Passive acoustic mapping and B-mode ultrasound imaging utilizing compressed sensing for real-time monitoring of cavitation-enhanced drug delivery

Abstract

Ultrasound imaging presents a high-speed, low-cost approach for monitoring of focused ultrasound (FUS) therapy, and includes both conventional (B-mode) sonography and passive acoustic mapping (PAM) of acoustic emissions (Gyöngy et al., 2010, Salgaonkar et al., 2009). Incorporation of novel algorithms and other signal processing techniques have improved the resolution and processing speed of PAM. However, while hardware developments such as increasing channel counts provide unprecedented data capture ability, real-time processing of the growing data stream presents an evolving challenge. Previous work has employed sparse array processing techniques for PAM including matching and basis pursuit (Gyöngy & Coviello, 2011) and co-array processing (Coviello et al, 2012). Here we propose to extend PAM utilizing compressed sensing (CS). Acoustic emissions from FUS may be sparse in several domains, e.g. due to limited regions of space and time in which cavitation is likely from a focused transducer, and correlation between sensors. By exploiting this sparsity, CS allows recovery of signals sampled well below the Nyquist limit. CS-PAM thus facilitates PAM with improved spatial resolution compared to conventional methods, from fewer measurements, allowing improved image quality and reduced computational load. The technique was demonstrated for monitoring of FUS-mediated drug delivery in a murine tumor model.