Ultrasound Vector Flow Imaging—Part II: Parallel Systems

We present functional ultrasound (fUS), a method for imaging transient changes in blood volume in the whole brain at better spatiotemporal resolution than with other functional brain imaging modalities. fUS uses plane-wave illumination at high frame rate and can measure blood volumes in smaller vessels than previous ultrasound methods. fUS identifies regions of brain activation and was used to image whisker-evoked cortical and thalamic responses and the propagation of epileptiform seizures in the rat brain.

Ultrafast ultrasonic imaging is a rapidly developing field based on the unfocused transmission of plane or diverging ultrasound waves. This recent approach to ultrasound imaging leads to a large increase in raw ultrasound data available per acquisition. Bigger synchronous ultrasound imaging datasets can be exploited in order to strongly improve the discrimination between tissue and blood motion in the field of Doppler imaging. Here we propose a spatiotemporal singular value decomposition clutter rejection of ultrasonic data acquired at ultrafast frame rate. The singular value decomposition (SVD) takes benefits of the different features of tissue and blood motion in terms of spatiotemporal coherence and strongly outperforms conventional clutter rejection filters based on high pass temporal filtering. Whereas classical clutter filters operate on the temporal dimension only, SVD clutter filtering provides up to a four-dimensional approach (3D in space and 1D in time). We demonstrate the performance of SVD clutter filtering with a flow phantom study that showed an increased performance compared to other classical filters (better contrast to noise ratio with tissue motion between 1 and 10mm/s and axial blood flow as low as 2.6 mm/s). SVD clutter filtering revealed previously undetected blood flows such as microvascular networks or blood flows corrupted by significant tissue or probe motion artifacts. We report in vivo applications including small animal fUltrasound brain imaging (blood flow detection limit of 0.5 mm/s) and several clinical imaging cases, such as neonate brain imaging, liver or kidney Doppler imaging.

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.