Publications by authors named "Kenneth Hoyt"

69 Publications

Three-dimensional visualization and improved quantification with super-resolution ultrasound imaging - validation framework for analysis of microvascular morphology using a chicken embryo model.

Phys Med Biol 2021 Mar 25. Epub 2021 Mar 25.

Bioengineering, The University of Texas at Dallas, Richardson, Texas, UNITED STATES.

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 (VOI) in 90 μm step increments. CEUS images were collected at each increment and stored as in-phase/quadrature (IQ) 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 quantification and for surface rendering. Vessel diameter 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.
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http://dx.doi.org/10.1088/1361-6560/abf203DOI Listing
March 2021

Multiparametric ultrasound imaging for the assessment of normal versus steatotic livers.

Sci Rep 2021 Jan 29;11(1):2655. Epub 2021 Jan 29.

Department of Bioengineering, University of Texas at Dallas, BSB 13.929, 800 W Campbell Rd, Richardson, TX, 75080, USA.

Liver disease is increasing in prevalence across the globe. We present here a multiparametric ultrasound (mpUS) imaging approach for assessing nonalcoholic fatty liver disease (NALFD). This study was performed using rats (N = 21) that were fed either a control or methionine and choline deficient (MCD) diet. A mpUS imaging approach that includes H-scan ultrasound (US), shear wave elastography, and contrast-enhanced US measurements were then performed at 0 (baseline), 2, and 6 weeks. Thereafter, animals were euthanized and livers excised for histological processing. A support vector machine (SVM) was used to find a decision plane that classifies normal and fatty liver conditions. In vivo mpUS results from control and MCD diet fed animals reveal that all mpUS measures were different at week 6 (P < 0.05). Principal component analysis (PCA) showed that the H-scan US data contributed the highest percentage to the classification among the mpUS measurements. The SVM resulted in 100% accuracy for classification of normal and high fat livers and 92% accuracy for classification of normal, low fat, and high fat livers. Histology findings found considerable steatosis in the MCD diet fed animals. This study suggests that mpUS examinations have the potential to provide a comprehensive estimation of the main components of early stage NAFLD.
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http://dx.doi.org/10.1038/s41598-021-82153-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7846566PMC
January 2021

Ultrasound Sensing Can Improve Continuous Classification of Discrete Ambulation Modes Compared to Surface Electromyography.

IEEE Trans Biomed Eng 2021 Apr 18;68(4):1379-1388. Epub 2021 Mar 18.

Clinical translation of "intelligent" lower-limb assistive technologies relies on robust control interfaces capable of accurately detecting user intent. To date, mechanical sensors and surface electromyography (EMG) have been the primary sensing modalities used to classify ambulation. Ultrasound (US) imaging can be used to detect user-intent by characterizing structural changes of muscle. Our study evaluates wearable US imaging as a new sensing modality for continuous classification of five discrete ambulation modes: level, incline, decline, stair ascent, and stair descent ambulation, and benchmarks performance relative to EMG sensing. Ten able-bodied subjects were equipped with a wearable US scanner and eight unilateral EMG sensors. Time-intensity features were recorded from US images of three thigh muscles. Features from sliding windows of EMG signals were analyzed in two configurations: one including 5 EMG sensors on muscles around the thigh, and another with 3 additional sensors placed on the shank. Linear discriminate analysis was implemented to continuously classify these phase-dependent features of each sensing modality as one of five ambulation modes. US-based sensing statistically improved mean classification accuracy to 99.8% (99.5-100% CI) compared to 8-EMG sensors (85.8%; 84.0-87.6% CI) and 5-EMG sensors (75.3%; 74.5-76.1% CI). Further, separability analyses show the importance of superficial and deep US information for stair classification relative to other modes. These results are the first to demonstrate the ability of US-based sensing to classify discrete ambulation modes, highlighting the potential for improved assistive device control using less widespread, less superficial and higher resolution sensing of skeletal muscle.
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http://dx.doi.org/10.1109/TBME.2020.3032077DOI Listing
April 2021

Use of Sonomyographic Sensing to Estimate Knee Angular Velocity During Varying Modes of Ambulation.

Annu Int Conf IEEE Eng Med Biol Soc 2020 07;2020:3799-3802

Ultrasound (US) imaging of muscle has been introduced as a promising sensing modality for assistive device control. Ten able-bodied subjects completed level, incline and decline walking on a treadmill in a motion capture laboratory while wearing reflective markers on upper- and lower-body. A wearable US transducer was affixed to subjects' anterior thigh, and time-intensity features were extracted from transverse US images of the knee extensor muscles. These features were used to train and test Gaussian process regression models for continuous estimation of knee flexion/extension angular velocity. Four regression models were evaluated: (1) subject-dependent/task-specific, (2) subject-dependent/pooled-tasks, (3) subject-independent/task-specific, and (4) subject-independent/pooled-tasks. Subject-independent models were "tuned" with up to six strides of the test subject's data to boost performance. A two-factor analysis of variance test was used to assess the effect of each approach on root mean square error (RMSE) of estimated knee angular velocity (α=0.05). Statistical parametric mapping (SPM) was completed to compare actual vs. estimated knee angular velocity as a function of the gait cycle (α=0.05). For incline and level walking, the subject-dependent/pooled-tasks model resulted in the lowest error while the subject-dependent/task-specific model resulted in the lowest error for decline walk. Impressively, the two-factor test revealed no difference between task-specific and pooled-task models. Furthermore, despite capturing many important features of knee velocity across individuals there were, as expected, significant differences between subject-dependent and subject-independent models. Collectively, these results are promising for potential assistive device control with error rates <10% for all regression models that were tested.Clinical Relevance-This work is the first study to demonstrate the feasibility of using ultrasound-based sensing for estimation of knee angular velocity during multiple modes of ambulation.
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http://dx.doi.org/10.1109/EMBC44109.2020.9176674DOI Listing
July 2020

Evaluating Microelectrode Arrays in Peripheral Nerve Using Micro Computed Tomography

Annu Int Conf IEEE Eng Med Biol Soc 2020 07;2020:3432-3435

Many advances have been made with imaging of implanted neural devices; however, the ability to image whole nerve samples remains limited. Further, few imaging modalities are well suited for visualizing both whole devices in vivo and individual microelectrodes within a nerve. In this study, we used micro-computed tomography (micro-CT) to evaluate Wireless Floating Microelectrode Arrays (WMFAs) implanted in rat sciatic nerve at the level of whole devices and individual electrodes. WFMAs were also used to track selective recruitment of plantar flexion and dorsiflexion of the rear paw, which was achieved by each implanted device (n=6) during chronic implantation. Evoked limb motion was correlated to end-of-study assessments using micro-CT to visualize electrode locations within the fascicular structure of the sciatic nerve. Results of this study show that micro-CT imaging can provide valuable assessments of microelectrode arrays implanted in peripheral nerves for both whole devices visualized in vivo and individual electrodes visualized in whole nerve tissue samples.Clinical relevance- This work informs the use of micro-computed tomography as a tool for correlating neural device performance with physical attributes of the implant location.
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http://dx.doi.org/10.1109/EMBC44109.2020.9176598DOI Listing
July 2020

Simultaneous Evalulation of Contrast Pulse Sequences for Super-Resolution Ultrasound Imaging - Preliminary In Vitro and In Vivo Results.

Annu Int Conf IEEE Eng Med Biol Soc 2020 07;2020:2121-2124

Super-resolution ultrasound imaging (SR-US) has enabled a tenfold improvement in resolution of the microvasculature with clinical application in many disease processes such as cancer, diabetes and cardiovascular disease. Plane wave ultrasound (US) platforms in turn are capable of the very high frame rates needed to track microbubble (MB) contrast agents used in SR-US. Both B-mode US imaging and contrast enhanced US imaging (CEUS) have been effectively used in SR-US, with B-mode US having higher signal-to-noise ratio (SNR) and CEUS providing higher contrast-to-tissue ratio (CTR). Lengthy imaging time needed for SR-US to allow perfusion and MB detection is an impediment to clinical adoption. Both SNR and CTR improvements can enhance SR-US imaging by enhancing the detection of MBs thus reducing imaging time. This study simultaneously evaluated nonlinear contrast pulse sequences (CPS) employing different amplitude modulation (AM) and pulse inversion (PI) nonlinear CEUS imaging techniques as well as combinations of the two, (AMPI) with B-mode US imaging. The objective was to improve the detection rate of MB during SR-US. Imaging was performed in vitro and in vivo in the rat hind limb using a Vantage 256 research scanner (Verasonics Inc.). Comparisons of four CPS compositions with B-mode US imaging was made based on the number of MB detected and localized in SR-US images. The use of a PI nonlinear CEUS imaging strategy improved SR-US imaging by increasing the number of MB detected in a sequence of frames by an average of 28.3% and up to 52.6% over a B-mode US imaging strategy, which would decrease imaging time accordingly.
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http://dx.doi.org/10.1109/EMBC44109.2020.9176087DOI Listing
July 2020

Multifocused Ultrasound Therapy for Controlled Microvascular Permeabilization and Improved Drug Delivery.

IEEE Trans Ultrason Ferroelectr Freq Control 2021 Apr 26;68(4):961-968. Epub 2021 Mar 26.

Focused ultrasound (FUS) exposure of micro-bubble (MB) contrast agents can transiently increase microvascular permeability allowing anticancer drugs to extravasate into a targeted tumor tissue. Either fixed or mechanically steered in space, most studies to date have used a single element focused transducer to deliver the ultrasound (US) energy. The goal of this study was to investigate various multi-FUS strategies implemented on a programmable US scanner (Vantage 256, Verasonics Inc.) equipped with a linear array for image guidance and a 128-element therapy transducer (HIFUPlex-06, Sonic Concepts). The multi-FUS strategies include multi-FUS with sequential excitation (multi-FUS-SE) and multi-FUS with temporal sequential excitation (multi-FUS-TSE) and were compared to single-FUS and sham treatment. This study was performed using athymic mice implanted with breast cancer cells ( N = 20 ). FUS therapy experiments were performed for 10 min after a solution containing MBs (Definity, Lantheus Medical Imaging Inc.) and near-infrared (NIR, surrogate drug) dye were injected via the tail vein. The fluorescent signal was monitored using an in vivo optical imaging system (Pearl Trilogy, LI-COR) to quantify intratumoral dye accumulation at baseline and again at 0.1, 24, and 48 h after receiving US therapy. Animals were then euthanized for ex vivo dye extraction analysis. At 48 h, fluorescent tracer accumulation within the tumor space for the multi-FUS-TSE therapy group animals was found to be 67.3%, 50.3%, and 36.2% higher when compared to sham, single-FUS, and multi-FUS-SE therapy group measures, respectively. Also, dye extraction and fluorescence measurements from excised tumor tissue found increases of 243.2%, 163.1%, and 68.1% for the multi-FUS-TSE group compared to sham, single-FUS, and multi-FUS-SE therapy group measures, respectively. In summary, experimental results revealed that for a multi-FUS sequence, increased microvascular permeability was considerably influenced by both the spatial and temporal aspects of the applied US therapy.
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http://dx.doi.org/10.1109/TUFFC.2020.3026697DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034541PMC
April 2021

Ultrasound Features of Skeletal Muscle Can Predict Kinematics of Upcoming Lower-Limb Motion.

Ann Biomed Eng 2021 Feb 21;49(2):822-833. Epub 2020 Sep 21.

Department of Bioengineering, The University of Texas at Dallas, Richardson, TX, 75080, USA.

Seamless integration of lower-limb assistive devices with the human body requires an intuitive human-machine interface, which would benefit from predicting the intent of individuals in advance of the upcoming motion. Ultrasound imaging was recently introduced as an intuitive sensing interface. The objective of the present study was to investigate the predictability of joint kinematics using ultrasound features of the rectus femoris muscle during a non-weight-bearing knee extension/flexion. Motion prediction accuracy was evaluated in 67 ms increments, up to 600 ms in time. Statistical analysis was used to evaluate the feasibility of motion prediction, and the linear mixed-effects model was used to determine a prediction time window where the joint angle prediction error is barely perceivable by the sample population, hence clinically reliable. Surprisingly, statistical tests revealed that the prediction accuracy of the joint angle was more sensitive to temporal shifts than the accuracy of the joint angular velocity prediction. Overall, predictability of the upcoming joint kinematics using ultrasound features of skeletal muscle was confirmed, and a time window for a statistically and clinically reliable prediction was found between 133 and 142 ms. A reliable prediction of user intent may provide the time needed for processing, control planning, and actuation of the assistive devices at critical points during ambulation, contributing to the intuitive behavior of lower-limb assistive devices.
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http://dx.doi.org/10.1007/s10439-020-02617-7DOI Listing
February 2021

3-D H-Scan Ultrasound Imaging and Use of a Convolutional Neural Network for Scatterer Size Estimation.

Ultrasound Med Biol 2020 Oct 9;46(10):2810-2818. Epub 2020 Jul 9.

Department of Bioengineering, University of Texas at Dallas, Richardson, TX, USA; Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Electrical and Computer Engineering, University of Texas at Dallas, Richardson, TX, USA. Electronic address:

H-Scan ultrasound (US) is a new imaging technology that estimates the relative size of acoustic scattering objects and structures. The purpose of this study was to introduce a three-dimensional (3-D) H-scan US imaging approach for scatterer size estimation in volume space. Using a programmable research scanner (Vantage 256, Verasonics Inc, Kirkland, WA, USA) equipped with a custom volumetric imaging transducer (4 DL7, Vermon, Tours, France), raw radiofrequency (RF) data was collected for offline processing to generate H-scan US volumes. A deep convolutional neural network (CNN) was modified and used to achieve voxel mapping from the input H-scan US image to underlying scatterer size. Preliminary studies were conducted using homogeneous gelatin-based tissue-mimicking phantom materials embedded with acoustic scatterers of varying size (15 to 250 μm) and concentrations (0.1 to 1%). Two additional phantoms were embedded with 63 or 125 µm-sized microspheres and used to test CNN estimation accuracy. In vitro results indicate that 3-D H-scan US imaging can visualize the spatial distribution of acoustic scatterers of varying size at different concentrations (R > 0.85, p < 0.03). The result of scatterer size estimation reveals that a CNN can achieve an average mapping accuracy of 93.3%. Overall, our preliminary in vitro findings reveal that 3-D H-scan US imaging allows the visualization of tissue scatterer patterns and incorporation of a CNN can be used to help estimate size of the acoustic scattering objects.
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http://dx.doi.org/10.1016/j.ultrasmedbio.2020.06.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7484237PMC
October 2020

Tumor Vascular Networks Depicted in Contrast-Enhanced Ultrasound Images as a Predictor for Transarterial Chemoembolization Treatment Response.

Ultrasound Med Biol 2020 Sep 16;46(9):2276-2286. Epub 2020 Jun 16.

Department of Bioengineering, University of Texas at Dallas, Richardson, Texas, USA. Electronic address:

Hepatocellular carcinoma (HCC) is prevalent worldwide. Among the various therapeutic options, transarterial chemoembolization (TACE) can be applied to the tumor vascular network by restricting the nutrients and oxygen supply to the tumor. Unique morphologic properties of this network may provide information predictive of future therapeutic responses, which would be significant for decision making during treatment planning. The extraction of morphologic features from the tumor vascular network depicted in abdominal contrast-enhanced ultrasound (CEUS) images faces several challenges, such as organ motion, limited resolution caused by clutter signal and segmentation of the vascular structures at multiple scales. In this study, we present an image processing and analysis approach for the prediction of HCC response to TACE treatment using clinical CEUS images and known pathologic responses. This method focuses on addressing the challenges of CEUS by incorporating a two-stage motion correction strategy, clutter signal removal, vessel enhancement at multiple scales and machine learning for predictive modeling. The morphologic features, namely, number of vessels (NV), number of bifurcations (NB), vessel to tissue ratio (VR), mean vessel length, tortuosity and diameter, from tumor architecture were quantified from CEUS images of 36 HCC patients before TACE treatment. Our analysis revealed that NV, NB and VR are the dominant features for the prediction of long-term TACE response. The model had an accuracy of 86% with a sensitivity and specificity of 89% and 82%, respectively. Reliable prediction of the TACE therapy response using CEUS-derived image features may help to provide personalized therapy planning, which will ultimately improve patient outcomes.
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http://dx.doi.org/10.1016/j.ultrasmedbio.2020.05.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725382PMC
September 2020

Multiscale and morphological analysis of microvascular patterns depicted in contrast-enhanced ultrasound images.

J Med Imaging (Bellingham) 2020 May 2;7(3):034001. Epub 2020 Jun 2.

University of Texas at Dallas, Department of Bioengineering, Richardson, Texas, United States.

Impaired insulin-induced microvascular recruitment in skeletal muscle contributes to insulin resistance in type 2 diabetic disease. Previously, quantification of microvascular recruitment at the capillary level has been performed with either the full image or manually selected region-of-interests. These subjective approaches are imprecise, time-consuming, and unsuitable for automated processes. Here, an automated multiscale image processing approach was performed by defining a vessel diameter threshold for an objective and reproducible analysis at the microvascular level. A population of C57BL/6J male mice fed standard chow and studied at age 13 to 16 weeks comprised the lean group and 24- to 31-week-old mice who received a high-fat diet were designated the obese group. A clinical ultrasound scanner (Acuson Sequoia 512) equipped with an 15L8-S linear array transducer was used in a nonlinear imaging mode for sensitive detection of an intravascular microbubble contrast agent. By eliminating large vessels from the dynamic contrast-enhanced ultrasound (DCE-US) images (above in diameter), obesity-related changes in perfusion and morphology parameters were readily detected in the smaller vessels, which are known to have a greater impact on skeletal muscle glucose disposal. The results from the DCE-US images including all of the vessels were compared for three different-sized vessel groups, namely, vessels smaller than 300, 200, and in diameter. Our automated image processing provides objective and reproducible results by focusing on a particular size of vessel, thereby allowing for a selective evaluation of longitudinal changes in microvascular recruitment for a specific-sized vessel group between diseased and healthy microvascular networks.
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http://dx.doi.org/10.1117/1.JMI.7.3.034001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7265038PMC
May 2020

Deep Learning of Spatiotemporal Filtering for Fast Super-Resolution Ultrasound Imaging.

IEEE Trans Ultrason Ferroelectr Freq Control 2020 09 15;67(9):1820-1829. Epub 2020 Apr 15.

Super-resolution ultrasound (SR-US) imaging is a new technique that breaks the diffraction limit and allows visualization of microvascular structures down to tens of micrometers. The image processing methods for the spatiotemporal filtering needed in SR-US, such as singular value decomposition (SVD), are computationally burdensome and performed offline. Deep learning has been applied to many biomedical imaging problems, and trained neural networks have been shown to process an image in milliseconds. The goal of this study was to evaluate the effectiveness of deep learning to realize a spatiotemporal filter in the context of SR-US processing. A 3-D convolutional neural network (3DCNN) was trained on in vitro and in vivo data sets using SVD as ground truth in tissue clutter reduction. In vitro data were obtained from a tissue-mimicking flow phantom, and in vivo data were collected from murine tumors of breast cancer. Three training techniques were studied: training with in vitro data sets, training with in vivo data sets, and transfer learning with initial training on in vitro data sets followed by fine-tuning with in vivo data sets. The neural network trained with in vitro data sets followed by fine-tuning with in vivo data sets had the highest accuracy at 88.0%. The SR-US images produced with deep learning allowed visualization of vessels as small as [Formula: see text] in diameter, which is below the diffraction limit (wavelength of [Formula: see text] at 14 MHz). The performance of the 3DCNN was encouraging for real-time SR-US imaging with an average processing frame rate for in vivo data of 51 Hz with GPU acceleration.
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http://dx.doi.org/10.1109/TUFFC.2020.2988164DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7523282PMC
September 2020

Contrast-enhanced ultrasound imaging using pulse inversion spectral deconvolution.

J Acoust Soc Am 2019 10;146(4):2466

Department of Bioengineering, University of Texas at Dallas, Richardson, Texas 75080, USA.

A contrast-enhanced ultrasound (CEUS) imaging approach, termed pulse inversion spectral deconvolution (PISD), is introduced. The approach uses two Gaussian-weighted Hermite polynomials to form two inverted pulse sequences. The two inversed pulses are then used to filter ultrasound (US) backscattered data and discrimination of the linear and nonlinear signal components. A research US scanner equipped with a linear array transducer was used for data acquisition. The receive data from all channels are shaped using plane wave imaging beamforming with angular compounding (from one to nine angles). In vitro data was collected with a tissue mimicking flow phantom perfused with an US contrast agent using PISD and traditional nonlinear (NLI) US imaging as comparison. The role of imaging frequency (between 4.5 and 6.25 MHz) and mechanical index (from 0.1 to 0.3) were evaluated. Preliminary in vivo data was collected in the hindlimb of three healthy mice. Preliminary experimental findings indicate that the PISD contrast-to-tissue ratio was improved nearly ten times compared to the NLI US imaging approach. Also, the spatial resolution was improved due to the effect of deconvolution and spatial angular compounding. Overall, PISD is a promising postprocessing technique for real-time CEUS imaging.
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http://dx.doi.org/10.1121/1.5129115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6794155PMC
October 2019

Adaptive attenuation correction during H-scan ultrasound imaging using K-means clustering.

Ultrasonics 2020 Mar 23;102:105987. Epub 2019 Aug 23.

Department of Biomedical Engineering, University of Texas at Dallas, Richardson, TX, USA; Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA. Electronic address:

H-scan ultrasound (US) imaging (where the 'H' stands for Hermite) is a novel non-invasive, low cost and real-time technology. Like traditional US, H-scan US suffers from frequency-dependent attenuation that must be corrected to have acceptable image quality for tissue characterization. The goal of this research was to develop a novel attenuation correction method based on adaptive K-means clustering. To properly isolate these signals, a lateral moving window approach applied to adaptively adjust GH filters based on the changing of RF vector spectrums. Then the signal isolated via the same filter will be combined together via overlap-add technology to keep the information loss minimum. Experimental data was collected using a Verasonics 256 US scanner equipped with a L11-4v linear array transducer. In vivo data indicates that H-scan US imaging after adaptive attenuation correction can optimally re-scale the GH kernels and match to the changing spectrum undergoing attenuation (i.e. high frequency shift). This approach produces H-scan US images with more uniform spatial intensity and outperforms global attenuation correction strategies. Overall, this approach will improve the ability of H-scan US imaging to estimate acoustic scatterer size and will improve its clinical use for tissue characterization when imaging complex tissues.
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http://dx.doi.org/10.1016/j.ultras.2019.105987DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7036031PMC
March 2020

p63 and SOX2 Dictate Glucose Reliance and Metabolic Vulnerabilities in Squamous Cell Carcinomas.

Cell Rep 2019 08;28(7):1860-1878.e9

Department of Biological Sciences, The University of Texas at Dallas, Richardson, TX, USA. Electronic address:

Squamous cell carcinoma (SCC), a malignancy arising across multiple anatomical sites, is responsible for significant cancer mortality due to insufficient therapeutic options. Here, we identify exceptional glucose reliance among SCCs dictated by hyperactive GLUT1-mediated glucose influx. Mechanistically, squamous lineage transcription factors p63 and SOX2 transactivate the intronic enhancer cluster of SLC2A1. Elevated glucose influx fuels generation of NADPH and GSH, thereby heightening the anti-oxidative capacity in SCC tumors. Systemic glucose restriction by ketogenic diet and inhibiting renal glucose reabsorption with SGLT2 inhibitor precipitate intratumoral oxidative stress and tumor growth inhibition. Furthermore, reduction of blood glucose lowers blood insulin levels, which suppresses PI3K/AKT signaling in SCC cells. Clinically, we demonstrate a robust correlation between blood glucose concentration and worse survival among SCC patients. Collectively, this study identifies the exceptional glucose reliance of SCC and suggests its candidacy as a highly vulnerable cancer type to be targeted by systemic glucose restriction.
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http://dx.doi.org/10.1016/j.celrep.2019.07.027DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7048935PMC
August 2019

Gait Phase Identification During Level, Incline and Decline Ambulation Tasks Using Portable Sonomyographic Sensing.

IEEE Int Conf Rehabil Robot 2019 06;2019:988-993

Clinical viability of powered lower-limb assistive devices requires reliable and intuitive control strategies. Stance and swing are the main phases of the gait cycle across different locomotion tasks. Hence, a reliable method to accurately identify these phases can decrease sensing complexity and assist in enabling high-level control of assistive devices. Ultrasound (US) imaging has recently been introduced as a new sensing modality that may provide a solution for intuitive device control. US images of the rectus femoris and vastus intermedius muscles were collected in humans during level, incline, and decline ambulation tasks. Five low-level static (i.e. time-independent) features of US images were measured with respect to a reference image, including correlation coefficient, sum of absolute differences, structural similarity index, sum of squared differences, and image echogenicity. Time-derivatives of the static features were also calculated as temporal features. Support vector machine classifiers were trained using these static features to identify the gait phase both dependent and independent of the ambulation tasks. The results indicate an accuracy of 88.3% in identifying the gait phases for task-independent classifiers when trained using only the static features. Performance of the classifiers improved significantly to 92.8% after using the temporal features (p $\lt0.01)$. The algorithm was efficient and the average processing speed was faster than 100 Hz. This study is the first demonstration on use of US imaging to provide continuous estimates of ambulation phase, and on multiple surfaces. These findings suggest task-independent approaches may reliably identify the main phases of the gait cycle. Advancements in this area of study may provide simpler intuitive strategies for high-level assistive device control and increase their clinical relevance.
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http://dx.doi.org/10.1109/ICORR.2019.8779534DOI Listing
June 2019

Prediction of Distal Lower-Limb Motion Using Ultrasound-Derived Features of Proximal Skeletal Muscle.

IEEE Int Conf Rehabil Robot 2019 06;2019:71-76

Control of lower-limb assistive devices would benefit from predicting the intent of individuals in advance of upcoming motion, rather than estimating the current states of their motion. Human lower-limb motion estimation using ultrasound (US) image derived features of skeletal muscle has been demonstrated. However, predictability of motion in time remains an open question. The objective of this study was to assess the predictability of distal lower-limb motion using US image features of rectus femoris (RF) muscle during non-weight-bearing knee flexion/extension. A series of time shifts was introduced between the US features and the joint position in 67 ms steps from 0 ms (i.e., estimation, no prediction) up to predicting 467 ms in advance. A US-based algorithm to estimate lower-limb motion was then used to predict the knee joint position in time using the US features after introducing the time shifts. The accuracy of joint motion prediction after each time shift was compared to the accuracy of joint motion estimation. The reliability of the prediction was then assessed using an analysis of variance (ANOVA) test. The motion prediction accuracy was found to be reliable up to 200 ms, where the average root mean square error (RMSE) of prediction across 9 healthy subjects was 0.89 degrees greater than the average RMSE (7.39 degrees) of motion estimation for the same group of subjects. These findings suggest a reliable prediction of upcoming lower-limb motion is feasible using the US features of skeletal muscle up to a certain point. A reliable prediction may provide lower-limb assistive device control systems with a time-window for processing and control planning, and actuation hence improving the volitional control behaviors of lower-limb assistive devices.
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http://dx.doi.org/10.1109/ICORR.2019.8779360DOI Listing
June 2019

Formulation and Characterization of Chemically Cross-linked Microbubble Clusters.

Langmuir 2019 08 7;35(33):10977-10986. Epub 2019 Aug 7.

University of Texas at Dallas , Richardson , Texas , 75080 , United States.

The purpose of this study is to introduce a new concept of chemically cross-linked microbubble clusters (CCMCs), which are individual microbubble ultrasound contrast agents (UCAs) physically tethered together. We demonstrate a facile means of their production, characterize their size and stability, and describe how they can potentially be used in biomedical applications. By tethering UCAs together into CCMCs, we propose that novel methods of ultrasound mediated imaging and therapy can be developed through unique interbubble interactions in an ultrasound field. One of the major challenges in generating CCMCs is controlling aggregate sizes and maintaining stability against Ostwald ripening and coalescence. In this study, we demonstrate that chemically cross-linked microbubble clusters can produce small (<10 μm) quasi-stable complexes that slowly fuse into bubbles with individual gas cores. Furthermore, we demonstrate that this process can be driven with low-intensity ultrasound pulses, enabling a rapid fusion of clusters which could potentially be used to develop novel ultrasound contrast imaging and drug delivery strategies in future studies. The development of novel microbubble clusters presents a simple yet robust process for generating novel UCAs with a design that could allow for more versatility in contrast-enhanced ultrasound (CEUS), molecular imaging, and drug delivery applications. Additionally, microbubble clustering is a unique way to control size, shell, and gas compositions that can be used to study bubble ripening and coalescence in a highly controlled environment or study the behavior of mixed-microbubble populations.
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http://dx.doi.org/10.1021/acs.langmuir.9b00475DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7061884PMC
August 2019

Impact of hydrostatic pressure on phase-change contrast agent activation by pulsed ultrasound.

J Acoust Soc Am 2019 06;145(6):3457

Department of Bioengineering, University of Texas at Dallas, Richardson, Texas 75080, USA.

A phase-change contrast agent (PCCA) can be activated from a liquid (nanodroplet) state using pulsed ultrasound (US) energy to form a larger highly echogenic microbubble (MB). PCCA activation is dependent on the ambient pressure of the surrounding media, so any increase in hydrostatic pressure demands higher US energies to phase transition. In this paper, the authors explore this basic relationship as a potential direction for noninvasive pressure measurement and foundation of a unique technology the authors are developing termed tumor interstitial pressure estimation using ultrasound (TIPE-US). TIPE-US was developed using a programmable US research scanner. A custom scan sequence interleaved pulsed US transmissions for both PCCA activation and detection. An automated US pressure sweep was applied, and US images were acquired at each increment. Various hydrostatic pressures were applied to PCCA samples. Pressurized samples were imaged using the TIPE-US system. The activation threshold required to convert PCCA from the liquid to gaseous state was recorded for various US and PCCA conditions. Given the relationship between the hydrostatic pressure applied to the PCCA and US energy needed for activation, phase transition can be used as a surrogate of hydrostatic pressure. Consistent with theoretical predictions, the PCCA activation threshold was lowered with increasing sample temperature and by decreasing the frequency of US exposure, but it was not impacted by PCCA concentration.
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http://dx.doi.org/10.1121/1.5111345DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6570615PMC
June 2019

Super-Resolution Ultrasound Imaging of Skeletal Muscle Microvascular Dysfunction in an Animal Model of Type 2 Diabetes.

J Ultrasound Med 2019 Oct 31;38(10):2589-2599. Epub 2019 Jan 31.

Department of Bioengineering, University of Texas at Dallas, Richardson, Texas, USA.

Objectives: To evaluate the use of super-resolution ultrasound (SR-US) imaging for quantifying microvascular changes in skeletal muscle using a mouse model of type 2 diabetes.

Methods: Study groups were young, standard chow-fed male C57BL/6J mice (lean group) and high fat diet-fed older mice (obese group). After an overnight fast, dynamic contrast-enhanced US imaging was performed on the proximal hind limb adductor muscle group for 10 minutes at baseline and again at 1 and 2 hours during administration of a hyperinsulinemic-euglycemic clamp. Dynamic contrast-enhanced US images were collected on a clinical US scanner (Acuson Sequoia 512; Siemens Healthcare, Mountain View, CA) equipped with a 15L8 linear array transducer. Dynamic contrast-enhanced US images were processed with a spatiotemporal filter to remove tissue clutter. Individual microbubbles were localized and counted to create an SR-US image. A frame-by-frame analysis of the microbubble count was generated (ie, time-microbubble count curve [TMC]) to estimate tissue perfusion and microvascular blood flow. The conventional time-intensity curve (TIC) was also generated for comparison.

Results: In vivo SR-US imaging could delineate microvascular structures in the mouse hind limb. Compared with lean animals, insulin-induced microvascular recruitment was attenuated in the obese group. The SR-US-based TMC analysis revealed differences between lean and obese animal data for select microvascular parameters (P < .04), which was not true for TIC-based measurements. Whereas the TMC and TIC microvascular parameters yielded similar temporal trends, there was less variance associated with the TMC-derived values.

Conclusions: Super-resolution US imaging is a new modality for measuring the microvascular properties of skeletal muscle and dysfunction from type 2 diabetes.
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http://dx.doi.org/10.1002/jum.14956DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6669112PMC
October 2019

Deep 3D convolutional neural networks for fast super-resolution ultrasound imaging.

Proc SPIE Int Soc Opt Eng 2019 Feb 15;10955. Epub 2019 Mar 15.

Dept. of Bioengineering, Univ. of Texas at Dallas, 800 W. Campbell Rd., Richardson, TX 75080.

Super-resolution ultrasound imaging (SR-US) is a new technique which breaks the diffraction limit and can help visualize microvascularity at a resolution of tens of microns. However, image processing methods for spatiotemporal filtering needed in SR-US for microvascular delineation, such as singular value decomposition (SVD), are computationally burdensome and must be performed off-line. The goal of this study was to evaluate a novel and fast method for spatiotemporal filtering to segment the microbubble (MB) contrast agent from the tissue signal with a trained 3D convolutional neural network (3DCNN). data was collected using a programmable ultrasound (US) imaging system (Vantage 256, Verasonics Inc, Kirkland, WA) equipped with an L11-4v linear array transducer and obtained from a tissue-mimicking vascular flow phantom at flow rates representative of microvascular conditions. SVD was used to detect MBs and label the data for training. Network performance was validated with a leave-one-out approach. The 3DCNN demonstrated a 22% higher sensitivity in MB detection than SVD on data. Further, 3DCNN results from a cancer-bearing murine model revealed a high level of detail in the SR-US image demonstrating the potential for transfer learning from a neural network trained with data. The preliminary performance of segmentation with the 3DCNN was encouraging for real-time SR-US imaging with computation time as low as 5 ms per frame.
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http://dx.doi.org/10.1117/12.2511897DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7261615PMC
February 2019

Lower Limb Motion Estimation Using Ultrasound Imaging: A Framework for Assistive Device Control.

IEEE J Biomed Health Inform 2019 11 9;23(6):2505-2514. Epub 2019 Jan 9.

Objective: Powered assistive devices need improved control intuitiveness to enhance their clinical adoption. Therefore, the intent of individuals should be identified and the device movement should adhere to it. Skeletal muscles contract synergistically to produce defined lower limb movements, so unique contraction patterns in lower extremity musculature may provide a means of device joint control. Ultrasound (US) imaging enables direct measurement of the local deformation of muscle segments. Hence, the objective of this study was to assess the feasibility of using US to estimate human lower limb movements.

Methods: A novel algorithm was developed to calculate US features of the rectus femoris muscle during a non-weight-bearing knee flexion/extension experiment by nine able-bodied subjects. Five US features of the skeletal muscle tissue were studied, namely thickness, angle between aponeuroses, pennation angle, fascicle length, and echogenicity. A multiscale ridge filter was utilized to extract the structures in the image and a random sample consensus (RANSAC) model was used to segment muscle aponeuroses and fascicles. A localization scheme further guided RANSAC to enable tracking in a US image sequence. Gaussian process regression models were trained using segmented features to estimate both knee joint angle and angular velocity.

Results: The proposed segmentation-estimation approach could estimate knee joint angle and angular velocity with an average root mean square error value of 7.45° and 0.262 rad/s, respectively. The average processing rate was 3-6 frames/s that is promising toward real-time implementation.

Conclusion: Experimental results demonstrate the feasibility of using US to estimate human lower extremity motion. The ability of the algorithm to work in real time may enable the use of US as a neural interface for lower limb applications.

Significance: Intuitive intent recognition of human lower extremity movements using wearable US imaging may enable volitional assistive device control and enhance locomotor outcomes for those with mobility impairments.
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http://dx.doi.org/10.1109/JBHI.2019.2891997DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6616025PMC
November 2019

Real-time H-scan ultrasound imaging using a Verasonics research scanner.

Ultrasonics 2019 Apr 20;94:28-36. Epub 2018 Dec 20.

Department of Bioengineering, University of Texas at Dallas, Richardson, TX 75080, USA; Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA. Electronic address:

H-scan ultrasound (US) is a new imaging technique that relies on matching a model that describes US image formation to the mathematics of a class of Gaussian-weighted Hermite polynomials (GH). In short, H-scan US (where the 'H' denotes Hermite or hue) is a tissue classification technique that images the relative size of acoustic scatterers. Herein, we detail development of a real-time H-scan US imaging technology that was implemented on a programmable US research scanner (Vantage 256, Verasonics Inc, Kirkland, WA). This custom US imaging system has a dual display for real-time visualization of both the H-scan and B-scan US images. This MATLAB-based (Mathworks Inc, Natick, MA) system includes a graphical user interface (GUI) for controlling the entire US scan sequence including the raw radio frequency (RF) data acquisition parameters, image processing, variable control of a parallel set of convolution filters used to derive the H-scan US signal, and data (cine loop) save. The system-level structure used for software-based image reconstruction and display is detailed. Imaging studies were conducted using a series of homogeneous and heterogeneous tissue-mimicking phantom materials embedded with monodisperse spherical US scatterers of size 15-40 µm in diameter. Relative to H-scan US image measurements from a phantom with 15 µm-sized scatterers, data from phantoms with the 30 and 40 µm-sized scatterers exhibited mean intensity increases of 5.2% and 11.6%, respectively. Overall, real-time H-scan US imaging is a promising approach for visualizing the relative size and distribution of acoustic scattering objects.
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http://dx.doi.org/10.1016/j.ultras.2018.12.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6467760PMC
April 2019

Pentagalloyl Glucose and Its Functional Role in Vascular Health: Biomechanics and Drug-Delivery Characteristics.

Ann Biomed Eng 2019 Jan 8;47(1):39-59. Epub 2018 Oct 8.

Vascular Biomechanics and Biofluids Laboratory, Department of Mechanical Engineering, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX, 78249-0670, USA.

Pentagalloyl glucose (PGG) is an elastin-stabilizing polyphenolic compound that has significant biomedical benefits, such as being a free radical sink, an anti-inflammatory agent, anti-diabetic agent, enzymatic resistant properties, etc. This review article focuses on the important benefits of PGG on vascular health, including its role in tissue mechanics, the different modes of pharmacological administration (e.g., oral, intravenous and endovascular route, intraperitoneal route, subcutaneous route, and nanoparticle based delivery and microbubble-based delivery), and its potential therapeutic role in vascular diseases such as abdominal aortic aneurysms (AAA). In particular, the use of PGG for AAA suppression and prevention has been demonstrated to be effective only in the calcium chloride rat AAA model. Therefore, in this critical review we address the challenges that lie ahead for the clinical translation of PGG as an AAA growth suppressor.
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http://dx.doi.org/10.1007/s10439-018-02145-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6318003PMC
January 2019

Monitoring Early Breast Cancer Response to Neoadjuvant Therapy Using H-Scan Ultrasound Imaging: Preliminary Preclinical Results.

J Ultrasound Med 2019 May 2;38(5):1259-1268. Epub 2018 Oct 2.

Department of Bioengineering, University of Texas at Dallas, Richardson, Texas, USA.

Objective: H-scan imaging is a new ultrasound technique used to visualize the relative size of acoustic scatterers. The purpose of this study was to evaluate the use of H-scan ultrasound imaging for monitoring early tumor response to neoadjuvant treatment using a preclinical breast cancer animal model.

Methods: Real-time H-scan ultrasound imaging was implemented on a programmable ultrasound scanner (Vantage 256; Verasonics Inc., Kirkland, WA) equipped with an L11-4v transducer. Bioluminescence and H-scan ultrasound was used to image luciferase-positive breast cancer-bearing mice at baseline and at 24, 48, and 168 hours after administration of a single dose of neoadjuvant (paclitaxel) or sham treatment. Animals were euthanized at 48 or 168 hours, and tumors underwent histologic processing to identify cancer cell proliferation and apoptosis.

Results: Baseline H-scan ultrasound images of control and therapy group tumors were comparable, but the latter exhibited significant changes over the 7-day study (P < .05). At termination, there was a marked difference between the H-scan ultrasound images of control and treated tumors (P < .05). Specifically, H-scan ultrasound images of treated tumors were more blue in hue than images obtained from control tumors. There was a significant linear correlation between the predominance of the blue hue found in the H-scan ultrasound images and intratumoral apoptotic activity (R  > 0.40, P < .04).

Conclusion: Preliminary preclinical results suggest that H-scan ultrasound imaging is a new and promising tissue characterization modality. H-scan ultrasound imaging may provide prognostic value when monitoring early tumor response to neoadjuvant treatment.
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http://dx.doi.org/10.1002/jum.14806DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6445796PMC
May 2019

Hyposialylated IgG activates endothelial IgG receptor FcγRIIB to promote obesity-induced insulin resistance.

J Clin Invest 2018 01 27;128(1):309-322. Epub 2017 Nov 27.

Center for Pulmonary and Vascular Biology, Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, Texas, USA.

Type 2 diabetes mellitus (T2DM) is a common complication of obesity. Here, we have shown that activation of the IgG receptor FcγRIIB in endothelium by hyposialylated IgG plays an important role in obesity-induced insulin resistance. Despite becoming obese on a high-fat diet (HFD), mice lacking FcγRIIB globally or selectively in endothelium were protected from insulin resistance as a result of the preservation of insulin delivery to skeletal muscle and resulting maintenance of muscle glucose disposal. IgG transfer in IgG-deficient mice implicated IgG as the pathogenetic ligand for endothelial FcγRIIB in obesity-induced insulin resistance. Moreover, IgG transferred from patients with T2DM but not from metabolically healthy subjects caused insulin resistance in IgG-deficient mice via FcγRIIB, indicating that similar processes may be operative in T2DM in humans. Mechanistically, the activation of FcγRIIB by IgG from obese mice impaired endothelial cell insulin transcytosis in culture and in vivo. These effects were attributed to hyposialylation of the Fc glycan, and IgG from T2DM patients was also hyposialylated. In HFD-fed mice, supplementation with the sialic acid precursor N-acetyl-D-mannosamine restored IgG sialylation and preserved insulin sensitivity without affecting weight gain. Thus, IgG sialylation and endothelial FcγRIIB may represent promising therapeutic targets to sever the link between obesity and T2DM.
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http://dx.doi.org/10.1172/JCI89333DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5749535PMC
January 2018

Ultrasound-Stimulated Drug Delivery Using Therapeutic Reconstituted High-Density Lipoprotein Nanoparticles.

Nanotheranostics 2017 1;1(4):440-449. Epub 2017 Nov 1.

Department of Bioengineering, University of Texas at Dallas, Richardson, TX 75080 USA.

The abnormal tumor vasculature and the resulting abnormal microenvironment are major barriers to optimal chemotherapeutic drug delivery. It is well known that ultrasound (US) can increase the permeability of the tumor vessel walls and enhance the accumulation of anticancer agents. Reconstituted high-density lipoproteins (rHDL) nanoparticles (NPs) allow selective delivery of anticancer agents to tumor cells via their overexpressed scavenger receptor type B1 (SR-B1) receptor. The goal of this study is to investigate the potential of noninvasive US therapy to further improve delivery and tumor uptake of the payload from rHDL NPs, preloaded with an infrared dye (IR-780), aimed to establish a surrogate chemotherapeutic model with optical localization. Athymic nude mice were implanted orthotopically with one million breast cancer cells (MDA-MB-231/Luc). Three weeks later, animals were divided into seven groups with comparable mean tumor size: control, low, moderate, and high concentration of rHDL NPs alone groups, as well as these three levels of rHDL NPs plus US therapy groups ( = 7 to 12 animals per group), where low, moderate and high denote 5, 10, and 50 µg of the IR-780 dye payload per rHDL NP injection, respectively. The US therapy system included a single element focused transducer connected in series with a function generator and power amplifier. A custom 3D printed cone with an acoustically transparent aperture and filled with degassed water allowed delivery of focused US energy to the tumor tissue. US exposure involved a pulsed sequence applied for a duration of 5 min. Each animal in the US therapy groups received a slow bolus co-injection of MB contrast agent and rHDL NPs. Animals were imaged using a whole-body optical system to quantify intratumoral rHDL NP accumulation at baseline and again at 1 min, 30 min, 24 h, and 48 h. At 48 h, all animals were euthanized and tumors were excised for analysis. We investigated a noninvasive optical imaging method for monitoring the effects of US-stimulated drug delivery of IR-780 dye-loaded rHDL NPs in living animals. No change in optical imaging data was found in the control animals. However, there was considerable dye accumulation (surrogate drug) within 48 h in the low (5 µg), moderate (10 µg), and high (50 µg) rHDL NP concentration-dosed group animals ( < 0.09). With US therapy added to the experimental protocol, there was an additional and significant increase in local tumor drug uptake at 48 h ( < 0.02). Optical image data collected from tumor samples confirmed tumor retention of the IR-780 dye-loaded rHDL NPs and correlated positively with optical imaging results ( > 0.69, < 0.003). IR-780 dye extraction from the tumor tissue samples confirmed the and US therapy findings. Overall, the addition of US therapy considerably improved local rHDL NP accumulation in tumor tissue. This study concludes that US-mediated drug delivery can facilitate tumor uptake of rHDL NPs and more research is warranted to optimize the drug dosing schedule and the respective therapeutic protocols.
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http://dx.doi.org/10.7150/ntno.21905DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5704009PMC
November 2017

H-scan sensitivity to scattering size.

J Med Imaging (Bellingham) 2017 Oct 6;4(4):043501. Epub 2017 Nov 6.

University of Rochester, Department of Electrical and Computer Engineering, Rochester, New York, United States.

In the H-scan analysis and display, visualization of different scattering sizes and types is enabled by a matched filter approach involving different orders of Gaussian weighted Hermite functions. An important question with respect to clinical applications involves the change in H-scan outputs with respect to small changes in scatterer sizes. The sensitivity of H-scan outputs is analyzed using the theory of backscatter from a compressible sphere. Experimental corroboration is established using mono dispersed spherical scatterers in phantoms. With a 6-MHz center frequency broadband transducer, it is possible to visualize changes in scattering size in the order of 10 to [Formula: see text] in phantoms and also changes in bovine liver tissue due to edema caused by hypotonic perfusion.
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http://dx.doi.org/10.1117/1.JMI.4.4.043501DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5673159PMC
October 2017

Spatial Angular Compounding Technique for H-Scan Ultrasound Imaging.

Ultrasound Med Biol 2018 Jan 12;44(1):267-277. Epub 2017 Oct 12.

Department of Bioengineering, University of Texas at Dallas, Richardson, Texas, USA; Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA. Electronic address:

H-Scan is a new ultrasound imaging technique that relies on matching a model of pulse-echo formation to the mathematics of a class of Gaussian-weighted Hermite polynomials. This technique may be beneficial in the measurement of relative scatterer sizes and in cancer therapy, particularly for early response to drug treatment. Because current H-scan techniques use focused ultrasound data acquisitions, spatial resolution degrades away from the focal region and inherently affects relative scatterer size estimation. Although the resolution of ultrasound plane wave imaging can be inferior to that of traditional focused ultrasound approaches, the former exhibits a homogeneous spatial resolution throughout the image plane. The purpose of this study was to implement H-scan using plane wave imaging and investigate the impact of spatial angular compounding on H-scan image quality. Parallel convolution filters using two different Gaussian-weighted Hermite polynomials that describe ultrasound scattering events are applied to the radiofrequency data. The H-scan processing is done on each radiofrequency image plane before averaging to get the angular compounded image. The relative strength from each convolution is color-coded to represent relative scatterer size. Given results from a series of phantom materials, H-scan imaging with spatial angular compounding more accurately reflects the true scatterer size caused by reductions in the system point spread function and improved signal-to-noise ratio. Preliminary in vivo H-scan imaging of tumor-bearing animals suggests this modality may be useful for monitoring early response to chemotherapeutic treatment. Overall, H-scan imaging using ultrasound plane waves and spatial angular compounding is a promising approach for visualizing the relative size and distribution of acoustic scattering sources.
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http://dx.doi.org/10.1016/j.ultrasmedbio.2017.09.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5712267PMC
January 2018

Thrombin-Activatable Microbubbles as Potential Ultrasound Contrast Agents for the Detection of Acute Thrombosis.

ACS Appl Mater Interfaces 2017 Nov 20;9(43):37587-37596. Epub 2017 Oct 20.

Department of Radiology, Translational Research in Ultrasound Theranostics (TRUST) Program, University of Texas Southwestern Medical Center , 5323 Harry Hines Boulevard, Dallas, Texas 75390-8514, United States.

Acute deep vein thrombosis (DVT) is the formation of a blood clot in the deep veins of the body that can lead to fatal pulmonary embolism. Acute DVT is difficult to distinguish from chronic DVT by ultrasound (US), the imaging modality of choice, and is therefore treated aggressively with anticoagulants, which can lead to internal bleeding. Here we demonstrate that conjugating perfluorobutane-filled (PFB-filled) microbubbles (MBs) with thrombin-sensitive activatable cell-penetrating peptides (ACPPs) could lead to the development of contrast agents that detect acute thrombosis with US imaging. Successful conjugation of ACPP to PFB-filled MBs was confirmed by fluorescence microscopy and flow cytometry. Fluorescein-labeled ACPP was used to evaluate the efficiency of thrombin-triggered cleavage by measuring the mean fluorescence intensity of ACPP-labeled MBs (ACPP-MBs) before and after incubation at 37 °C with thrombin. Lastly, control MBs and ACPP-MBs were infused through a tube containing a clot, and US contrast enhancement was measured with or without the presence of a thrombin inhibitor after washing the clot with saline. With thrombin activity, 91.7 ± 14.2% of the signal was retained after ACPP-MB infusion and washing, whereas only 16.7 ± 4% of the signal was retained when infusing ACPP-MBs in the presence of hirudin, a potent thrombin inhibitor.
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http://dx.doi.org/10.1021/acsami.7b10592DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5691601PMC
November 2017