This PDF file contains the front matter associated with SPIE Proceedings Volume 9419, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and Conference Committee listing.

This work presents the development and first results of in vivo transthoracic cardiac imaging using an implementation of Vector Flow Imaging (VFI) via the Transverse Oscillation (TO) method on a phased-array transducer. Optimal selection of the lateral wavelength of the transversely-oscillating receive field is described, and results from Field II simulations are presented. Measurements are made using the SARUS experimental ultrasound scanner driving an intercostal phased-array probe. The acquisition sequence was composed of interleaved frames of 68-line B-mode and 17-direction, 32-shot vector velocity flow images. A flow pump was programmed for constant flow for in vitro acquisitions at varying depths in a tissue-mimicking fluid. Additionally, mitral, aortic, and tricuspid valves of two healthy volunteers were scanned from intercostal acoustic windows. The acquired RF data were beam-formed via the TO method, and fourth-order estimators were employed for the velocity estimation. The resulting images were compared with those from conventional spectral Doppler and color flow mapping sequences. VFI is shown to be a clinically-feasible tool, which enables new flexibility for choosing acoustic windows, visualizing turbulent flow patterns, and measuring velocities.

Time gain compensation (TGC) is essential to ensure the optimal image quality of the clinical ultrasound scans. When large fluid collections are present within the scan plane, the attenuation distribution is changed drastically and TGC compensation becomes challenging. This paper presents an automated hierarchical TGC (AHTGC) algorithm that accurately adapts to the large attenuation variation between different types of tissues and structures. The algorithm relies on estimates of tissue attenuation, scattering strength, and noise level to gain a more quantitative understanding of the underlying tissue and the ultrasound signal strength. The proposed algorithm was applied to a set of 44 in vivo abdominal movie sequences each containing 15 frames. Matching pairs of in vivo sequences, unprocessed and processed with the proposed AHTGC were visualized side by side and evaluated by two radiologists in terms of image quality. Wilcoxon signed-rank test was used to evaluate whether radiologists preferred the processed sequences or the unprocessed data. The results indicate that the average visual analogue scale (VAS) is positive ( p-value: 2.34 × 10^-13) and estimated to be 1.01 (95% CI: 0.85; 1.16) favoring the processed data with the proposed AHTGC algorithm.

One of the major non-congenital cause of neurological impairment among neonates born very preterm is intraventricular hemorrhage (IVH) - bleeding within the lateral ventricles. Most IVH patients will have a transient period of ventricle dilation that resolves spontaneously. However, those patients most at risk of long-term impairment are those who have progressive ventricle dilation as this causes macrocephaly, an abnormally enlarged head, then later causes increases intracranial pressure (ICP). 2D ultrasound (US) images through the fontanelles of the patients are serially acquired to monitor the progression of the ventricle dilation. These images are used to determine when interventional therapies such as needle aspiration of the built up CSF might be indicated for a patient. Initial therapies usually begin during the third week of life. Such interventions have been shown to decrease morbidity and mortality in IVH patients; however, this comes with risks of further hemorrhage or infection; therefore only patients requiring it should be treated. Previously we have developed and validated a 3D US system to monitor the progression of ventricle volumes (VV) in IVH patients. This system has been validated using phantoms and a small set of patient images. The aim of this work is to determine the ability of 3D US generated VV to categorize patients into those who will require interventional therapies, and those who will have spontaneous resolution. Patients with higher risks could therefore be monitored better, by re-allocating some of the resources as the low risks infants would need less monitoring.

Cardiac ultrasound plays an important role in the imaging of hearts in basic cardiovascular research and clinical examinations. 3D ultrasound imaging can provide the geometry or motion information of the heart. Especially, the wrapping of cardiac fiber orientations to the ultrasound volume could supply useful information on the stress distributions and electric action spreading. However, how to acquire 3D ultrasound volumes of the heart of small animals in vivo for cardiac fiber wrapping is still a challenging problem. In this study, we provide an approach to acquire 3D ultrasound volumes of the rat hearts in vivo. The comparison between both in vivo and ex vivo geometries indicated 90.1% Dice similarity. In this preliminary study, the evaluations of the cardiac fiber orientation wrapping errors were 24.7° for the acute angle error and were 22.4° for the inclination angle error. This 3D ultrasound imaging and fiber orientation estimation technique have potential applications in cardiac imaging.

Photoacoustic imaging (PA) is becoming a promising modality for pre-clinical and clinical application by providing functional information with high penetration depth. In particular, PA computed tomography (PACT) aims to visualize the photoacoustic source distribution by scanning ultrasound transducers around a surface of the structure. Placing transducers around the subject or rotating the subject with fixing transducer position are two major approaches to scan in circular arc trajectory, but both are not flexible and have their drawbacks. To resolve the problem, we propose a new scanning method based on the robotic tracking technique. High flexibility of the scanning geometry is available because the trajectory of the tracked transducer generated by robot motion will be regarded as the scanning path. A simulation study of proposed method is conducted, assuming a 6cm array ultrasound transducer was used as receivers. To replicate the scenario that the probe is moved by robot, the probe is placed at two positions across a designated rotation angle, and received signals at both positions are used to generate an image. Compared to the result without robot motion, the lateral resolution of the target drastically improved due to aperture extension. In addition, the effect of error in one of the pose in lateral and axial direction was also simulated. Finally, an experiment was conducted to demonstrate the feasibility of the system. The result indicates that the ultrasound calibration is required to the system, and the robotically tracked PACT has a huge potential to be a new scanning strategy.

Functional opto-acoustic (OA) imaging was fused with gray-scale ultrasound acquired using a specialized duplex handheld probe. Feasibility Study findings indicated the potential to more accurately characterize breast masses for cancer than conventional diagnostic ultrasound (CDU). The Feasibility Study included OA imagery of 74 breast masses that were collected using the investigational Imagio® breast imaging system. Superior specificity and equal sensitivity to CDU was demonstrated, suggesting that OA fusion imaging may potentially obviate the need for negative biopsies without missing cancers in a certain percentage of breast masses. Preliminary results from a 100 subject Pilot Study are also discussed. A larger Pivotal Study (n=2,097 subjects) is underway to confirm the Feasibility Study and Pilot Study findings.

Acquiring nondestructive internal structures acoustic image as well as the morphology images using scanning probe acoustic microscope (SPAM) is a challenge and no known metrology tools to identify the ultrasonic internal resolution and detectable depth of SPAM in a nondestructive way. Monitoring these defects necessitates the identification of their technical parameters of SPAM. In this paper, the specific materials (test phantoms) were designed and processed so that the ultrasound internal resolution of SPAM in nondestructive imaging of the embedded or buried substructures as well as the morphology images were measured. Experimental results demonstrated the successful identification of embedded or buried defects under the test phantom with the resolution of 50nm for SPAM as well as the detectable depth of more than 100μm.

As an emerging hybrid Imaging, Photoacoustic became a powerful tool that can scan disease at the deeper site in tissue and monitor of drug delivery in vivo. PAI system used nano-particle as contrast agent to enhance the PA signal in deeper site in tissue. So this makes that PAI’s application have some limitation for monitoring of all kinds of anti-body drug, because of various anti-body’s absorption excitation. In this study, we designed a PAI system with a tunable pulse OPO laser (from 450~700nm excitation wavelength) to show the optimal wavelength for monitoring of the antibody drug; doxorubicin having peak absorption at near 500nm excitation without any nano-particle combine. We made a gelatin phantoms having 4 different concentration doxorubicin as an anti-body drug; Doxorubicin concentration were in- 0mg/ml, 0.5mg/ml, 1mg/ml, and 2mg/ml. We found that 500nm is optimization wavelength to produce PA peak signal and PAI can be tool to monitor of anti-body drug without contrast agent.

Ultrasound computed tomography (USCT) holds great promise for improving the detection and management of breast cancer. Because they are based on the acoustic wave equation, waveform inversion-based reconstruction methods can produce images that possess improved spatial resolution properties over those produced by ray-based methods. However, waveform inversion methods are computationally demanding and have not been applied widely in USCT breast imaging. In this work, source encoding concepts are employed to develop an accelerated USCT reconstruction method that circumvents the large computational burden of conventional waveform inversion methods. This method, referred to as the waveform inversion with source encoding (WISE) method, encodes the measurement data using a random encoding vector and determines an estimate of the speed-of-sound distribution by solving a stochastic optimization problem by use of a stochastic gradient descent algorithm. Computer-simulation studies are conducted to demonstrate the use of the WISE method. Using a single graphics processing unit card, each iteration can be completed within 25 seconds for a 128 × 128 mm² reconstruction region. The results suggest that the WISE method maintains the high spatial resolution of waveform inversion methods while significantly reducing the computational burden.

Ultrasound tomography is a promising modality for breast imaging. Many current ultrasound tomography imaging algorithms are based on ray theory and assume a homogeneous background which is inaccurate for complex heterogeneous regions. They fail when the size of lesions approaches the wavelength of ultrasound used. Therefore, to accurately image small lesions, wave theory must be used in ultrasound imaging algorithms to properly handle the heterogeneous nature of breast tissue and the diffraction effects that it induces. Using frequency-domain ultrasound waveform tomography, we present sound speed reconstructions of both a tissue-mimicking breast phantom and in vivo data sets. Significant improvements in contrast and resolution are made upon the previous ray based methods. Where it might have been difficult to differentiate a high sound speed tumor from bulk breast parenchyma using ray based methods, waveform tomography improves the shape and margins of a tumor to help more accurately differentiate it from the bulk breast tissue. Waveform tomography sound speed imaging might improve the ability of finding lesions in very dense tissues, a difficult environment for mammography. By comparing the sound speed images produced by waveform tomography to MRI, we see that the complex structures in waveform tomography are consistent with those in MRI. The robustness of the method is established by reconstructing data acquired by two different ultrasound tomography prototypes.

3D Ultrasound Computer Tomography (3D USCT) promises reproducible high-resolution images for early detection of breast tumors. The KIT prototype provides three different modalities: reflectivity, speed of sound, and attenuation. The reflectivity images are reconstructed using a Synthetic Aperture Focusing Technique (SAFT) algorithm. For high-resolution re ectivity images, with spatially homogeneous reflectivity, attenuation correction is necessary. In this paper we present a GPU accelerated attenuation correction for 3D USCT and evaluate the method by means of image quality metrics; i.e. absolute error, contrast and spatially homogeneous reflectivity. A threshold for attenuation correction was introduced to preserve a high contrast. Simulated and in-vivo data were used for analysis of the image quality. Attenuation correction increases the image quality by improving spatially homogeneous reflectivity by 25 %. This leads to a factor 2.8 higher contrast for in-vivo data.

Bent ray ultrasound sound speed tomography reconstruction can improve image quality comparing to straight ray. However, it suffers from time consuming ray linking, which finds bent ray to link a pair of given emitter and receiver. Currently, multi ray tracing always be required for single ray linking, but all of traced rays will be discarded excepting one which links the given emitter and receiver. It is important for reducing time cost to avoid the discarding and decrease ray tracing number. For this purpose, a novel bent ray reconstruction method (BRRM) using virtual receiver was proposed in this study. Single reconstruction iteration of proposed method includes five steps. Firstly, travel time difference map (TTDM) is picked by first peak method. Secondly, launch angles for straight rays are obtained. Thirdly, ray tracing for each obtained launch angle is implemented and their arrival positions in transducer ring are recorded. Fourthly, TTDM for virtual receivers, which are placed in each bent ray arrival position, is estimated by interpolation of picked TTDM. Fifthly, simultaneous algebraic reconstruction technique (SART) is employed for reconstruction. To evaluated proposed method, ultrasound tomography RF data of simple and complex sound speed models are simulated by PZFlex. Reconstruction results show that proposed method can reduce ray tracing number to be about 20% and time cost to be one third of previous BRRM with similar image quality. In this study, a novel BRRM using virtual receiver is proposed to reduce ray tracing number and time cost of BRRM without image quality decreasing.

A number of clinical trials have shown that screening ultrasound, supplemental to mammography, detects additional cancers in women with dense breasts. However, labor intensity, operator dependence and high recall rates have limited adoption. This paper describes the use of ultrasound tomography for whole-breast tissue stiffness measurements as a first step toward addressing the issue of high recall rates. The validation of the technique using an anthropomorphic phantom is described. In-vivo applications are demonstrated on 13 breast masses, indicating that lesion stiffness correlates with lesion type as expected. Comparison of lesion stiffness measurements with standard elastography was available for 11 masses and showed a strong correlation between the 2 measures. It is concluded that ultrasound tomography can map out the 3 dimensional distribution of tissue stiffness over the whole breast. Such a capability is well suited for screening where additional characterization may improve the specificity of screening ultrasound, thereby lowering barriers to acceptance.

Ultrasound imaging of deep targets is limited by the resolution of current ultrasound systems based on the available aperture size. We propose a system to synthesize an extended effective aperture in order to improve resolution and target detectability at depth using a precisely-tracked transducer swept across the region of interest. A Field II simulation was performed to demonstrate the swept aperture approach in both the spatial and frequency domains. The adaptively beam-formed system was tested experimentally using a volumetric transducer and an ex vivo canine abdominal layer to evaluate the impact of clutter-generating tissue on the resulting point spread function. Resolution was improved by 73% using a 30.8 degree sweep despite the presence of varying aberration across the array with an amplitude on the order of 100 ns. Slight variations were observed in the magnitude and position of side lobes compared to the control case, but overall image quality was not significantly degraded as compared by a simulation based on the experimental point spread function. We conclude that the swept aperture imaging system may be a valuable tool for synthesizing large effective apertures using conventional ultrasound hardware.

Synthetic aperture (SA) imaging can be used to achieve real-time volumetric ultrasound imaging using 2-D array transducers. The sensitivity of SA imaging is improved by maximizing the acoustic output, but one must consider the limitations of an ultrasound system, both technical and biological. This paper investigates the in vivo applicability and sensitivity of volumetric SA imaging. Utilizing the transmit events to generate a set of virtual point sources, a frame rate of 25 Hz for a 90° × 90° field-of-view was achieved. data were obtained using a 3.5 MHz 32 × 32 elements 2-D phased array transducer connected to the experimental scanner (SARUS). Proper scaling is applied to the excitation signal such that intensity levels are in compliance with the U.S. Food and Drug Administration regulations for in vivo ultrasound imaging. The measured Mechanical Index and spatial-peak-temporal-average intensity for parallel beam-forming (PB) are 0.83 and 377.5mW/cm², and for SA are 0.48 and 329.5mW/cm². A human kidney was volumetrically imaged with SA and PB techniques simultaneously. Two radiologists for evaluation of the volumetric SA were consulted by means of a questionnaire on the level of details perceivable in the beam-formed images. The comparison was against PB based on the in vivo data. The feedback from the domain experts indicates that volumetric SA images internal body structures with a better contrast resolution compared to PB at all positions in the entire imaged volume. Furthermore, the autocovariance of a homogeneous area in the in vivo SA data, had 23.5% smaller width at the half of its maximum value compared to PB.

Many modern high-end scanners use some form for coherent synthesis of image lines by combining beams acquired with different transmissions, such as retrospective dynamic transmit focusing (Acuson / Siemens), nSIGHT (Philips), and Zone imaging (Zonare). There are two major strategies described in the literature to uniformly focus both transmit and receive beams throughout the field of view - using virtual sources, and by applying spatial matched filtration. The virtual source model is precise, when the transmit is either strongly focused (f-number ~ 1, 2) or images are formed using circular or spherical waves. The spatial matched filtration can be used also with weakly focused transmissions, but requires the measurement and storage of the response of point targets within the limits of the transmit beam.

This paper presents a semi-analytic model for the transmitted field, which can be applied to synthetic transmit imaging. The model is more precise than the virtual source concept, does not require the measurement of the transmit field as matched filtration methods do, and can be applied to both strongly and weakly focused transmissions. Furthermore, the model is applicable to tissue harmonic and contrast enhanced ultrasound imaging.

The paper presents the development of the model using the principles of diffraction, and its validation using computer simulations and measurements on a phantom. Finally, the model is demonstrated for synthetic aperture tissue harmonic in-vivo imaging.

Synthetic aperture (SA) is a technique that enhances the image resolution by synthesizing information from multiple subapertures. The application of this technique for medical ultrasound imaging has been an active research area, but the resolution improvement is limited by the physical size of the ultrasound array transducer. With a large F number (depth to aperture-size ratio), it is hard to achieve high resolution at deep regions without extending the effective aperture size. In this paper, we investigate experimentally an approach to extend the available aperture size for SA by sweeping the ultrasound transducer using a precise robotic arm. Pose information from the robot’s kinematic for the calibrated probe is used to synthesize the signals received at different positions; therefore the available aperture is wider than the size of transducer. To experimentally validate this approach, a robot arm (UR5, Universal Robot) was used to hold a 64 elements phased array transducer (0.32 mm pitch, 2MHz central frequency), and in-plane lateral translational motion was applied. A line phantom as a point source and an ultrasound phantom with wire targets and anechoic region were used for evaluation. The full width at half maximum of a reconstructed point source improved a factor of 2.76 by moving five poses with 10.24 mm step size. For the ultrasound phantom, the contrast-to-noise ratio of anechoic region enhanced 12% by moving three poses with the same step. Results indicate that the technique to robotically extend aperture has potential to improve the image quality for SA ultrasound imaging.

The Internet of Things (IoT) is expected to grow to 26 billion connected devices by 2020, plus the PC, smart phone, and tablet segment that includes mobile Health (mHealth) connected devices is projected to account for another 7.3 billion units by 2020. This paper explores some of the real-time constraints on the data-flow and control of a wireless connected ultrasound machine. The paper will define an ultrasound server and the capabilities necessary for real-time use of the device.

The concept of an ultrasound server wirelessly (or over any network) connected to multiple lightweight clients on devices like an iPad, iPhone, or Android-based tablet, smartphone and other network-attached displays (i.e., Google Glass) is explored. Latency in the ultrasound data stream is one of the key areas to measure and to focus on keeping as small as possible (<30ms) so that the ultrasound operator can see what is at the probe at that moment, instead of where the probe was a short period earlier. By keeping the latency less than 30ms, the operator will feel like the data he sees on the wireless connected devices is running in real-time with the operator.

The second parameter is the management of bandwidth. At minimum we need to be able to see 20 frames-per- second. It is possible to achieve ultrasound in triplex mode at >20 frames-per-second on a properly configured wireless network.

The ultrasound server needs to be designed to accept multiple ultrasound data clients and multiple control clients. A description of the server and some of its key features will be described.

Ultrasound (US) tomography enables quantitative measurement of acoustic properties. Robot assisted ultrasound tomography system enables alignment of two US probes. The alignment is done automatically by the robotic arm so that tomographic reconstruction of more anatomies becomes possible. In this study, we propose a new system setup for robot assistance in US tomographic imaging. This setup includes two robotic arms holding two US probes. One of the robotic arms is operated by the sonographer to determine the desired location for the tomographic imaging; this probe can also provide the B-mode US image during the search. The other robotic arm can then move automatically to align the two probes. One of the probes will act as transmitter and the other one as receiver to enable tomographic imaging. We provide an overview of the system setup and components together with the calibration procedures. In an attempt to provide a complete framework for the tomography system, we also provide a sample tomographic reconstruction method that can reconstruct speed of sound image using two aligned linear US probes. The reconstruction algorithm is however very prone to alignment inaccuracies. We provide an error propagation analysis to provide an estimation of the overall alignment error and then show the effect of the in-plane translational error in the tomographic reconstruction.

Development of Ultrasound Computed Tomography (USCT) transducer elements position calibration method was described. USCT experimental system having 1024 ring array transducer elements, diameter of 104mm, electronic High Voltage multiplexer circuits and commercially available ultrasound research platform was used. The result of applying the transducer elements position calibration to the received data, -6dB Tx / Rx beam width was 0.68mm for uncorrected, 0.20mm for corrected. Corrected value was almost same as simulated value. As a result, when reconstructing crosssectional images in the present experimental system, expected a precise image, not only reflection black-and-white images but also sound-of-speed transmission image would be reconstructed.

3D Ultrasound Computer Tomography (USCT) is a new imaging method for breast cancer diagnosis. In the current state of development it is essential to correlate USCT with a known imaging modality like MRI to evaluate how different tissue types are depicted. Due to different imaging conditions, e.g. with the breast subject to buoyancy in USCT, a direct correlation is demanding. We present a 3D image registration method to reduce positioning differences and allow direct side-by-side comparison of USCT and MRI volumes. It is based on a two-step approach including a buoyancy simulation with a biomechanical model and free form deformations using cubic B-Splines for a surface refinement. Simulation parameters are optimized patient-specifically in a simulated annealing scheme. The method was evaluated with in-vivo datasets resulting in an average registration error below 5mm. Correlating tissue structures can thereby be located in the same or nearby slices in both modalities and three-dimensional non-linear deformations due to the buoyancy are reduced. Image fusion of MRI volumes and USCT sound speed volumes was performed for intuitive display. By applying the registration to data of our first in-vivo study with the KIT 3D USCT, we could correlate several tissue structures in MRI and USCT images and learn how connective tissue, carcinomas and breast implants observed in the MRI are depicted in the USCT imaging modes.

Women with elevated mammographic percent density, defined as the ratio of fibroglandular tissue area to total breast area on a mammogram are at an increased risk of developing breast cancer. Ultrasound tomography (UST) is an imaging modality that can create tomographic sound speed images of a patient’s breast, which can then be used to measure breast density. These sound speed images are useful because physical tissue density is directly proportional to sound speed. The work presented here updates previous results that compared mammographic breast density measurements with UST breast density measurements within an ongoing study. The current analysis has been expanded to include 158 women with negative digital mammographic screens who then underwent a breast UST scan. Breast density was measured for both imaging modalities and preliminary analysis demonstrated strong and positive correlations (Spearman correlation coefficient r_s = 0.703). Additional mammographic and UST related imaging characteristics were also analyzed and used to compare the behavior of both imaging modalities. Results suggest that UST can be used among women with negative mammographic screens as a quantitative marker of breast density that may avert shortcomings of mammography.

Radiation therapy (RT) plays an essential role in the management of cancers. The precision of the treatment delivery process in chest and abdominal cancers is often impeded by respiration induced tumor positional variations, which are accounted for by using larger therapeutic margins around the tumor volume leading to sub-optimal treatment deliveries and risk to healthy tissue. Real-time tracking of tumor motion during RT will help reduce unnecessary margin area and benefit cancer patients by allowing the treatment volume to closely match the positional variation of the tumor volume over time. In this work, we propose a fast approach which enables transferring the pre-estimated target (e.g. tumor) motion extracted from ultrasound (US) image sequences in training stage (e.g. before RT) to online data in real-time (e.g. acquired during RT). The method is based on extracting feature points of the target object, exploiting low-dimensional description of the feature motion through slow feature analysis, and finding the most similar image frame from training data for estimating current/online object location. The approach is evaluated on two 2D + time and one 3D + time US acquisitions. The locations of six annotated fiducials are used for designing experiments and validating tracking accuracy. The average fiducial distance between expert's annotation and the location extracted from our indexed training frame is 1.9±0.5mm. Adding a fast template matching procedure within a small search range reduces the distance to 1.4±0.4mm. The tracking time per frame is on the order of millisecond, which is below the frame acquisition time.

Background: Kidney stone is a major universal health problem, affecting 10% of the population worldwide. Percutaneous nephrolithotomy is a first-line and established procedure for disintegration and removal of renal stones. Its surgical success depends on the precise needle puncture of renal calyces, which remains the most challenging task for surgeons. This work describes and tests a new ultrasound based system to alert the surgeon when undesirable anatomical structures are in between the puncture path defined through a tracked needle.

Methods: Two circular ultrasound transducers were built with a single 3.3-MHz piezoelectric ceramic PZT SN8, 25.4 mm of radius and resin-epoxy matching and backing layers. One matching layer was designed with a concave curvature to work as an acoustic lens with long focusing. The A-scan signals were filtered and processed to automatically detect reflected echoes.

Results: The transducers were mapped in water tank and tested in a study involving 45 phantoms. Each phantom mimics different needle insertion trajectories with a percutaneous path length between 80 and 150 mm. Results showed that the beam cross-sectional area oscillates around the ceramics radius and it was possible to automatically detect echo signals in phantoms with length higher than 80 mm.

Conclusions: This new solution may alert the surgeon about anatomical tissues changes during needle insertion, which may decrease the need of X-Ray radiation exposure and ultrasound image evaluation during percutaneous puncture.

The aim of this study was prospectively to monitor the volume flow in patients with arteriovenous fistula (AVF) with the angle independent ultrasound technique Vector Flow Imaging (VFI). Volume flow values were compared with Ultrasound dilution technique (UDT). Hemodialysis patients need a well-functioning vascular access with as few complications as possible and preferred vascular access is an AVF. Dysfunction due to stenosis is a common complication, and regular monitoring of volume flow is recommended to preserve AVF patency. UDT is considered the gold standard for volume flow surveillance, but VFI has proven to be more precise, when performing single repeated instantaneous measurements. Three patients with AVF were monitored with UDT and VFI monthly for five months. A commercial ultrasound scanner with a 9 MHz linear array transducer with integrated VFI was used to obtain data. UDT values were obtained with Transonic HD03 Flow-QC Hemodialysis Monitor. Three independent measurements at each scan session were obtained with UDT and VFI each month. Average deviation of volume flow between UDT and VFI was 25.7 % (Cl: 16.7% to 34.7%) (p= 0.73). The standard deviation for all patients, calculated from the mean variance of each individual scan sessions, was 199.8 ml/min for UDT and 47.6 ml/min for VFI (p = 0.002). VFI volume flow values were not significantly different from the corresponding estimates obtained using UDT, and VFI measurements were more precise than UDT. The study indicates that VFI can be used for surveillance of volume flow.

Intraventricular hemorrhage (IVH) is a major cause of brain injury in preterm neonates. Quantitative measurement of ventricular dilation or shrinkage is important for monitoring patients and in evaluation of treatment options. 3D ultrasound (US) has been used to monitor the ventricle volume as a biomarker for ventricular dilation. However, volumetric quantification does not provide information as to where dilation occurs. The location where dilation occurs may be related to specific neurological problems later in life. For example, posterior horn enlargement, with thinning of the corpus callosum and parietal white matter fibres, could be linked to poor visuo-spatial abilities seen in hydrocephalic children. In this work, we report on the development and application of a method used to analyze local surface change of the ventricles of preterm neonates with IVH from 3D US images. The technique is evaluated using manual segmentations from 3D US images acquired in two imaging sessions. The surfaces from baseline and follow-up were registered and then matched on a point-by-point basis. The distance between each pair of corresponding points served as an estimate of local surface change of the brain ventricle at each vertex. The measurements of local surface change were then superimposed on the ventricle surface to produce the 3D local surface change map that provide information on the spatio-temporal dilation pattern of brain ventricles following IVH. This tool can be used to monitor responses to different treatment options, and may provide important information for elucidating the deficiencies a patient will have later in life.

We propose a general ultrasound (US) texture-analysis and machine-learning framework for detecting the presence of disease that is suitable for clinical application across clinicians, disease types, devices, and operators. Its stages are image selection, image filtering, ROI selection, feature parameterization, and classification. Each stage is modular and can be replaced with alternate methods. Thus, this framework is adaptable to a wide range of tasks.

Our two preliminary clinical targets are hepatic steatosis and adenomyosis diagnosis. For steatosis, we collected US images from 288 patients and their pathology-determined values of steatosis (%) from biopsies. Two radiologists independently reviewed all images and identified the region of interest (ROI) most representative of the hepatic echotexture for each patient.

To parameterize the images into comparable quantities, we filter the US images at multiple scales for various texture responses. For each response, we collect a histogram of pixel features within the ROI, and parameterize it as a Gaussian function using its mean, standard deviation, kurtosis, and skew to create a 36-feature vector. Our algorithm uses a support vector machine (SVM) for classification. Using a threshold of 10%, we achieved 72.81% overall accuracy, 76.18% sensitivity, and 65.96% specificity in identifying steatosis with leave-ten-out cross-validation (p<0.0001).

Extending this framework to adenomyosis, we identified 38 patients with MR-confirmed findings of adenomyosis and previous US studies and 50 controls. A single rater picked the best US-image and ROI for each case. Using the same processing pipeline, we obtained 76.14% accuracy, 86.00% sensitivity, and 63.16% specificity with leave-one-out cross-validation (p<0.0001).

Ultrasound (US) tissue characterization provides valuable information for the initialization of automatic segmentation algorithms, and can further provide complementary information for diagnosis of pathologies. US tissue characterization is challenging due to the presence of various types of image artifacts and dependence on the sonographer’s skills. One way of overcoming this challenge is by characterizing images based on the distribution of the backscatter data derived from the interaction between US waves and tissue. The goal of this work is to classify liver versus kidney tissue in 3D volumetric US data using the distribution of backscatter US data recovered from end-user displayed Bmode image available in clinical systems. To this end, we first propose the computation of a large set of features based on the homodyned-K distribution of the speckle as well as the correlation coefficients between small patches in 3D images. We then utilize the random forests framework to select the most important features for classification. Experiments on in-vivo 3D US data from nine pediatric patients with hydronephrosis showed an average accuracy of 94% for the classification of liver and kidney tissues showing a good potential of this work to assist in the classification and segmentation of abdominal soft tissue.

Spatio-temporal registration of baseline and follow-up intravascular ultrasound (IVUS) pullbacks is of paramount importance in studying the progression/regression of coronary artery disease. Automating these two tasks has the potential to increase productivity when studying large patient populations. Current automated methods are often designed for only one of the two tasks - spatial or temporal. In this paper, we propose an integrated framework which combines the two tasks and employs side-branches to constrain the IVUS pullback registration tasks. For temporal registration, canonical time warping technique optimizes extracted features and weighs cumulative distances. For spatial registration, the search range of cross-correlation based method is constrained by utilizing the angular differences between side-branches. Pilot validation is currently available for ten pairs of IVUS pullback sub-sequences. Results show average spatial and temporal registration errors of 0.49 mm ± 0.51 mm and 5.56° ± 3.35°, respectively, a notable improvement over our previous approach (p < 0.001) in temporal registration. Our method has the potential to improve spatial and temporal correspondence in studies of atherosclerotic vascular disease development using IVUS.

As thermal imaging attempts to estimate very small tissue motion (on the order of tens of microns), it can be negatively influenced by signal decorrelation. Patient's breathing and cardiac cycle generate shifts in the RF signal patterns. Other sources of movement could be found outside the patient's body, like transducer slippage or small vibrations due to environment factors like electronic noise. Here, we build upon a robust displacement estimation method for ultrasound elastography and we investigate an iterative motion compensation algorithm, which can detect and remove non-heat induced tissue motion at every step of the ablation procedure. The validation experiments are performed on laboratory induced ablation lesions in ex-vivo tissue. The ultrasound probe is either held by the operator's hand or supported by a robotic arm. We demonstrate the ability to detect and remove non-heat induced tissue motion in both settings. We show that removing extraneous motion helps unmask the effects of heating. Our strain estimation curves closely mirror the temperature changes within the tissue. While previous results in the area of motion compensation were reported for experiments lasting less than 10 seconds, our algorithm was tested on experiments that lasted close to 20 minutes.

A new image processing strategy is detailed for the simultaneous measurement of tumor perfusion and neovascular morphology parameters from a sequence of dynamic contrast-enhanced ultrasound (DCE-US) images. A technique for locally mapping tumor perfusion parameters using skeletonized neovascular data is also introduced. Simulated images were used to test the neovascular skeletonization technique and variance (error) of relevant parametric estimates. Preliminary DCE-US image datasets were collected in 6 female patients diagnosed with invasive breast cancer and using a Philips iU22 ultrasound system equipped with a L9-3 MHz transducer and Definity contrast agent. Simulation data demonstrates that neovascular morphology parametric estimation is reproducible albeit measurement error can occur at a lower signal-to-noise ratio (SNR). Experimental results indicate the feasibility of our approach to performing both tumor perfusion and neovascular morphology measurements from DCE-US images. Future work will expand on our initial clinical findings and also extent our image processing strategy to 3-dimensional space to allow whole tumor characterization.

To reduce the effects of respiratory motion in the quantitative analysis based on liver contrast-enhanced ultrasound (CEUS) image sequencesof single mode. The image gating method and the iterative registration method using model image were adopted to register liver contrast-enhanced ultrasound image sequences of single mode. The feasibility of the proposed respiratory motion correction method was explored preliminarily using 10 hepatocellular carcinomas CEUS cases. The positions of the lesions in the time series of 2D ultrasound images after correction were visually evaluated. Before and after correction, the quality of the weighted sum of transit time (WSTT) parametric images were also compared, in terms of the accuracy and spatial resolution. For the corrected and uncorrected sequences, their mean deviation values (mDVs) of time-intensity curve (TIC) fitting derived from CEUS sequences were measured. After the correction, the positions of the lesions in the time series of 2D ultrasound images were almost invariant. In contrast, the lesions in the uncorrected images all shifted noticeably. The quality of the WSTT parametric maps derived from liver CEUS image sequences were improved more greatly. Moreover, the mDVs of TIC fitting derived from CEUS sequences after the correction decreased by an average of 48.48±42.15. The proposed correction method could improve the accuracy of quantitative analysis based on liver CEUS image sequences of single mode, which would help in enhancing the differential diagnosis efficiency of liver tumors.

In order to detect the pulsatile tissues in neonatal cranial ultrasonic movies by avoiding probe-motion artifact, a time-frequency analysis has been performed in several movie fragments at typical three scenes: (a) a brain-lost, (b) a brain-captured and probe-stabilized, and (c) a brain-captured and probe-swayed ones. The pulsatile tissue, which is a key point of pediatric diagnosis, had successfully detected with an algorithm based on Fourier transform but it had required us to extract the probe-stabilized scene manually by visual observation of the movie. A spatial mean square of echo intensity E_tot and a total AC power P_tot over a fan-shape of field of view were evaluated according to a power spectrum of a time-variation of 64 samples of echo intensity at each pixel in each movie fragment split from actual B-mode ultrasonic movies taken at coronal sections of a neonate. The results revealed that (1) significant low E_tot was found at the brain-lost scene rather than that at the other scenes, and (2) lower P_tot was found at the probe-stabilized scene rather than the probe-swayed ones. This fact strongly suggests that the E_tot and P_tot are promising features for automatic extraction of probe-stabilized scenes. It must lead to detect the pulsatile tissues selectively by avoiding probe-motion artifact and to realize systematic analysis of the whole of our extensive movie archives, which is useful not only for retrospective study of ischemic diseases but also for bedside diagnosis to stabilize the freehand ultrasonic probe.

The objective of the paper is to introduce a novel method for nuchal translucency (NT) boundary detection and thickness measurement, which is one of the most significant markers in the early screening of chromosomal defects, namely Down syndrome. To improve the reliability and reproducibility of NT measurements, several automated methods have been introduced. However, the performance of their methods degrades when NT borders are tilted due to varying fetal movements. Therefore, we propose a principal direction estimation based NT measurement method to provide reliable and consistent performance regardless of both fetal positions and NT directions. At first, Radon Transform and cost function are used to estimate the principal direction of NT borders. Then, on the estimated angle bin, i.e., the main direction of NT, gradient based features are employed to find initial NT lines which are beginning points of the active contour fitting method to find real NT borders. Finally, the maximum thickness is measured from distances between the upper and lower border of NT by searching along to the orthogonal lines of main NT direction. To evaluate the performance, 89 of in vivo fetal images were collected and the ground-truth database was measured by clinical experts. Quantitative results using intraclass correlation coefficients and difference analysis verify that the proposed method can improve the reliability and reproducibility in the measurement of maximum NT thickness.

We report a wave physics-based approach to change detection which can be used to detect anomalies in biological tissues such as cancer lesions from active sensing data. Of particular interest are nonionizing radiation methods such as microwave breast imaging, ultrasound imaging, and diffuse optical tomography. The biological medium surrounding the target of interest, e.g., a tumor, is assumed to be highly nonhomogeneous and reverberating. This implies that there are in general multiple paths for the propagation of wave signals from an interior domain where the target of interest is located to the sensing aperture where the scattered fields are measured. Two physical concepts are used to exploit this rich multipath environment so as to enhance change detection performance: wave time reversal, and the optical theorem which describes energy conservation in scattering phenomena. Previous related work has reported the use of time reversal for breast cancer detection. We use not only time reversal, but also the optical theorem, and propose novel algorithms based on both.

Ultrasound tomography has great potential to provide quantitative estimations of physical properties of breast tumors for accurate characterization of breast cancer. We design and manufacture a new synthetic-aperture breast ultrasound tomography system with two parallel transducer arrays. The distance of these two transducer arrays is adjustable for scanning breasts with different sizes. The ultrasound transducer arrays are translated vertically to scan the entire breast slice by slice and acquires ultrasound transmission and reflection data for whole-breast ultrasound imaging and tomographic reconstructions. We use the system to acquire patient data at the University of New Mexico Hospital for clinical studies. We present some preliminary imaging results of in vivo patient ultrasound data. Our preliminary clinical imaging results show promising of our breast ultrasound tomography system with two parallel transducer arrays for breast cancer imaging and characterization.

The sound-speed distribution of the breast can be used for characterizing breast tumors, because they typically have a higher sound speed than normal breast tissue. This is understood to be the result of remodeling of the extracellular matrix surrounding tumors. Breast sound-speed distribution can be reconstructed using ultrasound bent-ray tomography (USRT). We have recently demonstrated that USRT, using arrival times of both transmission and reflection data, significantly improves image quality. To further improve the robustness of tomographic reconstructions, we develop a USRT method using a modified total-variation (MTV) regularization scheme. Regularization is often used in solving inverse problems by introducing restrictions such as for smoothness. Tikhonov regularization is a widely used regularization scheme that tends to smooth tomographic images, but oversmoothing can obscure critical diagnostic detail such as tumor margins. Total-variation (TV) regularization is another common regularization scheme that preserves tumor margins, but at the cost of increased image noise. Our new USRT with MTV regularization is a Tikhonov-TV hybrid, reducing image noise while preserving margins. We apply our new method to ultrasound transmission data from numerical phantoms, and compare the results with those obtained using Tikhonov regularization.

In these days ultrasound studies of non-invasive diagnostic methods using the elastic property of tissue have showed very promising results. Biological soft tissues are viscoelastic in nature; therefore several recent studies have shown the feasibility of shear wave dispersion in order to express viscosity which is considered to be valid for early diagnoses. Shear wave Dispersion Ultrasound Vibrometry (SDUV) has been conducted under ex vivo and in vivo conditions, which could estimate the value of shear elasticity and viscosity from a 40 x 40 mm² area. In this study, our proposed Multi-line (ML) acoustic radiation force method could map shear elasticity and viscosity at 0.2 x 0.2 mm² pixel in 25.6 mm width and 29.6 mm depth area. ML uses seven focus points in depth to create much planar shear wave than ever, and twenty pushing line to obtain data such a broader area than ever. These sequences contribute to express precise values of shear elasticity and viscosity at each pixel. A 10% gelatin phantom with a 10% gelatin and 1% xanthan gum mixture inclusion was prepared for ML experiment, and one homogenous phantom made of the same concentrations as the background of ML experiments was for ML and SDUV experiments three times to validate. The ML measurement resulted μ₁ = 1.129±0.118 kPa, μ₂ = 0.893±0.090 Pa･s in the 10% gelatin background; their corresponding SDUV measurement were μ₁ = 1.250±0.129 kPa, μ₂ = 0.833±0.098 Pa･s in 10% gelatin phantom. Though further evaluations such as frequency and rheological model are required, the results could show the effectiveness of this proposed method in mapping viscoelasticity and the feasibility of in vivo and ex vivo experiments.

Ultrasound (US) imaging is one of the most popular medical imaging modalities, with 3D US imaging gaining popularity recently due to its considerable advantages over 2D US imaging. However, as it is limited by long acquisition times and the huge amount of data processing it requires, methods for reducing these factors have attracted considerable research interest. Compressed sensing (CS) is one of the best candidates for accelerating the acquisition rate and reducing the data processing time without degrading image quality. However, CS is prone to introduce noise-like artefacts due to random under-sampling. To address this issue, we propose a combined prior-based reconstruction method for 3D US imaging. A Laplacian mixture model (LMM) constraint in the wavelet domain is combined with a total variation (TV) constraint to create a new regularization regularization prior. An experimental evaluation conducted to validate our method using synthetic 3D US images shows that it performs better than other approaches in terms of both qualitative and quantitative measures.

Conventional B-mode ultrasound images suffer from clutter composed of reverberation and aberration that exhibit only partial spatial coherence, making it possible to suppress these confounding signals using coherence- based imaging techniques. Coherence is typically measured by transmitting a focused wave into the tissue and computing the covariance of the returned echo signals across all combinations of receive channel pairs. We mathematically and experimentally prove the equivalence of the coherence measured as a function of transmit channel and as a function of receive channel. This forms the basis for an alternative method of coherence measurement using a synthetic aperture technique to store focused and summed receive channel data as a function of transmit channel. This technique avoids the need for access to individual receive channel data and is compatible with the existing signal pipeline on common commercial clinical scanners. We demonstrate in vivo short-lag spatial coherence imaging of the human liver to produce images with reduced clutter, using an ACUSON SC2000 ultrasound system to acquire data and perform full synthetic aperture focusing. The possibility to trade-off image quality for acquisition time is also presented in an effort to make the proposed sequences more accessible for real-time imaging.