Flow Phantom Research Articles

Visualization of two-dimensional transverse blood flow direction using optical coherence tomography angiography.

.Significance: Evaluation of vessel patency and blood flow direction is important in various medical situations, including diagnosis and monitoring of ischemic diseases, and image-guided vascular surgeries. While optical coherence tomography angiography (OCTA) is the most widely used functional extension of optical coherence tomography that visualizes three-dimensional vasculature, inability to provide information of blood flow direction is one of its limitations.Aim: We demonstrate two-dimensional (2D) transverse blood flow direction imaging in en face OCTA.Approach: A series of triangular beam scans for the fast axis was implemented in the horizontal direction for the first volume scan and in the vertical direction for the following volume scan, and the inter A-line OCTA was performed for the blood flow direction imaging while the stepwise pattern was used for each slow axis scan. The decorrelation differences between the forward and the backward inter A-line OCTA were calculated for the horizontal and the vertical fast axis scans, and the ratio of the horizontal and the vertical decorrelation differences was utilized to show the 2D transverse flow direction information.Results: OCTA flow direction imaging was verified using flow phantoms with various flow orientations and speeds, and we identified the flow speed range relative to the scan speed for reliable flow direction measurement. We demonstrated the visualization of 2D transverse blood flow orientations in mouse brain vascular networks in vivo.Conclusions: The proposed OCTA imaging technique that provides information of 2D transverse flow direction can be utilized in various clinical applications and preclinical studies.

Abstract 14534: In vitro Assessment of Transvalvular Peak Velocity Measurement for Various Orifice Shapes: Comparison Between 4D Flow MRI vs. Doppler Echocardiography

Introduction: 4D flow MRI can assess transvalvular velocity, but validation against continuous wave (CW) Doppler echo is limited in high-velocity regurgitation and stenosis situations. We sought to compare 4D flow MRI and echo peak velocity using a pulsatile echo-MRI flow phantom. Materials and Methods: An MRI-compatible flow phantom with restrictive orifice situated was driven by a left ventricular assist device at 50 bpm (figure 1A). Three orifice shapes were tested: circular, elliptical and 3D-printed patient-specific mitral regurgitant orifice model of prolapse with areas of 0.5, 0.41 and 0.35 cm 2 , respectively. CW Doppler was acquired with peak velocity extracted from the profile. Retrospectively-gated 4D flow MRI was performed (spatial resolution = 2 mm isotropic, temporal resolution = 36 ms, encoding velocity = 400 cm/s). Maximal velocity magnitude was extracted volumetrically (figure 1B). An echo-mimicking profile was also obtained with a “virtual” ultrasound beam in the 4D flow data to simulate CW Doppler (figure 1C). Bland-Altman analysis was used to assess the agreement of temporal peak velocities. Results: 4D flow MRI demonstrated a centrally directed jet for the circular and elliptical orifices and an oblique jet for the prolapse orifice (figure 1B). Peak velocities were in excellent agreement between 4D flow MRI vs. echo for the circular (peak: 5.13 vs. 5.08 m/s, bias = 0.06 ± 0.66 m/s, figure 1D) and the elliptical orifice (peak: 4.95 vs. 4.79 m/s, bias = 0.07 ± 0.87 m/s, figure 1E). The prolapse orifice velocity was underestimated somewhat by MRI by ~10% (peak: 4.41 vs. 4.90 m/s, bias=0.26±1.18, figure 1F). Conclusion: 4D flow MRI can quantify high velocities like echo for simple geometries while underestimating for more complex geometry, likely due to partial volume effects. Further investigation is warranted to systematically investigate the effects of 4D flow MRI spatial and temporal resolution as well as the jet angle on velocity quantification accuracy.

H-scan Subtraction Doppler Imaging: A Novel Ultrasound Small Blood Vessel Flow Characterization with Scattering and Reflection Identification

Ultrafast compound Doppler imaging (UCDI), which can be used to acquire Doppler information at very high spatial and temporal sampling rates, provides a great improvement to the characterization of the vasculature. The singular value decomposition (SVD) technique takes advantage of the different features of tissue and blood motion in terms of spatiotemporal coherence and strongly outperforms conventional clutter rejection filters in small animals. However, a major challenge of conventional UCDI with SVD clutter filtering for small vessel imaging is that it is not sensitive enough to detect the hemodynamic changes in deep tissue where the majority of the remaining signal is usually noise-saturated. In this study, with the first attempt to apply ultrasonic tissue characterization techniques to UCDI, we propose an H-scan subtraction Doppler imaging method to bypass the limitations associated with the high-order singular value thresholding selection and improve the image quality of fine vessels. The flow phantom experiments with different blood concentrations show that H-Scan is capable of estimating the relative size and spatial distribution of acoustic scattering objects. In the in vivo rabbit brain experiment, the H-Doppler method, together with the global and block-wise local SVD clutter filtering, are proposed to facilitate better power Doppler images with a significant improvement of background noise suppression. These results demonstrate that the contrast-to-noise-ratio (CNR) of the H-scan subtraction Doppler imaging is 15% to 65% higher than that of the conventional UCDI methods. Therefore, this approach can be potentially applied to the clinical applications of the functional ultrasound (fUS) imaging method.

Retrospective Transmit Beamforming and Coherent Plane-Wave Compounding for Microvascular Doppler Imaging: A Comparison Study.

Imaging blood flow in small vessels is of great clinical value for evaluating increased vascularization, potentially related to angiogenesis in cancer or inflammation processes in musculoskeletal disease. Using a traditional duplex imaging approach, a major challenge in color Doppler imaging is the limited amount of samples available for clutter filtering. Coherent plane-wave compounding (CPWC) enables a continuous high frame rate acquisition and improved image quality due to dynamic transmit focusing. However, the presence of moving scatterers in the image can lead to a loss in signal-to-noise ratio (SNR) and contrast. In this study, typical CPWC sequences for low-flow imaging were compared with retrospective transmit beamforming (RTB) sequences with similar frame rates and transmit power. The comparison was based on resolution, contrast, and SNR, using a stationary phantom, a flow phantom, a thread phantom, and in vivo recordings of blood vessels in the thyroid and kidney. A model was developed to estimate the difference in SNR between RTB and CPWC in the presence of static and moving scatterers while varying the transmit sequence parameters. The model predicted that RTB may yield an increased SNR compared with CPWC, especially for flow imaging, where the SNR difference reached 6 dB for a maximum velocity of 15 cm/s. The measured SNR values were in agreement with the predicted values, both in the case of stationary scatterers and for the flow phantom. We further demonstrated that reducing beam density to increase frame rate is associated with spatial undersampling (stripe) artifacts for RTB and grating lobes for CPWC. Both phantom and in vivo results indicate that transmit focusing may be beneficial in a low-flow imaging setup that, combined with adaptive clutter filtering, can yield superior microvascular imaging.

A dynamic bolus phantom for the evaluation of the spatio-temporal resolution of MPI scanners

Magnetic particle imaging (MPI) is a tomographic imaging method to determine the spatial distribution of magnetic nanoparticles (MNP) within a defined volume. To evaluate the spatio-temporal resolution of existing MPI scanners, enabling the consistent comparison of the performance of different scanner setups, we developed dynamic MPI measurement phantoms based on segmented flow. These segmented flow phantoms comprise a defined bolus of ferrofluid tracer material, which can be pumped through a tube system with defined velocities. Using a hydrophobic organic carrier oil, cylindrically shaped boluses of different diameter, length, and flow velocity can be emulated. Moving boluses were imaged by different MPI scanner types and the correlation of spatial resolution und velocity of the bolus was investigated. For all bolus dimension and flow velocity combinations investigated, we observed a decreasing spatial resolution and increasing blurring for increasing bolus velocity and decreasing bolus volume.

Two-dimensional iterative projection method for subsample speckle tracking of ultrasound images.

Speckle tracking provides robust motion estimation necessary to create accurate post-processed images. These methods are known to be less accurate in the lateral dimension compared with the axial dimension due to the limitations on the lateral resolution of ultrasound scanning. This paper proposes a two-dimensional iterative projection (TDIP) algorithm using the Riesz transform to generate the analytic signals. The TDIP is an improvement to an already accurate speckle tracking algorithm called the phase coupled (PC) method. The PC method projects the intersection of gradients on the correlation map to the zero phase contour to estimate displacement. The TDIP method performs iterative projections and uses the aggregate of these projected locations to estimate the motion, in addition to rejecting inaccurate projections by checking them against the aggregate projection location. The TDIP additionally adopts the Riesz transform to generate two-dimensional analytic signals to improve lateral accuracy. The Riesz transform is a multidimensional extension of the Hilbert transform into the nD Euclidean space and therefore can be used to include data in both axial and lateral dimensions as opposed to the commonly used Hilbert transform which is one dimensional. The accuracy of the TDIP is quantitatively proven on simulated datasets from the Field II simulation program and on experimental data from two flow phantoms. At all cases, the TDIP is more accurate than the PC algorithm at two-dimensional displacement estimation. Graphical Abstract The lateral estimates from the Phase Coupled algorithm. This method uses the Hilbert transform for the analytic signal. There is large estimated motion within the flow blockage bounded by the red, fin shape in the center of the flow channel. The flow channel itself is also bounded by dashed, red lines. Graphical Abstract The lateral estimates from the TDIP method. This method is not tracking motion within the blockage in the center of the flow channel. The channel and the blockage are both bounded by dashed, red lines.

Automated vessel diameter quantification and vessel tracing for OCT angiography.

Optical coherence tomography angiography (OCTA) is capable of non-invasively imaging the vascular networks within circulatory tissue beds in vivo. Following improvements in OCTA image quality, it is now possible to extract vascular parameters from imaging data to potentially facilitate the diagnosis and treatment of human disease. In this paper, we present a method for automated mapping of vessel diameter down to the individual capillary level, through gradient-guided minimum radial distance (MRD). During validation using well-characterized microfluidic flow phantoms, this method demonstrated superior consistency and a nearly threefold decrease in error when compared to currently accepted techniques. In addition, the MRD technique exhibited a high tolerance to rotation of the vasculature pattern. We also incorporated a modified A* path searching algorithm to trace vessel branches and calculate the diameter of each branch from the OCTA images. After validation in vitro, we applied these algorithms to the in vivo setting through analysis of mouse cortical vasculature. Our algorithm returned results that followed Murray's law, until reaching the capillary level, agreeing well with known physiological data. From our tracing process, vessel tortuosity and branching angle could also be measured. Our techniques provide a platform for the automated evaluation of the vasculature and may aid in diagnosis of vascular diseases, especially those resulting in regional early-stage morphological changes.

Semi-automated shear stress measurements in developing embryonic hearts.

Blood-induced shear stress influences gene expression. Abnormal shear stress patterns on the endocardium of the early-stage heart tube can lead to congenital heart defects. To have a better understanding of these mechanisms, it is essential to include shear stress measurements in longitudinal cohort studies of cardiac development. Previously reported approaches are computationally expensive and nonpractical when assessing many animals. Here, we introduce a new approach to estimate shear stress that does not rely on recording 4D image sets and extensive post processing. Our method uses two adjacent optical coherence tomography frames (B-scans) where lumen geometry and flow direction are determined from the structural data and the velocity is measured from the Doppler OCT signal. We validated our shear stress estimate by flow phantom experiments and applied it to live quail embryo hearts where observed shear stress patterns were similar to previous studies.

Improvement of Decorrelation-Based OCT Angiography by an Adaptive Spatial-Temporal Kernel in Monitoring Stimulus-Evoked Hemodynamic Responses.

Complex decorrelation-based OCT angiography (OCTA) has the potential for monitoring hemodynamic activities in a label-free, high-resolution, and quantitative manner. To improve the measurement dynamic range and uncertainty of blood flow, an adaptive spatial-temporal (ST) kernel was proposed for decorrelation estimation and it was validated through a theoretical simulation and experimental measurements. The ensemble size in the decorrelation computation was effectively enlarged by collecting samples of the phasor pair in both the spatial and temporal dimensions. The spatial sub-kernel size was adaptively changed to suppress the influence of bulk motion in the temporal dimension by solving a maximum entropy model. Using the flow phantom, it was observed that the decorrelation dynamic range presented an increase of ~49% and the uncertainty exhibited a decrease of ~40% and ~38% in the saturation and background limits, respectively. In monitoring the stimulus-evoked hemodynamic response, the extended dynamic range enabled an improvement of ~180% in the separability between different stimulation modes. Furthermore, the suppressed uncertainty and motion artifacts allowed a reliable temporal analysis of the hemodynamic response. The proposed adaptive ST-kernel will greatly promote the development of decorrelation-based quantitative OCTA in hemodynamic studies.

Optical coherence tomography angiography for mapping cerebral microvasculature based on normalized differentiation analysis.

Optical coherence tomography angiography (OCTA) is a label-free, noninvasive biomedical imaging modality for mapping microvascular networks and quantifying blood flow velocities in vivo. Simple computation and fast processing are critical for the OCTA in some applications. Herein, we report on a normalized differentiation method for mapping cerebral microvasculature with the advantages of simple analysis and high image quality, benefitting from computation of differentiation and characteristics of normalization. Normalized differentiation values are validated to have a nearly linear relationship with flow velocities in a range using a flow phantom. The measurements in a rat cerebral cortex show that the OCTA based on the normalized differentiation analysis can generate microvascular images with high quality and monitor spatiotemporal dynamics of blood flow with simple computation and fast processing before and after localized ischemia induced by arterial occlusion.

Developing an Interface and Investigating Optimal Parameters for Real-Time Intracardiac Subharmonic-Aided Pressure Estimation.

Thisstudy focuses on evaluating the real-time functionality of a customized interface and investigating the optimal parameters for intracardiac subharmonic-aided pressure estimation (SHAPE) utilizing Definity (Lantheus Medical Imaging Inc., North Billerica, MA, USA) and Sonazoid (GE Healthcare, Oslo, Norway) microbubbles. Pressure measurements within the chambers of the heart yield critical information for managing cardiovascular diseases. An alternative to current, invasive, clinical cardiac catheterization procedures is utilizing ultrasound contrast agents and SHAPE to noninvasively estimate intracardiac pressures. Therefore, this work developed a customized interface (on a SonixTablet, BK Ultrasound, Peabody, MA, USA) for real-time intracardiac SHAPE. In vitro, a Doppler flow phantom was utilized to mimic the dynamic pressure changes within the heart. Definity (15.0- [Formula: see text] microspheres corresponding to 0.1-0.15 mL) and Sonazoid (GE Healthcare; 0.4- [Formula: see text] microspheres corresponding to 0.05-0.15 mL) microbubbles were used. Data were acquired for varying transmit frequencies (2.5-4.0 MHz), and pulse shaping options (square wave and chirp down) to determine optimal transmit parameters. Simultaneously obtained radio frequency data and ambient pressure data were compared. For Definity, the chirp down pulse at 3.0 MHz yielded the highest correlation ( r = - 0.77 ± 0.2 ) between SHAPE and pressure catheter data. For Sonazoid, the square wave pulse at 2.5 MHz yielded the highest correlation ( r = - 0.72 ± 0.2 ). In conclusion, the real-time functionality of the customized interface has been verified, and the optimal parameters for utilizing Definity and Sonazoid for intracardiac SHAPE have been determined.

Stable Automatic Envelope Estimation for Noisy Doppler Ultrasound

Doppler ultrasound technology is widespread in clinical applications and is principally used for blood flow measurements in the heart, arteries, and veins. A commonly extracted parameter is the maximum velocity envelope. However, current methods of extracting it cannot produce stable envelopes in high noise conditions. This can limit clinical and research applications using the technology. In this article, a new method of automatic envelope estimation is presented. The method can handle challenging signals with high levels of noise and variable envelope shapes. Envelopes are extracted from a Doppler spectrogram image generated directly from the Doppler audio signal, making it less device-dependent than existing image-processing methods. The method's performance is assessed using simulated pulsatile flow, a flow phantom, and in vivo ascending aortic flow measurements and is compared with three state-of-the-art methods. The proposed method is the most accurate in noisy conditions, achieving, on average, for phantom data with signal-to-noise ratios (SNRs) below 10 dB, bias and standard deviation of 0.7% and 3.3% lower than the next-best performing method. In addition, a new method for beat segmentation is proposed. When combined, the two proposed methods exhibited the best performance using in vivo data, producing the least number of incorrectly segmented beats and 8.2% more correctly segmented beats than the next best performing method. The ability of the proposed methods to reliably extract timing indices for cardiac cycles across a range of signal quality is of particular significance for research and monitoring applications.

40-MHz high-frequency vector Doppler imaging for superficial venous valve flow estimation.

Doppler ultrasound imaging has been used widely for diagnosing vascular diseases. Recently, vector Doppler imaging (VDI) has been proposed for visualizing the blood flow in all directions to yield more detailed information for estimating flow conditions. Increasing the resolution of VDI is important for the structural mapping of superficial vessels with microstructure. However, VDI that operates under a high-frequency ultrasound (HFUS; >30MHz) is rare. In this study, a 40-MHz high-frequency VDI (HFVDI) based on ultrafast ultrasound imaging was developed to obtain the vector information of blood flow around the superficial venous valve. The use of HFUS imaging system causes an overload of data acquisition easily. In order to provide sufficient recording time, the frame rate should be reduced. Because the aliasing problem worsens due to a low frame rate when operating Doppler imaging, phase-unwrapping processing methods based on spatial and temporal continuities were applied. Flow phantom experiments were performed to validate the accuracy. In vivo experiments were performed on the valve of superficial veins of healthy volunteers. The experimental results from the phantom study indicated that the error of velocity estimation was <10% in most cases. Dynamic changes of valve movements and flow conditions (including velocity profiles and vector) were observed. Because of the high resolution of HFVDI, the jet and vortex phenomena were observed between the leaflets and in the sinus pocket, respectively. Flow velocities ranging from 2 to 15mm/s were measured at different locations around the venous valve during the opening and closing phases. All the results indicated that HFVDI has the potential to be a useful tool for vessel duplex scanning.

Evaluation of the Reproducibility of Bolus Transit Quantification With Contrast-Enhanced Ultrasound Across Multiple Scanners and Analysis Software Packages-A Quantitative Imaging Biomarker Alliance Study.

Contrast enhanced ultrasound (CEUS) is now broadly used clinically for liver lesion detection and characterization. Obstacles to the efforts to quantify perfusion with CEUS have been the lack of a standardized approach and undocumented reproducibility. The use of multiple scanners and different analysis software packages compounds the degree of variability. Our objectives were to standardize a CEUS-based approach for quantification of perfusion-related parameters of liver lesions and to evaluate the variability of bolus transit parameters (rise time [RT], mean transit time [MTT], peak intensity, and area under the curve) obtained from various clinical ultrasound scanners and analysis software. Bolus transit as a way of evaluating perfusion has been investigated both in vivo and in vitro in the past but without establishing its reproducibility. We developed a tissue flow phantom that produces time-intensity curves very similar to those extracted from clinical cine loops of liver lesions. We evaluated the variability of the bolus transit parameters with 4 commercial scanners (Philips iU22, Philips EPIQ, GE LOGIQ E9, and Siemens Acuson Sequoia) and 3 different analysis software packages in multiple trials (15 per scanner). The variability (coefficient of variation) from repeated trials and while using a single scanner and software was less than 8% for RT, less than 12% for MTT, less than 49% for peak intensity, and less than 50% for area under the curve. Currently, it is not possible to directly compare amplitude values from different scanners and analysis software packages owing to the arbitrary linearization algorithm used among manufacturers; however, it is possible for time parameters (RT and MTT). The variability when using a different scanner with the same analysis software package was less than 9% for RT and less than 21% for MTT. The variability when using a different analysis software with the same scanner was less than 9% for RT and less than 15% for MTT. In all the evaluations we have performed, RT is the least variable parameter, while MTT is only slightly more variable. The present study will lay the groundwork for multicenter patient evaluations with CEUS quantification of perfusion-related parameters with the bolus transit technique. When using the protocol and method developed here, it is possible to perform perfusion quantification on different scanners and analysis software and be able to compare the results. The current work is the first study that presents a comparison of bolus transit parameters derived from multiple systems and software packages.

3-D Intravascular Characterization of Blood Flow Velocity Fields with a Forward-Viewing 2-D Array

Risk stratification in coronary artery disease is an ongoing challenge for which few tools are available for quantifying physiology within coronary arteries. Recently, anatomy-driven computational fluid dynamic modeling has enabled the mapping of local flow dynamics in coronary stenoses, with derived parameters such as WSS exhibiting a strong capability for predicting adverse clinical events on a patient-specific basis. As cardiac catheterization is common in patients with coronary artery disease, minimally invasive technologies capable of identifying pathologic flow in situ in real time could have a significant impact on clinical decision- making. As a step toward in vivo quantification of slow flow near the arterial wall, proof-of-concept for 3-D intravascular imaging of blood flow dynamics is provided using a 118-element forward-viewing ring array transducer and a research ultrasound system. Blood flow velocity components are estimated in the direction of primary flow using an unfocused wave Doppler approach, and in the lateral and elevation directions, using a transverse oscillation approach. This intravascular 3-D vector velocity system is illustrated by acquiring real-time 3-D data sets in phantom experiments and in vivo in the femoral artery of a pig. The effect of the catheter on blood flow dynamics is also experimentally assessed in flow phantoms with both straight and stenotic vessels. Results indicate that 3-D flow dynamics can be measured using a small form factor device and that a hollow catheter design may provide minimal disturbance to flow measurements in a stenosis (peak velocity: 54.97 ± 2.13 cm/s without catheter vs. 51.37 ± 1.08 cm/s with hollow catheter, 6.5% error). In the future, such technologies could enable estimation of 3-D flow dynamics near the wall in patients already undergoing catheterization.

In vitro experiments on ICOSA6 4D flow MRI measurement for the quantification of velocity and turbulence parameters

PurposeTo perform comprehensive in vitro experiments using six-directional icosahedral flow encoding (ICOSA6) 4D flow magnetic resonance imaging (MRI) under various scan conditions to analyze the robustness of velocity and turbulence quantification. Materials and methodsIn vitro flow phantoms with steady flow rates of 10 and 20 L/min were scanned using both conventional 4D flow MRI and ICOSA6. Experiments focused on comparisons between ICOSA6 and conventional four point (4P) methods, and the effects of contrast agents, velocity encoding range (Venc), and scan direction on velocity and turbulence quantification. ResultsThe results demonstrated that 1) ICOSA6 improves the velocity-to-noise ratio (VNR) of velocity estimation by 33% (on average) and results in similar turbulent kinetic energy (TKE) estimation as the 4P method. 2) Measurements with a contrast agent resulted in more than a 2.5 fold increase in average VNR. However, the improvement of total TKE quantification was not obvious. 3) TKE estimation was less affected by Venc and the scan direction, whereas turbulence production (TP) estimation was largely affected by these measurement conditions. The effects of Venc and scan direction accounted for less than 11.63% of TKE estimation, but up to 33.89% of TP estimation. ConclusionThe ICOSA6 scheme is compatible with conventional 4D flow MRI for velocity and TKE measurement. Contrast agents are effective at increasing VNR, but not signal-to-noise ratio for TKE quantification. The effects of Venc and scan direction influence total TP more than total TKE.

Three-dimensional US for Quantification of Volumetric Blood Flow: Multisite Multisystem Results from within the Quantitative Imaging Biomarkers Alliance.

Background Quantitative blood flow (QBF) measurements that use pulsed-wave US rely on difficult-to-meet conditions. Imaging biomarkers need to be quantitative and user and machine independent. Surrogate markers (eg, resistive index) fail to quantify actual volumetric flow. Standardization is possible, but relies on collaboration between users, manufacturers, and the U.S. Food and Drug Administration. Purpose To evaluate a Quantitative Imaging Biomarkers Alliance-supported, user- and machine-independent US method for quantitatively measuring QBF. Materials and Methods In this prospective study (March 2017 to March 2019), three different clinical US scanners were used to benchmark QBF in a calibrated flow phantom at three different laboratories each. Testing conditions involved changes in flow rate (1-12 mL/sec), imaging depth (2.5-7 cm), color flow gain (0%-100%), and flow past a stenosis. Each condition was performed under constant and pulsatile flow at 60 beats per minute, thus yielding eight distinct testing conditions. QBF was computed from three-dimensional color flow velocity, power, and scan geometry by using Gauss theorem. Statistical analysis was performed between systems and between laboratories. Systems and laboratories were anonymized when reporting results. Results For systems 1, 2, and 3, flow rate for constant and pulsatile flow was measured, respectively, with biases of 3.5% and 24.9%, 3.0% and 2.1%, and -22.1% and -10.9%. Coefficients of variation were 6.9% and 7.7%, 3.3% and 8.2%, and 9.6% and 17.3%, respectively. For changes in imaging depth, biases were 3.7% and 27.2%, -2.0% and -0.9%, and -22.8% and -5.9%, respectively. Respective coefficients of variation were 10.0% and 9.2%, 4.6% and 6.9%, and 10.1% and 11.6%. For changes in color flow gain, biases after filling the lumen with color pixels were 6.3% and 18.5%, 8.5% and 9.0%, and 16.6% and 6.2%, respectively. Respective coefficients of variation were 10.8% and 4.3%, 7.3% and 6.7%, and 6.7% and 5.3%. Poststenotic flow biases were 1.8% and 31.2%, 5.7% and -3.1%, and -18.3% and -18.2%, respectively. Conclusion Interlaboratory bias and variation of US-derived quantitative blood flow indicated its potential to become a clinical biomarker for the blood supply to end organs. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Forsberg in this issue.

High Spatiotemporal Resolution 4D Flow MRI of Intracranial Aneurysms at 7T in 10 Minutes.

Patients with intracranial aneurysms may benefit from 4D flow MR imaging because the derived wall shear stress is considered a useful marker for risk assessment and growth of aneurysms. However, long scan times limit the clinical implementation of 4D flow MR imaging. Therefore, this study aimed to investigate whether highly accelerated, high resolution, 4D flow MR imaging at 7T provides reliable quantitative blood flow values in intracranial arteries and aneurysms. We used pseudospiral Cartesian undersampling with compressed sensing reconstruction to achieve high spatiotemporal resolution (0.5 mm isotropic, ∼30 ms) in a scan time of 10 minutes. We analyzed the repeatability of accelerated 4D flow scans and compared flow rates, stroke volume, and the pulsatility index with 2D flow and conventional 4D flow MR imaging in a flow phantom and 15 healthy subjects. Additionally, accelerated 4D flow MR imaging with high spatiotemporal resolution was acquired in 5 patients with aneurysms to derive wall shear stress. Flow-rate bias compared with 2D flow was lower for accelerated than for conventional 4D flow MR imaging (0.31 ± 0.13, P = .22, versus 0.79 ± 0.17 mL/s, P < .01). Pulsatility index bias gave similar results. Stroke volume bias showed no difference for accelerated as well as for conventional 4D flow compared to 2D flow MR imaging. Repeatability for accelerated 4D flow was similar to that of 2D flow MR imaging. Increased temporal resolution for wall shear stress measurements in 5 intracranial aneurysms did not show a consistent effect for the wall shear stress but did show an effect for the oscillatory shear index. Highly accelerated high spatiotemporal resolution 4D flow MR imaging at 7T in intracranial arteries and aneurysms provides repeatable and accurate quantitative flow values. Flow rate accuracy is significantly increased compared with conventional 4D flow scans.

Window-Modulated Compounding Nakagami Parameter Ratio Approach for Assessing Muscle Perfusion with Contrast-Enhanced Ultrasound Imaging

The assessment of microvascular perfusion is essential for the diagnosis of a specific muscle disease. In comparison with the current available medical modalities, the contrast-enhanced ultrasound imaging is the simplest and fastest means for probing the tissue perfusion. Specifically, the perfusion parameters estimated from the ultrasound time-intensity curve (TIC) and statistics-based time–Nakagami parameter curve (TNC) approaches were found able to quantify the perfusion. However, due to insufficient tolerance on tissue clutters and subresolvable effects, these approaches remain short of reproducibility and robustness. Consequently, the window-modulated compounding (WMC) Nakagami parameter ratio imaging was proposed to alleviate these effects, by taking the ratio of WMC Nakagami parameters corresponding to the incidence of two different acoustic pressures from an employed transducer. The time–Nakagami parameter ratio curve (TNRC) approach was also developed to estimate perfusion parameters. Measurements for the assessment of muscle perfusion were performed from the flow phantom and animal subjects administrated with a bolus of ultrasound contrast agents. The TNRC approach demonstrated better sensitivity and tolerance of tissue clutters than those of TIC and TNC. The fusion image with the WMC Nakagami parameter ratio and B-mode images indicated that both the tissue structures and perfusion properties of ultrasound contrast agents may be better discerned.

A Neural Network Approach to Quantify Blood Flow from Retinal OCT Intensity Time-Series Measurements

Many diseases of the eye are associated with alterations in the retinal vasculature that are possibly preceded by undetected changes in blood flow. In this work, a robust blood flow quantification framework is presented based on optical coherence tomography (OCT) angiography imaging and deep learning. The analysis used a forward signal model to simulate OCT blood flow data for training of a neural network (NN). The NN was combined with pre- and post-processing steps to create an analysis framework for measuring flow rates from individual blood vessels. The framework’s accuracy was validated using both blood flow phantoms and human subject imaging, and across flow speed, vessel angle, hematocrit levels, and signal-to-noise ratio. The reported flow rate of the calibrated NN framework was measured to be largely independent of vessel angle, hematocrit levels, and measurement signal-to-noise ratio. In vivo retinal flow rate measurements were self-consistent across vascular branch points, and approximately followed a predicted power-law dependence on the vessel diameter. The presented OCT-based NN flow rate estimation framework addresses the need for a robust, deployable, and label-free quantitative retinal blood flow mapping technique.