Experimental evaluation of velocity and power estimation forultrasound blood flow imaging, by means of a two-dimensionalautocorrelation approach

This paper evaluates experimentally the performance of a novel axial velocity estimator, the 2D autocorrelator, and its Doppler power estimation counterpart, the 2D zero-lag autocorrelator, in the context of ultrasound color flow mapping. The evaluation also encompasses the well-established 1D autocorrelation technique for velocity estimation and its corresponding power estimator (1D zero-lag autocorrelator), to allow performance comparisons under identical conditions. Clutter-suppressed in vitro data sets from a steady-flow system are used to document the effect of the range gate and ensemble length, noise level and angle of insonation on the precision of the velocity estimates. The same data sets are used to examine issues related to the estimation of the Doppler signal's power. The first-order statistics of power estimates from regions corresponding to flow and noise are determined experimentally and the ability of power-based thresholding to separate flow signals from noise is characterized by means of ROC analysis. In summary, the results of the in vitro evaluation show that the proposed 2D-autocorrelation form of processing is consistently better than the corresponding 1D-autocorrelation techniques, in terms of both velocity and power estimation. Therefore, given their relatively modest implementation requirements, the 2D-autocorrelation algorithms for velocity and power estimation appear to represent a superior, yet realistic, alternative to conventional Doppler processing for color flow mapping     

Quantification of blood echogenicity: evaluation of a semiquantitative method of grading spontaneous echo contrast

Spontaneous echo contrast (SEC) is an echogenic, swirling pattern of blood flow which may be observed by transesophageal echocardiography (TEE) in the left atrium in low flow states, such as atrial fibrillation (AF). The presence of SEC has been proposed as a marker of increased thromboembolic risk. Evaluation of the severity of SEC might be useful in stratification of thromboembolic risk. The aim of this study was to validate a semiquantitative method of grading SEC against quantitative videodensitometric analysis. TEE studies were performed in 50 patients with AF. The severity of left atrial SEC was graded by three independent observers and by videodensitometry. There was a strong, positive correlation between the semiquantitative grades of SEC and quantitative videodensitometric scores (r = 0.85, P < 0.0001). Inter- and intraobserver correlations in the grading of SEC were very high (observer 1 vs. 2: r = 0.98, P = 0.0001; observer 1 vs. 3: r = 0.93, P = 0.0001; observer 1 vs. 1: r = 0.97, P = 0.0001). Semiquantitative grading of SEC can be performed rapidly and reliably by experienced observers. These results support the use of semiquantitative grading in studies of the pathogenesis and prognostic implications of SEC.     

Ultrafast compound Doppler imaging: providing full blood flow characterization

Doppler-based flow analysis methods require acquisition of ultrasound data at high spatio-temporal sampling rates. These rates represent a major technical challenge for ultrasound systems because a compromise between spatial and temporal resolution must be made in conventional approaches. Consequently, ultrasound scanners can either provide full quantitative Doppler information on a limited sample volume (spectral Doppler), or averaged Doppler velocity and/or power estimation on a large region of interest (Doppler flow imaging). In this work, we investigate a different strategy for acquiring Doppler information that can overcome the limitations of the existing Doppler modes by significantly reducing the required acquisition time. This technique is called ultrafast compound Doppler imaging and is based on the following concept: instead of successively insonifying the medium with focused beams, several tilted plane waves are sent into the medium and the backscattered signals are coherently summed to produce high-resolution ultrasound images. We demonstrate that this strategy allows reduction of the acquisition time by a factor of up to of 16 while keeping the same Doppler performance. Depending on the application, different directions to increase performance of Doppler analysis are proposed and the improvement is quantified: the ultrafast compound Doppler method allows faster acquisition frame rates for high-velocity flow imaging, or very high sensitivity for low-flow applications. Full quantitative Doppler flow analysis can be performed on a large region of interest, leading to much more information and improved functionality for the physician. By leveraging the recent emergence of ultrafast parallel beamforming systems, this paper demonstrates that breakthrough performances in flow analysis can be reached using this concept of ultrafast compound Doppler.     

Low-order AR models for mean and maximum frequency estimation in the context of Doppler color flow mapping

Autoregressive (AR) techniques are investigated by developing mean and maximum frequency estimators suitable for use in Doppler color flow mapping systems, where they are most needed. The estimators are based on low-order (for computational efficiency) AR models applied to complex signals whose real and imaginary parts are the in-phase and quadrature components of the analytical Doppler signal, respectively. A large number of simulated data sequences generated by a sinusoidal computer model and having different number of samples, spectral shapes, bandwidths, and signal-to-noise ratios are used to examine the performance (bias and variance) of the estimators in a systematic manner. Comparisons are made with the established autocorrelation technique, whose output is shown to be identical to one of the AR mean frequency estimators described.     

On the performance of regression and step-initialized IIR clutterfilters for color Doppler systems in diagnostic medical ultrasound

One of the major issues in color Doppler ultrasound is the suppression of clutter that arises from stationary or slowly moving tissue. If not adequately suppressed, clutter can severely affect the ability of color Doppler systems to accurately estimate the Doppler mean frequency and power of blood, resulting in a potentially misleading depiction of flow. In this study, the performances of two classes of clutter suppression techniques-step-initialized infinite impulse response (IIR) and regression filters-were evaluated and compared by means of extensive simulations. The performance indicators used were the accuracy and precision of the mean frequency and the power estimates after clutter filtering. In summary, the ability of both filter classes to suppress clutter was found to vary considerably depending on factors such as the clutter-to-flow-signal ratio and the ensemble length. In particular, the performance of step-initialized IIR filters was shown to be noticeably inferior to that predicted by their steady-state response. Regression filters were found to offer significantly better performance than step-initialized IIR filters under heavy clutter conditions and, given their steeper roll-off, appear to be more effective clutter suppressors for power Doppler imaging. However, it should be noted that, as demonstrated by the simulations, the performance of IIR filters is severely degraded by their transient response which, in turn, is determined by the initialization scheme used. Therefore, more elaborate schemes-with superior transient characteristics than step-initialization-could significantly improve the effectiveness of IIR filtering under heavy clutter conditions     

Multifrequency Doppler: improving the quality of spectralestimation by making full use of the information present in thebackscattered RF echoes

This paper investigates the application of the two-dimensional Fourier transform in the context of pulsed wave Doppler. It is shown that two-dimensional spectral analysis of the backscattered RF echoes provides individual Doppler spectra corresponding to the whole range of transmitted frequencies which can be combined, after proper scaling, to form a “multifrequency” spectral estimate. Theoretical expressions are derived for the signal-to-noise ratio of the multifrequency sonogram which predict substantial gains over the conventional (one-dimensional) approach for Doppler processing. These predictions are verified by means of extensive simulations, which also provide an insight into the effect of electronic noise