Effect of the point spread function: Deconvolution strategies for accurate spatiotemporal cavitation doses by passive acoustic mapping

The ability to quantify and compare different cavitational treatments is essential given their accelerating clinical adoption. Passive acoustic mapping (PAM) can reconstruct quantitative maps of cavitational radiated energy density (CRED) in real time, providing a powerful platform for cavitation dosimetry. However, when compared to optical imaging, the relatively longer acoustic wavelengths and longitudinal nature of 2-D PAM result in greater variability and a more significant spatial impact of the point spread function (PSF). The associated imaging artifacts limit the spatial localization of cavitation dose and introduce errors in source energy estimation that vary across source parameters and between setups. Deconvolving with a constant PSF can reduce many of these errors and minimize the setup dependence of CRED estimates, but can introduce iteration-dependent errors in the estimated source location. This work explores the challenges of deconvolving images with large and variable PSFs using algorithms designed for optical applications and proposes strategies for mitigating errors. These approaches will be evaluated with respect to their quantitative performance, computation time, and robustness to noise both in silico and in vitro, with the aim of unlocking the full capabilities of PAM as a spatially resolved, energy preserving, setup independent platform for cavitational dosimetry.