Effective point spread function modeling of photoacoustic remote sensing microscopy towards resolution enhancement

Photoacoustic remote sensing (PARS) microscopy, as an all-optical non-contact imaging modality, has demonstrated considerable potential in biomedical applications. However, current studies on PARS resolution remain limited to experimental characterization, hindering the systematic analysis and optimization of its imaging performance. In this study, we develop an effective point spread function (PSF) model for PARS microscopy, revealing that the system resolution is jointly determined by the PSFs of both the excitation and probe paths. Utilizing a developed multipath confocal PARS (MC-PARS) system, we evaluate the model through numerical simulations and experimental measurements across various excitation-probe wavelength combinations. The results show excellent agreement between theoretical predictions and experimental data. Furthermore, by introducing a confocal configuration into the probe path, we achieve controlled contraction of the effective PSF, resulting in a twofold enhancement in axial resolution of MC-PARS. This work establishes a reliable framework for predicting and optimizing PARS resolution, providing a foundation for surpassing the resolution limit in non-contact photoacoustic imaging through advanced PSF engineering.