Multigate doppler signal analysis using 3-D regularized long AR modelling.

Autoregressive (AR) modelling has already been proposed as an alternative to fast Fourier transform to process ultrasound (US) Doppler signals. Previous works introduced long AR models, set up under a regularization framework. The latter may be in 1-D (frequency) or 2-D (frequency and space or time). This study generalizes the spectrum regularization in the three dimensions frequency, space and time. The problem of the penalization function is addressed, and a new convex solution is proposed, taking into account possible nonstationarity of the Doppler signal. The parameter tuning is based on simulations using a standard Doppler signal model. The first results show that this processing improves the spectral estimation, and is well suited to flow interpretation.     

A new method of encoding and displaying audio Doppler-shift signals: the chromagram

A technique based on chromaticity is described for processing and displaying audio Doppler-shift signals. A chromaticity vector is derived for a fixed time interval (e.g. 5 ms) of the input Doppler signal, which is directly related to the Fourier power spectrum distribution of that signal over that interval. An approximated approach is then described for implementing the above "chromagraphic analysis" in order to meet Doppler ultrasound real-time requirements. A static and dynamic chromagram display format is defined which enables the chromaticity information to be displayed in colour on a digital television monitor.     

Doppler angle estimation of pulsatile flows using AR modeling

In quantitative ultrasonic flow measurements, the beam-to-flow angle (i.e., Doppler angle) is an important parameter. An autoregressive (AR) spectral analysis technique in combination with the Doppler spectrum broadening effect was previously proposed to estimate the Doppler angle. Since only a limited number of flow samples are used, real-time two-dimensional Doppler angle estimation is possible. The method was validated for laminar flows with constant velocities. In clinical applications, the flow pulsation needs to be considered. For pulsatile flows, the flow velocity is time-varying and the accuracy of Doppler angle estimation may be affected. In this paper, the AR method using only a limited number of flow samples was applied to Doppler angle estimation of pulsatile flows. The flow samples were properly selected to derive the AR coefficients and then more samples were extrapolated based on the AR model. The proposed method was verified by both simulations and in vitro experiments. A wide range of Doppler angles (from 3o degrees to 78 degrees) and different flow rates were considered. The experimental data for the Doppler angle showed that the AR method using eight flow samples had an average estimation error of 3.50 degrees compared to an average error of 7.08 degrees for the Fast Fourier Transform (FFT) method using 64 flow samples. Results indicated that the AR method not only provided accurate Doppler angle estimates, but also outperformed the conventional FFT method in pulsatile flows. This is because the short data acquisition time is less affected by the temporal velocity changes. It is concluded that real-time two-dimensional estimation of the Doppler angle is possible using the AR method in the presence of pulsatile flows. In addition, Doppler angle estimation with turbulent flows is also discussed. Results show that both the AR and FFT methods are not adequate due to the spectral broadening effects from the turbulence.     

Selection of the order of autoregressive models for spectral analysis of Doppler ultrasound signals

Autoregressive modelling includes a model identification procedure, that is, it is necessary to choose the order of the autoregressive (AR) process that best describes the given finite record (frame) of the signal. Four previously suggested procedures to choose the "best order" of AR processes have been tested: The "first zero crossing" of the autocorrelation function (FZC), the "final prediction error" (FPE), "Akaike's information criterion" (AIC), and the "criterion autoregressive transfer-function" (CAT). It was found that: (i) For more than 98% of the 1280 frames of Doppler signals analyzed the order selected by the various criteria was ten or less. (ii) For the same records of Doppler signals, FPE, AIC and CAT behave in a very similar manner, but the FZC criterion underestimates the order in relation to the others. (iii) For true AR processes, the order selected is frequently different from the true AR order when frames of 64 samples are used. When more samples are used FPE, AIC and CAT tend to select the correct order. (iv) The effect on the spectral estimate of using too high a model order is usually insignificant, while using too low an order can change the estimate more dramatically, that is, overestimating the model order is better than underestimating it.     

The wall signal removal in Doppler ultrasound systems based on recursive PCA

In Doppler ultrasound (US) systems, a high-pass filter is usually employed to remove the wall component from the blood flow signal. However, this will lead to the loss of information from the low velocity flow. In this paper, an algorithm based on the principal components analysis (PCA) is proposed, in which singular value decomposition (SVD) is used to extract the main component from the mixed signals. Furthermore, the recursive process is incorporated into the PCA method to improve the performance of wall signal removal. This approach and the traditional high-pass filtering one are, respectively, applied to analyze the computer-simulated in vitro and in vivo Doppler US signals. With the proposed method, the wall signal can be removed while a large portion of low-velocity blood signal remains. Comparison experiments show that this novel approach can satisfy the requirements of Doppler US system and is practicable under a broad range of measurement conditions. Because this algorithm is based on real data, it is currently applied to unidirectional signals.     

Time delays in ultrasound systems can result in fallacious measurements

Even short time delays (less than 30 ms) in cardiac motion pattern may have clinical relevance. These delays can be measured with echocardiography, using techniques such as flow and tissue Doppler and M-mode together with external signals (e.g., ECG and phonocardiography). If one or more of these signals are delayed in relation to the other signals (asynchronous), an incorrect definition of cardiac time intervals can occur, the consequence of which is invalid measurement. To determine if this time delay in signal processing is a problem, we tested three common ultrasound (US) systems using the ECG as the reference signal. We used a digital ECG simulator and a Doppler string phantom to obtain test signals for flow and tissue pulsed Doppler, M-mode, phonocardiography, auxiliary and ECG signals. We found long time delays of up to 90 ms in one system, whereas delays were mostly short in the two other systems. The time delays varied relative to system settings. Consequently, to avoid these errors, precise knowledge of the characteristics of the system being used is essential.     

Arterial Doppler signal simulation by time domain processing

Objective: The study's aim was to develop and test a rapid and simply implemented computer simulation method for Doppler ultrasound signals incorporating mean frequency, bandwidth and signal power variation and vortex simulation. Methods: We describe a computer simulation method for arterial Doppler ultrasound signals based on the application of white noise to a filter with a time-varying impulse response. Results: This method is simple to implement and requires the input of only the mean frequency, spectrum shape and Doppler power variation during the cardiac cycle. Analysis with the short term Fourier transform shows good agreement with theoretical prediction. Conclusion: This simulation method can provide a useful tool for comparison of the performance of Doppler signal processing techniques.     

Dorsal aortic flow velocity in chick embryos of stage 16 to 28

The objective of this study was to evaluate two Doppler frequency-detection methods to measure blood flow velocity in the developing chick embryo. We compared the commonly used directional zero-crossing counter and a customized digital bidirectional spectrum analyzer. At development stages 16 up to 28 (2.5 to 6 days incubation), a reversed flow component in the dorsal aorta was demonstrated using the bidirectional spectrum analyzer. Dorsal aortic velocities obtained with the directional zero-crossing counter were significantly lower than with the bidirectional spectrum analyzer in stages 16, 20 and 28. In addition to the differences in the absolute velocity values, there was also a remarkable discrepancy in the velocity waveform shape using the two Doppler frequency processors. The calculated heart rate using the two Doppler frequency processors was identical. It is concluded that a Doppler velocity detector based on spectral analysis is superior to the hitherto used zero-crossing counter in the chick embryo. With the customized digital bidirectional spectrum analyzer, we can accurately measure the hemodynamics of the developing chick embryo.     

Adaptive,autoregressive spectral estimation for analysis of electrical signals of gastric origin

The electrical activity of the human stomach, which normally shows a frequency of about 0.05 Hz, may be studied non-invasively by either cutaneous electrogastrography (EGG) or surface magnetogastrography (MGG). Detection of changes in frequency with time may be useful to characterize gastric disorders. The fast Fourier transform (FFT) has been the most commonly used method for the automated spectral analysis of the signals obtained from the EGG or the MGG. We have used an autoregressive (AR) parametric spectrum estimator to analyse simulated signals of gastric electrical activity, and to evaluate the results of human studies using EGG and MGG. In comparison with the FFT, our results showed that the AR spectrum estimator provided more detailed qualitative information about frequency variations of short duration simulated signals than the FFT. In the human studies, the AR estimator was as good as the conventional FFT methods in detecting physiological changes in frequency and in identifying abnormal recordings. We conclude that the AR spectral estimator may provide a better qualitative analysis of frequency variations in small portions of the signal, and is as useful as the FFT to analyse human EGG or MGG studies.     

Stimulated acoustic emission: pseudo-Doppler shifts seen during the destruction of nonmoving microbubbles

The purpose of this study was to evaluate the appearance and the characteristics of stimulated acoustic emission (SAE) as an echo contrast-specific color Doppler phenomenon with impact on myocardial contrast echocardiography (MCE). Stationary microbubbles of the new contrast agent SH-U 563A (Schering AG) were embedded within a tissue-mimicking gel material. Harmonic power Doppler imaging (H-PDI), color Doppler and pulse-wave Doppler data were acquired using an HDI-5000 equipped with a phased-array transducer (1.67/3.3 MHz). In color Doppler mode, bubble destruction resulted in random noise like Doppler signals. PW-Doppler revealed short "pseudo-Doppler" shifts with a broadband frequency spectrum. Quantification of SAE events by H-PDI demonstrated an exponential decay of signal intensities over successive frames. A strong linear relationship was found between bubble concentration and the square root of the linearized H-PDI signal for a range of concentrations of more than two orders of magnitude (R = 0.993, p < 0.0001). Intensity of the H-PDI signals correlated well with emission power (R = 0.96, p = 0.0014). SAE results from disintegration of microbubbles and can be demonstrated by all Doppler imaging modalities, including H-PDI. Intensity of SAE signals is influenced by the applied acoustic power and correlates highly with the concentration of microbubbles. Because intensity of SAE signals correlates highly with echo contrast concentrations, analysis of SAE signals might be used for quantitative MCE.     

MP3 compression of Doppler ultrasound signals

The effect of lossy, MP3 compression on spectral parameters derived from Doppler ultrasound (US) signals was investigated. Compression was tested on signals acquired from two sources: 1. phase quadrature and 2. stereo audio directional output. A total of 11, 10-s acquisitions of Doppler US signal were collected from each source at three sites in a flow phantom. Doppler signals were digitized at 44.1 kHz and compressed using four grades of MP3 compression (in kilobits per second, kbps; compression ratios in brackets): 1400 kbps (uncompressed), 128 kbps (11:1), 64 kbps (22:1) and 32 kbps (44:1). Doppler spectra were characterized by peak velocity, mean velocity, spectral width, integrated power and ratio of spectral power between negative and positive velocities. The results suggest that MP3 compression on digital Doppler US signals is feasible at 128 kbps, with a resulting 11:1 compression ratio, without compromising clinically relevant information. Higher compression ratios led to significant differences for both signal sources when compared with the uncompressed signals.     

Directional Doppler techniques for detection of blood velocities.

Five different methods of obtaining directional information from Doppler Velocimeters are discussed, with comments on their relative applicability. These are based on the techniques of Single Sideband, Heterodyne, and Phase Quadrature detection.Real-time spectrum analysis of these Doppler signals and display of their waveform shapes is also considered. Some examples of directional waveforms taken from human subjects are shown and system configurations, suitable for clinical measurement, are outlined.     

Noninvasive assessment of left ventricular isovolumic contraction and relaxation with continuous wave Doppler aortic regurgitant velocity signals: an in vivo validation study.

The purpose of this study was to provide fundamental in vivo validation of a method with the use of aortic regurgitant (AR) jet signals recorded with continuous wave (CW) Doppler for assessing left ventricular (LV) isovolumic contraction and relaxation. Preliminary studies have suggested that analysis of CW Doppler AR velocity signals permits the estimation of LV positive and negative dP/dt. We studied 19 hemodynamically different states in 6 sheep with surgically induced chronic aortic regurgitation. CW AR velocity spectra and high-fidelity LV and aortic pressures were recorded simultaneously. Rates of LV pressure rise and fall (RPR and RPF) were calculated by determining the time interval between points at 1 m/s and 2.5 m/s in the deceleration and acceleration slopes of the CW Doppler AR velocity envelope (corresponding to a pressure change of 21 mm Hg). RPR and RPF calculated by CW Doppler analysis for each state were compared with the peak positive dP/dt and negative dP/dt, obtained from the corresponding high-fidelity LV pressure curve, respectively. The LV peak positive and negative dP/dt derived by catheter ranged from 817 to 2625 mm Hg/s and from 917 to 2583 mm Hg/s, respectively. Multiple regression analysis showed that Doppler RPR correlated well with catheter peak positive dP/dt (r = 0.93; mean differences, -413 +/- 250 mm Hg/s). There was also good correlation and agreement between Doppler RPF and the catheter peak negative dP/dt (r = 0.89; mean difference, -279 +/- 239 mm Hg/s). Both Doppler-determined RPR and RPF underestimated their respective LV peak dP/dt. CW Doppler AR spectra can provide a reliable noninvasive estimate of LV dP/dt and could be helpful in the serial assessment of ventricular function in patients with aortic regurgitation.     

Measurement of the Doppler Power of Flowing Blood Using Ultrasound Doppler Devices

Measurement of the Doppler power of signals backscattered from flowing blood (henceforth referred to as the Doppler power of flowing blood) and the echogenicity of flowing blood have been used widely to assess the degree of red blood cell (RBC) aggregation for more than 20 y. Many studies have used Doppler flowmeters based on an analogue circuit design to obtain the Doppler shifts in the signals backscattered from flowing blood; however, some recent studies have mentioned that the analogue Doppler flowmeter exhibits a frequency-response problem whereby the backscattered energy is lost at higher Doppler shift frequencies. Therefore, the measured Doppler power of flowing blood and evaluations of RBC aggregation obtained using an analogue Doppler device may be inaccurate. To overcome this problem, the present study implemented a field-programmable gate array-based digital pulsed-wave Doppler flowmeter to measure the Doppler power of flowing blood, in the aim of providing more accurate assessments of RBC aggregation. A clinical duplex ultrasound imaging system that can acquire pulsed-wave Doppler spectrograms is now available, but its usefulness for estimating the ultrasound scattering properties of blood is still in doubt. Therefore, the echogenicity and Doppler power of flowing blood under the same flow conditions were measured using a laboratory pulser–receiver system and a clinical ultrasound system, respectively, for comparisons. The experiments were carried out using porcine blood under steady laminar flow with both RBC suspensions and whole blood. The experimental results indicated that a clinical ultrasound system used to measure the Doppler spectrograms is not suitable for quantifying Doppler power. However, the Doppler power measured using a digital Doppler flowmeter can reveal the relationship between backscattering signals and the properties of blood cells because the effects of frequency response are eliminated. The measurements of the Doppler power and echogenicity of flowing blood were compared with those obtained in several previous studies.     

A simulation of transit time effects in Doppler ultrasound signals

A signal model is proposed which can be used to study frequency extraction techniques for Doppler ultrasound. The signal is based on the physics of the Doppler process and depends on a sliding window used to average a set of independent Gaussian random numbers. This window is related to the shape of the sample volume for the Doppler pulse and depends on the Doppler angle. Simulation results compare favorably with results from flow experiments in terms of the variance of the estimated Doppler shift, the shape of the power spectra and the behavior of the signals with respect to Burg autoregressive power spectra. A potential use of the signal in the study of spectral analysis techniques is presented.     

A real time programmable digital filter for biomedical signal enhancement incorporating a high-level design interface

A simple but highly integrated digital signal processing system is described for real time filtering of biomedical signals. It includes the necessary processing and communications hardware, the processing code itself and a high-level software interface that enables the user to design and download arbitrary finite impulse response filters to the run-time system. The filter coefficients are calculated using the frequency sampling method. Since the filters are realized using a finite impulse response, no phase distortion is introduced into the processed signals. A unique feature of the design is the manner in which the software and hardware components have been organized as an intelligent system, obviating on the part of the user a detailed knowledge of filter design theory or any abilities in processor architecture and assembly code programming.     

Digital acquisition and interactive processing of ultrasonic echoes

The requirements for an interactive digital signal processing system for ultrasonic pulse-echo signals are discussed. A system based on an Interdata Model 80 mini-computer and micro-processor interface is described. The system is capable of acquiring ultrasonic data at a sampling rate of 6 MHz. Ultrasonic B-mode data may be acquired in Line Mode, when echo waveform data and transducer position and orientation are stored, or in Section Mode when the data is converted directly into picture form in memory in the same way that a standard echogram is formed on the screen of an oscilloscope. In each case the data for single complete high resolution echogram may be acquired in less than 15 sec. It is shown that the 6 MHz sampling rate is sufficient to faithfully preserve the echo waveshape of a 2 MHz system independently of the relation to the phase of the sampling. Also shown is a cross-sectional echogram of the pregnant uterus, and its digital representation with a raster density of 80 × 100 and 160 × 200 picture elements.The computer is programmed with an interactive program to allow ultrasonic signals to be acquired, stored, processed and examined with the convenience of a desk calculator. Sample operations are illustrated including data interpolation, spectrum analysis, filtering and complex signal deconvolution. The ability of deconvolution techniques to resolve targets separated by less than one wavelength in depth is demonstrated. Possibilities of further processing techniques are outlined.     

A new and simple Doppler method for measurement of fetal cardiac isovolumetric contraction time.

OBJECTIVES: The fetal cardiac isovolumetric contraction time is defined as the interval between mitral valve closure and aortic valve opening. The objective of this study was to develop a simple and reliable Doppler method for measuring fetal isovolumetric contraction time using a digital filtering and processing system. METHODS: Cardiac Doppler signals were recorded from 40 fetuses at 18-40 weeks' gestation using a continuous-wave ultrasound transducer. The raw signal was digitized, filtered and divided into five different frequency ranges: 250-375, 375-500, 500-750, 750-1000 and 1000-1500 Hz. To determine the most suitable filter setting for detecting mitral valve closure and aortic valve opening signals, we examined whether they were detected clearly in each filter range. RESULTS: Both mitral valve closure and aortic valve opening signals were detected clearly in the 500-1000 Hz range. The atrioventricular flow and outflow noises in the 250-500 and 1000-1500 Hz ranges helped us to identify the signals. It was found that dividing the raw signals into three ranges of 250-500, 500-1000 and 1000-1500 Hz was the most suitable digital-filter setting for measuring isovolumetric contraction time. CONCLUSIONS: We have developed a simple Doppler method for measuring fetal isovolumetric contraction time. The advent of digital processing has simplified the equipment and the simultaneous multidisplay of three different filtered signals enables easy and accurate measurement.     

Automated embolus identification using a rule-based expert system

Transcranial Doppler ultrasound (US) can be used to detect microemboli in the cerebral circulation, but is still limited because it usually relies on "human experts" (HEs) to identify signals corresponding to embolic events. The purpose of this study was to develop an automatic system that could replace the HE and, thus, make the technique more widely applicable and, potentially, more reliable. An expert system, based around a digital signal-processing board, analysed Doppler signal patterns in both the time domain and frequency domain. The system was trained and tested on Doppler signals recorded during the dissection and recovery phases of carotid endarterectomy. It was tested with 74 separate 2.5-min recordings that contained at least 575 artefacts in addition to 253 s of diathermy interference. The results were compared with the results obtained by three HEs. Using a "gold-standard" that classified any event detected by the majority of HEs as an embolus, the automatic system displayed a sensitivity of 94.7% and a specificity of 95.1% for 1151 candidate events 7 dB or more above the clutter (signal-to-clutter ratio, SCR, > or = 7 dB), and 89.6% and 95.3%, respectively, for 2098 candidate events with SCR > or = 5 dB. The system had a very similar performance to individual HEs for SCR > or = 7dB, and was only marginally worse for SCR > or = 5 dB.     

Microembolic signal description: a reappraisal based on a customized digital postprocessing system

The high variability in presence and signature of microembolic signals (MES), detected with transcranial Doppler sonography (TCD) in the middle cerebral artery (MCA), cannot be explained with the currently available published data. We applied customized postprocessing on the radiofrequency (RF) signal of a standard TCD system. The spatial resolution was on the order of 2 mm, depending only on the length of the ultrasound (US) burst emitted. The amplitude of clutter-filtered RF signals was color-coded and plotted as a function of time and depth (range 30 mm). Additionally, 128 point fast Fourier transforms (FFTs) (50% temporal overlap) were calculated, visualizing both the background Doppler spectrum and the MES. We evaluated 122 gaseous MES from two patients during cardiac surgery and 52 particulate MES from four patients after carotid endarterectomy. Both MES categories showed comparable properties: they appeared in the RF amplitude plot as rather straight lines of increased intensity, indicating that the velocity remained approximately the same while they passed the US beam. The velocity calculated from the amplitude plot never exceeded that of the background Doppler spectrum. Various "MES patterns" could be identified with respect to the depth range at which the MES were visible. A quarter of the gaseous MES changed their direction at a specific depth, suggesting that the MES entered a branch (e.g., an M2 artery or the anterior cerebral artery). In the FFT analysis, these MES contained both positive and negative frequencies. It is concluded that MES show consistent signature patterns in the amplitude-time plots and that the previously reported variability of MES appearance in conventional Doppler systems is an artefact caused by relatively large signal amplitudes and sample volumes.