Context-aware deep learning enables high-efficacy localization of high concentration microbubbles for super-resolution ultrasound localization microscopy.

Ultrasound localization microscopy (ULM) enables deep tissue microvascular imaging by localizing and tracking intravenously injected microbubbles circulating in the bloodstream. However, conventional localization techniques require spatially isolated microbubbles, resulting in prolonged imaging time to obtain detailed microvascular maps. Here, we introduce LOcalization with Context Awareness (LOCA)-ULM, a deep learning-based microbubble simulation and localization pipeline designed to enhance localization performance in high microbubble concentrations. In silico, LOCA-ULM enhanced microbubble detection accuracy to 97.8% and reduced the missing rate to 23.8%, outperforming conventional and deep learning-based localization methods up to 17.4% in accuracy and 37.6% in missing rate reduction. In in vivo rat brain imaging, LOCA-ULM revealed dense cerebrovascular networks and spatially adjacent microvessels undetected by conventional ULM. We further demonstrate the superior localization performance of LOCA-ULM in functional ULM (fULM) where LOCA-ULM significantly increased the functional imaging sensitivity of fULM to hemodynamic responses invoked by whisker stimulations in the rat brain.

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

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

Three-Dimensional Shear Wave Elastography Using Acoustic Radiation Force and a 2-D Row-Column Addressing (RCA) Array.

Acoustic radiation force (ARF)-based shear wave elastography (SWE) is a clinically available ultrasound imaging mode that noninvasively and quantitatively measures tissue stiffness. Current implementations of ARF-SWE are largely limited to 2-D imaging, which does not provide a robust estimation of heterogeneous tissue mechanical properties. Existing 3-D ARF-SWE solutions that are clinically available are based on wobbler probes, which cannot provide true 3-D shear wave motion detection. Although 3-D ARF-SWE based on 2-D matrix arrays have been previously demonstrated, they do not provide a practical solution because of the need for a high channel-count ultrasound system (e.g., 1024-channel) to provide adequate volume rates and the delicate circuitries (e.g., multiplexers) that are vulnerable to the long-duration "push" pulses. To address these issues, here we propose a new 3-D ARF-SWE method based on the 2-D row-column addressing (RCA) array which has a much lower element count (e.g., 256), provides an ultrafast imaging volume rate (e.g., 2000 Hz), and can withstand the push pulses. In this study, we combined the comb-push shear elastography (CUSE) technique with 2-D RCA for enhanced SWE imaging field-of-view (FOV). In vitro phantom studies demonstrated that the proposed method had robust 3-D SWE performance in both homogenous and inclusion phantoms. An in vivo study on a breast cancer patient showed that the proposed method could reconstruct 3-D elasticity maps of the breast lesion, which was validated using a commercial ultrasound scanner. These results demonstrate strong potential for the proposed method to provide a viable and practical solution for clinical 3-D ARF-SWE.

Super-Resolution Ultrasound Reveals Cerebrovascular Impairment in a Mouse Model of Alzheimer's Disease.

Increasing evidence has suggested a link between cerebrovascular disease and the cognitive impairment associated with Alzheimer's disease. However, detailed descriptions of microvascular changes across brain regions and how they relate to other more traditional pathology have been lacking. Additionally, the efforts to elucidate the interplay between cerebral microvascular function and Alzheimer's disease progression are complicated by the necessity of probing deep-brain structures since early-stage Alzheimer's disease typically involves hippocampal pathology. The purpose of this study was to examine changes in microvascular dynamics in a mouse model of Alzheimer's disease using cohorts that were age-matched to wild-type controls. Data from both sexes were included in this study. Super-resolution ultrasound localization microscopy revealed microvascular functional and structural features throughout the whole brain depth to visualize and quantify. We found that functional decreases in hippocampal and entorhinal flow velocity preceded structural derangements in regional vascular density. Co-registered histological sectioning confirmed the regionalized perfusion deficits seen on ultrasound imaging, which were co-localized with amyloid beta plaque deposition. In addition to providing global vascular quantifications of deep brain structures with a high local resolution, this technology also permitted velocity-profile analysis of individual vessels and, in some cases, allowed for decoupling of arterial and venous flow contributions. These data suggest that microvascular pathology is an early and pervasive feature of Alzheimer's disease and may represent a novel therapeutic target for this disease.

Longitudinal Awake Imaging of Deep Mouse Brain Microvasculature with Super-resolution Ultrasound Localization Microscopy.

Super-resolution ultrasound localization microscopy (ULM) is an emerging imaging modality that resolves capillary-scale microvasculature in deep tissues. However, existing preclinical ULM applications are largely constrained to anesthetized animals, introducing confounding vascular effects such as vasodilation and altered hemodynamics. As such, ULM quantifications (e.g., vessel diameter, density, and flow velocity) may be confounded by the use of anesthesia, undermining the usefulness of ULM in practice. Here we introduce a method to address this limitation and achieve ULM imaging in awake mouse brain. Pupillary monitoring was used to confirm the awake state during ULM imaging. ULM revealed that veins showed a greater degree of vascularity reduction from anesthesia to awake states than did arteries. The reduction was most significant in the midbrain and least significant in the cortex. ULM also revealed a significant reduction in venous blood flow velocity across different brain regions under awake conditions. Serial in vivo imaging of the same animal brain at weekly intervals demonstrated the highly robust longitudinal imaging capability of the proposed technique. This is the first study demonstrating longitudinal ULM imaging in the awake mouse brain, which is essential for many ULM brain applications that require awake and behaving animals.

Contrast-Free Super-Resolution Power Doppler (CS-PD) Based on Deep Neural Networks.

Super-resolution ultrasound microvessel imaging based on ultrasound localization microscopy (ULM) is an emerging imaging modality that is capable of resolving micrometer-scaled vessels deep into tissue. In practice, ULM is limited by the need for contrast injection, long data acquisition, and computationally expensive postprocessing times. In this study, we present a contrast-free super-resolution power Doppler (CS-PD) technique that uses deep networks to achieve super-resolution with short data acquisition. The training dataset is comprised of spatiotemporal ultrafast ultrasound signals acquired from in vivo mouse brains, while the testing dataset includes in vivo mouse brain, chicken embryo chorioallantoic membrane (CAM), and healthy human subjects. The in vivo mouse imaging studies demonstrate that CS-PD could achieve an approximate twofold improvement in spatial resolution when compared with conventional power Doppler. In addition, the microvascular images generated by CS-PD showed good agreement with the corresponding ULM images as indicated by a structural similarity index of 0.7837 and a peak signal-to-noise ratio (PSNR) of 25.52. Moreover, CS-PD was able to preserve the temporal profile of the blood flow (e.g., pulsatility) that is similar to conventional power Doppler. Finally, the generalizability of CS-PD was demonstrated on testing data of different tissues using different imaging settings. The fast inference time of the proposed deep neural network also allows CS-PD to be implemented for real-time imaging. These features of CS-PD offer a practical, fast, and robust microvascular imaging solution for many preclinical and clinical applications of Doppler ultrasound.

High-Volume-Rate 3-D Ultrasound Imaging Using Fast-Tilting and Redirecting Reflectors.

Three-dimensional ultrasound imaging has many advantages over 2-D imaging such as more comprehensive tissue evaluation and less operator dependence. However, developing a low-cost and accessible 3-D ultrasound solution with high volume rate and imaging quality remains a challenging task. Recently, we proposed a 3-D ultrasound imaging technique: fast acoustic steering via tilting electromechanical reflectors (FASTER), which uses a fast-tilting acoustic reflector to steer ultrafast plane waves elevationally to achieve high-volume-rate 3-D imaging with conventional 1-D transducers. However, the initial FASTER implementation requires a water tank for acoustic wave conduction and cannot be conveniently used for regular handheld scanning. To address these limitations, here, we developed a novel ultrasound probe clip-on device that encloses a fast-tilting reflector, a redirecting reflector, and an acoustic wave conduction medium. The new FASTER 3-D imaging device can be easily attached to or removed from clinical ultrasound transducers, allowing rapid transformation from 2-D to 3-D imaging. In vitro B-mode studies demonstrated that the proposed method provided comparable imaging quality to conventional, mechanical-translation-based 3-D imaging while offering a much faster volume rate (e.g., 300 versus  âˆ¼  10 Hz). We also demonstrated 3-D power Doppler (PD) and 3-D super-resolution ultrasound localization microscopy (ULM) with the FASTER device. An in vivo imaging study showed that the FASTER device could clearly visualize the 3-D anatomy of the basilic vein. These results suggest that the newly developed redirecting reflector and the clip-on device could overcome key hurdles for future clinical translation of the FASTER 3-D imaging technology.

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

The field of super-resolution ultrasound microvascular imaging has been rapidly growing over the past decade. By leveraging contrast microbubbles as point targets for localization and tracking, super-resolution ultrasound pinpoints the location of microvessels and measures their blood flow velocity. Super-resolution ultrasound is the first in vivo imaging modality that can image micron-scale vessels at a clinically relevant imaging depth without tissue destruction. These unique capabilities of super-resolution ultrasound provide structural (vessel morphology) and functional (vessel blood flow) assessments of tissue microvasculature on a global and local scale, which opens new doors for many enticing preclinical and clinical applications that benefit from microvascular biomarkers. The goal of this short review is to provide an update on recent advancements in super-resolution ultrasound imaging, with a focus on summarizing existing applications and discussing the prospects of translating super-resolution imaging to clinical practice and research. In this review, we also provide brief introductions of how super-resolution ultrasound works, how does it compare with other imaging modalities, and what are the tradeoffs and limitations for an audience who is not familiar with the technology.

High-Level Synthesis Design of Scalable Ultrafast Ultrasound Beamformer With Single FPGA.

Ultrafast ultrasound imaging is essential for advanced ultrasound imaging techniques such as ultrasound localization microscopy (ULM) and functional ultrasound (fUS). Current ultrafast ultrasound imaging is challenged by the ultrahigh data bandwidth associated with the radio frequency (RF) signal, and by the latency of the computationally expensive beamforming process. As such, continuous ultrafast data acquisition and beamforming remain elusive with existing software beamformers based on CPUs or GPUs. To address these challenges, the proposed work introduces a novel method of implementing an ultrafast ultrasound beamformer specifically for ultrafast plane wave imaging (PWI) on a field programmable gate array (FPGA) by using high-level synthesis. A parallelized implementation of the beamformer on a single FPGA was proposed by 1) utilizing a delay compression technique to reduce the delay profile size, which enables both run-time pre-calculated delay profile loading from external memory and delay reuse, 2) vectorizing channel data fetching which is enabled by delay reuse, and 3) using fixed summing networks to reduce consumption of logic resources. Our proposed method presents two unique advantages over current FPGA beamformers: 1) high scalability that allows fast adaptation to different FPGA resources and beamforming speed demands by using Xilinx High-Level Synthesis as the development tool, and 2) allow a compact form factor design by using a single FPGA to complete the beamforming instead of multiple FPGAs. Current Xilinx FPGAs provide the capabilities of connecting up to 1024 ultrasound channels with a single FPGA and the newest JESD204B interface analog front end (AFE). This channel count is much more than the channel count needed by current linear arrays, which normally have 128 or 256 channels. With the proposed method, a sustainable average beamforming rate of 4.83 G samples/second in terms of input raw RF sample was achieved. The resulting image quality of the proposed beamformer was compared with the software beamformer on the Verasonics Vantage system for both phantom imaging and in vivo imaging of a mouse brain. Multiple imaging schemes including B-mode, power Doppler and ULM were assessed to verify that the image quality was not compromised for speed.

Localization Free Super-Resolution Microbubble Velocimetry Using a Long Short-Term Memory Neural Network.

Ultrasound localization microscopy is a super-resolution imaging technique that exploits the unique characteristics of contrast microbubbles to side-step the fundamental trade-off between imaging resolution and penetration depth. However, the conventional reconstruction technique is confined to low microbubble concentrations to avoid localization and tracking errors. Several research groups have introduced sparsity- and deep learning-based approaches to overcome this constraint to extract useful vascular structural information from overlapping microbubble signals, but these solutions have not been demonstrated to produce blood flow velocity maps of the microcirculation. Here, we introduce Deep-SMV, a localization free super-resolution microbubble velocimetry technique, based on a long short-term memory neural network, that provides high imaging speed and robustness to high microbubble concentrations, and directly outputs blood velocity measurements at a super-resolution. Deep-SMV is trained efficiently using microbubble flow simulation on real in vivo vascular data and demonstrates real-time velocity map reconstruction suitable for functional vascular imaging and pulsatility mapping at super-resolution. The technique is successfully applied to a wide variety of imaging scenarios, include flow channel phantoms, chicken embryo chorioallantoic membranes, and mouse brain imaging. An implementation of Deep-SMV is openly available at https://github.com/chenxiptz/SR_microvessel_velocimetry, with two pre-trained models available at https://doi.org/10.7910/DVN/SECUFD.

High Volume Rate 3-D Ultrasound Imaging Using Fast-Tilting and Redirecting Reflectors.

3-D ultrasound imaging has many advantages over 2-D imaging such as more comprehensive tissue evaluation and less operator dependence. Although many 3-D ultrasound imaging techniques have been developed in the last several decades, a low-cost and accessible solution with high imaging volume rate and imaging quality remains elusive. Recently we proposed a new, high volume rate 3-D ultrasound imaging technique: Fast Acoustic Steering via Tilting Electromechanical Reflectors (FASTER), which uses a water-immersible and fast-tilting acoustic reflector to steer ultrafast plane waves in the elevational direction to achieve high volume rate 3-D ultrasound imaging with conventional 1-D array transducers. However, the initial implementation of FASTER imaging only involves a single fast-tilting acoustic reflector, which is inconvenient to use because the probe cannot be held in the regular upright position. Also, conventional FASTER imaging can only be performed inside a water tank because of the necessity of using water for acoustic conduction. To address these limitations of conventional FASTER, here we developed a novel ultrasound probe clip-on device that encloses a fast-tilting reflector, a redirecting reflector, and an acoustic wave conduction medium. The new FASTER 3-D imaging device can be easily attached to or removed from clinical ultrasound transducers, allowing rapid transformation from 2-D to 3-D ultrasound imaging. In vitro B-mode imaging studies demonstrated that the proposed method provided comparable imaging quality (e.g., spatial resolution and contrast-to-noise ratio) to conventional, mechanical-translation-based 3-D imaging while providing a much faster 3-D volume rate (e.g., 300 Hz vs ∻10 Hz). In addition to B-mode imaging, we also demonstrated 3-D power Doppler imaging and 3-D super-resolution ultrasound localization microscopy with the newly developed FASTER device. An in vivo imaging study showed that the FASTER device could clearly visualize the 3-D anatomy of the basilic vein of a healthy volunteer, and customized beamforming was implemented to accommodate the speed of sound difference between the acoustic medium and the imaging object (e.g., soft tissue). These results suggest that the newly developed redirecting reflector and the clip-on device could overcome key hurdles for future clinical translation of the FASTER 3-D imaging technology.

Curvelet Transform-Based Sparsity Promoting Algorithm for Fast Ultrasound Localization Microscopy.

Ultrasound localization microscopy (ULM) based on microbubble (MB) localization was recently introduced to overcome the resolution limit of conventional ultrasound. However, ULM is currently challenged by the requirement for long data acquisition times to accumulate adequate MB events to fully reconstruct vasculature. In this study, we present a curvelet transform-based sparsity promoting (CTSP) algorithm that improves ULM imaging speed by recovering missing MB localization signal from data with very short acquisition times. CTSP was first validated in a simulated microvessel model, followed by the chicken embryo chorioallantoic membrane (CAM), and finally, in the mouse brain. In the simulated microvessel study, CTSP robustly recovered the vessel model to achieve an 86.94% vessel filling percentage from a corrupted image with only 4.78% of the true vessel pixels. In the chicken embryo CAM study, CTSP effectively recovered the missing MB signal within the vasculature, leading to marked improvement in ULM imaging quality with a very short data acquisition. Taking the optical image as reference, the vessel filling percentage increased from 2.7% to 42.2% using 50ms of data acquisition after applying CTSP. CTSP used 80% less time to achieve the same 90% maximum saturation level as compared with conventional MB localization. We also applied CTSP on the microvessel flow speed maps and found that CTSP was able to use only 1.6s of microbubble data to recover flow speed images that have similar qualities as those constructed using 33.6s of data. In the mouse brain study, CTSP was able to reconstruct the majority of the cerebral vasculature using 1-2s of data acquisition. Additionally, CTSP only needed 3.2s of microbubble data to generate flow velocity maps that are comparable to those using 129.6s of data. These results suggest that CTSP can facilitate fast and robust ULM imaging especially under the circumstances of inadequate microbubble localizations.

Deep Learning-Based Microbubble Localization for Ultrasound Localization Microscopy.

Ultrasound localization microscopy (ULM) is an emerging vascular imaging technique that overcomes the resolution-penetration compromise of ultrasound imaging. Accurate and robust microbubble (MB) localization is essential for successful ULM. In this study, we present a deep learning (DL)-based localization technique that uses both Field-II simulation and in vivo chicken embryo chorioallantoic membrane (CAM) data for training. Both radio frequency (RF) and in-phase and quadrature (IQ) data were tested in this study. The simulation experiment shows that the proposed DL-based localization was able to reduce both missing MB localization rate and MB localization error. In general, RF data showed better performance than IQ. For the in vivo CAM study with high MB concentration, DL-based localization was able to reduce the vessel MB saturation time by more than 50% compared to conventional localization. In addition, we propose a DL-based framework for real-time visualization of the high-resolution microvasculature. The findings of this article support the use of DL for more robust and faster MB localization, especially under high MB concentrations. The results indicate that further improvement could be achieved by incorporating temporal information of the MB data.

A Review of Clinical Applications for Super-resolution Ultrasound Localization Microscopy.

Microvascular structure and hemodynamics are important indicators for the diagnosis and assessment of many diseases and pathologies. The structural and functional imaging of tissue microvasculature in vivo is a clinically significant objective for the development of many imaging modalities. Contrast-enhanced ultrasound (CEUS) is a popular clinical tool for characterizing tissue microvasculature, due to the moderate cost, wide accessibility, and absence of ionizing radiation of ultrasound. However, in practice, it remains challenging to demonstrate microvasculature using CEUS, due to the resolution limit of conventional ultrasound imaging. In addition, the quantification of tissue perfusion by CEUS remains hindered by high operator-dependency and poor reproducibility. Inspired by super-resolution optical microscopy, super-resolution ultrasound localization microscopy (ULM) was recently developed. ULM uses the same ultrasound contrast agent (i.e. microbubbles) in CEUS. However, different from CEUS, ULM uses the location of the microbubbles to construct images, instead of using the backscattering intensity of microbubbles. Hence, ULM overcomes the classic compromise between imaging resolution and penetration, allowing for the visualization of capillary-scale microvasculature deep within tissues. To date, many in vivo ULM results have been reported, including both animal (kidney, brain, spinal cord, xenografted tumor, and ear) and human studies (prostate, tibialis anterior muscle, and breast cancer tumors). Furthermore, a variety of useful biomarkers have been derived from using ULM for different preclinical and clinical applications. Due to the high spatial resolution and accurate blood flow speed estimation (approximately 1 mm/s to several cm/s), ULM presents as an enticing alternative to CEUS for characterizing tissue microvasculature in vivo. This review summarizes the principles and present applications of CEUS and ULM, and discusses areas where ULM can potentially provide a better alternative to CEUS in clinical practice and areas where ULM may not be a better alternative. The objective of the study is to provide clinicians with an up-to-date review of ULM technology, and a practical guide for implementing ULM in clinical research and practice.

Aging-related cerebral microvascular changes visualized using ultrasound localization microscopy in the living mouse.

Aging-related cognitive decline is an emerging health crisis; however, no established unifying mechanism has been identified for the cognitive impairments seen in an aging population. A vascular hypothesis of cognitive decline has been proposed but is difficult to test given the requirement of high-fidelity microvascular imaging resolution with a broad and deep brain imaging field of view, which is restricted by the fundamental trade-off of imaging penetration depth and resolution. Super-resolution ultrasound localization microscopy (ULM) offers a potential solution by exploiting circulating microbubbles to achieve a vascular resolution approaching the capillary scale without sacrificing imaging depth. In this report, we apply ULM imaging to a mouse model of aging and quantify differences in cerebral vascularity, blood velocity, and vessel tortuosity across several brain regions. We found significant decreases in blood velocity, and significant increases in vascular tortuosity, across all brain regions in the aged cohort, and significant decreases in blood volume in the cerebral cortex. These data provide the first-ever ULM measurements of subcortical microvascular dynamics in vivo within the context of the aging brain and reveal that aging has a major impact on these measurements.

Three-Dimensional Shear Wave Elastography Using a 2D Row Column Addressing (RCA) Array.

Objective. To develop a 3D shear wave elastography (SWE) technique using a 2D row column addressing (RCA) array, with either external vibration or acoustic radiation force (ARF) as the shear wave source. Impact Statement. The proposed method paves the way for clinical translation of 3D SWE based on the 2D RCA, providing a low-cost and high volume rate solution that is compatible with existing clinical systems. Introduction. SWE is an established ultrasound imaging modality that provides a direct and quantitative assessment of tissue stiffness, which is significant for a wide range of clinical applications including cancer and liver fibrosis. SWE requires high frame rate imaging for robust shear wave tracking. Due to the technical challenges associated with high volume rate imaging in 3D, current SWE techniques are typically confined to 2D. Advancing SWE from 2D to 3D is significant because of the heterogeneous nature of tissue, which demands 3D imaging for accurate and comprehensive evaluation. Methods. A 3D SWE method using a RCA array was developed with a volume rate up to 2000 Hz. The performance of the proposed method was systematically evaluated on tissue-mimicking elasticity phantoms and in an in vivo case study. Results. 3D shear wave motion induced by either external vibration or ARF was successfully detected with the proposed method. Robust 3D shear wave speed maps were reconstructed for phantoms and in vivo. Conclusion. The high volume rate 3D imaging provided by the 2D RCA array provides a robust and practical solution for 3D SWE with a clear pathway for future clinical translation.

Pixel-Oriented Adaptive Apodization for Plane-Wave Imaging Based on Recovery of the Complete Dataset.

In theory, coherent plane-wave compounding (CPWC) enables ultrafast ultrasound imaging while maintaining a high imaging quality that is comparable to conventional B-mode imaging based on focused beam transmissions. However, in practice, due to the imperfect synthetization of transmit focusing (e.g., heterogeneous speed of sound in tissue and limited range of steering angle), CPWC suffers from a variety of imaging artifacts resulting from side lobes, grating lobes, and axial lobes. This study focuses on addressing the issues of axial lobes for CPWC, which constitutes an important source of clutter that leads to the degradation of contrast ratio and contrast-to-noise ratio (CR and CNR) of CPWC. We first investigated the source of the axial lobes based on plane-wave propagation and the delay-and-sum (DAS) beamforming. We then proposed a new method that is based on pixel-oriented adaptive apodization (POAA) to eliminate the axial lobes throughout the entire field of view (FOV). POAA was first validated in a simulation study, followed by in vitro phantom experiments and an in vivo case study on a carotid artery from a healthy volunteer. In the simulation study, suppression of axial lobes by 120 dB was observed from wire targets, and an improvement of CNR by up to 60% was found in a cyst-mimicking digital phantom. In the phantom experiment, POAA showed an improvement in CNR by around 20% over conventional methods. The effectiveness of axial lobe suppression was finally demonstrated in vivo, where POAA showed a substantial suppression of clutters throughout the entire FOV.

Dietary tomato inhibits angiogenesis in TRAMP prostate cancer but is not protective with a Western-style diet in this pilot study.

Prostate cancer (PCa) remains the second most diagnosed cancer worldwide. Higher body weight is associated with chronic inflammation, increased angiogenesis, and treatment-resistant tumor phenotypes. Dietary tomato reduces PCa risk, which may be due to tomato inhibition of angiogenesis and disruption of androgen signaling. This pilot study investigated the interplay between tomato powder (TP), incorporated into control (CON) and obesogenic (OB) diets, and PCa tumor growth and blood perfusion over time in a transgenic model of PCa (TRAMP). Ultrasound microvessel imaging (UMI) results showed good agreement with gold-standard immunohistochemistry quantification of endothelial cell density, indicating that this technique can be applied to non-invasively monitor tumor blood perfusion in vivo. Greater body weight was positively associated with tumor growth. We also found that TP significantly inhibited prostate tumor angiogenesis but that this inhibition differentially affected measured outcomes depending on CON or OB diets. TP led to reduced tumor growth, intratumoral inflammation, and intratumoral androgen-regulated gene expression (srd5a1, srd5a2) when incorporated with the CON diet but greater tumor growth and intratumoral gene expression when incorporated with the OB diet. Results from this study show that protective benefits from dietary tomato are lost, or may become deleterious, when combined with a Western-style diet.

Super-Resolution Ultrasound Localization Microscopy on a Rabbit Liver VX2 Tumor Model: An Initial Feasibility Study.

Ultrasound localization microscopy can image microvasculature in vivo without sacrificing imaging penetration depth. However, the reliance on super-resolution inference limits the applicability of the technique because subpixel tissue motion can corrupt microvascular reconstruction. Consequently, the majority of previous pre-clinical research on this super-resolution procedure has been restricted to low-motion experimental models with ample motion correction or data rejection, which precludes the imaging of organ sites that exhibit a high degree of respiratory and other motion. In this article, we present a novel anesthesia protocol in rabbits that induces safe, controllable periods of apnea to enable the long image-acquisition times required for ultrasound localization microscopy. We apply this protocol to a VX2 liver tumor model undergoing sorafenib therapy and compare the results to super-resolution images from conventional high-dose isoflurane anesthesia. We find that the apneic protocol was necessary to correctly identify the poorly vascularized tumor cores, as verified by immunohistochemistry, and to reveal the tumoral microvascular architecture.

Improved Ultrasound Microvessel Imaging Using Deconvolution with Total Variation Regularization.

Singular value decomposition-based clutter filters can robustly reject tissue clutter, allowing for detection of slow blood flow in imaging microvasculature. However, to identify microvessels, high ultrasound frequency must be used to increase the spatial resolution at the expense of shorter depth of penetration. Deconvolution using Tikhonov regularization is an imaging processing method widely used to improve spatial resolution. The ringing artifact of Tikhonov regularization, though, can produce image artifacts such as non-existent microvessels, which degrade image quality. Therefore, a deconvolution method using total variation is proposed in this study to improve spatial resolution and mitigate the ringing artifact. Performance of the proposed method was evaluated using chicken embryo brain, ex ovo chicken embryo chorioallantoic membrane and tumor data. Results revealed that the reconstructed power Doppler (PD) images are substantially improved in spatial resolution compared with original PD images: the full width half-maximum (FWHM) of the cross-sectional profile of a microvessel was improved from 132 to 83 µm. Two neighboring microvessels that were 154 µm apart were better separated using the proposed method than conventional PD imaging. Additionally, 223 FWHMs measured from the cross-sectional profiles of 223 vessels were used to determine the improvement in FWHM with the proposed method statistically. The mean ± standard deviation of the FWHM without and with the proposed method was 233.19 ± 85.08 and 172.31 ± 75.11 µm, respectively; the maximum FWHM without and with the proposed method was 693.01 and 668.69 µm; and the minimum FWHM without and with the proposed method was 73.92 and 45.74 µm. There were statistically significant differences between FWHMs with and without the proposed method according to the rank-sum test, p < 0.0001. The contrast-to-noise ratio improved from 1.06 to 4.03 dB with use of the proposed method. We also compared the proposed method with Tikhonov regularization using ex ovo chicken embryo chorioallantoic membrane data. We found that the proposed method outperformed Tikhonov regularization as false microvessels appeared using the Tikhonov regularization but not with the proposed method. These results indicate that the proposed method is capable of providing more robust PD images with higher spatial resolution and higher contrast-to-noise ratio.