Systematic analysis of frequency dependent differential photoacoustic cross-section data for source size estimation

Area of Science:

• Biophysics
• Acoustics
• Optical Imaging

Background:

• Photoacoustic (PA) imaging offers label-free contrast for biological tissues.
• Quantifying cell morphology is crucial for diagnosing diseases like hereditary blood disorders.

Purpose of the Study:

• To compute frequency-dependent differential photoacoustic cross-section (DPACS) for various cell models.
• To develop an inverse problem framework for quantifying photoacoustic source morphology.

Main Methods:

• Utilized Green's function approach to calculate DPACS for spheroidal droplets, Chebyshev particles, and red blood cells (normal and diseased).
• Modeled PA wave propagation through dispersive and absorbing media with finite-sized detectors.
• Fitted frequency-dependent DPACS with tri-axial ellipsoid, finite cylinder, and toroid form factor models.

Main Results:

• Calculated DPACS over a 100-1000 MHz frequency band.
• The tri-axial ellipsoid model demonstrated superior accuracy in estimating shape parameters for diverse PA sources.
• Successfully quantified morphological parameters of simulated and biological cell models.

Conclusions:

• The developed inverse problem framework enables quantitative assessment of single-cell morphology using PA signals.
• This approach holds potential for developing advanced PA-based diagnostic tools for hematological disorders.
• Highlights the utility of frequency-dependent DPACS in characterizing complex biological structures.