Branched Convolutional Neural Networks for Receiver Channel Recovery in High-Frame-Rate Sparse-Array Ultrasound Imaging.

For high-frame-rate ultrasound imaging, it remains challenging to implement on compact systems as a sparse imaging configuration with limited array channels. One key issue is that the resulting image quality is known to be mediocre not only because unfocused plane-wave excitations are used but also because grating lobes would emerge in sparse-array configurations. In this article, we present the design and use of a new channel recovery framework to infer full-array plane-wave channel datasets for periodically sparse arrays that operate with as few as one-quarter of the full-array aperture. This framework is based on a branched encoder-decoder convolutional neural network (CNN) architecture, which was trained using full-array plane-wave channel data collected from human carotid arteries (59 864 training acquisitions; 5-MHz imaging frequency; 20-MHz sampling rate; plane-wave steering angles between -15° and 15° in 1° increments). Three branched encoder-decoder CNNs were separately trained to recover missing channels after differing degrees of channelwise downsampling (2, 3, and 4 times). The framework's performance was tested on full-array and downsampled plane-wave channel data acquired from an in vitro point target, human carotid arteries, and human brachioradialis muscle. Results show that when inferred full-array plane-wave channel data were used for beamforming, spatial aliasing artifacts in the B-mode images were suppressed for all degrees of channel downsampling. In addition, the image contrast was enhanced compared with B-mode images obtained from beamforming with downsampled channel data. When the recovery framework was implemented on an RTX-2080 GPU, the three investigated degrees of downsampling all achieved the same inference time of 4 ms. Overall, the proposed framework shows promise in enhancing the quality of high-frame-rate ultrasound images generated using a sparse-array imaging setup.

Transrectal ultrasound vector projectile imaging for time-resolved visualization of flow dynamics in the male urethra: A clinical pilot study.

BACKGROUND: Quantitative and comprehensive visualization of urinary flow dynamics in the urethra is crucial for investigating patient-specific mechanisms of lower urinary tract symptoms (LUTS). Although some methods can evaluate the global properties of the urethra, it is critical to assess the local information, such as the location of the responsible lesion and its interactions with urinary flow in relation to LUTS. This approach is vital for enhancing personalized and focal treatments. However, there is a lack of such diagnostic tools that can directly observe how the urethral shape and motion impact urinary flow in the urethra. PURPOSE: This study aimed to develop a novel transrectal ultrasound imaging modality based on the contrast-enhanced urodynamic vector projectile imaging (CE-UroVPI) framework and validate its clinical applicability for visualizing time-resolved flow dynamics in the urethra. METHODS: A new CE-UroVPI system was developed using a research-purpose ultrasound platform and a custom transrectal linear probe, and an imaging protocol for acquiring urodynamic echo data in male patients was designed. Thirty-four male patients with LUTS participated in this study. CE-UroVPI was performed to acquire ultrasound echo signals from the participant's urethra and urinary flow at various voiding phases (initiation, maintenance, and terminal). The ultrasound datasets were processed with custom software to visualize urinary flow dynamics and urethra tissue deformation. RESULTS: The transrectal CE-UroVPI system successfully visualized the time-resolved multidirectional urinary flow dynamics in the prostatic urethra during the initiation, maintenance, and terminal phases of voiding in 17 patients at a frame rate of 1250 fps. The maximum flow speed measured in this study was 2.5 m/s. In addition, when the urethra had an obstruction or an irregular partial deformation, the devised imaging modality visualized complex flow patterns, such as vortices and flow jets around the lesion. CONCLUSIONS: Our study findings demonstrate that the transrectal CE-UroVPI system developed in this study can effectively image fluid-structural interactions in the urethra. This new diagnostic technology has the potential to facilitate quantitative and precise assessments of urethral voiding functions and aid in the improvement of focal and effective treatments for patients with LUTS.

A GPU-Based, Real-Time Dealiasing Framework for High-Frame-Rate Vector Doppler Imaging.

Vector Doppler is well regarded as a potential way of deriving flow vectors to intuitively visualize complex flow profiles, especially when it is implemented at high frame rates. However, this technique's performance is known to suffer from aliasing artifacts. There is a dire need to devise real-time dealiasing solutions for vector Doppler. In this article, we present a new methodological framework for achieving aliasing-resistant flow vector estimation at real-time throughput from precalculated Doppler frequencies. Our framework comprises a series of compute kernels that have synergized: 1) an extended least squares vector Doppler (ELS-VD) algorithm; 2) single-instruction, multiple-thread (SIMT) processing principles; and 3) implementation on a graphical processing unit (GPU). Results show that this new framework, when executed on an RTX-2080 GPU, can effectively generate aliasing-free flow vector maps using high-frame-rate imaging datasets acquired from multiple transmit-receive angle pairs in a carotid phantom imaging scenario. Over the entire cardiac cycle, the frame processing time for aliasing-resistant vector estimation was measured to be less than 16 ms, which corresponds to a minimum processing throughput of 62.5 frames/s. In a human femoral bifurcation imaging trial with fast flow (150 cm/s), our framework was found to be effective in resolving two-cycle aliasing artifacts at a minimum throughput of 53 frames/s. The framework's processing throughput was generally in the real-time range for practical combinations of ELS-VD algorithmic parameters. Overall, this work represents the first demonstration of real-time, GPU-based aliasing-resistant vector flow imaging using vector Doppler estimation principles.

Ultrasound vector flow imaging during veno-arterial extracorporeal membrane oxygenation in a thoracic aorta model.

In veno-arterial extracorporeal membrane oxygenation (VA-ECMO) treatment, the mixing zone is a key hemodynamic factor that determines the efficacy of the treatment. This study aimed to evaluate the applicability of a novel ultrasound technique called vector flow imaging (VFI) for visualizing complex flow patterns in an aorta phantom under VA-ECMO settings. VFI experiments were performed to image aortic hemodynamics under VA-ECMO treatment simulated in an anthropomorphic thoracic aorta phantom using a pulsatile pump (cardiac output: 2.7 L/min) and an ECMO pump with two different flow rates, 0.35 L/min and 1.0 L/min. The cardiac cycle of hemodynamics in the ascending aorta, aortic arch, and descending aorta was visualized, and the spatio-temporal dynamics of flow vectors were analyzed. VFI successfully visualized dynamic flow patterns in the aorta phantom. When the flow rate of the ECMO pump increased, ECMO flow was more dominant than cardiac output in the diastole phase, and the speed of cardiac output was suppressed in the systole phase. Vortex flow patterns were also detected in the ascending aorta and the arch under both ECMO flow rate conditions. The VFI technique may provide new insights into aortic hemodynamics and facilitates effective and safe VA-ECMO treatment.

Deep-learning-assisted and GPU-accelerated vector Doppler imaging with aliasing-resistant velocity estimation.

Vector flow imaging is a diagnostic ultrasound modality that is suited for the visualization of complex blood flow dynamics. One popular way of realizing vector flow imaging at high frame rates over 1000 fps is to apply multi-angle vector Doppler estimation principles in conjunction with plane wave pulse-echo sensing. However, this approach is susceptible to flow vector estimation errors attributed to Doppler aliasing, which is prone to arise when a low pulse repetition frequency (PRF) is inevitably used due to the need for finer velocity resolution or because of hardware constraints. Existing dealiasing solutions tailored for vector Doppler may have high computational demand that makes them unfeasible for practical applications. In this paper, we present the use of deep learning and graphical processing unit (GPU) computing principles to devise a fast vector Doppler estimation framework that is resilient against aliasing artifacts. Our new framework works by using a convolutional neural network (CNN) to detect aliased regions in vector Doppler images and subsequently applying an aliasing correction algorithm only at these affected regions. The framework's CNN was trained using 15,000 in vivo vector Doppler frames acquired from the femoral and carotid arteries, including healthy and diseased conditions. Results show that our framework can perform aliasing segmentation with an average precision of 90 % and can render aliasing-free vector flow maps with real-time processing throughputs (25-100 fps). Overall, our new framework can improve the visualization quality of vector Doppler imaging in real-time.

Efficacy of ultrasound vector flow imaging in tracking omnidirectional pulsatile flow.

BACKGROUND: Ultrasound vector flow imaging (VFI) shows potential as an emerging non-invasive modality for time-resolved flow mapping. However, its efficacy in tracking multidirectional pulsatile flow with temporal resolvability has not yet been systematically evaluated because of the lack of an appropriate test protocol. PURPOSE: We present the first systematic performance investigation of VFI in tracking pulsatile flow in a meticulously designed scenario with time-varying, omnidirectional flow fields (with flow angles from 0° to 360°). METHODS: Ultrasound VFI was performed on a three-loop spiral flow phantom (4 mm diameter; 5 mm pitch) that was configured to operate under pulsatile flow conditions (10 ml/s peak flow rate; 1 Hz pulse rate; carotid pulse shape). The spiral lumen geometry was designed to simulate recirculatory flow dynamics observed in the heart and in curvy blood vessel segments such as the carotid bulb. The imaging sequence was based on steered plane wave pulsing (-10°, 0°, +10° steering angles; 5 MHz imaging frequency; 3.3 kHz interleaved pulse repetition frequency). VFI's pulsatile flow estimation performance and its ability to detect secondary flow were comparatively assessed against flow fields derived from computational fluid dynamics (CFD) simulations that included consideration of fluid-structure interactions (FSI). The mean percentage error (MPE) and the coefficient of determination (R2 ) were computed to assess the correspondence of the velocity estimates derived from VFI and CFD-FSI simulations. In addition, VFI's efficacy in tracking pulse waves was analyzed with respect to pressure transducer measurements made at the phantom's inlet and outlet. RESULTS: Pulsatile flow patterns rendered by VFI agreed with the flow profiles computed from CFD-FSI simulations (average MPE: -5.3%). The shape of the VFI-measured velocity magnitude profile generally matched the inlet flow profile. High correlation exists between VFI measurements and simulated flow vectors (lateral velocity: R2  = 0.8; axial velocity R2  = 0.89; beam-flow angle: R2  = 0.98; p < 0.0001 for all three quantities). VFI was found to be capable of consistently tracking secondary flow. It also yielded pulse wave velocity (PWV) estimates (5.72 ± 1.02 m/s) that, on average, are within 6.4% of those obtained from pressure transducer measurements (6.11 ± 1.15 m/s). CONCLUSION: VFI can consistently track omnidirectional pulsatile flow on a time-resolved basis. This systematic investigation serves well as a quality assurance test of VFI.

Time-Resolved Wall Shear Rate Mapping Using High-Frame-Rate Ultrasound Imaging.

In atherosclerosis, low wall shear stress (WSS) is known to favor plaque development, while high WSS increases plaque rupture risk. To improve plaque diagnostics, WSS monitoring is crucial. Here, we propose wall shear imaging (WASHI), a noninvasive contrast-free framework that leverages high-frame-rate ultrasound (HiFRUS) to map the wall shear rate (WSR) that relates to WSS by the blood viscosity coefficient. Our method measures WSR as the tangential flow velocity gradient along the arterial wall from the flow vector field derived using a multi-angle vector Doppler technique. To improve the WSR estimation performance, WASHI semiautomatically tracks the wall position throughout the cardiac cycle. WASHI was first evaluated with an in vitro linear WSR gradient model; the estimated WSR was consistent with theoretical values (an average error of 4.6% ± 12.4 %). The framework was then tested on healthy and diseased carotid bifurcation models. In both scenarios, key spatiotemporal dynamics of WSR were noted: 1) oscillating shear patterns were present in the carotid bulb and downstream to the internal carotid artery (ICA) where retrograde flow occurs; and 2) high WSR was observed particularly in the diseased model where the measured WSR peaked at 810 [Formula: see text] due to flow jetting. We also showed that WASHI could consistently track arterial wall motion to map its WSR. Overall, WASHI enables high temporal resolution mapping of WSR that could facilitate investigations on causal effects between WSS and atherosclerosis.

Unfocused Field Analysis of a Density-Tapered Spiral Array for High-Volume-Rate 3-D Ultrasound Imaging.

Spiral array transducers with a sparse 2-D aperture have demonstrated their potential in realizing 3-D ultrasound imaging with reduced data rates. Nevertheless, their feasibility in high-volume-rate imaging based on unfocused transmissions has yet to be established. From a metrology standpoint, it is essential to characterize the acoustic field of unfocused transmissions from spiral arrays not only to assess their safety but also to identify the root cause of imaging irregularities due to the array's sparse aperture. Here, we present a field profile analysis of unfocused transmissions from a density-tapered spiral array transducer (256 hexagonal elements, 220- [Formula: see text] element diameter, and 1-cm aperture diameter) through both simulations and hydrophone measurements. We investigated plane- and diverging-wave transmissions (five-cycle, 7.5-MHz pulses) from 0° to 10° steering for their beam intensity characteristics and wavefront arrival time profiles. Unfocused firings were also tested for B-mode imaging performance (ten compounded angles, -5° to 5° span). The array was found to produce unfocused transmissions with a peak negative pressure of 93.9 kPa at 2 cm depth. All transmissions steered up to 5° were free of secondary lobes within 12 dB of the main beam peak intensity. All wavefront arrival time profiles were found to closely match the expected profiles with maximum root-mean-squared errors of [Formula: see text] for plane wave (PW) and [Formula: see text] for diverging wave. The B-mode images showed good spatial resolution with a penetration depth of 22 mm in PW imaging. Overall, these results demonstrate that the density-tapered spiral array can facilitate unfocused transmissions below regulatory limits (mechanical index: 0.034; spatial-peak, pulse-average intensity: 0.298 W/cm2) and with suppressed secondary lobes while maintaining smooth wavefronts.

Minimizing Image Quality Loss After Channel Count Reduction for Plane Wave Ultrasound via Deep Learning Inference.

High-frame-rate ultrasound imaging uses unfocused transmissions to insonify an entire imaging view for each transmit event, thereby enabling frame rates over 1000 frames per second (fps). At these high frame rates, it is naturally challenging to realize real-time transfer of channel-domain raw data from the transducer to the system back end. Our work seeks to halve the total data transfer rate by uniformly decimating the receive channel count by 50% and, in turn, doubling the array pitch. We show that despite the reduced channel count and the inevitable use of a sparse array aperture, the resulting beamformed image quality can be maintained by designing a custom convolutional encoder-decoder neural network to infer the radio frequency (RF) data of the nullified channels. This deep learning framework was trained with in vivo human carotid data (5-MHz plane wave imaging, 128 channels, 31 steering angles over a 30° span, and 62 799 frames in total). After training, the network was tested on an in vitro point target scenario that was dissimilar to the training data, in addition to in vivo carotid validation datasets. In the point target phantom image beamformed from inferred channel data, spatial aliasing artifacts attributed to array pitch doubling were found to be reduced by up to 10 dB. For carotid imaging, our proposed approach yielded a lumen-to-tissue contrast that was on average within 3 dB compared to the full-aperture image, whereas without channel data inferencing, the carotid lumen was obscured. When implemented on an RTX-2080 GPU, the inference time to apply the trained network was 4 ms, which favors real-time imaging. Overall, our technique shows that with the help of deep learning, channel data transfer rates can be effectively halved with limited impact on the resulting image quality.

Quantitative Blood Flow Measurements in the Common Carotid Artery: A Comparative Study of High-Frame-Rate Ultrasound Vector Flow Imaging, Pulsed Wave Doppler, and Phase Contrast Magnetic Resonance Imaging.

V Flow is commercially developed by high-frame-rate ultrasound vector flow imaging. Compared to conventional color Doppler, V Flow is angle-independent and is capable of measuring both the magnitude and the direction of blood flow velocities. This paper aims to investigate the differences between V Flow and pulsed wave Doppler (PW) relative to phase contrast magnetic resonance imaging (PC-MRI), for the quantitative measurements of blood flow in common carotid arteries (CCA) and, consequently, to evaluate the accuracy of the new technique, V Flow. Sixty-four CCAs were measured using V Flow, PW, and PC-MRI. The maximum velocities, time-averaged mean (TAMEAN) velocities, and volume flow were measured using different imaging technologies. The mean error with standard deviation (Std), the median of absolute errors, and the r-values between V Flow and PC-MRI results for the maximum velocity, the TAMEAN velocity, and the volume flow measurements are {9.40% ± 14.91%; 11.84%; 0.84}, {21.52% ± 14.46%; 19.28%; 0.86}, and {-2.80% ± 14.01%; 10.38%; 0.7}, respectively, and are {53.44% ± 29.68%; 49.79%; 0.74}, {27.83% ± 31.60%; 23.83; 0.71}, and {21.01% ± 29.64%; 25.48%; 0.34}, respectively, for those between PW and PC-MRI. The boxplot, linear regression and Bland-Altman plots were performed for each comparison, which illustrated that the results measured via V Flow rather than via PW agreed more closely with those measured via PC-MRI.

Vascular Imaging in Small Animals Using Clinical Ultrasound Scanners.

Conventional ultrasound with frequency (2-15 MHz) has been a global diagnostic and therapeutic tool in clinical medicine, and high-frequency ultrasound (>30 MHz) has been a powerful investigative device for preclinical studies such as cardiovascular research. In this chapter, we describe the use of conventional ultrasound with a 2.5-10 MHz transducer as an investigative device for the measurement/detection of blood flow in rabbit model. The chapter will describe the procedures for the preparation of sonographer, imaging locations, and the details of the rabbits used as well as detailed imaging steps for the preoperative, immediately after operation, and postoperative follow-up ultrasound for vascular surgery, using a vascular graft implantation as an example. We also provide useful notes to avoid pitfalls for successful imaging. The overall goal of this chapter is to deliver the steps in using low-cost, non-invasive, and highly versatile clinical ultrasound imaging in preclinical small animal testing.

Helical toroid phantom for 3D flow imaging investigations.

The medical physics community has hitherto lacked an effective calibration phantom to holistically evaluate the performance of three-dimensional (3D) flow imaging techniques. Here, we present the design of a new omnidirectional, three-component (3-C) flow phantom whose lumen is consisted of a helical toroid structure (4 mm lumen diameter; helically winded for 5 revolutions over a torus with 10 mm radius; 5 mm helix radius). This phantom's intraluminal flow trajectory embraces all combinations of x, y, and z directional components, as confirmed using computational fluid dynamics (CFD) simulations. The phantom was physically fabricated via lost-core casting with polyvinyl alcohol cryogel (PVA) as the tissue mimic. 3D ultrasound confirmed that the phantom lumen expectedly resembled a helical toroid geometry. Pulsed Doppler measurements showed that the phantom, when operating under steady flow conditions (3 ml s-1 flow rate), yielded flow velocity magnitudes that agreed well with those derived from CFD at both the inner torus (-47.6 ± 5.7 versus -52.0 ± 2.2 cm s-1; mean ± 1 S.D.) and the outer torus (49.5 ± 4.2 versus 48.0 ± 1.7 cm s-1). Additionally, 3-C velocity vectors acquired from multi-angle pulsed Doppler showed good agreement with CFD-derived velocity vectors (<7% and 10° difference in magnitude and flow angle, respectively). Ultrasound color flow imaging further revealed that the phantom's axial flow pattern was aligned with the CFD-derived flow profile. Overall, the helical toroid phantom has strong potential as an investigative tool in 3D flow imaging innovation endeavors, such as the development of flow vector estimators and visualization algorithms.

A Deep Learning Approach to Resolve Aliasing Artifacts in Ultrasound Color Flow Imaging.

Despite being used clinically as a noninvasive flow visualization tool, color flow imaging (CFI) is known to be prone to aliasing artifacts that arise due to fast blood flow beyond the detectable limit. From a visualization standpoint, these aliasing artifacts obscure proper interpretation of flow patterns in the image view. Current solutions for resolving aliasing artifacts are typically not robust against issues such as double aliasing. In this article, we present a new dealiasing technique based on deep learning principles to resolve CFI aliasing artifacts that arise from single- and double-aliasing scenarios. It works by first using two convolutional neural networks (CNNs) to identify and segment CFI pixel positions with aliasing artifacts, and then it performs phase unwrapping at these aliased pixel positions. The CNN for aliasing identification was devised as a U-net architecture, and it was trained with in vivo CFI frames acquired from the femoral bifurcation that had known presence of single- and double-aliasing artifacts. Results show that the segmentation of aliased CFI pixels was achieved successfully with intersection over union approaching 90%. After resolving these artifacts, the dealiased CFI frames consistently rendered the femoral bifurcation's triphasic flow dynamics over a cardiac cycle. For dealiased CFI pixels, their root-mean-squared difference was 2.51% or less compared with manual dealiasing. Overall, the proposed dealiasing framework can extend the maximum flow detection limit by fivefold, thereby improving CFI's flow visualization performance.

Contrast-Enhanced Urodynamic Vector Projectile Imaging (CE-UroVPI) for Urethral Voiding Visualization: Principles and Phantom Studies.

OBJECTIVE: To devise a new urodynamic imaging framework that can provide time-resolved visualization of urinary flow and urethral deformation during the initiation phase of voiding. MATERIALS AND METHODS: Contrast-enhanced urodynamic vector projectile imaging (CE-UroVPI) was devised using the principles of high-frame rate ultrasound, microbubble contrast agents, and flow vector mapping. CE-UroVPI was implemented using a research-purpose ultrasound scanner (5 MHz frequency) and commercial contrast agents (USphere Prime). The performance of CE-UroVPI was evaluated using 2 custom-designed deformable urethra phantoms - a healthy model and a diseased model with benign prostatic hyperplasia (BPH) - that respectively simulate urodynamics in the urinary tract with and without mechanical obstruction. The corresponding spatiotemporal urodynamics were investigated and analyzed. RESULTS: Using a frame rate of 1,250 fps that corresponds to 0.8 ms time resolution, CE-UroVPI effectively depicted the transient urodynamic events during the initiation phase of voiding. Anomalous spatiotemporal characteristics were observed in the urodynamics of the BPH-obstructed urethra. Specifically, upstream from the obstruction site, a transient surge in flow speed was observed in the first 100 ms of voiding. Also, downstream from the obstruction site, complex urodnyamics had emerged in the forms of flow jet and vortices. These anomalies were not found in the healthy urethra. CONCLUSION: CE-UroVPI is the first imaging framework that can visualize complex urodynamics over an entire voiding episode including its initiation phase. This new tool may be used to potentially gain new insight into the causal relationships between urethral morphokinetic factors and lower urinary tract symptoms.

Ultrasound vector projectile imaging for detection of altered carotid bifurcation hemodynamics during reductions in cardiac output.

PURPOSE: Complex blood flow is commonly observed in the carotid bifurcation, although the factors that regulate these patterns beyond arterial geometry are unknown. The emergence of high-frame-rate ultrasound vector flow imaging allows for noninvasive, time-resolved analysis of complex hemodynamic behavior in humans, and it can potentially help researchers understand which physiological stressors can alter carotid bifurcation hemodynamics in vivo. Here, we seek to pursue the first use of vector projectile imaging (VPI), a dynamic form of vector flow imaging, to analyze the regulation of carotid bifurcation hemodynamics during experimental reductions in cardiac output induced via a physiological stressor called lower body negative pressure (LBNP). METHODS: Seven healthy adults (age: 27 ± 4 yr, 4 men) underwent LBNP at -45 mmHg to simulate a postural hemodynamic response in a controlled environment. Using a research-grade, high-frame-rate ultrasound platform, vector flow estimation in each subject's right carotid bifurcation was performed through a multi-angle plane wave imaging (two transmission angles of 10° and -10°) formulation, and VPI cineloops were generated at a frame rate of 750 fps. Vector concentration was quantified by the resultant blood velocity vector angles within a region of interest; lower concentration indicated greater flow dispersion. Discrete concentration values during peak and late systole were compared across different segments of the carotid artery bifurcation before, and during, LBNP. RESULTS: Vector projectile imaging revealed that external and internal carotid arteries exhibited regional hemodynamic changes during LBNP, which acted to reduce both the subject's cardiac output (Δ - 1.2 ± 0.5 L/min, -19%; P < 0.01) and peak carotid blood velocity (Δ - 6.30 ± 8.27 cm/s, -7%; P = 0.05). In these carotid artery branches, the vector concentration time trace before and during LBNP were observed to be different. The impact of LBNP on flow complexity in the two carotid artery branches showed variations between subjects. CONCLUSIONS: Using VPI, intuitive visualization of complex hemodynamic changes can be obtained in healthy humans subjected to LBNP. This imaging tool has potential for further applications in vascular physiology to identify and quantify complex hemodynamic features in humans during different physiological stressor tests that regulate hemodynamics.

Case Studies in Physiology: Visualization of blood recirculation in a femoral artery "trifurcation" using ultrasound vector flow imaging.

The femoral bifurcation is typically composed of a common femoral artery that bifurcates into the superficial (SFA) and deep (DFA) femoral arteries, with the lateral circumflex femoral artery (LCFA) branching distal to the origin of the DFA. We report a unique case of a 22-yr-old woman with a femoral "trifurcation," where the origin of the LCFA coincides with the origin of the DFA, resulting in a true three-way branching of the common femoral artery. We characterized the complex hemodynamics of the trifurcation region with ultrasound vector flow imaging at rest, and during 80 mmHg cuff compression of the calf to induce greater oscillatory blood flow. At rest, a clear trifurcation is observed with color Doppler imaging, while vector flow imaging further revealed a large area of flow circulation proximal to the LCFA and DFA. Cuff compression reduced SFA blood flow to 0 cm3/min, characterized by almost constant retrograde blood flow throughout diastole. When visualized with vector flow imaging, diastolic retrograde blood flow from the SFA appeared to reperfuse the DFA and LCFA during late systole, eliminating the retrograde flow component and providing a secondary source of anterograde blood flow to the thigh. In a rare case of a femoral trifurcation, we demonstrate blood recirculation patterns at rest, as well as collateral retrograde blood flow redistribution during lower limb compression. While it is unknown whether these trifurcation findings extend to typical bifurcations, it is evident that advanced methods of blood flow characterization are necessary to visualize and study complex vascular regions.NEW & NOTEWORTHY A femoral "trifurcation" is observed when the lateral circumflex femoral artery has an atypical proximal origin, branching at the same level as the superficial and deep femoral arteries. Ultrasound vector flow imaging at 750 fps was able to reveal substantial blood recirculation within the trifurcation at rest, as well as unique redistribution of blood flow between downstream branches during external cuff manipulation of retrograde flow, indicating novel ways in which diastolic blood flow is controlled.

Deformable phantoms of the prostatic urinary tract for urodynamic investigations.

PURPOSE: Assessment of urethral dynamics is clinically regarded to be important in analyzing the functional impact of pathological features like urethral obstruction, albeit it is difficult to perform directly in vivo. To facilitate such an assessment, urethra phantoms may serve well as investigative tools by reconstructing urethral dynamics based on anthropomorphic factors. Here, our aim is to design a new class of anatomically realistic, deformable urethra phantoms that can simulate the geometric, mechanical, and hydrodynamic characteristics of the male prostatic urethra. METHODS: A new lost-core tube casting protocol was devised. It first involved the drafting of urethra geometry in computer-aided design software. Next, 3D printing was used to fabricate the urethra geometry and an outer mold. These parts were then used to cast a urinary tract using a polyvinyl alcohol (PVA)-based material (with 26.6 ± 4.0 kPa Young's elastic modulus). After forming a surrounding tissue-mimicking slab using an agar-gelatin mixture (with 17.4 ± 3.4 kPa Young's modulus), the completed urethra phantom was connected to a flow circuit that simulates voiding. To assess the fabricated phantoms' morphology, ultrasound imaging was performed over different planes. Also, color Doppler imaging was performed to visualize the flow profile within the urinary tract. RESULTS: Deformable phantoms were devised for the normal urethra and a diseased urethra with obstruction due to benign prostatic hyperplasia (BPH). During voiding, the short-axis lumen diameter at the verumontanum of the BPH-featured phantom (0.91 ± 0.08 mm) was significantly smaller than that for the normal phantom (2.49 ± 0.20 mm). Also, the maximum flow velocity of the BPH-featured phantom (59.3 ± 5.8 cm/s; without Doppler angle correction) was found to be higher than that of the normal phantom (22.7 ± 9.0 cm/s). CONCLUSION: The fabricated phantoms were effective in simulating urethra deformation resulting from urine passage during voiding. They can be used for mechanistic studies of urethral dynamics and for the testing of urodynamic diagnostic techniques in urology.

High frame rate doppler ultrasound bandwidth imaging for flow instability mapping.

PURPOSE: Flow instability has been shown to contribute to the risk of future cardiovascular and cerebrovascular events. Nonetheless, it is challenging to noninvasively detect and identify flow instability in blood vessels. Here, we present a new framework called Doppler ultrasound bandwidth imaging (DUBI) that uses high-frame-rate ultrasound and Doppler bandwidth analysis principles to assess flow instability within an image view. METHODS: Doppler ultrasound bandwidth imaging seeks to estimate the instantaneous Doppler bandwidth based on autoregressive modeling at every pixel position of data frames acquired from high-frame-rate plane wave pulsing. This new framework is founded upon the principle that flow instability naturally gives rise to a wide range of flow velocities over a sample volume, and such velocity range in turn yields a larger Doppler bandwidth estimate. The ability for DUBI to map unstable flow was first tested over a range of fluid flow conditions (ranging from laminar to turbulent) with a nozzle-flow phantom. As a further demonstration, DUBI was applied to assess flow instability in healthy and stenosed carotid bifurcation phantoms. RESULTS: Nozzle-flow phantom results showed that DUBI can effectively detect and visualize the difference in Doppler bandwidth magnitude (increased from 2.1 to 5.2 kHz) at stable and unstable flow regions in an image view. Receiver operating characteristic analysis also showed that DUBI can achieve optimal sensitivity and specificity of 0.72 and 0.83, respectively. In the carotid phantom experiments, differences were observed in the spatiotemporal dynamics of Doppler bandwidth over a cardiac cycle. Specifically, as the degree of stenosis increased (from 50% to 75%), DUBI showed an increase in Doppler bandwidth magnitude from 1.4 kHz in the healthy bifurcation to 7.7 kHz at the jet tail located downstream from a 75% stenosis site, thereby indicating flow perturbation in the stenosed bifurcations. CONCLUSION: DUBI can detect unstable flow. This new technique can provide useful hemodynamic information that may aid clinical diagnosis of atherosclerosis.

Live Ultrasound Color-Encoded Speckle Imaging Platform for Real-Time Complex Flow Visualization In Vivo.

Complex flow patterns are prevalent in the vasculature, but they are difficult to image noninvasively in real time. This paper presents the first real-time scanning platform for a high-frame-rate ultrasound technique called color-encoded speckle imaging (CESI) and its use in visualizing arterial flow dynamics in vivo. CESI works by simultaneously rendering flow speckles and color-coded flow velocity estimates on a time-resolved basis. Its live implementation was achieved by integrating a 192-channel programmable ultrasound front-end module, a 4.8-GB/s capacity data streaming link, and a series of computing kernels implemented on the graphical processing unit (GPU) for beamforming and Doppler processing. A slow-motion replay mode was also included to offer coherent visualization of CESI frames acquired at high frame rate [3000 frames per second (fps) in our experiments]. The live CESI scanning platform was found to be effective in facilitating real-time image guidance (at least 20 fps for live video display with 55-fps GPU processing throughout). In vivo pilot trials also showed that live CESI, when running in replay mode, can temporally resolve triphasic flow at the brachial bifurcation and can reveal flow dynamics in the brachial vein during a fist-clenching maneuver. Overall, live CESI has potential for use in routine investigations in vivo that seek to identify complex flow dynamics in real time and relate these dynamics to vascular physiology.

Ultrasound Imaging and Measurement of Choroidal Blood Flow.

PURPOSE: The choroid is a vascular network providing the bulk of the oxygen and nutrient supply to the retina and may play a pivotal role in retinal disease pathogenesis. While optical coherence tomography angiography provides an en face depiction of the choroidal vasculature, it does not reveal flow dynamics. In this report, we describe the use of plane-wave ultrasound to image and characterize choroidal blood flow. METHODS: We scanned both eyes of 12 healthy subjects in a horizontal plane superior to the optic nerve head using an 18-MHz linear array. Plane-wave data were acquired over 10 transmission angles that were coherently compounded to produce 1000 images/sec for 3 seconds. These data were processed to produce a time series of power Doppler images and spectrograms depicting choroidal flow velocity. Analysis of variance was used to characterize peak systolic, and end diastolic velocities and resistive index, and their variability between scans, eyes, and subjects. RESULTS: Power Doppler images showed distinct arterioles within a more diffuse background. Choroidal flow was moderately pulsatile, with peak systolic velocity averaging approximately 10 mm/sec and resistive index of 0.55. There was no significant difference between left and right eyes, but significant variation among subjects. CONCLUSIONS: Plane-wave ultrasound visualized individual arterioles and allowed measurement of flow over the cardiac cycle. Characterization of choroidal flow dynamics offers a novel means for assessment of the choroid's role in ocular disease. TRANSLATIONAL RELEVANCE: Characterization of choroidal flow dynamics offers a novel means for assessment of the choroid's role in ocular disease.