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 to 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 paper 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 imaging, motion estimation, echo canceling, peak detection, and recursive nearest neighbor tracker. The SURE tracking pipeline is capable of distinguishing the flow direction and separating tubes of a simulated Field II phantom with 125 to 25 μm wall-to-wall tube distances, as well as a 3D-printed hydrogel micro-flow phantom with 100 to 60 μm wall-to-wall channel distances. The comparison of an in-vivo SURE scan of a Sprague-Dawley rat kidney with ULM and micro-CT scans with voxel sizes of 26.5μm and 5μm 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.

A new approach for vascular super resolution imaging using the erythrocytes as targets (SURE imaging) is described and investigated. SURE imaging does not require fragile contrast agent bubbles, making it possible to use the maximum allowable mechanical index for ultrasound scanning for an increased penetration depth. A synthetic aperture ultrasound sequence was employed with 12 virtual sources using a 10 MHz GE L8-18i-D linear array hockey stick probe. The axial resolution was 1.20λ,(185.0μm) and the lateral resolution was 1.50λ,(231.3μm). Field IIpro simulations were conducted on 12.5 μm radius vessel pairs with varying separations. A vessel pair with a separation of 70 μm could be resolved, indicating a SURE image resolution below half a wavelength. A Verasonics research scanner was used for the in vivo experiments to scan the kidneys of Sprague-Dawley rats for up to 46 s to visualize their microvasculature by processing from 0.1 up to 45 s of data for SURE imaging, and for 46.8 s for super resolution (SR) imaging with a SonoVue contrast agent. Afterward, the renal vasculature was filled with the ex vivo micro-CT contrast agent Microfil, excised, and scanned in a micro-CT scanner at both a 22.6 μm voxel size for 11 hours, and for 20 hours in a 5 μm voxel size for validating the SURE images. Comparing the SURE and micro-CT images revealed that vessels with a diameter of 28 μm, five times smaller than the ultrasound wavelength, could be detected, and the dense grid of microvessels in the full kidney was shown for scan times between 1 to 10 s. The vessel structure in the cortex was also similar for the SURE and SR images. Fourier ring correlation indicated a resolution capability of 29 μm. SURE images are acquired in seconds rather than minutes without any patient preparation or contrast injection, making the method translatable to clinical use.

This work demonstrates a microvascular ultrasound flow simulator implementing a volume-preserving static flow approximation in a microvascular graph, suitable for use with ultrasound simulation. The hypothesis is that volume-preserving particle flow enables the simulation of the microvasculature together with tissue such that the effects of echo-cancellation as seen in vivo is replicated. To enable volume-preserving flow, volumetric flow mapping of bifurcations and a full connected arterial-venous vessel coupling through the capillaries is implemented. The simulator is used together with either computer-generated microvasculature or with microvasculatures extracted from an ex-vivo segmented 3D mu CT dataset from the excised kidney of a Sprague-Dawley rat, with the simulation result of the latter being visually validated against a flow image (power-Doppler) of the same rat. Simulating the blood flow together with tissue results in a flow image closely resembling one derived from real in-vivo flow data. This thus confirms that by circulating continous flow in a graph vasculature, blood-flow images of the microvasculature necessitating echo cancellation can be replicated in a simulator.

Individuals with diabetes at risk of developing diabetic kidney disease (DKD) are challenging to identify using currently available clinical methods. Prognostic accuracy and initiation of treatment could be improved by a quantification of the renal microvascular rarefaction and the increased vascular tortuosity during the development of DKD. Super-resolution ultrasound (SRUS) imaging is an in vivo technique capable of visualizing blood vessels at sizes below 75 µm. This preclinical study aimed to investigate the alterations in renal blood vessels’ density and tortuosity in a type 2 diabetes rat model, Zucker diabetic fatty (ZDF) rats, as a prediction of DKD. Lean age-matched Zucker rats were used as controls. A total of 36 rats were studied, subdivided into ages of 12, 22, and 40 weeks. Measured albuminuria indicated the early stage of DKD, and the SRUS was compared with the ex vivo micro-computed tomography (µCT) of the same kidneys. Assessed using the SRUS imaging, a significantly decreased cortical vascular density was detected in the ZDF rats from 22 weeks of age compared to the healthy controls, concomitant with a significantly increased albuminuria. Already by week 12, a trend towards a decreased cortical vascular density was found prior to the increased albuminuria. The quantified vascular density in µCT corresponded with the in vivo SRUS imaging, presenting a consistently lower vascular density in the ZDF rats. Regarding vessel tortuosity, an overall trend towards an increased tortuosity was present in the ZDF rats. SRUS shows promise for becoming an additional tool for monitoring and prognosing DKD. In the future, large-scale animal studies and human trials are needed for confirmation.

Aim: Our overall aim is to create 3D in vivo microvascular imaging of the renal vasculature in healthy and diabetic rats in real time. Methods-1: Super-resolution ultrasound imaging (SRUS) using intravascular microbubbles (MBs) can generate in vivo images of the renal microcirculation. Spatially separated MBs are followed over numerous image frames to create anatomical vascular images showing MB direction and velocity. Presently, images with a resolution of 50 μm are obtainable. Results-1: As diabetes mellitus is associated with micro- and macrovascular diseases also affecting the kidneys we used SRUS on Zucker Diabetic Fat rats (ZDF) aged 12-, 20- and 40-weeks. We show a significant decrease in vascular density in the cortex at week 12 before onset of proteinuria when compared to age-matched lean Zucker rats. At week 20 vascular density decreased in the outer medulla and inner medulla. No significant changes were found in vascular tortuosity. However, the SRUS images are collected over several minutes, and are challenged by tissue motion and the lack of real-time imaging. The fragile MBs limit emission pressure and thus scan depth. Hypothesis: We hypothesize that tracking erythrocytes instead of MBs will reduce these obstacles and make the method non-invasive. Resolution and scan depth will increase and scan time will shorten. This will allow an easy transition into the clinic. Results-2: Using this innovative method, we have generated images of healthy rat kidneys. Within 24 seconds, we can create an image of the renal vasculature showing the vasa recta (the capillary network penetrating the medulla) and the arcuate and cortical radial arteries. μCT scans have verified the structure of the vascular tree. However, even at these short scan times, there is considerable tissue motion from heart-beat, respiration etc. moving the image out of plane. To clearly image the true microcirculation, 3D imaging is needed. We have recently obtained this amazing step and made a 3D in vivo scan of a healthy rat kidney. The project is funded by an ERC Synergy Grant SURE, project no. 854796. This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Current super resolution imaging is conducted using ultrasound contrast agents, where a sparse distribution of bubbles must be employed to separate individual targets. The sparse targets make the acquisition time long in the range of 1 to 10 minutes, and therefore demands an accurate motion correction over a long time. The employment of a contrast agent also lowers MI to below 0.2 to not disrupt the bubbles, with a corresponding lower signal-to-noise ratio in the images. A new method, SURE (SUper Resolution ultrasound imaging using Erythrocytes), where erythrocytes are used as targets, is suggested to alleviate these problems. Perfused tissues contain an abundance of targets, and the full clinical pressure range can be used. It is hypothesized that super resolution imaging below the diffraction limit can be attained in seconds using SURE imaging. A SURE processing pipeline was developed with modules for beamforming, tissue motion estimation, alignment, singular value decomposition for echo canceling, and subsequent peak detection in the speckle pattern. The detected peaks were summed in a high-resolution image for yielding the SURE image. Data were acquired using a 10 MHz linear array GE L10-18i probe (150 µm wavelength) and a Verasonics Vantage 256 scanner. A synthetic aperture scan sequence with 12 emissions was employed at a pulse repetition frequency of 5 kHz for a 417 Hz frame rate. Kidneys of Sprague-Dawley rats were scanned for 24 seconds and RF data stored for off-line processing. The excised kidneys were micro-CT scanned for 11 hours for generating reference maps of the vasculature with a voxel size of 21 µm. SURE images revealed vessels with sizes down to 50 µm. Fourier ring correlations between independent images measured for 12 s revealed a resolution between 25 to 49 µm, demonstrating the super resolution capability of the method. The SURE images are obtained in 1 to 12 seconds, demand no injection of intravenous contrast agents, and can use the full pressure and intensity range allowed in medical ultrasound, making the method easily adaptable to clinical use.

Super-resolution ultrasound imaging (SRI) is a widely used technique for visualization of the microvasculature. The technique generally relies on long observation times if the smallest vessels have to be resolved. This makes it impractical for 3D imaging due to the large amounts of data required. Especially, matrix probes suffer from this, as the channel count is typically above 1024, which results in either a limited acquisition time or a greatly reduced frame rate. This work investigated the feasibility of using a row-column array (RCA) for 3D SRI. The 3D vascular tree of a Sprague Dawley rat kidney was imaged in a 26×26×40 mm 3 volume using only 128 active elements in receive for a 6 MHz 128+128 Vermon RCA connected to a Verasonics Vantage 256™ scanner. Forty eight virtual sources with an amplitude modulated sequences were used to acquire 36 seconds of contrast-enhanced volumes. The data rate was 2.74 GBytes/s. Then, the 3D visualization of the vasculature was provided by localization of peaks in the acquired volumes. The estimated resolution using Fourier shell correlation for the reconstructed vasculature in this volume was 43 µm with half-bit and 61 µm with one-bit threshold, which was a factor of 6 below the wavelength (λ = 256 µm). In conclusion, the study showed the feasibility of super-resolution vascular imaging of a rat kidney using a RCA.

Super-resolution ultrasound imaging (SRUS) is a branch of ultrasound techniques aiming to image and quantify the vasculature beyond the diffraction limit [1]. Going beyond the diffraction limit of conventional ultrasound entails the possibility of imaging the microvasculature, namely arterioles, venules, and maybe even the smallest vessels in the body: the capillaries. In one of the main SRUS techniques, also called ultrasound localization microscopy, isolated microbubbles from ultrasound contrast agents are used to acquire data for SRUS image formation. Super-resolution ultrasound imaging using isolated microbubbles was inspired by one of the Nobel prize-winning approaches for super-resolution microscopy [2]. In one of these approaches, the ability to turn the fluorescence of single molecules on and off was used. By capturing numerous images of the same object, each image with a different group of molecules fluorescently turned on and superposing the resultant image stack, a super-resolved microscopy image, i. e., an image showing structures below the diffraction limit of light, could be created. Likewise, the SRUS images are created by superposing thousands of successive ultrasound images of isolated microbubbles as they move through the vasculature. More specifically, the SRUS images are created using a series of post-processing steps. After scanning the organ or tissue of interest, the sparsely distributed intravascular microbubbles must be detected. Detection can be done with, e. g., contrast-enhancing sequences, such as pulse inversion or amplitude modulation, or with singular value decomposition (SVD) techniques [3]. Next, the single microbubbles are isolated and localized [4]. The precision of this localization is a critical step in obtaining super-resolution [5]. Instead of merely superposing each of the microbubble localizations, as done in super-resolution microscopy, the movements of the microbubbles as they follow the bloodstream between frames are used to create trajectories that can reveal microbubble velocity and direction [6–10]. Lastly, another essential difference between super-resolved microscopy and ultrasound is motion. In order to localize the microbubbles precisely, it is necessary to compensate for the motion that stems from, e. g., breathing and heart beating during scanning [11, 12]. The resulting trajectory-based images, created from localizing and tracking the isolated microbubbles, are used to reveal physiological or pathological changes in the vasculature. The majority of studies that have been published are preclinical studies, many of which have investigated technical feasibilities and developments. As microvascular disease can occur anywhere in the body, SRUS has been applied to various anatomical structures, from the eyes to the heart to the prostate [13–15]. However, the largest areas of interest have been the vasculature of the brain, the kidneys, and malignant tumors. In the brain, SRUS has been used to evaluate age-related vascular alterations, which revealed that microbubble velocities were slower and vessels more tortuous in old mouse brains compared with younger ones [16]. It has also been used to measure cerebral arterial pulsatility in mice to improve our understanding of the effects of increased pulse pressure on the brain’s microvasculature [17]. As a last example, SRUS has been acquired through an intact human skull at the temporal acoustic window [18], demonstrating cerebrovascular hemodynamics, including turbulent flow in an aneurism and chaotic flow Sofie Bech Andersen Charlotte Mehlin Sørensen Jørgen Arendt Jensen Michael Bachmann Nielsen Editorial

Super-resolution ultrasound imaging, based on the localization and tracking of single intravascular microbubbles, makes it possible to map vessels below 100 µm. Microbubble velocities can be estimated as a surrogate for blood velocity, but their clinical potential is unclear. We investigated if a decrease in microbubble velocity in the arterial and venous beds of the renal cortex, outer medulla, and inner medulla was detectable after intravenous administration of the α1-adrenoceptor antagonist prazosin. The left kidneys of seven rats were scanned with super-resolution ultrasound for 10 min before, during, and after prazosin administration using a bk5000 ultrasound scanner and hockey-stick probe. The super-resolution images were manually segmented, separating cortex, outer medulla, and inner medulla. Microbubble tracks from arteries/arterioles were separated from vein/venule tracks using the arterial blood flow direction. The mean microbubble velocities from each scan were compared. This showed a significant prazosin-induced velocity decrease only in the cortical arteries/arterioles (from 1.59 ± 0.38 to 1.14 ± 0.31 to 1.18 ± 0.33 mm/s, p = 0.013) and outer medulla descending vasa recta (from 0.70 ± 0.05 to 0.66 ± 0.04 to 0.69 ± 0.06 mm/s, p = 0.026). Conclusively, super-resolution ultrasound imaging makes it possible to detect and differentiate microbubble velocity responses to prazosin simultaneously in the renal cortical and medullary vascular beds.

Microbubble (MB) tracking is an integral part of super-resolution ultrasound imaging by providing sharper images and enabling velocity estimation. Tracking the MBs from the last to the first frame can generate different trajectories than tracking from the first to the last frame, when the next positions of a track depends on its previous positions, e.g., in Kalman-based methods. Our hypothesis is that tracking in a forward-backward manner can increase the overall tracking performance. In simulations, MB positions with a parabolic flow profile were generated inside two tubes. Three different tracking methods, including nearest-neighbor, Kalman, and hierarchical Kalman, were investigated. Using the proposed forward-backward strategy, all estimated velocity profiles for all trackers were improved and were closer to the actual velocity profiles with an improvement between 28% to 40% in the relative standard deviation (RSD) of the velocity values over 10 cross-sections of the tubes. A Sprague Dawley rat kidney was scanned for 10 minutes using a BK5000 scanner and X18L5s transducer, which is a linear array probe with 150 elements. The tracking results from the in vivo experiments showed that the combined image of the forward and backward tracks had 35% additional unique track positions. It showed a clear visual enhancement in the super-resolved velocity map. Overall, the improvement in visual aspects and velocity estimates suggest forward-backward strategy as an upgrade for Kalman-based trackers.

Obesity is a risk factor of chronic kidney disease (CKD), leading to alterations in the renal vascular structure. This study tested if renal vascular density and tortuosity was quantifiable in vivo in obese rats using microbubble-based super-resolution ultrasound imaging. The kidneys of two 11-week-old and two 20-week-old male obese Zucker rats were compared with age-matched male lean Zucker rats. The super-resolution ultrasound images were manually divided into inner medulla, outer medulla, and cortex, and each area was subdivided into arteries and veins. We quantified vascular density and tortuosity, number of detected microbubbles, and generated tracks. For comparison, we assessed glomerular filtration rate, albumin/creatinine ratio, and renal histology to evaluate CKD. The number of detected microbubbles and generated tracks varied between animals and significantly affected quantification of vessel density. In areas with a comparable number of tracks, density increased in the obese animals, concomitant with a decrease in glomerular filtration rate and an increase in albumin/creatinine ratio, but without any pathology in the histological staining. The results indicate that super-resolution ultrasound imaging can be used to quantify structural alterations in the renal vasculature. Techniques to generate more comparable number of microbubble tracks and confirmation of the findings in larger-scale studies are needed.

One of the integral parts of super-resolution ultrasound imaging (SRI) is particle tracking. This paper presents tracking for a new approach for SUper Resolution ultrasound imaging using Erythrocytes (SURE), which uses the erythrocytes as the target instead of fragile microbubbles. The acquisition of the SURE data can be accomplished in seconds due to the abundance of erythrocytes as targets. The nearest-neighbor (NN) algorithm was used to track erythrocytes. The erythrocyte targets were tracked to create SURE intensity map by three NN trackers with a constraint on the maximum velocities of 20, 40, 80 mm/s. By combining the outputs of three trackers, and inserting them into one map, and also using an image fusion method based on discrete wavelet transform for fusion the intensity maps, it was demonstrated that the combination of trajectories from different velocities and fusion of intensity maps carried more information from all the maps.

Microbubble (MB) tracking plays an important role in ultrasound super-resolution imaging (SRI) by enabling velocity estimation and improving image quality. This work presents a new hierarchical Kalman (HK) tracker to achieve better performance at scenarios with high concentrations of MBs and high localization uncertainty. The method attempts to follow MBs with different velocity ranges using different Kalman filters. An extended simulation framework for evaluating trackers is also presented and used for comparison of the proposed HK tracker with the nearest-neighbor (NN) and Kalman (K) trackers. The HK tracks were most similar to the ground truth with the highest Jaccard similarity coefficient in 79% of the scenarios and the lowest root-mean-square error in 72% of the scenarios. The HK tracker reconstructed vessels with a more accurate diameter. In a scenario with an uncertainty of 51.2μm in MB localization, a vessel diameter of 250μm was estimated as 257μm by HK tracker, compared with 329μm and 389μm for the K and NN trackers. In the same scenario, the HK tracker estimated MB velocities with a relative bias down to 1.7% and a relative standard deviation down to 8.3%. Finally, the different tracking techniques were applied to in vivo data from rat kidneys, and trends similar to the simulations were observed. Conclusively, the results showed an improvement in tracking performance, when the HK tracker was employed in comparison with the NN and K trackers.

Velocity is one of the clinically interesting parameters. A number of studies have shown the ability of super-resolution (SR) ultrasound imaging to visualize this parameter using velocity maps. However, manual separation of the velocity estimates for arteries from veins can be quite demanding. This study used the anatomical knowledge of rat kidneys for automatic classification of arterial and venous blood velocities in SR images and measured their variations in the medullary regions of four healthy Sprague-Dawley rat kidneys. The measurements were conducted using a modified bk5000 scanner (BK Medical, Herlev, Denmark) and a BK 9009 linear array probe with a pulse amplitude modulation scheme. Ten minutes of acquired B-mode and contrast images with frame-rate of 54 Hz were processed using a SR processing pipeline. The micro-bubble trajectories were filtered using coarse anatomy labels for classification of arterial and venous flow. The velocity estimates of separated arterioles and venules of the outer medulla showed separation of data in all rats. A Wilcoxon test showed that this difference was statistically significant (p=0.002). Considering the sample size for this study, the t-distributions predicted that the median velocity in the OM arterioles and venules were in the range of 0.84 ± 0.09 mm/s and 0.70 ± 0.07 mm/s with 95% confidence. The result showed how the blood flow in outer medulla arterioles and venules of rat kidneys can be automatically distinguished using the known anatomical information about the renal vasculature.

This review looks at highlights of the development in ultrasound, ranging from interventional ultrasound and Doppler to the newest techniques like contrast-enhanced ultrasound and elastography, and gives reference to some of the valuable articles in Acta Radiologica. Ultrasound equipment is now available in any size and for any purpose, ranging from handheld devices to high-end devices, and the scientific societies include ultrasound professionals of all disciplines publishing guidelines and recommendations. Interventional ultrasound is expanding the field of use of ultrasound-guided interventions into nearly all specialties of medicine, from ultrasound guidance in minimally invasive robotic procedures to simple ultrasound-guided punctures performed by general practitioners. Each medical specialty is urged to define minimum requirements for equipment, education, training, and maintenance of skills, also for medical students. The clinical application of contrast-enhanced ultrasound and elastography is a topic often seen in current research settings.

Super-resolution ultrasound imaging (SRUS) enables in vivo microvascular imaging of deeper-lying tissues and organs, such as the kidneys or liver. The technique allows new insights into microvascular anatomy and physiology and the development of disease-related microvascular abnormalities. However, the microvascular anatomy is intricate and challenging to depict with the currently available imaging techniques, and validation of the microvascular structures of deeper-lying organs obtained with SRUS remains difficult. Our study aimed to directly compare the vascular anatomy in two in vivo 2D SRUS images of a Sprague–Dawley rat kidney with ex vivo μCT of the same kidney. Co-registering the SRUS images to the μCT volume revealed visually very similar vascular features of vessels ranging from ~ 100 to 1300 μm in diameter and illustrated a high level of vessel branching complexity captured in the 2D SRUS images. Additionally, it was shown that it is difficult to use μCT data of a whole rat kidney specimen to validate the super-resolution capability of our ultrasound scans, i.e., validating the actual microvasculature of the rat kidney. Lastly, by comparing the two imaging modalities, fundamental challenges for 2D SRUS were demonstrated, including the complexity of projecting a 3D vessel network into 2D. These challenges should be considered when interpreting clinical or preclinical SRUS data in future studies.

Super-resolution (SR) imaging has the potential of visualizing the microvasculature down to the 10- $\mu \text{m}$ level, but motion induced by breathing, heartbeats, and muscle contractions are often significantly above this level. This article, therefore, introduces a method for estimating tissue motion and compensating for this. The processing pipeline is described and validated using Field II simulations of an artificial kidney. In vivo measurements were conducted using a modified bk5000 research scanner (BK Medical, Herlev, Denmark) with a BK 9009 linear array probe employing a pulse amplitude modulation scheme. The left kidney of ten Sprague-Dawley rats was scanned during open laparotomy. A 1:10 diluted SonoVue contrast agent (Bracco, Milan, Italy) was injected through a jugular vein catheter at 100 $\mu \text{l}$ /min. Motion was estimated using speckle tracking and decomposed into contributions from the heartbeats, breathing, and residual motion. The estimated peak motions and their precisions were: heart: axial— $7.0~\pm ~0.55~\mu \text{m}$ and lateral— $38~\pm ~2.5~\mu \text{m}$ , breathing: axial— $5~\pm ~0.29~\mu \text{m}$ and lateral— $26~\pm ~1.3~\mu \text{m}$ , and residual: axial—30 $\mu \text{m}$ and lateral—90 $\mu \text{m}$ . The motion corrected microbubble tracks yielded SR images of both bubble density and blood vector velocity. The estimation was, thus, sufficiently precise to correct shifts down to the 10- $\mu \text{m}$ capillary level. Similar results were found in the other kidney measurements with a restoration of resolution for the small vessels demonstrating that motion correction in 2-D can enhance SR imaging quality.

Super-resolution Ultrasound imaging (SRI) can visualize and quantify changes in the microvasculature. Metabolic syndrome is associated with hypertension and hyperlipidemia that affects different organs, including the kidneys. Ex vivo studies have shown glomerular injury in Obese Zucker rats (OZR) over time. If in vivo SRI can diagnose renal disease earlier than currently possible, treatment can be initiated in time to postpone the onset of renal complications in persons with metabolic syndrome. The overall aim of this study was to investigate whether SRI can detect early microvascular changes in the kidneys of rats with metabolic syndrome. The rats presented in this work were scanned at an early age to get a baseline scan prior to further studies. An 11-week-old OZR and a healthy age-matched Zucker rat were investigated. During open surgery, the left kidney was scanned for 10 min using a modified BK5000 scanner (BK Medical, Denmark) and a fixated X18L5s transducer. SonoVue (Bracco, Italy) was injected intravenously (1:10 dilution). Contrast images were obtained using a pulse amplitude modulation sequence and interleaved B-mode images were obtained for tissue motion correction (focused beam transmission, 6 MHz, 50 Hz, MI: 0.2). An in-house tool was used to track microbubble (MB) movements between frames to estimate the MB velocities measured in a large region of the cortex and the outer medulla. Both the cortex and the medulla were well-perfused with MBs, and no morphological differences in the microvasculature were found between the two rats. The thickness of the cortex and the medulla was almost identical; cortex 1.8 mm, medulla 8 mm, craniocaudal length 2.0 vs. 1.9 cm (healthy vs. OZR). The same was true regarding the MB velocities (median (IQR; difference between upper and lower quartiles = Q3 - Q1) in mm/s) for healthy vs. OZR; cortex 0.75 (3.51) vs. 0.65 (2.64) and medulla 0.75 (0.32) vs. 0.62 (0.30). This is the first time SRI has been used on the kidneys of rats with metabolic syndrome. The results will be used as the foundation for further investigations of the renal microvascular changes, which occur in the course of metabolic syndrome.

In vivo monitoring of the microvasculature is relevant since diseases such as diabetes, ischemia, or cancer cause microvascular impairment. Super-resolution ultrasound imaging allows in vivo examination of the microvasculature by detecting and tracking sparsely distributed intravascular microbubbles over a minute-long period. The ability to create detailed images of the renal vasculature of Sprague-Dawley rats using a modified clinical ultrasound platform was investigated in this study. Additionally, we hypothesized that early ischemic damage to the renal microcirculation could be visualized. After a baseline scan of the exposed kidney, 10 rats underwent clamping of the renal vein (n = 5) or artery (n = 5) for 45 min. The kidneys were rescanned at the onset of clamp release and after 60 min of reperfusion. Using a processing pipeline for tissue motion compensation and microbubble tracking, super-resolution images with a very high level of detail were constructed. Image filtration allowed further characterization of the vasculature by isolating specific vessels such as the ascending vasa recta with a 15–20 μm diameter. Using the super-resolution images alone, it was only possible for six assessors to consistently distinguish the healthy renal microvasculature from the microvasculature at the onset of vein clamp release. Future studies will aim at attaining quantitative estimations of alterations in the renal microvascular blood flow using super-resolution ultrasound imaging.

In vivo visualization of the microvasculature is feasible with super-resolution ultrasound imaging (SRI), but the method needs more affirmative data before clinical use. The kidneys have a rich vasculature, and microvascular dysfunction decreases the kidney function. Therefore, detection of subtle renal microvascular changes could benefit patients with renal disease. We hypothesized that our SRI setup can visualize the microvascular network of two healthy rat kidneys and subsequently demonstrate microvascular flow changes immediately after ischemia- reperfusion. The left kidney of two male Sprague-Dawley rats was scanned during laparotomy using a customized BK5000 scanner, an X18L5s transducer, and interleaved contrast and B-mode sequences with focused beam transmission. Images were acquired over 10 min using SonoVue (1:10) as the contrast agent. After a baseline scan, one rat had the renal vein clamped, while the other rat had the renal artery clamped, both for 45 min. The kidneys were rescanned immediately after clamp release and after 60 min of reperfusion. Motion correction was applied before microbubble (MB) detection. The characteristic renal microvascular structure was visualized with anatomical distinction between the dense cortical vascular network and the straight vessels of the medulla. Immediately after vein clamp release, almost no MBs perfused the medullary vessels. After 60 min of reperfusion, MBs refilled the renal vascular bed, but with a slower velocity compared with the baseline scan. The results after artery clamping were subtler, with more MBs perfusing the medulla immediately after clamp release compared with the vein clamping. The results imply that this SRI setup can evaluate different stages of ischemic kidney disease in rats as it can visualize the entire renal vascular bed and differentiate the pattern of reperfusion in two types of ischemic injury.