A method for differentiating targeted microbubbles in real time using subharmonic micro-ultrasound and interframe filtering.

This study introduces a new method for differentiating targeted microbubbles in the presence of flowing microbubbles and tissue using micro-ultrasound. The method relies on subharmonic (SH) imaging for segmenting microbubble signals from tissue signals, and low-pass interframe filtering for segmenting bound targeted microbubbles from flowing microbubbles. The method is evaluated with 30 frames per second SH B-mode imaging in vitro, using a wall-less vessel flow phantom. The SH B-mode cineloops were postprocessed using an interframe moving average filter to segment the regions of bound microbubbles on the inner surface of the vessel phantom. The bound bubbles were then disrupted with sufficiently high ultrasound pressures, so that the dynamic process of targeted microbubble binding under flowing conditions could be observed. These preliminary results show that the proposed method is a feasible solution to the challenge of differentiating targeted microbubbles in the presence of tissue and freely flowing microbubbles at high frequencies, which in turn should improve the specificity of targeted microbubble detection.