LAUSR

Passive cavitation mapping (PCM) techniques typically utilize a time-exposure acoustic (TEA) approach, where the received radio frequency data are beamformed, squared, and integrated over time. Such PCM-TEA cavitation maps typically suffer from long-tail artifacts and poor axial resolution with pulse–echo diagnostic arrays. Here, we utilize a recently developed PCM technique based on cavitation source localization (CSL), which fits a hyperbolic function to the received cavitation wavefront. A filtering method based on the root-mean-square error (rmse) of the hyperbolic fit is utilized to filter out spurious signals. We apply a wavefront correction technique to the signals with poor fit quality to recover additional cavitation signals and improve cavitation localization. Validation of the PCM-CSL technique with rmse filtering and wavefront correction was conducted in experiments with a tissue-mimicking flow phantom and an in vivo mouse model of cancer. It is shown that the quality of the hyperbolic fit, necessary for the PCM-CSL, requires an rmse < 0.05 mm2 in order to accurately localize the cavitation sources. A detailed study of the wavefront correction technique was carried out, and it was shown that, when applied to experiments with high noise and interference from multiple cavitating microbubbles, it was capable of effectively correcting noisy wavefronts without introducing spurious cavitation sources, thereby improving the quality of the PCM-CSL images. In phantom experiments, the PCM-CSL was capable of precisely localizing sources on the therapy beam axis and off-axis sources. In vivo cavitation experiments showed that PMC-CSL showed a significant improvement over PCM-TEA and yielded acceptable localization of cavitation signals in mice.