Advance in Ultrasound Super-resolution Imaging, Cell Manipulation and Inter-brain Communication

Introduction: Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related deaths worldwide. Transarterial chemoembolization (TACE) treatment of HCC restricts the blood supply to the tumor. Conventional assessment of tumor response is performed by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) or computed tomography (DCE-CT) at 4 to 6 weeks after the TACE procedure. An earlier indication of treatment effectiveness would improve patient management and prognosis. Super-resolution ultrasound (SR-US) imaging allows a ten-fold improvement in spatial resolution compared to traditional ultrasound (US) and allows visualization of microvascular networks. The goal of this preclinical research study was to use SR-US imaging to assess the effectiveness of TACE treatment in a relatively brief time frame. Methods: Eight male Sprague Dawley rats weighing around 300 g were injected with 5 million N1S1 cells in the upper left liver lobe and the tumors were allowed to grow for 14 days. The TACE procedure consisted of transhepatic arterial delivery of a mixture of 25 µL Lipiodol and 25 µL Doxorubicin (10 mg/kg) via a polyethylene microcatheter. After intravenous injection of a microbubble (MB) contrast agent, contrast-enhanced US images were acquired (N = 3000) with a preclinical system (Vevo 3100, FUJIFILM VisualSonics Inc) equipped with an MX201 linear array transducer. US images were processed to remove high motion frames, followed by tissue suppression filtering, and then MB localization and accumulation. Morphological filtering was used to enhance the vessel structures. In vivo US, MRI, and CT imaging were performed at baseline before TACE and again at 1 and 2 wk. After euthanasia, tumor tissue was removed for ex vivo analysis. Results: A rat model of HCC for assessing TACE treatment was introduced. Based on tumor size changes and residual perfusion after the TACE procedure, treatments were determined to be a complete responder, partial responder, or non-responder. Initial results demonstrate that SR-US imaging can sensitively detect any reduction in HCC perfusion as measured by a microvascular density (MVD) metric within 2 wk after a single TACE procedure. MVD measurements from the SR-US images were consistence with tumor volume data from MRI and CT imaging. Conclusions: In vivo SR-US images of tumor microvascular networks provided insight into treatment efficacy. Citation Format: Junjie Li, Katherine Brown, Megan Yociss, John Eisenbrey, Kenneth Hoyt. Assessing the effectiveness of transarterial chemoembolization using super-resolution ultrasound imaging and a rat model of hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2460.

The purpose of this study was to improve the morphological analysis of microvascular networks depicted in three-dimensional (3D) super-resolution ultrasound (SR-US) images. This was supported by qualitative and quantitative validation by comparison to matched brightfield microscopy and traditional B-mode ultrasound (US) images. Contrast-enhanced US (CEUS) images were collected using a preclinical US scanner (Vevo 3100, FUJIFILM VisualSonics Inc.) equipped with an MX250 linear array transducer. CEUS imaging was performed after administration of a microbubble (MB) contrast agent into the vitelline network of a developing chicken embryo. Volume data was collected by mechanically scanning the US transducer throughout a tissue volume-of-interest in 90 μm step increments. CEUS images were collected at each increment and stored as in-phase/quadrature data (2000 frames at 152 frames per sec). SR-US images were created for each cross-sectional plane using established data processing methods. All SR-US images were then used to reconstruct a final 3D volume for vessel diameter (VD) quantification and for surface rendering. VD quantification from the 3D SR-US data exhibited an average error of 6.1% ± 6.0% when compared with matched brightfield microscopy images, whereas measurements from B-mode US images had an average error of 77.1% ± 68.9%. Volume and surface renderings in 3D space enabled qualitative validation and improved visualization of small vessels below the axial resolution of the US system. Overall, 3D SR-US image reconstructions depicted the microvascular network of the developing chicken embryos. Improved visualization of isolated vessels and quantification of microvascular morphology from SR-US images achieved a considerably greater accuracy compared to B-mode US measurements.

Microvascular processes play key roles in many diseases including diabetes. Improved understanding of the microvascular changes involved in disease development could offer crucial insight into the relationship of these changes to disease pathogenesis. Super-resolution ultrasound (SR-US) imaging has showed the potential to visualize microvascular detail down to the capillary level (i.e., subwavelength resolution), but optimization is still necessary. The purpose of this study was to investigate invivo SR-US imaging of skeletal muscle microvascularity using microbubble (MB) contrast agents of various size and concentration while evaluating different ultrasound (US) system level parameters such as imaging frame rate and image acquisition length. An US system equipped with a linear array transducer was used in a harmonic imaging mode at low transmit power. C57BL/6J mice fed a normal diet were used in this study. An assortment of size-selected MB contrast agents (1-2μm, 3-4μm, and 5-8μm in diameter) were slowly infused in the tail vein at various doses (1.25×107 , 2.5×107 , or 5×107 MBs). US image data were collected before MB injection and thereafter for 10min at 30 frames per s (fps). The US transducer was fixed throughout and between each imaging period to help capture microvascular patterns along the same image plane. An adaptive SR-US image processing technique was implemented using custom Matlab software. Experimental findings illustrate the use of larger MB results in better SR-US images in terms of skeletal muscle microvascular detail. A dose of 2.5×107 MBs resulted in SR-US images with optimal spatial resolution. An US imaging rate of at least 20fps and image acquisition length of at least 8min also resulted in SR-US images with pronounced microvascular detail. This study indicates that MB size and dose and US system imaging rate and data acquisition length have significant impact on the quality of invivo SR-US images of skeletal muscle microvascularity.

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

Assessment of Transarterial Chemoembolization Using Super-resolution Ultrasound Imaging and a Rat Model of Hepatocellular Carcinoma.

Super-resolution ultrasound (SR-US) imaging improves ultrasound (US) resolution by up to ten-fold. However, translation to the clinical setting has been hindered by long computation times. Conventional algorithms used to detect and localize a microbubble (MB) contrast agent during SR-US image construction suffer from high complexity and computational intensity. Deep learning methods have been used to help implement solutions to these two key SR-US image processing steps. Such developments allow frame processing on the time scale of milliseconds. The goal of this study was to combine a single deep network to both detect and localize MBs for use during SR-US imaging. We propose SRUSnet, which is a fully convolutional network architecture based on MobileNetV3 with enhancements for 2 + 1D input data, fast convergence time, and support for high-resolution data output. The architecture features both a classification and a regression head to provide a flexible level of increased resolution for the output SR-US image. Training was performed with synthetic in silico data computed as a sequence of images with MBs flowing at different rates against a background of tissue. In vitro imaging of a flow phantom perfused with MBs was performed using a programmable US scanner (Vantage 256, Verasonics Inc.) equipped with an L11-4v linear array transducer. The network operating on in silico data exceeded 99% detection accuracy and averaged less than the resolution of a pixel in localization accuracy (i.e. λ/8). The processing time for a 128 × 128-pixel image averaged 25.9 ms on a Nvidia GeForce 2080Ti GPU. Overall, these preliminary results are a promising advance in moving towards a real-time implementation of SR-US imaging.

Recently, we proved in the first measurements of breast carcinomas the feasibility of super-resolution ultrasound (US) imaging by motion-model ultrasound localization microscopy in a clinical setup. Nevertheless, pronounced in-plane and out-of-plane motions, a nonoptimized microbubble injection scheme, the lower frame rate and the larger slice thickness made the processing more complex than in preclinical investigations. Here, we compare the results of state-of-the-art contrast-enhanced to super-resolution US imaging and systematically analyze the measurements to get indications for the improvement of image acquisition and processing in the future clinical studies. In this regard, the application of a saturation model to the reconstructed vessels is shown to be a valuable tool not only to estimate the measurement times necessary to adequately reconstruct the microvasculature but also for the validation of the measurements. The parameters from this model can also serve to optimize contrast agent concentration and injection protocols. Finally, for the measurements of well-perfused tumors, we observed between 28% and 50% filling for 90-s examination times.

Background: Oncologic emergencies in critically ill cancer patients frequently require rapid, real-time assessment of tumor responses to therapeutic interventions. However, conventional imaging modalities such as computed tomography and magnetic resonance imaging are often impractical in intensive care units (ICUs) due to logistical constraints and patient instability. Super-resolution ultrasound (SR-US) imaging has emerged as a promising noninvasive alternative, facilitating bedside evaluation of tumor microvascular dynamics with exceptional spatial resolution. This study assessed the clinical utility of real-time SR-US imaging in monitoring tumor perfusion changes during emergency management in oncological ICU settings. Methods: In this prospective observational study, critically ill patients with oncologic emergencies underwent bedside SR-US imaging before and after the initiation of emergency therapy (e.g., corticosteroids, decompression, or chemotherapy). SR-US was employed to quantify microvascular parameters, including perfusion density and flow heterogeneity. Data processing incorporated artificial intelligence for real-time vessel segmentation and quantitative analysis. Results: SR-US imaging successfully detected perfusion changes within hours of therapy initiation. A significant correlation was observed between reduced tumor perfusion and clinical improvement, including symptom relief and shorter ICU stay. This technology enables visualization of microvessels as small as 30 µm, surpassing conventional ultrasound limits. No adverse events were reported with the use of contrast microbubbles. In addition, SR-US imaging reduces the need for transportation to radiology departments, thereby optimizing ICU workflow. Conclusions: Real-time SR-US imaging offers a novel, bedside-compatible method for evaluating tumor vascular response during the acute phase of oncological emergencies. Its integration into ICU care pathways could enhance timely decision-making, reduce reliance on static imaging, and support personalized cancer management. Further multicenter validation is required.

The purpose of this present study was to improve the quantification of microvascular networks depicted in three-dimensional (3D) super-resolution ultrasound (SR-US) images and compare results with matched brightfield microscopy and B-mode ultrasound (US) images. Standard contrast-enhanced US (CEUS) images were collected using a high-frequency US scanner (Vevo 3100, FUJIFILM VisualSonics Inc) equipped with an MX250 linear array transducer. Using a developing chicken embryo as our model system, US imaging was performed after administration of a custom microbubble (MB) contrast agent. Guided by stereo microscopy, MBs were introduced into a perfused blood vessel by microinjection with a glass capillary needle. Volume data was collected by mechanically scanning the US transducer throughout a tissue volume-of-interest (VOI) in 90 μm step increments. CEUS images were collected at each increment and stored as in-phase/quadrature (IQ) data (N = 2000 at 152 frames per sec). SR-US images were created for each cross-sectional plane using established data processing methods, and all were then used to form a final 3D volume for subsequent quantification of morphological features. Vessel diameter quantifications from 3D SR-US data exhibited an average error of 1.9% when compared with microscopy images, whereas measures from B-mode US images had an average error of 75.3%. Overall, 3D SR-US images clearly depicted the microvascular network of the developing chicken embryo and measurements of microvascular morphology achieved better accuracy compared to traditional B-mode US.

The lack of sensibility of traditional ultrasound (US) imaging to the slow blood flow in small vessels resulted in the development of microbubble (MB) contrast agents. These MBs are given intravenously, and US imaging can detect them quite effectively. This noninvasive imaging method, known as contrast-enhanced US (CEUS), now makes it possible to accurately assess tissue perfusion and blood flow. Though CEUS offers several benefits, diffraction restricts the spatial resolution of all US imaging systems to length scales equal to roughly half the wavelength of the transmitted US beam. Based on individual MB detection and localization, the recently developed super-resolution US (SRUS) imaging method has shown unprecedentedly high spatial resolution exceeding the physical diffraction limit. It is now possible to visualize the microvasculature beyond the diffraction-limited resolution by localizing spatially isolated MBs across several frames. The highest resolution possible at clinical US frequencies can be on the order of several micrometers when tissue and probe motion are not present. Enhancing the functional study of tissue microvascular networks with structural data could lead to improved disease management. Through the localization and tracking of MBs, SRUS may reconstruct images of the microvasculature with resolution exceeding the diffraction limit in both 2-dimensional (2D) and 3-dimensional (3D) space. In contrast to the 2D approach, 3D SRUS imaging does not suffer from out-of-plane motion and can offer volumetric coverage with super-resolution in all three dimensions. Research has used two primary methods for 3D SRUS imaging including arrays that can electronically gather volumetric information or mechanically scanning the volume with a linear probe to produce a stack of 2D SRUS images. This manuscript aims to offer a comprehensive review of 3D SRUS imaging, clarifying methodologies, clinical applications, and notable challenges that could motivate future research and help facilitate clinical translation.

Peripheral kidney microvascular damage and chronic perfusion dysfunction in kidney fibrosis are demonstrated in most chronic kidney diseases. There is an urgent clinical need to develop an in vivo, noninvasive, and quantitative diagnostic tool to monitor the renal microcirculation. The present study aims to investigate the feasibility of super-resolution ultrasound (SRU) imaging in the visualization and quantification of renal microvascular and microcirculation in mice of unilateral ureteral obstruction (UUO). The SRU for renal micro-vessels imaging in healthy mice was performed and compared with conventional power Doppler ultrasound (US) and micro-computed tomography (CT). Renal fibrosis was prepared in vivo using UUO. B-mode, conventional power Doppler US, and SRU imaging were performed on the sham kidneys and UUO models at 3, 7, and 14 days. Then these kidneys were followed by histopathologic analysis and comparisons with SRU quantification parameters. SRU helped to evaluate the function and structure of vessels in progressive renal disease via quantifying the renal microvascular. The quantitative parameters of SRU based on total blood flow of the kidney were calculated in the sham group, 3, 7, and 14 days after UUO. Renal cortical vessel density (r = 0.881), vessel curvature (r = -0.506), cortical perfusion index (PI) (r = 0.668) showed correlations with pathologically derived vessel density labeled with the expression of CD31. Vessel density (r = -0.615) and cortical curvature (r = -0.842), cortical PI (r = -0.508) also showed correlations with Masson's trichrome stain. Vessel curvature (r = -0.591) showed correlations with the expression of Col-1. SRU imaging provides the noninvasive, dynamic, and longitudinal monitoring of vessel functionality and can provide quantification of renal microvascular changes in a murine model of renal fibrosis.

The purpose of this research project was to evaluate the use of 3-dimensional (3-D) super-resolution ultrasound (SR-US) imaging to assess any early changes in breast cancer after treatment with a vascular-disrupting agent (VDA). A Vevo 3100 ultrasound system (FUJIFILM VisualSonics Inc) equipped with an MX 201 transducer was used for image acquisition. A total of 2.5 × 107 microbubbles (MBs) were injected into the tail vein of anesthetized breast cancer-bearing mice using repeat bolus injections every 5 min. A total of 10 stacks of ultrasound images were collected as the transducer was mechanically moved across the tumor at 0.6 mm intervals yielding a 6-mm thick volume. At each tumor location, a stack contained 1 × 104 frames of ultrasound data that were acquired at 463 frames/sec and stored as in-phase/quadrature (IQ) format. After motion correction, each temporal stack of ultrasound images was processed separately for clutter signal removal, which was followed by MB localization and enumeration before generation of the final SR-US image. After reconstruction of the 3-D SR-US volume dataset, the tumor microvasculature was enhanced using a multiscale vessel enhancement filter. Vessels from the resultant microvascular network were then segmented using an adaptive thresholding method. Finally, mean microvascular density (MVD) measurements from each tumor volume were computed as a summarizing statistic. While no differences were found between baseline SR-US image-derived measures of MVD (p = 0.76), these same measurements were significantly lower at 24 h after VDA treatment (p < 0.001). Overall, 3-D SR-US imaging detected early tumor changes following treatment with a vascular-targeted drug.

Accurate preoperative localization and characterization of sentinel lymph nodes (SLNs) is vital in breast cancer management. The application of super-resolution ultrasound (SRUS) imaging to visualize intranodal lymphatic sinuses for the prediction of SLN metastasis has yet to be investigated. The study aimed to assess the value of SRUS imaging of intranodal lymphatic sinuses in predicting SLN metastasis in breast cancer patients. A total of 154 SLNs from 143 patients with breast cancer were prospectively included. All patients underwent conventional US of axillary lymph nodes and SRUS imaging of lymph sinus by percutaneous microbubble injection. Qualitative and quantitative analysis were performed for SRUS imaging, with qualitative analysis focusing on identifying perfusion defects and quantitative analysis including parameters such as lymphatic sinus density, sinus diameter, sinus distance, and lymph flow velocity. The areas under the receiver operating characteristic curve (AUC), sensitivity, and specificity were calculated for conventional US, SRUS, and combined conventional US and SRUS. Among the 154 SLNs, 73 were metastatic and 81 were reactive. In predicting metastatic SLNs, the AUC for SRUS (0.824; 95% CI: 0.761-0.888) was significantly higher than that for conventional US (0.661; 95% CI: 0.596-0.726) (p < 0.001). The combination of SRUS and conventional US achieved the highest AUC (0.844; 95% CI: 0.785-0.904), which was significantly higher than conventional US alone (p < 0.001), but not significantly different from SRUS alone (p = 0.2). Imaging lymphatic sinuses by SRUS has the potential to predict metastatic SLNs in patients with breast cancer. Question Super-resolution ultrasound (SRUS) used for visualizing intranodal lymphatic sinuses for the prediction of sentinel lymph nodes (SLNs) metastasis has yet to be investigated. Findings Microlymphatic circulation of SLNs were imaged by SRUS at ten microns scale. SRUS showed better performance for predicting metastatic SLNs than conventional ultrasound. Clinical relevance SRUS is a reliable tool to image lymphatic sinuses and characterize metastatic SLNs in patients with breast cancer. It helps diagnosis of lymph node status and clinical decision-making of breast cancer.

Super-resolution ultrasound microvascular imaging: Is it ready for clinical use?

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.