Three-Dimensional Photoacoustic Tomography with Ultrasound Localization Priors

Three-dimensional photoacoustic tomography (3D-PAT) enables noninvasive structural and functional imaging with optical absorption contrast and ultrasonic detection depth. However, its spatial resolution is limited by acoustic diffraction, and incomplete detection geometry can substantially degrade image fidelity and quantitative accuracy. Here, we present a ULM-guided model-based reconstruction framework, termed 3D-PAULM^prior that incorporates sub-diffraction vascular priors from concurrent ultrasound localization microscopy (ULM) into 3D photoacoustic reconstruction. The method uses weighted regional Laplacian regularization to integrate high-resolution vascular information into the inverse problem, thereby enhancing vascular sharpness, suppressing limited-view artifacts, and improving blood oxygen saturation estimation. We validated 3D-PAULM^prior using numerical simulations, tissue-mimicking phantoms, and in vivo mouse brain imaging. Compared with conventional reconstruction, 3D-PAULM^prior improved spatial resolution by over 50%, increased contrast-to-noise ratio by 261.2%, and enhanced structural similarity index by 24.6%. In vivo, 3D-PAULM^prior recovered vascular structures that were poorly resolved or missing in conventional reconstructions and produced more spatially confined sO₂ maps. These results establish 3D-PAULM^prior as a robust multimodal reconstruction strategy for high-resolution structural and functional photoacoustic imaging.