KEYWORDS: 3D modeling, Photoacoustic tomography, Model-based design, Image restoration, Data modeling, 3D image reconstruction, Reconstruction algorithms, Tissues, Acoustics, Monte Carlo methods
Three-dimensional quantitative photoacoustic tomography (3D-QPAT) aims to recover tissue chromophore concentrations from multispectral images but is often hampered by the unknown light fluence and the transfer function of the scanner. Inversion schemes that use hybrid light transport and acoustic propagation models may be used to address this challenge. While model-based inversions have shown promising results in in silico and tissue phantom studies, limitations in accuracy arose from limited view artefacts. This study evaluated reconstruction methods such as time-reversal, maximum a posteriori, iterative least square and total variation to improve the accuracy of 3D-QPAT inversion techniques.
Polymer-based nanoparticles are promising contrast agents for photoacoustic (PA) imaging as their properties can be tailored to maximize detection sensitivity against the overwhelming endogenous background, while pump-probe excitation and fluence-dependent image acquisition may provide alternative approaches for contrast agent detection instead of multispectral imaging and unmixing. In this study, PA signals were measured in single-chain nanoparticle (SCNP) suspensions at pump and probe wavelengths of 690 nm and 730 nm and showed a strong nonlinear fluence dependence, which provides a unique contrast mechanism for molecular PA imaging.
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