Understanding the effects of microbubble concentration on localization accuracy in super-resolution ultrasound imaging.

Super-resolution ultrasound (SRUS) through localising and tracking of microbubbles (MBs) can achieve sub-wavelength resolution for imaging microvascular structure and flow dynamics in deep tissuein vivo. The technique assumes that signals from individual MBs can be isolated and localised accurately, but this assumption starts to break down when the MB concentration increases and the signals from neighbouring MBs start to interfere. The aim of this study is to gain understanding of the effect of MB-MB distance on ultrasound images and their localisation. Ultrasound images of two MBs approaching each other were synthesised by simulating both ultrasound field propagation and nonlinear MB dynamics. Besides the distance between MBs, a range of other influencing factors including MB size, ultrasound frequency, transmit pulse sequence, pulse amplitude and localisation methods were studied. The results show that as two MBs approach each other, the interference fringes can lead to significant and oscillating localisation errors, which are affected by both the MB and imaging parameters. When modelling a clinical linear array probe operating at 6 MHz, localisation errors between 20 and 30µm (∼1/10 wavelength) can be generated when MBs are ∼500µm (2 wavelengths or ∼1.7 times the point spread function (PSF)) away from each other. When modelling a cardiac probe operating at 1.5 MHz, the localisation errors were as high as 200µm (∼1/5 wavelength) even when the MBs were more than 10 wavelengths apart (2.9 times the PSF). For both frequencies, at smaller separation distances, the two MBs were misinterpreted as one MB located in between the two true positions. Cross-correlation or Gaussian fitting methods were found to generate slightly smaller localisation errors than centroiding. In conclusion, caution should be taken when generating and interpreting SRUS images obtained using high agent concentration with MBs separated by less than 1.7 to 3 times the PSF, as significant localisation errors can be generated due to interference between neighbouring MBs.

3D Acoustic Wave Sparsely Activated Localization Microscopy With Phase Change Contrast Agents.

OBJECTIVE: The aim of this study is to demonstrate 3-dimensional (3D) acoustic wave sparsely activated localization microscopy (AWSALM) of microvascular flow in vivo using phase change contrast agents (PCCAs). MATERIALS AND METHODS: Three-dimensional AWSALM using acoustically activable PCCAs was evaluated on a crossed tube microflow phantom, the kidney of New Zealand White rabbits, and the brain of C57BL/6J mice through intact skull. A mixture of C 3 F 8 and C 4 F 10 low-boiling-point fluorocarbon gas was used to generate PCCAs with an appropriate activation pressure. A multiplexed 8-MHz matrix array connected to a 256-channel ultrasound research platform was used for transmitting activation and imaging ultrasound pulses and recording echoes. The in vitro and in vivo echo data were subsequently beamformed and processed using a set of customized algorithms for generating 3D super-resolution ultrasound images through localizing and tracking activated contrast agents. RESULTS: With 3D AWSALM, the acoustic activation of PCCAs can be controlled both spatially and temporally, enabling contrast on demand and capable of revealing 3D microvascular connectivity. The spatial resolution of the 3D AWSALM images measured using Fourier shell correlation is 64 µm, presenting a 9-time improvement compared with the point spread function and 1.5 times compared with half the wavelength. Compared with the microbubble-based approach, more signals were localized in the microvasculature at similar concentrations while retaining sparsity and longer tracks in larger vessels. Transcranial imaging was demonstrated as a proof of principle of PCCA activation in the mouse brain with 3D AWSALM. CONCLUSIONS: Three-dimensional AWSALM generates volumetric ultrasound super-resolution microvascular images in vivo with spatiotemporal selectivity and enhanced microvascular penetration.

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

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

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

PURPOSE: Detecting and distinguishing metastatic lymph nodes (LNs) from those with benign lymphadenopathy are crucial for cancer diagnosis and prognosis but remain a clinical challenge. A recent advance in super-resolution ultrasound (SRUS) through localizing individual microbubbles has broken the diffraction limit and tracking enabled in vivo noninvasive imaging of vascular morphology and flow dynamics at a microscopic level. In this study we hypothesize that SRUS enables quantitative markers to distinguish metastatic LNs from benign ones in patients with lymphadenopathy. MATERIALS AND METHODS: Clinical contrast-enhanced ultrasound image sequences of LNs from 6 patients with lymph node metastasis and 4 with benign lymphadenopathy were acquired and motion-corrected. These were then used to generate super-resolution microvascular images and super-resolved velocity maps. From these SRUS images, morphological and functional measures were obtained including micro-vessel density, fractal dimension, mean flow speed, and Local Flow Direction Irregularity (LFDI) measuring the variance in local flow direction. These measures were compared between pathologically proven reactive and metastasis LNs. RESULTS: Our initial results indicate that the difference in the indicator of flow irregularity (LFDI) derived from the SRUS images is statistically significant between the two groups. The LFDI is 60% higher in metastatic LNs compared with reactive nodes. CONCLUSION: This pilot study demonstrates the feasibility of super-resolution ultrasound for clinical imaging of lymph nodes and the potential of using the irregularity of local blood flow directions afforded by SRUS for the characterization of LNs.

Robust deep learning optical autofocus system applied to automated multiwell plate single molecule localization microscopy.

We presenta robust, long-range optical autofocus system for microscopy utilizing machine learning. This can be useful for experiments with long image data acquisition times that may be impacted by defocusing resulting from drift of components, for example due to changes in temperature or mechanical drift. It is also useful for automated slide scanning or multiwell plate imaging where the sample(s) to be imaged may not be in the same horizontal plane throughout the image data acquisition. To address the impact of (thermal or mechanical) fluctuations over time in the optical autofocus system itself, we utilize a convolutional neural network (CNN) that is trained over multiple days to account for such fluctuations. To address the trade-off between axial precision and range of the autofocus, we implement orthogonal optical readouts with separate CNN training data, thereby achieving an accuracy well within the 600 nm depth of field of our 1.3 numerical aperture objective lens over a defocus range of up to approximately +/-100 µm. We characterize the performance of this autofocus system and demonstrate its application to automated multiwell plate single molecule localization microscopy.

Many microscopy experiments involve extended imaging of samples over timescales from minutes to days, during which the microscope can 'drift' out of focus. When imaging at high magnification, the depth of field is of the order of one micron and so the imaging system should keep the sample in the focal plane of the microscope objective lens to this precision. Unfortunately, temperature changes in the laboratory can cause thermal expansion of microscope components that can move the focal plane by more than a micron and such changes can occur on a timescale of minutes. This is a particular issue for super-resolved microscopy experiments using single molecule localization microscopy (SMLM) techniques, for which 1000s of images are acquired, and for automated imaging of multiple samples in multiwell plates. It is possible to maintain the sample in the focal plane focus position by either automatically moving the sample or adjusting the imaging system, for example by moving the objective lens. This is called 'autofocus' and is frequently achieved by reflecting a light beam from the microscope coverslip and measuring its position of beam profile as a function of defocus of the microscope. The correcting adjustment is then usually calculated analytically but there is recent interest in using machine learning techniques to determine the required focussing adjustment. Here, we present a system that uses a neural network to determine the required defocus correcting adjustment from camera images of a laser beam that is reflected from the coverslip. Unfortunately, this approach will only work when the microscope is in the same condition as it was when the neural network was trained - and this can be compromised by the same drift of the optical system that causes the defocus needing to be corrected. We show, however, that by training a neural network over an extended period, for example 10 days, this approach can 'learn' about the optical system drifts and provide the required autofocus function. We also show that an optical system utilizing a rectangular slit can make two measurements of the defocus simultaneously, with one measurement being optimized for high accuracy over a limited range (±10 µm) near focus and the other providing lower accuracy but over a much longer range (±100 µm). This robust autofocus system is suitable for automated super-resolved microscopy of arrays of samples in a multiwell plate using SMLM, for which an experiment routinely lasts more than 5 h.

Application of direct stochastic optical reconstruction microscopy (dSTORM) to the histological analysis of human glomerular disease.

Electron microscopy (EM) following immunofluorescence (IF) imaging is a vital tool for the diagnosis of human glomerular diseases, but the implementation of EM is limited to specialised institutions and it is not available in many countries. Recent progress in fluorescence microscopy now enables conventional widefield fluorescence microscopes to be adapted at modest cost to provide resolution below 50 nm in biological specimens. We show that stochastically switched single-molecule localisation microscopy can be applied to clinical histological sections stained with standard IF techniques and that such super-resolved IF may provide an alternative means to resolve ultrastructure to aid the diagnosis of kidney disease where EM is not available. We have implemented the direct stochastic optical reconstruction microscopy technique with human kidney biopsy frozen sections stained with clinically approved immunofluorescent probes for the basal laminae and immunoglobulin G deposits. Using cases of membranous glomerulonephritis, thin basement membrane lesion, and lupus nephritis, we compare this approach to clinical EM images and demonstrate enhanced imaging compared to conventional IF microscopy. With minor modifications in established IF protocols of clinical frozen renal biopsies, we believe the cost-effective adaptation of conventional widefield microscopes can be widely implemented to provide super-resolved image information to aid diagnosis of human glomerular disease.

Single-cell resolved imaging reveals intra-tumor heterogeneity in glycolysis, transitions between metabolic states, and their regulatory mechanisms.

Inter-cellular heterogeneity in metabolic state has been proposed to influence many cancer phenotypes, including responses to targeted therapy. Here, we track the transitions and heritability of metabolic states in single PIK3CA mutant breast cancer cells, identify non-genetic glycolytic heterogeneity, and build on observations derived from methods reliant on bulk analyses. Using fluorescent biosensors in vitro and in tumors, we have identified distinct subpopulations of cells whose glycolytic and mitochondrial metabolism are regulated by combinations of phosphatidylinositol 3-kinase (PI3K) signaling, bromodomain activity, and cell crowding effects. The actin severing protein cofilin, as well as PI3K, regulates rapid changes in glucose metabolism, whereas treatment with the bromodomain inhibitor slowly abrogates a subpopulation of cells whose glycolytic activity is PI3K independent. We show how bromodomain function and PI3K signaling, along with actin remodeling, independently modulate glycolysis and how targeting these pathways affects distinct subpopulations of cancer cells.

DDR1 autophosphorylation is a result of aggregation into dense clusters.

The collagen receptor DDR1 is a receptor tyrosine kinase that promotes progression of a wide range of human disorders. Little is known about how ligand binding triggers DDR1 kinase activity. We previously reported that collagen induces DDR1 activation through lateral dimer association and phosphorylation between dimers, a process that requires specific transmembrane association. Here we demonstrate ligand-induced DDR1 clustering by widefield and super-resolution imaging and provide evidence for a mechanism whereby DDR1 kinase activity is determined by its molecular density. Ligand binding resulted in initial DDR1 reorganisation into morphologically distinct clusters with unphosphorylated DDR1. Further compaction over time led to clusters with highly aggregated and phosphorylated DDR1. Ligand-induced DDR1 clustering was abolished by transmembrane mutations but did not require kinase activity. Our results significantly advance our understanding of the molecular events underpinning ligand-induced DDR1 kinase activity and provide an explanation for the unusually slow DDR1 activation kinetics.

Multidimensional luminescence microscope for imaging defect colour centres in diamond.

We report a multidimensional luminescence microscope providing hyperspectral imaging and time-resolved (luminescence lifetime) imaging for the study of luminescent diamond defects. The instrument includes crossed-polariser white light transmission microscopy to reveal any birefringence that would indicate strain in the diamond lattice. We demonstrate the application of this new instrument to detect defects in natural and synthetic diamonds including N3, nitrogen and silicon vacancies. Hyperspectral imaging provides contrast that is not apparent in conventional intensity images and the luminescence lifetime provides further contrast.

Poisson Statistical Model of Ultrasound Super-Resolution Imaging Acquisition Time.

A number of acoustic super-resolution techniques have recently been developed to visualize microvascular structure and flow beyond the diffraction limit. A crucial aspect of all ultrasound (US) super-resolution (SR) methods using single microbubble localization is time-efficient detection of individual bubble signals. Due to the need for bubbles to circulate through the vasculature during acquisition, slow flows associated with the microcirculation limit the minimum acquisition time needed to obtain adequate spatial information. Here, a model is developed to investigate the combined effects of imaging parameters, bubble signal density, and vascular flow on SR image acquisition time. We find that the estimated minimum time needed for SR increases for slower blood velocities and greater resolution improvement. To improve SR from a resolution of λ /10 to λ /20 while imaging the microvasculature structure modeled here, the estimated minimum acquisition time increases by a factor of 14. The maximum useful imaging frame rate to provide new spatial information in each image is set by the bubble velocity at low blood flows (<150 mm/s for a depth of 5 cm) and by the acoustic wave velocity at higher bubble velocities. Furthermore, the image acquisition procedure, transmit frequency, localization precision, and desired super-resolved image contrast together determine the optimal acquisition time achievable for fixed flow velocity. Exploring the effects of both system parameters and details of the target vasculature can allow a better choice of acquisition settings and provide improved understanding of the completeness of SR information.

3D Super-Resolution US Imaging of Rabbit Lymph Node Vasculature in Vivo by Using Microbubbles.

Background Variations in lymph node (LN) microcirculation can be indicative of metastasis. The identification and quantification of metastatic LNs remains essential for prognosis and treatment planning, but a reliable noninvasive imaging technique is lacking. Three-dimensional super-resolution (SR) US has shown potential to noninvasively visualize microvascular networks in vivo. Purpose To study the feasibility of three-dimensional SR US imaging of rabbit LN microvascular structure and blood flow by using microbubbles. Materials and Methods In vivo studies were carried out to image popliteal LNs of two healthy male New Zealand white rabbits aged 6-8 weeks. Three-dimensional, high-frame-rate, contrast material-enhanced US was achieved by mechanically scanning with a linear imaging probe. Individual microbubbles were identified, localized, and tracked to form three-dimensional SR images and super-resolved velocity maps. Acoustic subaperture processing was used to improve image contrast and to generate enhanced power Doppler and color Doppler images. Vessel size and blood flow velocity distributions were evaluated and assessed by using Student paired t test. Results SR images revealed microvessels in the rabbit LN, with branches clearly resolved when separated by 30 µm, which is less than half of the acoustic wavelength and not resolvable by using power or color Doppler. The apparent size distribution of most vessels in the SR images was below 80 µm and agrees with micro-CT data, whereas most of those detected with Doppler techniques were larger than 80 µm in the images. The blood flow velocity distribution indicated that most of the blood flow in rabbit popliteal LN was at velocities lower than 5 mm/sec. Conclusion Three-dimensional super-resolution US imaging using microbubbles allows noninvasive nonionizing visualization and quantification of lymph node microvascular structures and blood flow dynamics with resolution below the wave diffraction limit. This technology has potential for studying the physiologic functions of the lymph system and for clinical detection of lymph node metastasis. Published under a CC BY 4.0 license. Online supplemental material is available for this article.

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

Localization-based ultrasound super-resolution imaging using microbubble contrast agents and phase-change nano-droplets has been developed to visualize microvascular structures beyond the diffraction limit. However, the long data acquisition time makes the clinical translation more challenging. In this study, fast acoustic wave sparsely activated localization microscopy (fast-AWSALM) was developed to achieve super-resolved frames with sub-second temporal resolution, by using low-boiling-point octafluoropropane nanodroplets and high frame rate plane waves for activation, destruction, as well as imaging. Fast-AWSALM was demonstrated on an in vitro microvascular phantom to super-resolve structures that could not be resolved by conventional B-mode imaging. The effects of the temperature and mechanical index on fast-AWSALM was investigated. Experimental results show that sub-wavelength micro-structures as small as 190 lm were resolvable in 200 ms with plane-wave transmission at a center frequency of 3.5 MHz and a pulse repetition frequency of 5000 Hz. This is about a 3.5 fold reduction in point spread function full-width-half-maximum compared to that measured in conventional B-mode, and two orders of magnitude faster than the recently reported AWSALM under a non-flow/very slow flow situations and other localization based methods. Just as in AWSALM, fast-AWSALM does not require flow, as is required by current microbubble based ultrasound super resolution techniques. In conclusion, this study shows the promise of fast-AWSALM, a super-resolution ultrasound technique using nanodroplets, which can generate super-resolution images in milli-seconds and does not require flow.

Investigation of Microbubble Detection Methods for Super-Resolution Imaging of Microvasculature.

Ultrasound super-resolution techniques use the response of microbubble (MB) contrast agents to visualize the microvasculature. Techniques that localize isolated bubble signals first require detection algorithms to separate the MB and tissue responses. This work explores the three main MB detection techniques for super-resolution of microvasculature. Pulse inversion (PI), differential imaging (DI), and singular value decomposition (SVD) filtering were compared in terms of the localization accuracy, precision, and contrast-to-tissue ratio. MB responses were simulated based on the properties of Sonovue and using the Marmottant model. Nonlinear propagation through tissue was modeled using the k-Wave software package. For the parameters studied, the results show that PI is most appropriate for low frequency applications, but also most dependent on transducer bandwidth. SVD is preferable for high frequency acquisition where localization precision on the order of a few microns is possible. PI is largely independent of flow direction and speed compared to SVD and DI, so is appropriate for visualizing the slowest flows and tortuous vasculature. SVD is unsuitable for stationary MBs and can introduce a localization error on the order of hundreds of microns over the speed range 0-2 mm/s and flow directions from lateral (parallel to probe) to axial (perpendicular to probe). DI is only suitable for flow rates >0.5 mm/s or as flow becomes more axial. Overall, this study develops an MB and tissue nonlinear simulation platform to improve understanding of how different MB detection techniques can impact the super-resolution process and explores some of the factors influencing the suitability of each.

Automated Fluorescence Lifetime Imaging High-Content Analysis of Förster Resonance Energy Transfer between Endogenously Labeled Kinetochore Proteins in Live Budding Yeast Cells.

We describe an open-source automated multiwell plate fluorescence lifetime imaging (FLIM) methodology to read out Förster resonance energy transfer (FRET) between fluorescent proteins (FPs) labeling endogenous kinetochore proteins (KPs) in live budding yeast cells. The low copy number of many KPs and their small spatial extent present significant challenges for the quantification of donor fluorescence lifetime in the presence of significant cellular autofluorescence and photobleaching. Automated FLIM data acquisition was controlled by µManager and incorporated wide-field time-gated imaging with optical sectioning to reduce background fluorescence. For data analysis, we used custom MATLAB-based software tools to perform kinetochore foci segmentation and local cellular background subtraction and fitted the fluorescence lifetime data using the open-source FLIMfit software. We validated the methodology using endogenous KPs labeled with mTurquoise2 FP and/or yellow FP and measured the donor fluorescence lifetimes for foci comprising 32 kinetochores with KP copy numbers as low as ~2 per kinetochore under an average labeling efficiency of 50%. We observed changes of median donor lifetime ≥250 ps for KPs known to form dimers. Thus, this FLIM high-content analysis platform enables the screening of relatively low-copy-number endogenous protein-protein interactions at spatially confined macromolecular complexes.

easySLM-STED: Stimulated emission depletion microscopy with aberration correction, extended field of view and multiple beam scanning.

We demonstrate a simplified set-up for STED microscopy with a straightforward alignment procedure that uses a single spatial light modulator (SLM) with collinear incident excitation and depletion beams to provide phase modulation of the beam profiles and correction of optical aberrations. We show that this approach can be used to extend the field of view for STED microscopy by correcting chromatic aberration that otherwise leads to walk-off between the focused excitation and depletion beams. We further show how this arrangement can be adapted to increase the imaging speed through multibeam excitation and depletion. Fine adjustments to the alignment can be accomplished using the SLM only, conferring the potential for automation.

Heterogeneity in tumor chromatin-doxorubicin binding revealed by in vivo fluorescence lifetime imaging confocal endomicroscopy.

We present an approach to quantify drug-target engagement using in vivo fluorescence endomicroscopy, validated with in vitro measurements. Doxorubicin binding to chromatin changes the fluorescence lifetime of histone-GFP fusions that we measure in vivo at single-cell resolution using a confocal laparo/endomicroscope. We measure both intra- and inter-tumor heterogeneity in doxorubicin chromatin engagement in a model of peritoneal metastasis of ovarian cancer, revealing striking variation in the efficacy of doxorubicin-chromatin binding depending on intra-peritoneal or intravenous delivery. Further, we observe significant variations in doxorubicin-chromatin binding between different metastases in the same mouse and between different regions of the same metastasis. The quantitative nature of fluorescence lifetime imaging enables direct comparison of drug-target engagement for different drug delivery routes and between in vitro and in vivo experiments. This uncovers different rates of cell killing for the same level of doxorubicin binding in vitro and in vivo.

Two-Stage Motion Correction for Super-Resolution Ultrasound Imaging in Human Lower Limb.

The structure of microvasculature cannot be resolved using conventional ultrasound (US) imaging due to the fundamental diffraction limit at clinical US frequencies. It is possible to overcome this resolution limitation by localizing individual microbubbles through multiple frames and forming a superresolved image, which usually requires seconds to minutes of acquisition. Over this time interval, motion is inevitable and tissue movement is typically a combination of large- and small-scale tissue translation and deformation. Therefore, super-resolution (SR) imaging is prone to motion artifacts as other imaging modalities based on multiple acquisitions are. This paper investigates the feasibility of a two-stage motion estimation method, which is a combination of affine and nonrigid estimation, for SR US imaging. First, the motion correction accuracy of the proposed method is evaluated using simulations with increasing complexity of motion. A mean absolute error of 12.2 was achieved in simulations for the worst-case scenario. The motion correction algorithm was then applied to a clinical data set to demonstrate its potential to enable in vivo SR US imaging in the presence of patient motion. The size of the identified microvessels from the clinical SR images was measured to assess the feasibility of the two-stage motion correction method, which reduced the width of the motion-blurred microvessels to approximately 1.5-fold.

Quantitative time domain analysis of lifetime-based Förster resonant energy transfer measurements with fluorescent proteins: Static random isotropic fluorophore orientation distributions.

Förster resonant energy transfer (FRET) measurements are widely used to obtain information about molecular interactions and conformations through the dependence of FRET efficiency on the proximity of donor and acceptor fluorophores. Fluorescence lifetime measurements can provide quantitative analysis of FRET efficiency and interacting population fraction. Many FRET experiments exploit the highly specific labelling of genetically expressed fluorescent proteins, applicable in live cells and organisms. Unfortunately, the typical assumption of fast randomization of fluorophore orientations in the analysis of fluorescence lifetime-based FRET readouts is not valid for fluorescent proteins due to their slow rotational mobility compared to their upper state lifetime. Here, previous analysis of effectively static isotropic distributions of fluorophore dipoles on FRET measurements is incorporated into new software for fitting donor emission decay profiles. Calculated FRET parameters, including molar population fractions, are compared for the analysis of simulated and experimental FRET data under the assumption of static and dynamic fluorophores and the intermediate regimes between fully dynamic and static fluorophores, and mixtures within FRET pairs, is explored. Finally, a method to correct the artefact resulting from fitting the emission from static FRET pairs with isotropic angular distributions to the (incorrect) typically assumed dynamic FRET decay model is presented.

Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging.

Acoustic super-resolution imaging has allowed the visualization of microvascular structure and flow beyond the diffraction limit using standard clinical ultrasound systems through the localization of many spatially isolated microbubble signals. The determination of each microbubble position is typically performed by calculating the centroid, finding a local maximum, or finding the peak of a 2-D Gaussian function fit to the signal. However, the backscattered signal from a microbubble depends not only on diffraction characteristics of the waveform, but also on the microbubble behavior in the acoustic field. Here, we propose a new axial localization method by identifying the onset of the backscattered signal. We compare the accuracy of localization methods using in vitro experiments performed at 7-cm depth and 2.3-MHz center frequency. We corroborate these findings with simulation results based on the Marmottant model. We show experimentally and in simulations that detecting the onset of the returning signal provides considerably increased accuracy for super-resolution. Resulting experimental cross-sectional profiles in super-resolution images demonstrate at least 5.8 times improvement in contrast ratio and more than 1.8 times reduction in spatial spread (provided by 90% of the localizations) for the onset method over centroiding, peak detection, and 2-D Gaussian fitting methods. Simulations estimate that these latter methods could create errors in relative bubble positions as high as at these experimental settings, while the onset method reduced the interquartile range of these errors by a factor of over 2.2. Detecting the signal onset is, therefore, expected to considerably improve the accuracy of super-resolution.

3-D In Vitro Acoustic Super-Resolution and Super-Resolved Velocity Mapping Using Microbubbles.

Standard clinical ultrasound (US) imaging frequencies are unable to resolve microvascular structures due to the fundamental diffraction limit of US waves. Recent demonstrations of 2-D super-resolution both in vitro and in vivo have demonstrated that fine vascular structures can be visualized using acoustic single bubble localization. Visualization of more complex and disordered 3-D vasculature, such as that of a tumor, requires an acquisition strategy which can additionally localize bubbles in the elevational plane with high precision in order to generate super-resolution in all three dimensions. Furthermore, a particular challenge lies in the need to provide this level of visualization with minimal acquisition time. In this paper, we develop a fast, coherent US imaging tool for microbubble localization in 3-D using a pair of US transducers positioned at 90°. This allowed detection of point scatterer signals in 3-D with average precisions equal to [Formula: see text] in axial and elevational planes, and [Formula: see text] in the lateral plane, compared to the diffraction limited point spread function full-widths at half-maximum of 488, 1188, and [Formula: see text] of the original imaging system with a single transducer. Visualization and velocity mapping of 3-D in vitro structures was demonstrated far beyond the diffraction limit. The capability to measure the complete flow pattern of blood vessels associated with disease at depth would ultimately enable analysis of in vivo microvascular morphology, blood flow dynamics, and occlusions resulting from disease states.