Objective selection of high-frequency power Doppler wall filter cutoff velocity for regions of interest containing multiple small vessels

Receiver-Operating Characteristic Analysis of Eigen-Based Clutter Filters for Ultrasound Color Flow Imaging

The eigen-based filter has theoretically established itself as a potent solution in ultrasound color flow imaging (CFI) for combating against clutter arising from moving tissues. Yet, it remains poorly understood on how much gain in flow detection sensitivity and specificity can be delivered by this adaptive clutter filter. Here, we investigated the receiver operating characteristic (ROC) of the eigen-based clutter filter to statistically evaluate its efficacy. Our investigation was conducted using a new vascular phantom testbed that incorporated both intrinsic tissue motion (vessel pulsation: 7.58 cm/s peak velocity) and extrinsic tissue motion (vibration: 5-Hz frequency, 2.98 cm/s peak velocity), as well as pulsatile flow (pulse rate: 60 beats/min; systolic flow rate: 6.5 mL/s). The eigen-filter (single-ensemble formulation) was applied to CFI raw data sets obtained from the phantom's short-axis view (slow-time ensemble size: 12; pulse repetition frequency: 2 kHz; and ultrasound frequency: 5 MHz), and post-filter Doppler power was compared between flow and tissue regions. Results show that, in the presence of vessel pulsation and tissue vibration, the eigen-filter yielded a high true positive rate in depicting flow pixels in CFI frames (0.945 and 0.917, respectively, during peak systole and end diastole at 60° beam-flow angle), while maintaining a low false alarm rate (0.10) in rendering tissue pixels. Also, the eigen-filter posed ROC curves whose area under curve was higher than those for the polynomial regression filter (statistically significant; t-test p values were less than 0.05). These findings serve well to substantiate the merit of using eigen-filters to enhance the vascular visualization capability of CFI.

A method to validate quantitative high-frequency power doppler ultrasound with fluorescence in vivo video microscopy

Flow quantification with high-frequency (>20 MHz) power Doppler ultrasound can be performed objectively using the wall-filter selection curve (WFSC) method to select the cutoff velocity that yields a best-estimate color pixel density (CPD). An in vivo video microscopy system (IVVM) is combined with high-frequency power Doppler ultrasound to provide a method for validation of CPD measurements based on WFSCs in mouse testicular vessels. The ultrasound and IVVM systems are instrumented so that the mouse remains on the same imaging platform when switching between the two modalities. In vivo video microscopy provides gold-standard measurements of vascular diameter to validate power Doppler CPD estimates. Measurements in four image planes from three mice exhibit wide variation in the optimal cutoff velocity and indicate that a predetermined cutoff velocity setting can introduce significant errors in studies intended to quantify vascularity. Consistent with previously published flow-phantom data, in vivo WFSCs exhibited three characteristic regions and detectable plateaus. Selection of a cutoff velocity at the right end of the plateau yielded a CPD close to the gold-standard vascular volume fraction estimated using IVVM. An investigator can implement the WFSC method to help adapt cutoff velocity to current blood flow conditions and thereby improve the accuracy of power Doppler for quantitative microvascular imaging.

Comparison of Kasai autocorrelation and maximum likelihood estimators for Doppler optical coherence tomography

In optical coherence tomography (OCT) and ultrasound, unbiased Doppler frequency estimators with low variance are desirable for blood velocity estimation. Hardware improvements in OCT mean that ever higher acquisition rates are possible, which should also, in principle, improve estimation performance. Paradoxically, however, the widely used Kasai autocorrelation estimator's performance worsens with increasing acquisition rate. We propose that parametric estimators based on accurate models of noise statistics can offer better performance. We derive a maximum likelihood estimator (MLE) based on a simple additive white Gaussian noise model, and show that it can outperform the Kasai autocorrelation estimator. In addition, we also derive the Cramer Rao lower bound (CRLB), and show that the variance of the MLE approaches the CRLB for moderate data lengths and noise levels. We note that the MLE performance improves with longer acquisition time, and remains constant or improves with higher acquisition rates. These qualities may make it a preferred technique as OCT imaging speed continues to improve. Finally, our work motivates the development of more general parametric estimators based on statistical models of decorrelation noise.

Improved objective selection of power Doppler wall-filter cut-off velocity for accurate vascular quantification

The wall-filter selection curve method is proposed to objectively identify a cut-off velocity that minimizes artifacts in power Doppler images. A selection curve, which is constructed by plotting the color pixel density (CPD) as a function of the cut-off velocity, exhibits characteristic intervals hypothesized to include the optimum cut-off velocity. This article presents an improved implementation of the method that automatically detects characteristic intervals in a selection curve and selects an operating point cut-off velocity along a characteristic interval. The method is applied to subregions within the Doppler image to adapt the cut-off velocity to local variations in vascularity. The method's performance is evaluated in 30-MHz power Doppler images of a four-vessel flow phantom. At high (>5 mm/s) flow velocities, qualitative improvements in vessel delineation are achieved and the CPD in the resulting images is accurate to within 3% of the vascular volume fraction of the phantom.

3-D microvessel-mimicking ultrasound phantoms produced with a scanning motion system

Ultrasound techniques are currently being developed that can assess the vascularization of tissue as a marker for therapeutic response. Some of these ultrasound imaging techniques seek to extract quantitative features about vessel networks, whereas high-frequency imaging also allows individual vessels to be resolved. The development of these new techniques, and subsequent imaging analysis strategies, necessitates an understanding of their sensitivities to vessel and vessel network structural abnormalities. Constructing in-vitro flow phantoms for this purpose can be prohibitively challenging, because simulating precise flow environments with nontrivial structures is often impossible using conventional methods of construction for flow phantoms. Presented in this manuscript is a method to create predefined structures with <10 μm precision using a three-axis motion system. The application of this technique is demonstrated for the creation of individual vessel and vessel networks, which can easily be made to simulate the development of structural abnormalities typical of diseased vasculature in vivo. In addition, beyond facilitating the creation of phantoms that would otherwise be very challenging to construct, the method presented herein enables one to precisely simulate very slow blood flow and respiration artifacts, and to measure imaging resolution.