Enhancing Passive Cavitation Imaging Using p

objectivePassive cavitation imaging (PCI) derived metrics can serve as surrogates for the outcome of bubble-mediated therapies. Passive cavitation imaging is limited by poor axial resolution and side lobe artifacts, particularly when algorithms such as delay, sum and integrate (DSI) beamforming are used. Methods to improve PCI performance remain an active research area given the need to balance imaging performance with computational complexity. The current study evaluated p

methodsFirst, PCI was performed on a flow phantom perfused with ultrasound contrast agent (SonoVue) exposed to focused ultrasound. Next, the performance of prDSI was assessed on histotripsy bubble clouds generated in a red blood cell (RBC)-doped phantom. Finally, PCI was performed on data collected during histotripsy ablation of a thrombus in the femoral vein of a pig. Acoustic emissions generated by cavitation were recorded and processed with DSI, robust Capon, and prDSI beamforming. The imaging performance was evaluated using the axial width, signal-to-interference ratio, and binary statistical analysis-derived metrics.

resultsThe prDSI approach demonstrated comparable imaging performance to RCB, both in vitro and in vivo based on binary statistical metrics. Considerable improvement was observed in axial width and signal-to-interference ratio, while incurring only a moderately higher computational cost relative to standard DSI beamforming.

conclusionsThe findings of this study demonstrate the potential of prDSI for monitoring of cavitation-mediated therapies.