Quantitative photoacoustic image reconstruction improves accuracy in deep tissue structures

Area of Science:

• Biomedical Imaging
• Optical Physics
• Computational Science

Background:

• Photoacoustic imaging (PAI) shows promise but is limited by poor modeling of light delivery in deep tissues.
• Existing PAI reconstruction methods often struggle with depth and spectral artifacts, hindering quantitative accuracy.
• Accurate reconstruction is crucial for PAI's clinical and preclinical applications.

Purpose of the Study:

• To develop a numerical approach for quantitative photoacoustic image reconstruction.
• To minimize depth and spectrally derived artifacts in PAI.
• To create quantitative images of absorption coefficients using acoustic data.

Main Methods:

• Developed a first-of-its-kind time-domain quantitative photoacoustic image reconstruction algorithm.
• Modeled optical sources through acoustic data for quantitative absorption coefficient imaging.
• Validated the algorithm in 2D geometries (3cm and 6cm diameter) and with spectral data.

Main Results:

• Achieved quantitative accuracy with less than 5% error in 3cm geometries and within 22% error in 6cm geometries.
• Reconstructed 6 varying chromophores to within 17% of true values using spectral data.
• Demonstrated significant improvements in image quality and quantification over filtered-back projection.

Conclusions:

• The developed quantitative photoacoustic tomography method provides accurate absorption coefficient imaging.
• This approach minimizes artifacts and enhances quantification, especially for deep-tissue PAI.
• The method has potential for both preclinical and clinical applications using endogenous and exogenous contrast agents.