Three-Dimensional Photoacoustic Tomography with Ultrasound Localization Priors

Three-dimensional photoacoustic tomography (3D-PAT) enables noninvasive structural and functional imaging with optical absorption contrast. However, its spatial resolution is limited by acoustic diffraction and incomplete detection geometry. Here, we present a ULM-guided model-based reconstruction framework, termed 3D-PAULMprior, which incorporates sub-diffraction vascular priors from ultrasound localization microscopy (ULM) into 3D-PAT. A weighted regional Laplacian regularization is introduced to integrate high-resolution vascular information into the inverse problem. The proposed method enhances vascular sharpness, suppresses limited-view artifacts, and improves blood oxygen saturation (sO₂) estimation. Validation using simulations, phantoms, and in vivo mouse brain imaging demonstrates that 3D-PAULMprior improves spatial resolution by over 50%, increases contrast-to-noise ratio by 261.2%, and enhances structural similarity by 24.6%. It also recovers vascular structures missed by conventional methods and produces more spatially confined sO₂ maps. These results demonstrate its potential for high-resolution photoacoustic imaging.

Duke Scholars

Author Pengfei Song Biomedical Engineering