REGISTRATION NUMBER/DATE

Chinese Clinical Trial Registry ChiCTR2100048361/6th/July/2021. This study is a part of that clinical trial.

3D ultrasound localization microscopy of the nonhuman primate brain

BACKGROUND

Haemodynamic changes occur in stroke and neurodegenerative diseases. Developing imaging techniques allowing the in vivo visualisation and quantification of cerebral blood flow would help better understand the underlying mechanism of these cerebrovascular diseases.

METHODS

3D ultrasound localization microscopy (ULM) is a recently developed technology that can map the microvasculature of the brain at large depth and has been mainly used until now in rodents. In this study, we tested the feasibility of 3D ULM of the nonhuman primate (NHP) brain with a single 256-channel programmable ultrasound scanner.

FINDINGS

We achieved a highly resolved vascular map of the macaque brain at large depth (down to 3 cm) in presence of craniotomy and durectomy using an 8-MHz multiplexed matrix probe. We were able to distinguish vessels as small as 26.9 μm. We also demonstrated that transcranial imaging of the macaque brain at similar depth was feasible using a 3-MHz probe and achieved a resolution of 60 μm.

INTERPRETATION

This work paves the way to clinical applications of 3D ULM. In particular, transcranial 3D ULM in humans could become a tool for the non-invasive study and monitoring of the brain cerebrovascular changes occurring in neurological diseases.

FUNDING

This work was supported by the New Frontier in Research Fund (NFRFE-2022-00590), by the Canada Foundation for Innovation under grant 38095, by the Natural Sciences and Engineering Research Council of Canada (NSERC) under discovery grant RGPIN-2020-06786, by Brain Canada under grant PSG2019, and by the Canadian Institutes of Health Research (CIHR) under grant PJT-156047 and MPI-452530. Computing support was provided by the Digital Research Alliance of Canada.

Microbubble tracking based on partial smoothing-based adaptive generalized labelled Multi-Bernoulli filter for super-resolution imaging

Super-resolution ultrasound (SRUS) can image the vasculature at microscopic resolution according to microbubble (MB) localization, with velocity vector maps obtained based on MB tracking information. High MB concentrations can reduce the acquisition time of SRUS imaging, however adjacent and intersecting vessels are difficult to distinguish, thus decreasing resolution. Low acquisition frame rates affect the precision of flow velocity estimation. This study proposes a partial smoothing-based adaptive generalized labeled multi-Bernoulli filter (SAGLMB) to precisely track the MB motion at different flow velocities. SAGLMB employs a generalized labelled multi-Bernoulli filter (GLMB) for MB trajectory allocation to separate adjacent and intersecting vessels. Furthermore, the nonlinear motion of MB was predicted by an unscented Kalman filter, and a cardinalized probability hypothesis density filter was applied to suppress clutter interference. Finally, the trajectories were smoothed by unscented Rauch-Tung-Striebel to improve the resolution of the SRUS image. The simulation results demonstrate that SAGLMB outperforms the conventional bipartite graph-based tracking at high MB concentrations, achieving at least an 8.55 % improvement in the correctly paired precision, with 3 times increase in the structural similarity index measure. Moreover, SAGLMB can obtain more precise flow velocity estimations with a 4 times improvement than the conventional method. The SRUS results of rabbit kidney show that the proposed method significantly improves resolution of adjacent and intersecting vessels at higher MB concentrations and maintains this performance as the acquisition frame rate decreases. Furthermore, the rat brain microvascular network was reconstructed with 9.21 μm (λ/11.1) resolution. Therefore, SAGLMB can achieve robust SRUS imaging at high concentrations and low acquisition frame rates.

Assessment of microvascular flow in human atherosclerotic carotid plaques using ultrasound localization microscopy

BACKGROUND

Neovascularisation of carotid plaques contributes to their vulnerability. Current imaging methods such as contrast-enhanced ultrasound (CEUS) usually lack the required spatial resolution and quantification capability for precise neovessels identification. We aimed at quantifying plaque vascularisation with ultrasound localization microscopy (ULM) and compared the results to histological analysis.

METHODS

We conducted a prospective, monocentric, study involving patients who were undergoing carotid endarterectomy (CEA) for carotid artery stenosis. The day before CEA ultrasound examination coupled with the injection of microbubbles (MB) as a contrast agent (CEUS) to image the MB circulating within and around the carotid plaque was performed. CEUS images analysis classified patients into 2 groups: absence of neovascularisation (group A) or presence of neovascularisation (group B). ULM was performed by localising and tracking individual MB centres to reconstruct the neovessels structure with a resolution of around 60 μm. Plaques were manually segmented on the images to quantify the number of neovessels and various haemodynamic metrics inside the plaques. Histological analysis of the excised carotid plaque specimens classified patients into 2 groups: absence of neovascularisation (group I) or presence of neovascularisation (group II).

FINDINGS

Among the 26 patients included, classification was as follows: group I: n = 8 and group II: n = 18, 18 patients had analysable CEUS images and were classified as follows: group A: n = 10, group B: n = 8. The median (Q1-Q3) number of MB tracked per second inside the plaque was 0.03 (0-0.37) for patients in group I and 0.51 (0-3) for patients in group A versus (vs.) 3.55 (1.26-17.68) for patients in group II and 9.69 (5.83-34.68) for patients in group B (p = 0.00049; p = 0.010 respectively). The length of the MB tracks was 0.02 mm (0-0.16) in group I vs. 0.29 mm (0.22-0.45) in group II (p = 0.0069). The study also showed that flow in the neovessels was greater during systole than during diastole period: 9.38 (1.67-19.17) MB tracked per second vs. 1.35 (0.28-6.56) (p = 0.021).

INTERPRETATION

ULM allows the detection of neovessels within the carotid atherosclerotic plaque. Thus, ULM provides a precise picture of plaque neovascularisation in patients and could be used as a non-invasive imaging technique to assess carotid plaque vulnerability.

FUNDING

The study was sponsored and funded by Assistance Publique-Hôpitaux de Paris (CRC 1806 APHP INNOVATION 2018). Co-funding by ART (Technological Research Accelerator) biomedical ultrasound program of INSERM, France.

Focal liver lesions: multiparametric microvasculature characterization via super-resolution ultrasound imaging

BACKGROUND

Noninvasive and functional imaging of the focal liver lesion (FLL) vasculature at microscopic scales is clinically challenging. We investigated the feasibility of using super-resolution ultrasound (SR-US) imaging for visualizing and quantifying the microvasculature of intraparenchymal FLLs.

METHODS

Patients with FLLs between June 2022 and February 2023 were prospectively screened. Following bolus injection of microbubbles at clinical concentration, SR-US was performed using a high frame rate (350-500 Hz) modified ultrasound scanner and a convex array transducer with a central frequency of 3.1 MHz.

RESULTS

In total, 47 pathologically proven FLLs at a depth of 5.7 ± 1.7 cm (mean ± standard deviation) were included: 30 hepatocellular carcinomas (HCC), 11 liver metastases (LM), and 6 focal nodular hyperplasias (FNH). The smallest detectable vessel size of the hepatic microvasculature was 128.4 ± 18.6 μm (mean ± standard deviation) at a depth of 8 cm. Significant differences were observed among the three types of lesions in terms of pattern categories, vessel density, minimum flow velocity, and perfusion index. We observed higher vessel density for FNH versus liver parenchyma (p < 0.001) as well as fractal dimension and local flow direction entropy value for FNH versus HCC (p = 0.002 and p < 0.001, respectively) and for FNH versus LM (p = 0.006 and p = 0.002, respectively).

CONCLUSION

Multiparametric SR-US showed that these three pathological types of FLLs have specific microvascular phenotypes. Vessel density, fractal dimension and local flow direction entropy served as valuable parameters in distinguishing between benign and malignant FLLs.

TRIAL REGISTRATION

ClinicalTrials.gov (NCT06018142).

RELEVANCE STATEMENT

Multiparametric SR-US imaging offers precise morphological and functional assessment of the microvasculature of intraparenchymal focal liver lesions, providing insights into tumor heterogeneity and angiogenesis.

KEY POINTS

Super-resolution (SR)-US imaging allowed morphological and functional evaluation of intraparenchymal hepatic lesion microvasculature. Hepatocellular carcinoma, liver metastasis, and focal nodular hyperplasia exhibit distinct microvascular architectures and hemodynamic profiles. Multiparametric microvasculature characterization via SR-US imaging facilitates the differentiation between benign and malignant microvascular phenotypes.

Non-invasive 4D transcranial functional ultrasound and ultrasound localization microscopy for multimodal imaging of neurovascular response

A long-standing goal of neuroimaging is the non-invasive volumetric assessment of whole brain function and structure at high spatial and temporal resolutions. Functional ultrasound (fUS) and ultrasound localization microscopy (ULM) are rapidly emerging techniques that promise to bring advanced brain imaging and therapy to the clinic with the safety and low-cost advantages associated with ultrasound. fUS has been used to study cerebral hemodynamics at high temporal resolutions while ULM has been used to study cerebral microvascular structure at high spatial resolutions. These two methods have complementary spatio-temporal characteristics, making them ideally suited for multimodal imaging, but both suffer from limitations associated with transcranial ultrasound imaging. Here, these two methods are combined on the same data acquisition, completely non-invasively, using contrast-enhancements, which solves the dual challenges of sensitivity during transcranial imaging and the ability to implement super-resolution. From this combined approach, the cerebral blood flow, activated brain region, brain connectivity, vessel diameter, and vessel velocity were all calculated from the same data acquisition. During stimulation periods, there was a statistically significant (p<0.0001) increase in cerebral blood flow, diameter, and global velocity, but a decrease in velocity in the activated region. Additionally, the global flow increased (p=0.11) and connectivity decreased (24.7%) when compared to baseline. This multimodal approach allows for the study of the relationship between cerebral hemodynamics (30 ms resolution) and the microvasculature (14.6 μm resolution) using one ultrasound scan.

Underestimation of Flow Velocity in 2-D Super-Resolution Ultrasound Imaging

Velocity estimation in ultrasound imaging is a technique to measure the speed and direction of blood flow. The flow velocity in small blood vessels, i.e., arterioles, venules, and capillaries, can be estimated using super-resolution ultrasound imaging (SRUS). However, the vessel width in SRUS is relatively small compared with the full-width-half-maximum of the ultrasound beam in the elevation direction, which directly impacts the velocity estimation. By taking into consideration the small vessel widths in SRUS, it is hypothesized that the velocity is underestimated in 2-D SRUS when the vessel diameter is smaller than the full width at half maximum elevation resolution of the transducer (FWHMy). A theoretical model is introduced to show that the velocity of a 3-D parabolic velocity profile is underestimated by up to 33% in 2-D SRUS, if the width of the vessel is smaller than FWHMy. This model was tested using Field II simulations and 3-D-printed micro-flow hydrogel phantom measurements. A Verasonics Vantage 256 scanner and a GE L8-18i-D linear array transducer with FWHMy of approximately at the elevation focus were used in the simulations and measurements. Simulations of different parabolic velocity profiles showed that the velocity underestimation was 36.8% % (mean ± standard deviation). The measurements showed that the velocity was underestimated by 30% %. Moreover, the results of vessel diameters, ranging from FWHMy to FWHMy, indicate that velocities are estimated according to the theoretical model. The theoretical model can, therefore, be used for the compensation of velocity estimates under these circumstances.

An adaptive spatiotemporal filter for ultrasound localization microscopy based on density canopy clustering

Ultrasound Localization Microscopy (ULM) facilitates structural and hemodynamic imaging of microvessels with a resolution of tens of micrometers. In ULM, the extraction of effective microbubble signals is crucial for image quality. Singular Value Decomposition (SVD) is currently the most prevalent method for microbubble signal extraction in ULM. Most existing ULM studies employ a fixed SVD filter threshold using empirical values which will lead to imaging quality degradation due to the insufficient separation of blood signals. In this study, we propose an adaptive and non-threshold SVD filter based on canopy-density clustering, termed DCC-SVD. This filter automatically classifies the components of the SVD based on the density of their spatiotemporal features, eliminating the need for parameter selection. In in vitro tube phantom, DCC-SVD demonstrated its ability to adaptive separation of blood and bubble signal at varying microbubble concentrations and flow rates. We compared the proposed DCC-SVD method with the Block-match 3D (BM3D) filter and a classical adaptive method called spatial similarity matrix (SSM), using concentration-variable in vivo rat brain data, as well as open-source rat kidney and mouse tumor datasets. The proposed DCC-SVD improved the global spatial resolution by approximately 4 μm from 30.39 μm to 26.02 μm. It also captured vessel structure absent in images obtained by other methods and yielded a smoother vessel intensity profile, making it a promising spatiotemporal filter for ULM imaging.

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.

Deep Learning in Ultrasound Localization Microscopy: Applications and Perspectives

Ultrasound localization microscopy (ULM) is a novel super-resolution imaging technique that can image the vasculature in vivo at depth with resolution far beyond the conventional limit of diffraction. By relying on the localization and tracking of clinically approved microbubbles injected in the blood stream, ULM can provide not only anatomical visualization but also hemodynamic quantification of the microvasculature. Several deep learning approaches have been proposed to address challenges in ULM including denoising, improving microbubble localization, estimating blood flow velocity, or performing aberration correction. Proposed deep learning methods often outperform their conventional counterparts by improving image quality and reducing processing time. In addition, their robustness to high concentrations of microbubbles can lead to reduced acquisition times in ULM, addressing a major hindrance to ULM clinical application. Herein, we propose a comprehensive review of the diversity of deep learning applications in ULM focusing on approaches assuming a sparse microbubble distribution. We first provide an overview of how existing studies vary in the constitution of their datasets or in the tasks targeted by the deep learning model. We also take a deeper look into the numerous approaches that have been proposed to improve the localization of microbubbles since they differ highly in their formulation of the optimization problem, their evaluation, or their network architectures. We finally discuss the current limitations and challenges of these methods, as well as the promises and potential of deep learning for ULM in the future.

Optically Validated Microvascular Phantom for Super-Resolution Ultrasound Imaging

Super-resolution ultrasound (SRUS) visualizes microvasculature beyond the ultrasound (US) diffraction limit (wavelength( )/2) by localizing and tracking spatially isolated microbubble (MB) contrast agents. SRUS phantoms typically consist of simple tube structures, where diameter channels below m are not available. Furthermore, these phantoms are generally fragile and unstable, have limited ground truth validation, and their simple structure limits the evaluation of SRUS algorithms. To aid SRUS development, robust and durable phantoms with known and physiologically relevant microvasculature are needed for repeatable SRUS testing. This work proposes a method to fabricate durable microvascular phantoms that allow optical gauging for SRUS validation. The methodology used a microvasculature negative print embedded in a Polydimethylsiloxane (PDMS) to fabricate a microvascular phantom. Branching microvascular phantoms with variable microvascular density were demonstrated with optically validated vessel diameters down to m ( ; m). SRUS imaging was performed and validated with optical measurements. The average SRUS error was m ( ) with a standard deviation error of m. The average error decreased to m ( ) once the number of localized MBs surpassed 1000 per estimated diameter. In addition, less than 10% variance of acoustic and optical properties and the mechanical toughness of the phantoms measured a year after fabrication demonstrated their long-term durability. This work presents a method to fabricate durable and optically validated complex microvascular phantoms which can be used to quantify SRUS performance and facilitate its further development.

Influence of Image Discretization and Patch Size on Microbubble Localization Precision

For ultrasound localization microscopy, the localization of microbubbles (MBs) is an essential part to obtain super-resolved maps of the vasculature. This article analyzes the impact of image discretization and patch size on the precision of different MB localization methods to reconcile different observations from previous studies, provide an estimate of feasible localization precision, and derive guidelines for an optimal parameter selection. For this purpose, the images of MBs were simulated with Gaussian point-spread functions (PSFs) of varying width parameter at randomly generated subpixel positions, and Rician distributed noise was added. Four localization methods were tested on the patches of different sizes (number of pixels ): Gaussian fit (GF), radial symmetry (RS) method, calculation of center of mass (CoM), and peak detection (PD). Additionally, the Cramér-Rao lower bound (CRLB) for the given estimation problem was calculated. Our results show that the localization precision is strongly influenced by the ratio of the PSF width parameter to the pixel size , as well as the patch size N. The best parameter combination depends on the localization method. Generally, very small ratios as well as large ratios in combination with small N lead to performance degradation. The GF as a representative of a model-based fit comes close to the CRLB and always performs best for the ratios given by image discretization if N is adapted to the PSF. To achieve good results with the GF and the RS method, a good rule of thumb is to set the pixel sizes and the patch sizes .

Ultrasound Control of Genomic Regulatory Toolboxes for Cancer Immunotherapy

There remains a critical need for the precise control of CRISPR (clustered regularly interspaced short palindromic repeats)-based technologies. Here, we engineer a set of inducible CRISPR-based tools controllable by focused ultrasound (FUS), which can penetrate deep and induce localized hyperthermia for transgene activation. We demonstrate the capabilities of FUS-inducible CRISPR, CRISPR activation (CRISPRa), and CRISPR epigenetic editor (CRISPRee) in modulating the genome and epigenome. We show that FUS-CRISPR-mediated telomere disruption primes solid tumours for chimeric antigen receptor (CAR)-T cell therapy. We further deliver FUS-CRISPR in vivo using adeno-associated viruses (AAVs), followed by FUS-induced telomere disruption and the expression of a clinically validated antigen in a subpopulation of tumour cells, functioning as "training centers" to activate synthetic Notch (synNotch) CAR-T cells to produce CARs against a universal tumour antigen to exterminate neighboring tumour cells. The FUS-CRISPR(a/ee) toolbox hence allows the noninvasive and spatiotemporal control of genomic/epigenomic reprogramming for cancer treatment.

Volumetric Ultrasound Localization Microscopy

Super-resolution ultrasound (SRUS) has evolved significantly with the advent of ultrasound localization microscopy (ULM). This technique enables subwavelength resolution imaging using microbubble contrast agents. Initially confined to 2-D imaging, ULM has progressed toward volumetric approaches, allowing for comprehensive 3-D visualization of microvascular networks. This review explores the technological advancements and challenges associated with volumetric ULM, focusing on key aspects such as transducer design, acquisition speed, data processing algorithms, or integration into clinical practice. We discuss the limitations of traditional 2-D ULM, including dependence on precise imaging plane selection and compromised resolution in microvasculature quantification. In contrast, volumetric ULM offers enhanced spatial resolution and allows motion correction in all directions, promising transformative insights into microvascular pathophysiology. By examining current research and future directions, this review highlights the potential of volumetric ULM to contribute significantly to diagnostic across various medical conditions, including cancers, arteriosclerosis, strokes, diabetes, and neurodegenerative diseases.

Efficient Microbubble Trajectory Tracking in Ultrasound Localization Microscopy Using a Gated Recurrent Unit-Based Multitasking Temporal Neural Network

Ultrasound localization microscopy (ULM), an emerging medical imaging technique, effectively resolves the classical tradeoff between resolution and penetration inherent in traditional ultrasound imaging, opening up new avenues for noninvasive observation of the microvascular system. However, traditional microbubble tracking methods encounter various practical challenges. These methods typically entail multiple processing stages, including intricate steps such as pairwise correlation and trajectory optimization, rendering real-time applications unfeasible. Furthermore, existing deep learning-based tracking techniques neglect the temporal aspects of microbubble motion, leading to ineffective modeling of their dynamic behavior. To address these limitations, this study introduces a novel approach called the gated recurrent unit-based multitasking temporal neural network (GRU-MT). GRU-MT is designed to simultaneously handle microbubble trajectory tracking and trajectory optimization tasks. In addition, we enhance the nonlinear motion model initially proposed by Piepenbrock et al. to better encapsulate the nonlinear motion characteristics of microbubbles, thereby improving trajectory tracking accuracy. In this study, we perform a series of experiments involving network layer replacements to systematically evaluate the performance of various temporal neural networks, including recurrent neural network (RNN), long short-term memory network (LSTM), GRU, Transformer, and its bidirectional counterparts, on the microbubble trajectory tracking task. Concurrently, the proposed method undergoes qualitative and quantitative comparisons with traditional microbubble tracking techniques. The experimental results demonstrate that GRU-MT exhibits superior nonlinear modeling capabilities and robustness, both in simulation and in vivo dataset. In addition, it achieves reduced trajectory tracking errors in shorter time intervals, underscoring its potential for efficient microbubble trajectory tracking. The model code is open-sourced at https://github.com/zyt-Lib/GRU-MT.

Volumetric Ultrasound Localization Microscopy With Diverging Cylindrical Waves

Transcranial ultrasound plays a limited role in neuroradiology due to its lack of resolution, planar imaging, and user dependency. By breaching the diffraction limit using injected microbubbles, volumetric ultrasound localization microscopy (ULM) could help alleviate those issues. However, performing 3-D ultrasound imaging at a high frame rate with sufficient signal-to-noise ratio (SNR) to track individual microbubbles through the skull remains a challenge, especially with a portable scanner. In this study, we describe a ULM sequence suitable for volumetric transcranial imaging exploiting cylindrical emissions on multiplexed matrix probes, through simulations, hydrophone measurements, and flow phantoms. This geometry leads to a doubling of the peak acoustic pressure, up to 400 kPa, with respect to spherical emission and improved volume rate, up to 180 Hz. Cylindrical emissions also improve the ULM saturation rate by 60% through a skull phantom. The assessment of microbubble velocity was also improved from a 33% error in the average flow measured with spherical waves to a 5% error with cylindrical waves. Conversely, we demonstrate the detrimental impacts of cylindrical waves toward the field of view and isotropic sensitivity. Nevertheless, due to its enhanced SNR and 3-D nature, such a cylindrical volumetric sequence could be beneficial for ULM as a diagnostic tool in humans, especially when portability is a necessity.

Whole Organ Volumetric Sensing Ultrasound Localization Microscopy for Characterization of Kidney Structure

Glomeruli are the filtration units of the kidney and their function relies heavily on their microcirculation. Despite its obvious diagnostic importance, an accurate estimation of blood flow in the capillary bundle within glomeruli defies the resolution of conventional imaging modalities. Ultrasound Localization Microscopy (ULM) has demonstrated its ability to image in-vivo deep organs in the body. Recently, the concept of sensing ULM or sULM was introduced to classify individual microbubble behavior based on the expected physiological conditions at the micrometric scale. In the kidney of both rats and humans, it revealed glomerular structures in 2D but was severely limited by planar projection. In this work, we aim to extend sULM in 3D to image the whole organ and in order to perform an accurate characterization of the entire kidney structure. The extension of sULM into the 3D domain allows better localization and more robust tracking. The 3D metrics of velocity and pathway angular shift made glomerular mask possible. This approach facilitated the quantification of glomerular physiological parameter such as an interior traveled distance of approximately 7.5 ±0.6 microns within the glomerulus. This study introduces a technique that characterize the kidney physiology which can serve as a method to facilite pathology assessment. Furthermore, its potential for clinical relevance could serve as a bridge between research and practical application, leading to innovative diagnostics and improved patient care.

Phase-change ultrasound contrast agents for proton range verification: towards anin vivoapplication

Objective.In proton therapy, range uncertainties prevent optimal benefit from the superior depth-dose characteristics of proton beams over conventional photon-based radiotherapy. To reduce these uncertainties we recently proposed the use of phase-change ultrasound contrast agents as an affordable and effective range verification tool. In particular, superheated nanodroplets can convert into echogenic microbubbles upon proton irradiation, whereby the resulting ultrasound contrast relates to the proton range with high reproducibility. Here, we provide a firstin vivoproof-of-concept of this technology.Approach.First, thein vitrobiocompatibility of radiation-sensitive poly(vinyl alcohol) perfluorobutane nanodroplets was investigated using several colorimetric assays. Then,in vivoultrasound contrast was characterized using acoustic droplet vaporization (ADV) and later using proton beam irradiations at varying energies (49.7 MeV and 62 MeV) in healthy Sprague Dawley rats. A preliminary evaluation of thein vivobiocompatibility was performed using ADV and a combination of physiology monitoring and histology.Main results.Nanodroplets were non-toxic over a wide concentration range (<1 mM). In healthy rats, intravenously injected nanodroplets primarily accumulated in the organs of the reticuloendothelial system, where the lifetime of the generated ultrasound contrast (<30 min) was compatible with a typical radiotherapy fraction (<5 min). Spontaneous droplet vaporization did not result in significant background signals. Online ultrasound imaging of the liver of droplet-injected rats demonstrated an energy-dependent proton response, which can be tuned by varying the nanodroplet concentration. However, caution is warranted when deciding on the exact nanodroplet dose regimen as a mild physiological response (drop in cardiac rate, granuloma formation) was observed after ADV.Significance.These findings underline the potential of phase-change ultrasound contrast agents forin vivoproton range verification and provide the next step towards eventual clinical applications.

Super-resolution ultrasound imaging reveals temporal cerebrovascular changes with disease progression in female 5×FAD mouse model of Alzheimer's disease: correlation with pathological impairments

BACKGROUND

Vascular dysfunction is closely associated with the progression of Alzheimer's disease (AD). A critical research gap exists that no studies have explored the in vivo temporal changes of cerebrovascular alterations with AD progression in mouse models, encompassing both structure and flow dynamics at micron-scale resolution across the early, middle, and late stages of the disease.

METHODS

In this study, ultrasound localisation microscopy (ULM) was applied to image the cerebrovascular alterations of the transgenic female 5×FAD mouse model across different stages of disease progression: early (4 months), moderate (7 months), and late (12 months). Age-matched non-transgenic (non-Tg) littermates were used as controls. Immunohistology examinations were performed to evaluate the influence of disease progression on the β-amyloid (Aβ) load and microvascular alterations, including morphological changes and the blood-brain barrier (BBB) leakage.

FINDINGS

Our findings revealed a significant decline in both vascular density and flow velocity in the retrosplenial cortex of 5×FAD mice at an early stage, which subsequently became more pronounced in the visual cortex and hippocampus as the disease progressed. Additionally, we observed a reduction in vascular length preceding diminished flow velocities in cortical penetrating arterioles during the early stages. The quantification of vascular metrics derived from ULM imaging showed significant correlations with those obtained from vascular histological images. Immunofluorescence staining identified early vascular abnormalities in the retrosplenial cortex. As the disease advanced, there was an exacerbation of Aβ accumulation and BBB disruption in a regionally variable manner. The vascular changes observed through ULM imaging exhibited a negative correlation with amyloid load and were associated with the compromise of the BBB integrity.

INTERPRETATION

Through high-resolution, in vivo imaging of cerebrovasculature, this study reveals significant spatiotemporal dysfunction in cerebrovascular dynamics accompanying disease progression in a mouse model of AD, enhancing our understanding of its pathophysiology.

FUNDING

This study is supported by grants from National Key Research and Development Program of China (2020YFA0908800), National Natural Science Foundation of China (12074269, 82272014, 82327804, 62071310), Shenzhen Basic Science Research (20220808185138001, JCYJ20220818095612027, JCYJ20210324093006017), STI 2030-Major Projects (2021ZD0200500) and Guangdong Natural Science Foundation (2024A1515012591, 2024A1515011342).

Capillary-scale Microvessel Imaging with High-frequency Ultrasound Localization Microscopy in Mouse 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 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.

RF-ULM: Ultrasound Localization Microscopy Learned From Radio-Frequency Wavefronts

In Ultrasound Localization Microscopy (ULM), achieving high-resolution images relies on the precise localization of contrast agent particles across a series of beamformed frames. However, our study uncovers an enormous potential: The process of delay-and-sum beamforming leads to an irreversible reduction of Radio-Frequency (RF) channel data, while its implications for localization remain largely unexplored. The rich contextual information embedded within RF wavefronts, including their hyperbolic shape and phase, offers great promise for guiding Deep Neural Networks (DNNs) in challenging localization scenarios. To fully exploit this data, we propose to directly localize scatterers in RF channel data. Our approach involves a custom super-resolution DNN using learned feature channel shuffling, non-maximum suppression, and a semi-global convolutional block for reliable and accurate wavefront localization. Additionally, we introduce a geometric point transformation that facilitates seamless mapping to the B-mode coordinate space. To understand the impact of beamforming on ULM, we validate the effectiveness of our method by conducting an extensive comparison with State-Of-The-Art (SOTA) techniques. We present the inaugural in vivo results from a wavefront-localizing DNN, highlighting its real-world practicality. Our findings show that RF-ULM bridges the domain shift between synthetic and real datasets, offering a considerable advantage in terms of precision and complexity. To enable the broader research community to benefit from our findings, our code and the associated SOTA methods are made available at https://github.com/hahnec/rf-ulm.

Curved Toroidal Row Column Addressed Transducer for 3D Ultrafast Ultrasound Imaging

3D Imaging of the human heart at high frame rate is of major interest for various clinical applications. Electronic complexity and cost has prevented the dissemination of 3D ultrafast imaging into the clinic. Row column addressed (RCA) transducers provide volumetric imaging at ultrafast frame rate by using a low electronic channel count, but current models are ill-suited for transthoracic cardiac imaging due to field-of-view limitations. In this study, we proposed a mechanically curved RCA with an aperture adapted for transthoracic cardiac imaging ( 24×16 mm2). The RCA has a toroidal curved surface of 96 elements along columns (curvature radius rC = 4.47 cm) and 64 elements along rows (curvature radius rR = 3 cm). We implemented delay and sum beamforming with an analytical calculation of the propagation of a toroidal wave which was validated using simulations (Field II). The imaging performance was evaluated on a calibrated phantom. Experimental 3D imaging was achieved up to 12 cm deep with a total angular aperture of 30° for both lateral dimensions. The Contrast-to-Noise ratio increased by 12 dB from 2 to 128 virtual sources. Then, 3D Ultrasound Localization Microscopy (ULM) was characterized in a sub-wavelength tube diameter. Finally, 3D ULM was demonstrated on a perfused ex-vivo swine heart to image the coronary microcirculation.

Dynamic Ultrasound Localization Microscopy Without ECG-Gating

OBJECTIVE

Dynamic Ultrasound Localization Microscopy (DULM) has first been developed for non-invasive Pulsatility measurements in the rodent brain. DULM relies on the localization and tracking of microbubbles (MBs) injected into the bloodstream, to obtain highly resolved velocity and density cine-loops. Previous DULM techniques required ECG-gating, limiting its application to specific datasets, and increasing acquisition time. The objective of this study is to eliminate the need for ECG-gating in DULM experiments by introducing a motion-matching method for time registration.

METHODS

We developed a motion-matching algorithm based on tissue Doppler that leverages the cyclic tissue motion within the brain. Tissue Doppler was estimated for each group of frames in the acquisitions, at multiple locations identified as local maxima in the skin above the skull. Subsequently, each group of frames was time-registered to a reference group by delaying it based on the maximum correlation value between their respective tissue Doppler signals. This synchronization ensured that each group of frames aligned with the brain tissue motion of the reference group, and consequently, with its cardiac cycle. As a result, velocities of MBs could be averaged to retrieve flow velocity variations over time.

RESULTS

Initially validated in ECG-gated acquisitions in a rat model (n = 1), the proposed method was successfully applied in a mice model in 2D (n = 3) and in a feline model in 3D (n = 1). Performing time-registration with the proposed motion-matching method or by using ECG-gating leads to similar results. For the first time, dynamic velocity and density cine-loops were extracted without the need for any information on the animal ECG, and complex dynamic markers such as the Pulsatility index were estimated.

CONCLUSION

Results suggest that DULM can be performed without external gating, enabling the use of DULM on any ULM dataset where enough MBs are detectable. Time registration by motion-matching represents a significant advancement in DULM techniques, making DULM more accessible by simplifying its experimental complexity.

High-Resolution Power Doppler Using Null Subtraction Imaging

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 three types of singular value decomposition (SVD)-based clutter filters and noise equalization to generate high-resolution PD images. An element sensitivity correction scheme was also proposed as a crucial component of NSI-based PD imaging. First, a microbubble trace experiment was performed to evaluate the resolution improvement of NSI-based PD over traditional DAS-based PD. Then, both contrast-enhanced and contrast free ultrasound PD images were generated from the scan of a rat brain. The cross-sectional profile of the microbubble traces and microvessels were plotted. FWHM was also estimated to provide a quantitative metric. Furthermore, iso-frequency curves were calculated to provide a resolution evaluation metric over the global field of view. Up to six-fold resolution improvement was demonstrated by the FWHM estimate and four-fold resolution improvement was demonstrated by the iso-frequency curve from the NSI-based PD microvessel images compared to microvessel images generated by traditional DAS-based beamforming. A resolvability of [Formula: see text] was measured from the NSI-based PD microvessel image. The computational cost of NSI-based PD was only increased by 40 percent over the DAS-based PD.

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.

Multiparametric Brain Hemodynamics Imaging Using a Combined Ultrafast Ultrasound and Photoacoustic System

Studying brain-wide hemodynamic responses to different stimuli at high spatiotemporal resolutions can help gain new insights into the mechanisms of neuro- diseases and -disorders. Nonetheless, this task is challenging, primarily due to the complexity of neurovascular coupling, which encompasses interdependent hemodynamic parameters including cerebral blood volume (CBV), cerebral blood flow (CBF), and cerebral oxygen saturation (SO2). The current brain imaging technologies exhibit inherent limitations in resolution, sensitivity, and imaging depth, restricting their capacity to comprehensively capture the intricacies of cerebral functions. To address this, a multimodal functional ultrasound and photoacoustic (fUSPA) imaging platform is reported, which integrates ultrafast ultrasound and multispectral photoacoustic imaging methods in a compact head-mountable device, to quantitatively map individual dynamics of CBV, CBF, and SO2 as well as contrast agent enhanced brain imaging at high spatiotemporal resolutions. Following systematic characterization, the fUSPA system is applied to study brain-wide cerebrovascular reactivity (CVR) at single-vessel resolution via relative changes in CBV, CBF, and SO2 in response to hypercapnia stimulation. These results show that cortical veins and arteries exhibit differences in CVR in the stimulated state and consistent anti-correlation in CBV oscillations during the resting state, demonstrating the multiparametric fUSPA system's unique capabilities in investigating complex mechanisms of brain functions.

Super-Resolution Ultrasound Imaging Using the Erythrocytes-Part II: Velocity Images

Super-resolution ultrasound imaging using the erythrocytes (SURE) has recently been introduced. The method uses erythrocytes as targets instead of fragile microbubbles (MBs). The abundance of erythrocyte scatterers makes it possible to acquire SURE data in just a few seconds compared with several minutes in ultrasound localization microscopy (ULM) using MBs. A high number of scatterers can reduce the acquisition time; however, the tracking of uncorrelated and high-density scatterers is quite challenging. This article hypothesizes that it is possible to detect and track erythrocytes as targets to obtain vascular flow images. A SURE tracking pipeline is used with modules for beamforming, recursive synthetic aperture (SA) imaging, motion estimation, echo canceling, peak detection, and recursive nearest-neighbor (NN) tracker. The SURE tracking pipeline is capable of distinguishing the flow direction and separating tubes of a simulated Field II phantom with 125-25- [Formula: see text] wall-to-wall tube distances, as well as a 3-D printed hydrogel micr-flow phantom with 100-60- [Formula: see text] wall-to-wall channel distances. The comparison of an in vivo SURE scan of a Sprague-Dawley rat kidney with ULM and micro-computed tomography (CT) scans with voxel sizes of 26.5 and [Formula: see text] demonstrated consistent findings. A microvascular structure composed of 16 vessels exhibited similarities across all imaging modalities. The flow direction and velocity profiles in the SURE scan were found to be concordant with those from ULM.

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

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

An Automated Heart Shunt Recognition Pipeline Using Deep Neural Networks

Automated recognition of heart shunts using saline contrast transthoracic echocardiography (SC-TTE) has the potential to transform clinical practice, enabling non-experts to assess heart shunt lesions. This study aims to develop a fully automated and scalable analysis pipeline for distinguishing heart shunts, utilizing a deep neural network-based framework. The pipeline consists of three steps: (1) chamber segmentation, (2) ultrasound microbubble localization, and (3) disease classification model establishment. The study's normal control group included 91 patients with intracardiac shunts, 61 patients with extracardiac shunts, and 84 asymptomatic individuals. Participants' SC-TTE images were segmented using the U-Net model to obtain cardiac chambers. The segmentation results were combined with ultrasound microbubble localization to generate multivariate time series data on microbubble counts in each chamber. A classification model was then trained using this data to distinguish between intracardiac and extracardiac shunts. The proposed framework accurately segmented heart chambers (dice coefficient = 0.92 ± 0.1) and localized microbubbles. The disease classification model achieved high accuracy, sensitivity, specificity, F1 score, kappa value, and AUC value for both intracardiac and extracardiac shunts. For intracardiac shunts, accuracy was 0.875 ± 0.008, sensitivity was 0.891 ± 0.002, specificity was 0.865 ± 0.012, F1 score was 0.836 ± 0.011, kappa value was 0.735 ± 0.017, and AUC value was 0.942 ± 0.014. For extracardiac shunts, accuracy was 0.902 ± 0.007, sensitivity was 0.763 ± 0.014, specificity was 0.966 ± 0.008, F1 score was 0.830 ± 0.012, kappa value was 0.762 ± 0.017, and AUC value was 0.916 ± 0.006. The proposed framework utilizing deep neural networks offers a fast, convenient, and accurate method for identifying intracardiac and extracardiac shunts. It aids in shunt recognition and generates valuable quantitative indices, assisting clinicians in diagnosing these conditions.

Visualization of Renal Glomeruli in Human Native Kidneys With Sensing Ultrasound Localization Microscopy

OBJECTIVES

Kidney diseases significantly impact individuals' quality of life and strongly reduce life expectancy. Glomeruli play a crucial role in kidney function. Current imaging techniques cannot visualize them due to their small size. Sensing ultrasound localization microscopy (sULM) has shown promising results for visualizing in vivo the glomeruli of human kidney grafts. This study aimed to evaluate the ability of sULM to visualize glomeruli in vivo in native human kidneys despite their depth and a shorter duration of ultrasound acquisition limited by the period of the patient's apnea. Sensing ultrasound localization microscopy parameters in native kidneys and kidney grafts and their consequence regarding glomeruli detection were also compared.

MATERIALS AND METHODS

Exploration by sULM was conducted in 15 patients with native kidneys and 5 with kidney allografts. Glomeruli were counted using a normalized distance metric projected onto sULM density maps. The difference in the acquisition time, the kidney depth, and the frame rate between native kidneys and kidney grafts and their consequence regarding glomeruli detection were assessed.

RESULTS

Glomerular visualization was achieved in 12 of 15 patients with native kidneys. It failed due to impossible breath-holding for 2 patients and a too-deep kidney for 1 patient. Sensing ultrasound localization microscopy found 16 glomeruli per square centimeter in the native kidneys (6-31) and 33 glomeruli per square centimeter in kidney transplant patients (18-55).

CONCLUSIONS

This study demonstrated that sULM can visualize glomeruli in native human kidneys in vivo. The proposed method may have many hypothetical applications, including biomarker development, assisting biopsy, or potentially avoiding it. It establishes a framework for improving the detection of local microstructural pathology, influencing the evaluation of allografts, and facilitating disease monitoring in the native kidney.

Metabolic Pathways in Hydrocephalus: Profiling with Proteomics and Advanced Imaging

Hemorrhagic hydrocephalus is a common pathology in neonates with high mortality and morbidity. Current imaging approaches fail to capture the mechanisms behind its pathogenesis. Here, we discuss the processes underlying this pathology, the metabolic dysfunction that occurs as a result, and the ways in which these metabolic changes inform novel methods of clinical imaging. The imaging advances described allow earlier detection of the cellular and metabolic changes, leading to better outcomes for affected neonates.

High-Resolution Ultrasound Platform for Infant Meningitis Detection: An In Vitro Demonstration

Infant meningitis remains a severe burden on global health, particularly for young infants. Traditional ultrasound imaging techniques are limited in spatial resolution to visualize white blood cells (WBCs) in the cerebrospinal fluid (CSF), which is considered a well-established marker for meningitis detection. This work presents a novel platform that uses high-resolution ultrasound to detect the backscatter signals from microscopic CSF WBCs through the anterior fontanelle of neonates and young infants. The whole system was built around a custom probe that allows for a 20 MHz focused transducer to be mechanically controlled to map the area of interest in the CSF. Data processing can be performed internally in the device without the need to extract the images for further analysis. The in vitro feasibility of the proposed solution was evaluated in imaging 7 μm particle suspensions at different concentrations relevant to meningitis diagnosis ranging from 7- to 646-particles (pp)/μL. The experimental tests were conducted from a simple setup using a sample container to a more realistic setup based on an anatomical phantom of the neonatal head. The results show high-quality images, where 7 μm particles can be resolved for the different concentrations.

Ultrawideband sub-pascal sensitivity piezopolymer detectors

Piezoelectric detectors are integral part of modern ultrasound imaging systems. Their utility has also been extended beyond the established methodologies into the emerging realm of hybrid optoacoustic imaging. Conventional piezoceramic detectors, however, struggle to combine high detection sensitivity with ultrawide bandwidth, both considered critical for attaining optimal optoacoustic imaging performance. Our research, both theoretical and empirical, unveils that damped piezopolymer detectors fabricated from PVDF-TrFE are markedly capable of achieving a synergistic blend between broad bandwidth and superb sensitivity. Experimental evaluations reflected an average sensitivity of 15.5 µV/Pa within a 1-10 MHz band for a 120 µm thick detector and 6.4 µV/Pa within a 1-30 MHz band for a 20 µm thick detector, thus outperforming conventional piezoelectric analogues. The resultant noise equivalent pressure (NEPs) values were 0.3 Pa and 1.2 Pa for the 20 µm and 120 µm detectors, respectively. Our findings herald a significant stride towards enhancing the efficacy of ultrawideband ultrasound and optoacoustic imaging systems.

Inspiring a convergent engineering approach to measure and model the tissue microenvironment

Understanding the molecular and physical complexity of the tissue microenvironment (TiME) in the context of its spatiotemporal organization has remained an enduring challenge. Recent advances in engineering and data science are now promising the ability to study the structure, functions, and dynamics of the TiME in unprecedented detail; however, many advances still occur in silos that rarely integrate information to study the TiME in its full detail. This review provides an integrative overview of the engineering principles underlying chemical, optical, electrical, mechanical, and computational science to probe, sense, model, and fabricate the TiME. In individual sections, we first summarize the underlying principles, capabilities, and scope of emerging technologies, the breakthrough discoveries enabled by each technology and recent, promising innovations. We provide perspectives on the potential of these advances in answering critical questions about the TiME and its role in various disease and developmental processes. Finally, we present an integrative view that appreciates the major scientific and educational aspects in the study of the TiME.

Vasa vasorum interna in the carotid wall of active forms of Takayasu arteritis evidenced by ultrasound localization microscopy

Introduction: Takayasu arteritis (TA) is associated with microvascularization of the wall of large arteries and is related to inflammation. Ultrasound localization microscopy (ULM), combining ultrafast ultrasound imaging with microbubble (MB) injection, can track the path of MBs within the arterial wall and thus provide imaging of the vasa vasorum. From the analysis of MB tracks in the common carotid arteries of patients with active TA, we report the presence of microvessels in connection with the carotid lumen (i.e., vasa vasorum interna [VVI]). Methods: ULM maps were obtained on five patients with active disease in the observational single-center series of the TAK-UF study. MB tracks connected to the carotid lumen were automatically identified, allowing the reconstruction of VVI. Results: MB tracking allows us to observe a microvascular network on the inner part of the wall, with some vessels in communication with the carotid lumen. This type of vessel was identified in all patients with active TA (n = 5) with a median of 2.2 [1.1-3.0] vessels per acquisition (2D longitudinal view of 3 cm of the common carotid artery). The blood flow within these vessels is mainly centrifugal; that is, toward the adventitia (88% [54-100] of MB tracks with flow directed to the outer part of the wall). Conclusion: VVI are present in humans in the case of active TA and emphasize the involvement of the intima in the pathological process. ClinicalTrials.gov Identifier: NCT03956394.

Transthoracic ultrasound localization microscopy of myocardial vasculature in patients

Myocardial microvasculature and haemodynamics are indicative of potential microvascular diseases for patients with symptoms of coronary heart disease in the absence of obstructive coronary arteries. However, imaging microvascular structure and flow within the myocardium is challenging owing to the small size of the vessels and the constant movement of the patient's heart. Here we show the feasibility of transthoracic ultrasound localization microscopy for imaging myocardial microvasculature and haemodynamics in explanted pig hearts and in patients in vivo. Through a customized data-acquisition and processing pipeline with a cardiac phased-array probe, we leveraged motion correction and tracking to reconstruct the dynamics of microcirculation. For four patients, two of whom had impaired myocardial function, we obtained super-resolution images of myocardial vascular structure and flow using data acquired within a breath hold. Myocardial ultrasound localization microscopy may facilitate the understanding of myocardial microcirculation and the management of patients with cardiac microvascular diseases.

Super-Resolution Ultrasound Imaging for Monitoring the Therapeutic Efficacy of a Vascular Disrupting Agent in an Animal Model of Breast Cancer

OBJECTIVE

Evaluate the use of super-resolution ultrasound (SRUS) imaging for the early detection of tumor response to treatment using a vascular-disrupting agent (VDA).

METHODS

A population of 28 female nude athymic mice (Charles River Laboratories) were implanted with human breast cancer cells (MDA-MB-231, ATCC) in the mammary fat pad and allowed to grow. Ultrasound imaging was performed using a Vevo 3100 scanner (FUJIFILM VisualSonics Inc) equipped with the MX250 linear array transducer immediately before and after receiving bolus injections of a microbubble (MB) contrast agent (Definity, Lantheus Medical Imaging) via the tail vein. Following baseline ultrasound imaging, VDA drug (combretastatin A4 phosphate, CA4P, Sigma Aldrich) or control saline was injected via the placed catheter. After 4 or 24 hours, repeat ultrasound imaging along the same tumor cross-section occurred. Direct intratumoral pressure measurements were obtained using a calibrated sensor. All raw ultrasound data were saved for offline processing and SRUS image reconstruction using custom MATLAB software (MathWorks Inc). From a region encompassing the tumor space and the entire postprocessed ultrasound image sequence, time MB count (TMC) curves were generated in addition to traditional SRUS maps reflecting MB enumeration at each pixel location. Peak enhancement (PE) and wash-in rate (WIR) were extracted from these TMC curves. At termination, intratumoral microvessel density (MVD) was quantified using tomato lectin labeling of patent blood vessels.

RESULTS

SRUS images exhibited a clear difference between control and treated tumors. While there was no difference in any group parameters at baseline (0 hour, P > .09), both SRUS-derived PE and WIR measurements in tumors treated with VDA exhibited significant decreases by 4 (P = .03 and P = .05, respectively) and 24 hours (P = .02 and P = .01, respectively), but not in control group tumors (P > .22). Similarly, SRUS derived microvascular maps were not different at baseline (P = .81), but measures of vessel density were lower in treated tumors at both 4 and 24 hours (P < .04). An inverse relationship between intratumoral pressure and both PE and WIR parameters were found in control tumors (R2 > .09, P < .03).

CONCLUSION

SRUS imaging is a new modality for assessing tumor response to treatment using a VDA.

A Preliminary Investigation of Radiation-Sensitive Ultrasound Contrast Agents for Photon Dosimetry

Radiotherapy treatment plans have become highly conformal, posing additional constraints on the accuracy of treatment delivery. Here, we explore the use of radiation-sensitive ultrasound contrast agents (superheated phase-change nanodroplets) as dosimetric radiation sensors. In a series of experiments, we irradiated perfluorobutane nanodroplets dispersed in gel phantoms at various temperatures and assessed the radiation-induced nanodroplet vaporization events using offline or online ultrasound imaging. At 25 °C and 37 °C, the nanodroplet response was only present at higher photon energies (≥10 MV) and limited to <2 vaporization events per cm2 per Gy. A strong response (~2000 vaporizations per cm2 per Gy) was observed at 65 °C, suggesting radiation-induced nucleation of the droplet core at a sufficiently high degree of superheat. These results emphasize the need for alternative nanodroplet formulations, with a more volatile perfluorocarbon core, to enable in vivo photon dosimetry. The current nanodroplet formulation carries potential as an innovative gel dosimeter if an appropriate gel matrix can be found to ensure reproducibility. Eventually, the proposed technology might unlock unprecedented temporal and spatial resolution in image-based dosimetry, thanks to the combination of high-frame-rate ultrasound imaging and the detection of individual vaporization events, thereby addressing some of the burning challenges of new radiotherapy innovations.