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Perpendicular ultrasound velocity measurement by 2D cross correlation of RF data. Part A: Validation in a straight tube
Abstract and Figures
An ultrasound velocity assessment technique was validated, which allows the estimation of velocity components perpendicular
to the ultrasound beam, using a commercially available ultrasound scanner equipped with a linear array probe. This enables
the simultaneous measurement of axial blood velocity and vessel wall position, rendering a viable and accurate flow assessment.
The validation was performed by comparing axial velocity profiles as measured in an experimental setup to analytical and computational
fluid dynamics calculations. Physiologically relevant pulsating flows were considered, employing a blood analog fluid, which
mimics both the acoustic and rheological properties of blood. In the core region (|r|/a<0.9), an accuracy of 3cms−1 was reached. For an accurate estimation of flow, no averaging in time was required, making a beat to beat analysis of pulsating
flows possible.
Figures - uploaded by Frans van de Vosse
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... The derivatives of the formulas are essentially taken from the works of [8,13,20,21]. ...
... The parameters of pulse wave velocity (PWV, calculated according to [8,13,20,21]) as well as d (t) and ∆d, were part of the MKE algorithm. In contrast, only d (t) and ∆d were included in the application of the algorithm from the working group of San Diego (SanD). ...
... For calculation of both algorithms, NIBP data served as a reference for calibration. The parameters of pulse wave velocity (PWV, calculated according to [8,13,20,21]) as well as d (t) and ∆d, were part of the MKE algorithm. In contrast, only d (t) and ∆d were included in the application of the algorithm from the working group of San Diego (SanD). ...
Objective:
Due to ongoing technical progress, the ultrasonic measurement of blood pressure (BP) as an alternative to oscillometric measurement (NIBP) or the continuous non-invasive arterial pressure method (CNAP) moves further into focus. The US method offers several advantages over NIBP and CNAP, such as deep tissue penetration and the utilization of different arterial locations.
Approach:
Ten healthy subjects (six female, aged 30.9 ± 4.6 years) volunteered in our investigation. In the ultrasonic BP measurement, we differentiated between the directly measured (pulsatile diastolic and systolic vessel diameter) and indirectly calculated variables at three different artery locations on both arms, with two different ultrasound devices in the transversal and longitudinal directions of the transducer. Simultaneously, NIBP monitoring served as reference BP, while CNAP monitored the steady state condition of the arm under investigation. The Moens-Korteweg algorithm (MKE) and the algorithm of the working group of San Diego (SanD) were selected for the indirectly calculated ultrasonic BP data.
Main results:
With US, we were able to measure the BP at each selected arterial position. Due to the investigation setup, we found small but significant interactions of the main effects. Bland and Altman analysis revealed that US-BP measurement was similar to NIBP, with superior accuracy when compared to the established CNAP method. In addition, US-BP measurement showed that the measurement accuracy of both arms can be regarded as identical. In a detailed comparison of the selected arterial vascular sections, systematic discrepancies between the right and left arm could be observed.
Conclusion:
In our pilot study, we measured BP effectively and accurately by US using two different devices. Our findings suggest that ultrasonic BP measurement is an adequate alternative for live and continuous hemodynamic monitoring.
... only reading out a central subgroup of the transducer array. As an extreme example, Beulen et al. (2010) only read out 14 elements to obtain a frame rate of 730 s −1 . Naturally, this reduces the lateral field-of-view, but in many cases even a single velocity profile (in the beam direction) will already provide sufficient information about Page 11 of 28 3 the flow. ...
... The consequences of the 'beam sweep' effect were acknowledged by some authors (Beulen et al. 2010;Poelma et al. 2011), and an extensive discussion is given in the study by Zhou et al. (2013). The velocities can be corrected for the beam sweep effect using the following expressions: ...
... Understandably, the first wave of studies using UIV focussed on the validation of the technique. This was done for increasingly complex flows: initially using steady laminar flow (Beulen et al. 2010;Zheng et al. 2006;Qian et al. 2010;Niu et al. 2010;Poelma et al. 2012), followed by pulsatile flows (Kim et al. 2004b;Poelma et al. 2011) and ultimately in flow phantoms. The latter are 'in vitro' studies using models that represent e.g. a ventricle (Kheradvar et al. 2010) or (diseased) blood vessels (Zhang et al. 2011;Zhu et al. 2011). ...
Whole-field velocity measurement techniques based on ultrasound imaging (a.k.a. ‘ultrasound imaging velocimetry’ or ‘echo-PIV’) have received significant attention from the fluid mechanics community in the last decade, in particular because of their ability to obtain velocity fields in flows that elude characterisation by conventional optical methods. In this review, an overview is given of the history, typical components and challenges of these techniques. The basic principles of ultrasound image formation are summarised, as well as various techniques to estimate flow velocities; the emphasis is on correlation-based techniques. Examples are given for a wide range of applications, including in vivo cardiovascular flow measurements, the characterisation of sediment transport and the characterisation of complex non-Newtonian fluids. To conclude, future opportunities are identified. These encompass not just optimisation of the accuracy and dynamic range, but also extension to other application areas.
... As described in part A of this two-part manuscript ( Beulen et al. 2010) ultrasonic perpendicular velocimetry (UPV) enables simultaneous assessment of axial velocity profile and vessel wall position. It was shown that for an accurate estimation of flow, no averaging is required, making a beat to beat analysis of pulsating flows possible. ...
... The data from the flow probe measurements were acquired simultaneously with the data from the ultrasound scanner using a common trigger signal generated by a PC using the same LabVIEW data acquisition software. For a description of the blood mimicking fluid (BMF), data acquisition and data processing, the reader is referred to Part A, Beulen et al. (2010). ...
... Overall, the deviations found between calculated and measured velocity profiles are comparable to the deviations found between calculated and measured velocity profiles in straight geometries ( Beulen et al. 2010). Both for the d = 0.01 and d = 0.02 geometry, the deviation between the velocity profile measurements and calculated velocity profile increases in the near-wall region, 0.9 \ |r|/a \ 1.0 and especially near the anterior wall (r/a =-1), probably due to the fact that the signal of the wall dominates the scattering signal in this region. ...
... But the robustness and solidness about those methods in blood flow velocity profile estimate may not guarantee due to the low signal-noise-ratio (LSR) of the RFS received at the finite detection time. With the purpose of enhancement the robustness and solidness of the estimation about the blood flow velocity profile, the narrow-band methods [5][6] have been bring forward. Not only the robustness and solidness of the estimated blood flow velocity profile has been ensured, but also their spatial resolution based on the evaluating the phase-shift or frequency-shift of demodulated Doppler signals of the RFS with in-phase and quadrature components (IQS). ...
This paper presents a study on blood flow velocity profile estimation based on the pulse-echo RF signals generated with adaptively varying pulse-shooting intervals (VPI). With the purpose of evaluating the correctness and reliability about the estimation of blood flow velocity profile, the relevant simulation experiments are carried out in this paper based on a Field II ultrasound emulation model for common carotid artery without stenosis lesions. In simulation experiments, the RF signals are firstly generated with the fixed pulse-shooting interval (FPI) of 1/10000 s and VPIs predefined by parabolic velocity profile of blood flow (VPI_PV). Then the relevant PW Doppler signals are obtained for estimating the blood flow velocity profiles by employing the autocorrelation algorithm. It can be found from the results that the estimated blood flow velocity profiles from the PW Doppler signals of VPI_PV have enhancing validity compared with that received from the PW Doppler signals of FPI. The blood flow velocity profiles with enhanced validity would be used as basic contents for disease diagnosis.
... This upper limit on the measureable velocity is well known [26,33], with authors reporting velocity measurements up to around 70 cm s 21 [30]. Restricting the field of view [34], or skipping lines [35], can increase the frame rate but at the expense of reduced image width or detail. Leow et al. [36] used plane wave imaging, in which the whole image frame is captured simultaneously, to achieve frame rates of 1000 Hz and measured velocities up to 80 cm s 21 . ...
Blood velocity measurements are important in physiological science and clinical diagnosis. Doppler ultrasound is the most commonly used method but can only measure one velocity component. Ultrasound imaging velocimetry (UIV) is a promising technique capable of measuring two velocity components; however, there is a limit on the maximum velocity that can be measured with conventional hardware which results from the way images are acquired by sweeping the ultrasound beam across the field of view. Interleaved UIV is an extension of UIV in which two image frames are acquired concurrently, allowing the effective inter-frame separation time to be reduced and therefore increasing the maximum velocity that can be measured. The sweeping of the ultrasound beam across the image results in a systematic error which must be corrected: in this work we derived and implemented a new velocity correction method which accounts for acceleration of the scatterers. We then, for the first time, assessed the performance of interleaved UIV for measuring pulsatile arterial velocities by measuring flows in phantoms and in vivo and comparing the results with spectral Doppler ultrasound and transit-time flow probe data. The velocity and flow rate in the phantom agreed within 5-10 % of peak velocity, and 2-9% of peak flow, respectively and in vivo the velocity difference was 9 % of peak velocity. The maximum velocity measured was 1.8 m/s, the highest velocity reported with UIV. This will allow flows in diseased arteries to be investigated and so has the potential to increase diagnostic accuracy and enable new vascular research.
... Many validation studies have appeared in the last few years, benchmarking the technique against, e.g. optical PIV or theoretical velocity profiles Poelma et al. 2011;Beulen et al. 2010;Walker et al. 2014). However, all of these studies used time-averaged data, or phase-averaged profiles in the case of pulsatile flow. ...
Ultrasound imaging velocimetry (UIV) has received considerable interest as a tool to measure in non-transparent flows. So far, studies have only reported statistics for steady flows or used a qualitative approach. In this study, we demonstrate that UIV has matured to a level where accurate turbulence statistics can be obtained. The technique is first validated in laminar and fully developed turbulent pipe flow (single-phase, with water as fluid) at a Reynolds number of 5300. The flow statistics agree with the literature data. Subsequently, we obtain similar statistics in turbulent two-phase flows at the same Reynolds number, by adding solid particles up to volume fraction of 3 %. In these cases, the medium is completely opaque, yet UIV provides useable data. The error in the measurements is estimated using an ad hoc approach at a volume load up to 10 %. For this case, the errors are approximately 1.9 and 0.3 % of the centerline velocity for the streamwise and radial velocity components, respectively. Additionally, it is demonstrated that it is possible to estimate the local concentration in stratified flows.
... The current Echo-PIV technique is mainly based on focused beam excitations and PIV processing on B-mode ultrasound images. To overcome the limitation of low frame rates due to the conventional method, we examined the PIV technique using radio-frequency (RF) ultrasound images [9] issued from planar wavefronts. The Field II program [10,11] was used as the scattering acoustic model. ...
This work aims to study the potential of high-speed echographic particle image velocimetry (Echo-PIV) technique based on plane wave excitation in physiological flows. We evaluate the Echo-PIV technique using a simulation environment integrating smoothed particle hydrodynamics (SPH), a mesh-free method in computational mechanics, and linear acoustics. In SPH, the fluid domain is divided into a set of particles and the physical properties of each particle are calculated based on the properties of the neighboring particles. By contrast with standard computational methods, fluid-acoustic coupling is effortless since SPH particles can be used directly as sound scatterers. Field II is used as a scattering acoustic model. SPH particles are insonified with ultrasound plane waves and the backscattered RF signals are analyzed. The Poiseuille and Womersley flows, as standard benchmark cases, and then pulsatile flow in a bifurcation artery are insonified perpendicularly by acoustic plane waves at a rate higher than 1000 fps. The velocity fields are then determined using iterative multigrid PIV processing on the RF images. The velocity profiles derived by high-speed Echo-PIV were very concordant with those yielded by SPH.
Cardiovascular diseases (CVD) are the leading cause of morbidity and mortality in the western world. In the last three decades, fluid dynamics investigations have been an important component in the study of the cardiovascular system and CVD. A large proportion of studies have been restricted to computational fluid dynamic (CFD) modeling of blood flow. However, with the development of flow measurement techniques such as particle image velocimetry (PIV), and recent advances in additive manufacturing, experimental investigation of such flow systems has become of interest to validate CFD studies, testing vascular implants and using the data for therapeutic procedures. This article reviews the technical aspects of in-vitro arterial flow measurement with the focus on PIV. CAD modeling of geometries and rapid prototyping of molds has been reviewed. Different processes of casting rigid and compliant models for experimental analysis have been reviewed and the accuracy of construction of each method has been compared. A review of refractive index matching and blood mimicking flow circuits is also provided. Methodologies and results of the most influential experimental studies are compared to elucidate the benefits, accuracy and limitations of each method.
Conventional color Doppler imaging is limited, since it only provides velocity estimates along the ultrasound beam direction for a restricted field of view at a limited frame rate. High frame rate speckle tracking, using plane wave transmits, has shown potential for 2D blood velocity estimation. However, due to the lack of focusing in transmit, image quality gets reduced, which hampers speckle tracking. Although ultrafast imaging facilitates improved clutter filtering, it still remains a major challenge in blood velocity estimation. Signal drop-outs and poor velocity estimates are still present for high beam-to-flow angles and low blood flow velocities. In this work, ultrafast plane wave imaging was combined with multi-scale speckle tracking to assess the 2D blood velocity vector in a common carotid artery (CCA) flow field. A multi-angled plane wave imaging sequence was used to compare the performance of displacement compounding, coherent compounding and compound speckle tracking. Zero-degree plane wave imaging was also evaluated. The performance of the methods was evaluated before and after clutter filtering for the large range of velocities (0 to 1.5 m/s) that are normally present in a healthy CCA during the cardiac cycle. An extensive simulation study was performed, based on a sophisticated model of the CCA, to investigate and evaluate the performance of the methods at different pulse repetition frequencies and signal-to-noise levels. In vivo data were acquired of a healthy carotid artery bifurcation to support the simulation results. In general, methods utilizing compounding after speckle tracking, i.e., displacement compounding and compound speckle tracking, were least affected by clutter filtering and provided the most robust and accurate estimates for the entire velocity range. Displacement compounding, which uses solely axial information to estimate the velocity vector, provided most accurate velocity estimates, although it required sufficiently high pulse repetition frequencies in high blood velocity phases and reliable estimates for all acquisition angles. When this latter requirement was not met, compound speckle tracking was most accurate, because it uses the possibility to discarded angular velocity estimates corrupted by clutter filtering. Similar effects were observed for in vivo data obtained at the carotid artery bifurcation. Investigating a combination of these two compounding techniques is recommended for future research.
Doppler ultrasound has now developed to the point where the rate of flow of blood in a given vessel can be measured with appropriate instrumentation. The theoretical basis of Doppler flow measurement is reviewed in this paper, with particular emphasis on the potential and actual sources of error. Three distinct approaches are identified, and the strengths and weaknesses of each discussed. The separate errors involved in estimating the vessel cross-sectional area, the angle of approach, and the Doppler shift are analyzed, together with the question of the uniformity of scattering from the blood. In vivo and in vitro tests of the accuracy obtained using a number of Doppler flow measuring instruments are then reviewed. It is concluded that the Doppler methods are capable of good absolute accuracy when suitably designed equipment is used in appropriate situations, with systematic errors of 6% of less. There are, however, considerable random errors, attributable primarily to errors in measuring the cross-sectional area and the angle of approach. Repeating the measurement of flow several times and averaging the results can reduce these random errors to an acceptable level.
In clinical practice, ultrasound velocimetry is often used as a non-invasive method to determine flow through arteries. Generally, the flow is derived by assessment of the centerline velocity and assuming a certain velocity profile, e.g. a Poiseuille or Womersley profile. In order to apply these velocity profiles it is assumed that the measurement is performed on a relatively long, straight vessel. However, in-vivo vessels are slightly curved, which causes asymmetry in the velocity distribution and thus an inaccurate flow determination.
Conventional ultrasound scanners are restricted to display the blood velocity component in the ultrasound beam direction. By introducing a laterally oscillating field, signals are created from which the transverse velocity component can be estimated. This paper presents velocity and volume flow estimates obtained from flow phantom and in-vivo measurements at 90° relative to the ultrasound beam axis. The flow phantom experiment setup consists of a SMI140 flow phantom connected to a CompuFlow 1000 programmable flow pump, which generates a flow similarly to that in the femoral artery. A B-K medical 8804 linear array transducer with 128 elements and a center frequency of 7 MHz is emitting 8 cycle ultrasound pulses with a pulse repetition frequency of 7 kHz in a direction perpendicular to the flow direction in the phantom. The transducer is connected to the experimental ultrasound scanner RASMUS, and 1.4 seconds of data is acquired. Using 2 parallel receive beamformers a transverse oscillation is introduced with an oscillation period 1.2 mm. The velocity estimation is performed using an extended autocorrelation algorithm. The volume flow can be estimated with a relative standard deviation of 13.0% and a relative mean bias of 3.4%. The in-vivo experiment is performed on the common carotid artery of a healthy 25 year old male. The same transducer and setup is used as in the flow phantom experiment, and the data is acquired using the RASMUS scanner. The peak velocity of the carotid flow is estimated to 1.2 m/s and the volume flow to 290 ml/min. This is within normal physiological range.
A technique for imaging fluid flows is proposed, based on the ultrafast analysis of the ultrasonic speckle signal backscattered by particles following the flow. Such an “ultrasonic speckle velocimetry” (USV) provides two-dimensional measurements of one component of the fluid velocity field at about 5000 frames per second. USV is applied to three different flows and future improvements of the technique are described. © 2001 American Institute of Physics.
After a short introduction on generalities about probability distributions, the book consists of 40 chapters describing in alphabetical order individual distributions commonly encountered in applications. It is a substantially revised edition with, in particular, new diagrams and a longer treatment of the Weibull distribution in its two, three and five parameter forms. With two exceptions the distributions are univariate, i.e. one-dimensional.
Typically for each distribution there is an introductory paragraph about potential applications, the formula for the distribution, the main properties of the distribution, usually some diagrams illustrating the shape of the distribution, and some notes on relations with other distributions and on how its parameters might be estimated from data. In some cases a note on simulation of values is included. The book ends with some computational references, some statistical tables and a short bibliography.
The book contains a large amount of information clearly set out in concise form. The introductory notes on the motivation for the individual distributions are sometimes perfunctory and inevitably are no substitute for a careful discussion of the domain of potential applicability of, for example, the exponential distribution or the negative binomial distribution. They are of little or no help in dealing with the question: `Here is a particular kind of problem calling for a simple form of probability distribution: what kind of distribution might be useful?' However, the book could certainly be a valuable reference source on such specific if rather narrow questions as: `Given involvement in the use of the negative binomial distribution, what are its moments?'
A criticism of the book is the failure to give references for further reading about individual special distributions. The short general bibliography is no help on where to look for particular points.
D R Cox