Search Results (20)

Background: Vascular imaging is essential for clinical practice, research, and the diagnosis and management of vascular diseases. Super-resolution ultrasound (SRUS) imaging is an emerging high-resolution imaging technique with broad applications in soft tissue vascular imaging. However, the impact of biological and clinical variables on its imaging accuracy is currently unknown. This study investigates these factors in an animal model and compares SRUS with contrast-enhanced µCT. Methods: Kidney scans from 29 Zucker rats (Zucker Diabetic Fatty and Zucker Lean) were retrospectively analysed. The left kidney was imaged in vivo using SRUS during microbubble infusion, then filled with Microfil and excised for ex vivo µCT. SRUS parameters and clinical variables were analysed, and SRUS scans were co-registered with µCT to compare vascular density measurements. Results: Mean arterial blood pressure and anaesthesia time showed significant linear relationships with SRUS microbubble detection and vascular track reconstruction. The anaesthesia time was also strongly correlated with vascular density measurement. Visualisation and velocity estimations of renal arteries were limited with SRUS. Ultrasound signal attenuation had significant impacts, particularly in cortical far-field imaging. Despite differences between kidney regions, the vascular density distribution did not differ considerably between SRUS and µCT datasets for whole-kidney imaging. Conclusions: This study outlines key factors SRUS users must consider for optimal technique use. Careful region selection and control of clinical variables ensure more reliable and comparable images. Further research is necessary to translate these findings from a rat model into clinical application. Full article

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. Full article

The present study aimed to explore the clinical applicability of ultrasound super-resolution imaging (US SRI) for assessing renal microcirculation in patients with acute kidney injury (AKI). A total of 62 patients with sepsis were enrolled in the present study—38 with AKI and 24 control patients—from whom renal ultrasounds and clinical data were obtained. SonoVue contrast (1.5 mL) was administered through the elbow vein and contrast-enhanced ultrasound (CEUS) images were obtained on a Mindray Resona A20 ultrasound unit for 2 min. The renal perfusion time-intensity curve (TIC) was analyzed and, after 15 min, additional images were obtained to create a microscopic blood flow map. Microvascular density (MVD) was calculated and its correlation with serum creatinine (Scr) levels was analyzed. There were significant differences in heart rate, Scr, blood urea nitrogen, urine volume at 24 h, and glomerular filtration rate between the two groups (p < 0.01), whereas other characteristics, such as renal morphology, did not differ significantly between the AKI group and control group (p > 0.05). The time to peak and mean transit times of the renal cortex in the AKI group were prolonged compared to those in the control group (p < 0.01), while the peak intensity and area under the TIC were lower than those in the control group (p < 0.05). The MVD of the renal cortex in the AKI group was lower than that in the control group (18.46 ± 5.90% vs. 44.93 ± 11.65%; p < 0.01) and the MVD in the AKI group showed a negative correlation with Scr (R = −0.84; p < 0.01). Based on the aforementioned results, US SRI can effectively assess renal microcirculation in patients with AKI and is a noninvasive technique for the diagnosis of AKI and quantitative evaluation of renal microcirculation. Full article

We are currently investigating the ultrasound imaging of a sensor that consists of a randomized encoding mask attached to a single lead zirconate titanate (PZT) oscillator for a puncture microscope application. The proposed model was conducted using a finite element method (FEM) simulator. To increase the number of measurements required by a single element system that affects its resolution, the transducer was rotated at different angles. The image was constructed by solving a linear equation of the image model resulting in a poor quality. In a previous work, the phase information was extracted from the echo signal to improve the image quality. This study proposes a strategy by integrating the weighted frequency subbands compound and a super-resolution technique to enhance the resolution in range and lateral direction. The image performance with different methods was also evaluated using the experimental data. The results indicate that better image resolution and speckle suppression were obtained by applying the proposed method. Full article

Ultrasound imaging is widely used as a noninvasive lesion detection method in diagnostic medicine. Improving the quality of these ultrasound images is very important for accurate diagnosis, and deep learning-based algorithms have gained significant attention. This study proposes a multiscale deep encoder–decoder with phase congruency (MSDEPC) algorithm based on deep learning to improve the quality of diagnostic ultrasound images. The MSDEPC algorithm included low-resolution (LR) images and edges as inputs and constructed a multiscale convolution and deconvolution network. Simulations were conducted using the Field 2 program, and data from real experimental research were obtained using five clinical datasets containing images of the carotid artery, liver hemangiomas, breast malignancy, thyroid carcinomas, and obstetric nuchal translucency. LR images, bicubic interpolation, and super-resolution convolutional neural networks (SRCNNs) were modeled as comparison groups. Through visual assessment, the image processed using the MSDEPC was the clearest, and the lesions were clearly distinguished. The structural similarity index metric (SSIM) value of the simulated ultrasound image using the MSDEPC algorithm improved by approximately 38.84% compared to LR. In addition, the peak signal-to-noise ratio (PSNR) and SSIM values of clinical ultrasound images using the MSDEPC algorithm improved by approximately 2.33 times and 88.58%, respectively, compared to LR. In conclusion, the MSDEPC algorithm is expected to significantly improve the spatial resolution of ultrasound images. Full article

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. Full article

Ultrasound-based engineering of carrier-free nanodrugs by supramolecular self-assembly has recently emerged as an innovative and environmentally friendly synthetic approach. By applying high-frequency sound waves (490 kHz) in aqueous solutions, the transformation of small chemotherapeutic and antibiotic drug molecules into carrier-free nanodrugs with anticancer and antimicrobial activities was recently achieved. The transformation of the antibiotic drug molecules, i.e., doxycycline, into stable nanodrugs (~130 nm) with selective anticancer activity was achieved without requiring organic solvents, chemical agents, or surfactants. The obtained nanodrug exhibited reactive oxygen species (ROS)-mediated cytotoxicity on human breast cancer (MDA-MB 231 cells) but a negligible antiproliferative effect on healthy fibroblast cells. Imaging by super-resolution microscopy (STORM) provided insights into the intracellular trafficking and endosomal escape of the nanodrugs. Overall, these findings suggest that small antibiotic drugs can be transformed into chemotherapeutic nanodrugs with high selectivity against cancer cells. Full article

Imaging of the ocular vasculature can provide new insights into the pathophysiology of ocular diseases. This study proposes a novel high-frequency super-resolution ultrasound localization microscopy (SRULM) technique and evaluates its ability to measure in vivo perfusion changes in the rat eye at elevated intraocular pressure (IOP). A 38.4 MHz center frequency linear array transducer on a VisualSonics Vevo F2 imaging platform was used to collect high frame rate (1 kHz) radiofrequency data of the posterior rat eye following systemic microbubble contrast injection. Following clutter and spatiotemporal non-local means filtering, individual microbubbles were localized and tracked. The microbubble tracks were accumulated over 10,000 frames to generate vascular images quantifying perfusion velocity and direction. Experiments were performed using physiologic relevant controlled flow states for algorithm validation and subsequently performed in vivo on the rat eye at 10 mm Hg IOP increments from 10 to 60 mm Hg. The posterior vasculature of the rat eye, including the ophthalmic artery, long posterior ciliary arteries and their branches, central retinal artery and retinal arterioles and venules were successfully visualized, and velocities quantified at each IOP level. Significant reductions in arterial flow were measured as IOP was elevated. High-frequency SRULM can be used to visualize and quantify the perfusion velocity of the rat eye in both the retrobulbar and intraocular vasculature simultaneously. The ability to detect ocular perfusion changes throughout the depth of the eye may help elucidate the role ischemia has in the pathophysiology of ocular diseases such as glaucoma. Full article

Ocular choroidal melanoma (OCM) is the most common ocular primary malignant tumor in adults, and there is an increasing emphasis on its early detection and treatment worldwide. The main obstacle in early detection of OCM is its overlapping clinical features with benign choroidal nevus. Thus, we propose ultrasound localization microscopy (ULM) based on the image deconvolution algorithm to assist the diagnosis of small OCM in early stages. Furthermore, we develop ultrasound (US) plane wave imaging based on three-frame difference algorithm to guide the placement of the probe on the field of view. A high-frequency Verasonics Vantage system and an L22-14v linear array transducer were used to perform experiments on both custom-made modules in vitro and a SD rat with ocular choroidal melanoma in vivo. The results demonstrate that our proposed deconvolution method implement more robust microbubble (MB) localization, reconstruction of microvasculature network in a finer grid and more precise flow velocity estimation. The excellent performance of US plane wave imaging was successfully validated on the flow phantom and in an in vivo OCM model. In the future, the super-resolution ULM, a critical complementary imaging modality, can provide doctors with conclusive suggestions for early diagnosis of OCM, which is significant for the treatment and prognosis of patients. Full article

This study addresses the issue of energy optimization by investigating solutions for the reduction of energy consumption in the diagnostics and monitoring of technological processes. The implementation of advanced process control is identified as a key approach for achieving energy savings and improving product quality, process efficiency, and production flexibility. The goal of this research is to develop a cost-effective system with a minimal number of ultrasound sensors, thus reducing the energy consumption of the overall system. To accomplish this, a novel method for obtaining high-resolution reconstruction in transmission ultrasound tomography (t-UST) is proposed. The method involves utilizing a convolutional neural network to take low-resolution measurements as input and output high-resolution sinograms that are used for tomography image reconstruction. This approach allows for the construction of a super-resolution sinogram by utilizing information hidden in the low-resolution measurement. The model is trained on simulation data and validated on real measurement data. The results of this technique demonstrate significant improvement compared to state-of-the-art methods. The study also highlights that UST measurements contain more information than previously thought, and this hidden information can be extracted and utilized with the use of machine learning techniques to further improve image quality and object recognition. Full article

Ultrasound (US) imaging is a medical imaging modality that uses the reflection of sound in the range of 2–18 MHz to image internal body structures. In US, the frequency bandwidth (BW) is directly associated with image resolution. BW is a property of the transducer and more bandwidth comes at a higher cost. Thus, methods that can transform strongly bandlimited ultrasound data into broadband data are essential. In this work, we propose a deep learning (DL) technique to improve the image quality for a given bandwidth by learning features provided by broadband data of the same field of view. Therefore, the performance of several DL architectures and conventional state-of-the-art techniques for image quality improvement and artifact removal have been compared on in vitro US datasets. Two training losses have been utilized on three different architectures: a super resolution convolutional neural network (SRCNN), U-Net, and a residual encoder decoder network (REDNet) architecture. The models have been trained to transform low-bandwidth image reconstructions to high-bandwidth image reconstructions, to reduce the artifacts, and make the reconstructions visually more attractive. Experiments were performed for 20%, 40%, and 60% fractional bandwidth on the original images and showed that the improvements obtained are as high as 45.5% in RMSE, and 3.85 dB in PSNR, in datasets with a 20% bandwidth limitation. Full article

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. Full article

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. Full article

In this paper, we propose a symmetric series convolutional neural network (SS-CNN), which is a novel deep convolutional neural network (DCNN)-based super-resolution (SR) technique for ultrasound medical imaging. The proposed model comprises two parts: a feature extraction network (FEN) and an up-sampling layer. In the FEN, the low-resolution (LR) counterpart of the ultrasound image passes through a symmetric series of two different DCNNs. The low-level feature maps obtained from the subsequent layers of both DCNNs are concatenated in a feed forward manner, aiding in robust feature extraction to ensure high reconstruction quality. Subsequently, the final concatenated features serve as an input map to the latter 2D convolutional layers, where the textural information of the input image is connected via skip connections. The second part of the proposed model is a sub-pixel convolutional (SPC) layer, which up-samples the output of the FEN by multiplying it with a multi-dimensional kernel followed by a periodic shuffling operation to reconstruct a high-quality SR ultrasound image. We validate the performance of the SS-CNN with publicly available ultrasound image datasets. Experimental results show that the proposed model achieves a high-quality reconstruction of the ultrasound image over the conventional methods in terms of peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM), while providing compelling SR reconstruction time. Full article

A variety of different nanomaterials (NMs) such as microbubbles (MBs), nanobubbles (NBs), nanodroplets (NDs), and silica hollow meso-structures have been tested as ultrasound contrast agents for the detection of heart diseases. The inner part of these NMs is made gaseous to yield an ultrasound contrast, which arises from the difference in acoustic impedance between the interior and exterior of such a structure. Furthermore, to specifically achieve a contrast in the diseased heart region (DHR), NMs can be designed to target this region in essentially three different ways (i.e., passively when NMs are small enough to diffuse through the holes of the vessels supplying the DHR, actively by being associated with a ligand that recognizes a receptor of the DHR, or magnetically by applying a magnetic field orientated in the direction of the DHR on a NM responding to such stimulus). The localization and resolution of ultrasound imaging can be further improved by applying ultrasounds in the DHR, by increasing the ultrasound frequency, or by using harmonic, sub-harmonic, or super-resolution imaging. Local imaging can be achieved with other non-gaseous NMs of metallic composition (i.e., essentially made of Au) by using photoacoustic imaging, thus widening the range of NMs usable for cardiac applications. These contrast agents may also have a therapeutic efficacy by carrying/activating/releasing a heart disease drug, by triggering ultrasound targeted microbubble destruction or enhanced cavitation in the DHR, for example, resulting in thrombolysis or helping to prevent heart transplant rejection. Full article