CColor and Vector Flow Imaging in Parallel Ultrasound with Sub-Nyquist Sampling

Transcranial ultrafast ultrasound Doppler imaging: A phantom study

Ultrafast ultrasound Doppler imaging facilitates the assessment of cerebral hemodynamics with high spatio-temporal resolution. However, the significant acoustic impedance mismatch between the skull and soft tissue results in phase aberrations, which can compromise the quality of transcranial imaging and introduce biases in velocity and direction quantification of blood flow. This paper proposed an aberration correction method that combines deep learning-based skull sound speed modelling with ray theory to realize transcranial plane-wave imaging and ultrafast Doppler imaging. The method was validated through phantom experiments using a linear array with a center frequency of 6.25 MHz, 128 elements, and a pitch of 0.3 mm. The results demonstrated an improvement in the imaging quality of intracranial targets when using the proposed method. After aberration correction, the average locating deviation decreased from 1.40 mm to 0.27 mm in the axial direction, from 0.50 mm to 0.20 mm in the lateral direction, and the average full-width-at-half-maximum (FWHM) decreased from 1.37 mm to 0.97 mm for point scatterers. For circular inclusions, the average contrast-to-noise ratio (CNR) improved from 8.1 dB to 11.0 dB, and the average eccentricity decreased from 0.36 to 0.26. Furthermore, the proposed method was applied to transcranial ultrafast Doppler flow imaging. The results showed a significant improvement in accuracy and quality for blood Doppler flow imaging. The results in the absence of the skull were considered as the reference, and the average normalized root-mean-square errors of the axial velocity component on the five selected axial profiles were reduced from 17.67% to 8.02% after the correction.

Ultrasound Speckle Decorrelation Analysis-Based Velocimetry for 3D-Velocity-Components Measurement Using a 1D Transducer Array

Ultrasound velocimetry has been widely used for blood flow imaging. However, the flow measurements are constrained to resolve the in-plane 2D flow components when using a 1D transducer array. In this work, an ultrasound speckle decorrelation analysis-based velocimetry (3C-vUS) is proposed for 3D velocity components measurement using a 1D transducer array. The 3C-vUS theory is first derived and validated with numerical simulations and phantom experiments. The in vivo testing results show that 3C-vUS can accurately measure the blood flow 3D-velocity-components of the human carotid artery at arbitrary probe-to-vessel angles throughout the cardiac cycle. With such capability, the 3C-vUS will alleviate the requirement of operators and promote disease screening for blood flow-related disorders.

Nonlinear beamforming for intracardiac echocardiography: a comparative study

Intracardiac echocardiography (ICE) enables cardiac imaging with a wide field of view, deep imaging depth, and high frame rate during surgery. However, strong sidelobe and grating lobe artifacts created by the ultra-compact transducer degrade its image quality, making diagnosis and monitoring of treatment difficult. Conventionally, aperture apodization algorithms are often used to suppress sidelobe and grating lobe artifacts at the expense of lateral resolution, which is undesirable in ICE. In this study, we present comparative results of the beamforming methods specifically in ICE application. We demonstrate and compare five nonlinear beamforming algorithms in ICE: nonlinear pth root delay and sum (NL-p-DAS), nonlinear pth root spectral magnitude scaling (NL-p-SMS), delay-and-sum with coherence factors (DAS + SCF), delay and sum with apodization (DAS + apodization) and delay and sum (DAS). Phantom and ex-vivo experiment compare the performance of each algorithm in static and dynamic conditions. DAS + SCF shows the best lateral resolution, and all four algorithms improve the image contrast and sidelobe suppression over conventional DAS. NL-p-SMS stands out for the best axial resolution and suppression of grating lobe artifacts. For motion tracking, NL-p-SMS shows better temporal resolution than other methods. Overall, all the beamforming algorithms other than DAS showed improved image quality. Among them, NL-p-SMS, which has a high temporal resolution, showed the potential for providing more accurate information regards movement tracking.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13534-024-00352-9.

Verification of effect of interference between multiple scatterers on the evaluation of backscattering coefficient

Backscatter coefficient analysis methods for biological tissues have been clinically applied but assume a homogeneous scattering medium. In addition, there are few examples of actual measurement studies in the HF band, and the consistency with theory has not been sufficiently confirmed. In this paper, the effect of correlations among scatterer positions on backscattering was investigated by performing experiments on inhomogeneous media having two types of scattering source with different structural and acoustic properties. In the echo data of phantoms containing two types of scatterer acquired by multiple sensors, the power and frequency dependence of the backscatter coefficient were different from theoretical calculations due to the interference effects of each scatterer. The effect of interference between the two types of scatterer was confirmed to be particularly strong for echoes acquired by the sensor at high intensity and HF, or for a higher number density of strong scatterers.

Spectral-based Quantitative Ultrasound Imaging Processing Techniques: Comparisons of RF Versus IQ Approaches

Quantitative ultrasound (QUS) is an imaging technique which includes spectral-based parameterization. Typical spectral-based parameters include the backscatter coefficient (BSC) and attenuation coefficient slope (ACS). Traditionally, spectral-based QUS relies on the radio frequency (RF) signal to calculate the spectral-based parameters. Many clinical and research scanners only provide the in-phase and quadrature (IQ) signal. To acquire the RF data, the common approach is to convert IQ signal back into RF signal via mixing with a carrier frequency. In this study, we hypothesize that the performance, that is, accuracy and precision, of spectral-based parameters calculated directly from IQ data is as good as or better than using converted RF data. To test this hypothesis, estimation of the BSC and ACS using RF and IQ data from software, physical phantoms and in vivo rabbit data were analyzed and compared. The results indicated that there were only small differences in estimates of the BSC between when using the original RF, the IQ derived from the original RF and the RF reconverted from the IQ, that is, root mean square errors (RMSEs) were less than 0.04. Furthermore, the structural similarity index measure (SSIM) was calculated for ACS maps with a value greater than 0.96 for maps created using the original RF, IQ data and reconverted RF. On the other hand, the processing time using the IQ data compared to RF data were substantially less, that is, reduced by more than a factor of two. Therefore, this study confirms two things: (1) there is no need to convert IQ data back to RF data for conducting spectral-based QUS analysis, because the conversion from IQ back into RF data can introduce artifacts. (2) For the implementation of real-time QUS, there is an advantage to convert the original RF data into IQ data to conduct spectral-based QUS analysis because IQ data-based QUS can improve processing speed.

Four-dimensional computational ultrasound imaging of brain hemodynamics

Four-dimensional ultrasound imaging of complex biological systems such as the brain is technically challenging because of the spatiotemporal sampling requirements. We present computational ultrasound imaging (cUSi), an imaging method that uses complex ultrasound fields that can be generated with simple hardware and a physical wave prediction model to alleviate the sampling constraints. cUSi allows for high-resolution four-dimensional imaging of brain hemodynamics in awake and anesthetized mice.

Advanced Fourier migration for Plane-Wave vector flow imaging

Ultrafast ultrasound imaging modalities have been studied extensively in the ultrasound community. It breaks the compromise between the frame rate and the region of interest by imaging the whole medium with wide unfocused waves. Continuously available data allow monitoring fast transient dynamics at hundreds to thousands of frames per second. This feature enables a more accurate and robust velocity estimation in vector flow imaging (VFI). On the other hand, the huge amount of data and real-time processing demands are still challenging in VFI. A solution is to provide a more efficient beamforming approach with smaller computation complexity than the conventional time-domain beamformer like delay-and-sum (DAS). Fourier-domain beamformers are shown to be more computationally efficient and can provide equally good image quality as DAS. However, previous studies generally focus on B-mode imaging. In this study, we propose a new framework for VFI which is based on two advanced Fourier migration methods, namely, slant stack migration (SSM) and ultrasound Fourier slice beamform (UFSB). By carefully modifying the beamforming parameters, we successfully apply the cross-beam technique within the Fourier beamformers. The proposed Fourier-based VFI is validated in simulation studies, in vitro, and in vivo experiments. The velocity estimation is evaluated via bias and standard deviation and the results are compared with conventional time-domain VFI using the DAS beamformer. In the simulation, the bias is 6.4%, -6.2%, and 5.7%, and the standard deviation is 4.3%, 2.4%, and 3.9% for DAS, UFSB, and SSM, respectively. In vitro studies reveal a bias of 4.5%, -5.3%, and 4.3% and a standard deviation of 3.5%, 1.3%, and 1.6% from DAS, UFSB, and SSM, respectively. The in vivo imaging of the basilic vein and femoral bifurcation also generate similar results using all three methods. With the proposed Fourier beamformers, the computation time can be shortened by up to 9 times and 14 times using UFSB and SSM.

SIMUS: An open-source simulator for medical ultrasound imaging. Part II: Comparison with four simulators

BACKGROUND AND OBJECTIVE

Computational ultrasound imaging has become a well-established methodology in the ultrasound community. In the accompanying paper (part I), we described a new ultrasound simulator (SIMUS) for MATLAB, which belongs to the Matlab UltraSound Toolbox (MUST). SIMUS can generate pressure fields and radiofrequency RF signals for simulations in medical ultrasound imaging. It works in a harmonic domain and uses far-field and paraxial linear equations.

METHODS

In this article (part II), we illustrate how SIMUS compares with other ultrasound simulators (Field II, k-Wave, FOCUS, and Verasonics) for a homogeneous medium. We designed different transmit sequences (focused, planar, and diverging wavefronts) and calculated the corresponding 2-D and 3-D (with elevation focusing) RMS pressure fields.

RESULTS

SIMUS produced pressure fields similar to those of Field II, FOCUS, and k-Wave. The acoustic fields provided by the Verasonics simulator were significantly different from those of SIMUS and k-Wave, although the overall appearance remained consistent.

CONCLUSION

Our simulations tend to demonstrate that SIMUS is reliable and can be used for realistic medical ultrasound simulations.

High-Frequency Ultrasound Imaging With Sub-Nyquist Sampling

Implementation of a high-frequency ultrasound (HFUS) beamformer is computationally challenging because of its high sampling rate. This article introduces an efficient beamformer with sub-Nyquist sampling (or bandpass sampling) that is suitable for HFUS imaging. Our approach used channel radio frequency data sampled at bandpass sampling rate (i.e., 4/ 3f_c ) and postfiltering-based interpolation to reduce the computational complexity. A polyphase structure for interpolation was used to further reduce the computational burden while maintaining an adequate delay resolution ( δ ). The performance of the proposed beamformer (i.e., 4/ 3f_c sampling with sixfold interpolation, δ = 8f_c ) was compared with that of the conventional method (i.e., 4f_c sampling with fourfold interpolation, δ = 16f_c ). Ultrafast coherent compounding imaging was used in simulation, in vitro and in vivo imaging experiments. Axial/lateral resolution and contrast-to-noise ratio (CNR) values were measured for quantitative evaluation. The number of transmit pulse cycles was varied from 1 to 3 using two transducers with different fractional bandwidths (67% and 98%). In the simulation, the proposed and conventional methods showed the similar -6-dB axial beam widths (63.5 and 61.5 μm , respectively) from the two-cycle transmit pulse using the transducer with a bandwidth of 67%. In vitro and in vivo imaging experiments were performed using a Verasonics ultrasound research platform equipped with a high-frequency array transducer (20-46 MHz). The in vitro imaging results using a wire target showed consistent results with the simulation study (i.e., disparity at -6-dB axial resolution). The in vivo feasibility study with a murine mouse model with breast cancer was also performed, and the proposed method yielded a similar image quality compared with the conventional method. From these studies, it was demonstrated that the proposed HFUS beamformer based on the bandpass sampling can substantially reduce the computational complexity while minimizing the loss of spatial resolution for HFUS imaging.

SIMUS: An open-source simulator for medical ultrasound imaging. Part I: Theory & examples

BACKGROUND AND OBJECTIVE

Computational ultrasound imaging has become a well-established methodology in the ultrasound community. Simulations of ultrasound sequences and images allow the study of innovative techniques in terms of emission strategy, beamforming, and probe design. There is a wide spectrum of software dedicated to ultrasound imaging, each having its specificities in its applications and the numerical method.

METHODS

We describe in this two-part paper a new ultrasound simulator (SIMUS) for MATLAB, which belongs to the MATLAB UltraSound Toolbox (MUST). The SIMUS software simulates acoustic pressure fields and radiofrequency RF signals for uniform linear or convex probes. SIMUS is an open-source software whose features are 1) ease of use, 2) time-harmonic analysis, 3) pedagogy. The main goal was to offer a comprehensive turnkey tool, along with a detailed theory for pedagogical and research purposes.

RESULTS

This article describes in detail the underlying linear theory of SIMUS and provides examples of simulated acoustic fields and ultrasound images. The accompanying article (part II) is devoted to the comparison of SIMUS with several software packages: Field II, k-Wave, FOCUS, and the Verasonics simulator. The MATLAB open codes for the simulator SIMUS are distributed under the terms of the GNU Lesser General Public License, and can be downloaded from https://www.biomecardio.com/MUST.

CONCLUSIONS

The simulations described in this part and in the accompanying paper (Part II) show that SIMUS can be used for realistic simulations in medical ultrasound imaging.

A Pipeline for the Generation of Synthetic Cardiac Color Doppler

Color Doppler imaging (CDI) is the modality of choice for simultaneous visualization of myocardium and intracavitary flow over a wide scan area. This visualization modality is subject to several sources of error, the main ones being aliasing and clutter. Mitigation of these artifacts is a major concern for better analysis of intracardiac flow. One option to address these issues is through simulations. In this article, we present a numerical framework for generating clinical-like CDI. Synthetic blood vector fields were obtained from a patient-specific computational fluid dynamics CFD model. Realistic texture and clutter artifacts were simulated from real clinical ultrasound cineloops. We simulated several scenarios highlighting the effects of 1) flow acceleration; 2) wall clutter; and 3) transmit wavefronts, on Doppler velocities. As a comparison, an "ideal" color Doppler was also simulated, without these harmful effects. This synthetic dataset is made publicly available and can be used to evaluate the quality of Doppler estimation techniques. Besides, this approach can be seen as a first step toward the generation of comprehensive datasets for training neural networks to improve the quality of Doppler imaging.

Physics-constrained intraventricular vector flow mapping by color Doppler

Color Doppler by transthoracic echocardiography creates two-dimensional fan-shaped maps of blood velocities in the cardiac cavities. It is a one-component velocimetric technique since it only returns the velocity components parallel to the ultrasound beams. Intraventricular vector flow mapping (iVFM) is a method to recover the blood velocity vectors from the Doppler scalar fields in an echocardiographic three-chamber view. We improved ouriVFM numerical scheme by imposing physical constraints. TheiVFM consisted in minimizing regularized Doppler residuals subject to the condition that two fluid-dynamics constraints were satisfied, namely planar mass conservation, and free-slip boundary conditions. The optimization problem was solved by using the Lagrange multiplier method. A finite-difference discretization of the optimization problem, written in the polar coordinate system centered on the cardiac ultrasound probe, led to a sparse linear system. The single regularization parameter was determined automatically for non-supervision considerations. The physics-constrained method was validated using realistic intracardiac flow data from a patient-specific computational fluid dynamics (CFD) model. The numerical evaluations showed that theiVFM-derived velocity vectors were in very good agreement with the CFD-based original velocities, with relative errors ranged between 0.3% and 12%. We calculated two macroscopic measures of flow in the cardiac region of interest, the mean vorticity and mean stream function, and observed an excellent concordance between physics-constrainediVFM and CFD. The capability of physics-constrainediVFM was finally tested within vivocolor Doppler data acquired in patients routinely examined in the echocardiographic laboratory. The vortex that forms during the rapid filling was deciphered. The physics-constrainediVFM algorithm is ready for pilot clinical studies and is expected to have a significant clinical impact on the assessment of diastolic function.

Volumetric Flow Estimation in a Coronary Artery Phantom Using High-Frame-Rate Contrast-Enhanced Ultrasound, Speckle Decorrelation, and Doppler Flow Direction Detection

The coronary flow reserve (CFR), relating to the volumetric flow rate, is an effective functional parameter to assess the stenosis in the left anterior descending (LAD) coronary artery. We have recently proposed to use high-frame-rate (HFR) contrast-enhanced ultrasound (CEUS) to estimate the volumetric flow rate using ultrasound (US) speckle decorrelation (SDC) without any assumptions about the velocity profile. However, this method still has challenges in imaging deep and small vessels, such as LAD. In this study, we proposed to address the challenges and demonstrate the feasibility of volumetric flow rate measurement in a coronary mimicking phantom with pulsatile flow using a 1-D array cardiac probe, vector Doppler, and an optimal probe rotation/tilting for flow direction detection. Both simulations and in vitro experiments were conducted to validate the proposed method. It is shown that in-plane velocities estimated by vector Doppler under a 10° probe tilting resulted in smaller percentage error (+5.2%) in flow rate estimates than that in US imaging velocimetry (-20.2%) although their relative standard deviations were very close, being 2.6 and 2.8 ml/min, respectively. The flow rate estimated by SDC without direction detection had an error higher than 70%. A 10° tilting of the probe had the best results in flow rate estimation compared to the 5° or 15° tilting. Realistic global motions in the LAD increased the flow rate estimation error from 5.2% to 14.2%. It is concluded that it is feasible to measure the volumetric flow rate in a coronary artery flow phantom with a conventional cardiac probe, using HFR acquisition, Doppler, and SDC analysis. Potentially, this technique could also be applied to investigate the volumetric flow rate in other small vessels similar to the LAD.

An Angle Independent Depth Aware Fusion Beamforming Approach for Ultrafast Ultrasound Flow Imaging. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021;2021:3399-3402. [PMID: 34891969 DOI: 10.1109/embc46164.2021.9630742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

In the case of vector flow imaging systems, the most employed flow estimation techniques are the directional beamforming based cross correlation and the triangulation-based autocorrelation. However, the directional beamforming-based techniques require an additional angle estimator and are not reliable if the flow angle is not constant throughout the region of interest. On the other hand, estimates with triangulation-based techniques are prone to large bias and variance at low imaging depths due to limited angle for left and right apertures. In view of this, a novel angle independent depth aware fusion beamforming approach is proposed and evaluated in this paper. The hypothesis behind the proposed approach is that the peripheral flows are transverse in nature, where directional beamforming can be employed without the need of an angle estimator and the deeper flows being non-transverse and directional, triangulation-based vector flow imaging can be employed. In the simulation study, an overall 67.62% and 74.71% reduction in magnitude bias along with a slight reduction in the standard deviation are observed with the proposed fusion beamforming approach when compared to triangulation-based beamforming and directional beamforming, respectively, when implemented individually. The efficacy of the proposed approach is demonstrated with in-vivo experiments.

Dealiasing High-Frame-Rate Color Doppler Using Dual-Wavelength Processing

Doppler ultrasound is the premier modality to analyze blood flow dynamics in clinical practice. With conventional systems, Doppler can either provide a time-resolved quantification of the flow dynamics in sample volumes (spectral Doppler) or an average Doppler velocity/power [color flow imaging (CFI)] in a wide field of view (FOV) but with a limited frame rate. The recent development of ultrafast parallel systems made it possible to evaluate simultaneously color, power, and spectral Doppler in a wide FOV and at high-frame rates but at the expense of signal-to-noise ratio (SNR). However, like conventional Doppler, ultrafast Doppler is subject to aliasing for large velocities and/or large depths. In a recent study, staggered multi-pulse repetition frequency (PRF) sequences were investigated to dealias color-Doppler images. In this work, we exploit the broadband nature of pulse-echo ultrasound and propose a dual-wavelength approach for CFI dealiasing with a constant PRF. We tested the dual-wavelength bandpass processing, in silico, in laminar flow phantom and validated it in vivo in human carotid arteries ( n = 25 ). The in silico results showed that the Nyquist velocity could be extended up to four times the theoretical limit. In vivo, dealiased CFI were highly consistent with unfolded Spectral Doppler ( r²=0.83 , y=1.1x+0.1 , N=25 ) and provided consistent vector flow images. Our results demonstrate that dual-wavelength processing is an efficient method for high-velocity CFI.

So you think you can DAS? A viewpoint on delay-and-sum beamforming

Delay-and-sum (DAS) is the most widespread digital beamformer in high-frame-rate ultrasound imaging. Its implementation is simple and compatible with real-time applications. In this viewpoint article, we describe the fundamentals of DAS beamforming. The underlying theory and numerical approach are detailed so that users can be aware of its functioning and limitations. In particular, we discuss the importance of the f-number and speed of sound on image quality, and propose one solution to set their values from a physical viewpoint. We suggest determining the f-number from the directivity of the transducer elements and the speed of sound from the phase dispersion of the delayed signals. Simplified Matlab codes are provided for the sake of clarity and openness. The effect of the f-number and speed of sound on the lateral resolution and contrast-to-noise ratio was investigated in vitro and in vivo. If not properly preset, these two factors had a substantial negative impact on standard metrics of image quality (namely CNR and FWHM). When beamforming with DAS in vitro or in vivo, it is recommended to optimize these parameters in order to use it wisely and prevent image degradation.

Vortex dynamics and transport phenomena in stenotic aortic models using Echo-PIV

Atherosclerosis is the most fatal cardiovascular disease. As disease progresses, stenoses grow inside the arteries blocking their lumen and altering blood flow. Analysing flow dynamics can provide a deeper insight on the stenosis evolution. In this work we combined Eulerian and Lagrangian descriptors to analyze blood flow dynamics and fluid transport in stenotic aortic models with morphology, mechanical and optical properties close to those of real arteries. To this end, vorticity, particle residence time (PRT), particle's final position (FP) and finite time Lyapunov's exponents (FTLE) were computed from the experimental fluid velocity fields acquired using ultrasonic particle imaging velocimetry (Echo-PIV). For the experiments, CT-images were used to create morphological realistic models of the descending aorta with 0%, 35% and 50% occlusion degree with same mechanical properties as real arteries. Each model was connected to a circuit with a pulsatile programmable pump which mimics physiological flow and pressure conditions. The pulsatile frequency was set to ≈0.9 Hz (55 bpm) and the upstream peak Reynolds number (Re) was changed from 1100 to 2000. Flow in the post-stenotic region was composed of two main structures: a high velocity jet over the stenosis throat and a recirculation region behind the stenosis where vortex form and shed. We characterized vortex kinematics showing that vortex propagation velocity increases withRe. Moreover, from the FTLE field we identified Lagrangian coherent structures (i.e. material barriers) that dictate transport behind the stenosis. The size and strength of those barriers increased withReand the occlusion degree. Finally, from the PRT and FP maps, we showed that independently ofRe, the same amount of fluid remains on the stenosis over more than a pulsatile period.

Rapid Multi-Sensor Feature Fusion Based on Non-Stationary Kernel JADE for the Small-Amplitude Hunting Monitoring of High-Speed Trains

Joint Approximate Diagonalization of Eigen-matrices (JADE) cannot deal with non-stationary data. Therefore, in this paper, a method called Non-stationary Kernel JADE (NKJADE) is proposed, which can extract non-stationary features and fuse multi-sensor features precisely and rapidly. In this method, the non-stationarity of the data is considered and the data from multi-sensor are used to fuse the features efficiently. The method is compared with EEMD-SVD-LTSA and EEMD-JADE using the bearing fault data of CWRU, and the validity of the method is verified. Considering that the vibration signals of high-speed trains are typically non-stationary, it is necessary to utilize a rapid feature fusion method to identify the evolutionary trends of hunting motions quickly before the phenomenon is fully manifested. In this paper, the proposed method is applied to identify the evolutionary trend of hunting motions quickly and accurately. Results verify that the accuracy of this method is much higher than that of the EEMD-JADE and EEMD-SVD-LTSA methods. This method can also be used to fuse multi-sensor features of non-stationary data rapidly.

Meshfree simulations of ultrasound vector flow imaging using smoothed particle hydrodynamics

Before embarking on a series of in vivo tests, design of ultrasound-flow-imaging modalities are generally more efficient through computational models as multiple configurations can be tested methodically. To that end, simulation models must generate realistic blood flow dynamics and Doppler signals. The current in silico ultrasound simulation techniques suffer mainly from uncertainty in providing accurate trajectories of moving ultrasound scatterers. In mesh-based Eulerian methods, numerical truncation errors from the interpolated velocities, both in the time and space dimensions, can accumulate significantly and make the pathlines unreliable. These errors can distort beam-to-beam inter-correlation present in ultrasound flow imaging. It is thus a technical issue to model a correct motion of the scatterers by considering their interaction with boundaries and neighboring scatterers. We hypothesized that in silico analysis of emerging ultrasonic imaging modalities can be implemented more accurately with meshfree approaches. We developed an original fluid-ultrasound simulation environment based on a meshfree Lagrangian CFD (computational fluid dynamics) formulation, which allows analysis of ultrasound flow imaging. This simulator combines smoothed particle hydrodynamics (SPH) and Fourier-domain linear acoustics (SIMUS  =  simulator for ultrasound imaging). With such a particle-based computation, the fluid particles also acted as individual ultrasound scatterers, resulting in a direct and physically sound fluid-ultrasonic coupling. We used the in-house algorithms for fluid and ultrasound simulations to simulate high-frame-rate vector flow imaging. The potential of the particle-based method was tested in 2D simulations of vector Doppler for the intracarotid flow. The Doppler-based velocity fields were compared with those issued from SPH. The numerical evaluations showed that the vector flow fields obtained by vector Doppler components were in good agreement with the original SPH velocities, with relative errors less than 10% and 2% in the cross-beam and axial directions, respectively. Our results showed that SPH-SIMUS coupling enables direct and realistic simulations of ultrasound flow imaging. The proposed coupled algorithm has also the advantage to be 3D compatible and parallelizable.