An iterative method of light fluence distribution estimation for quantitative photoacoustic imaging

Abstract

Tissue heterogeneities and the presence of strong optical absorbers hinder the applications of quantitative photoacoustic imaging (PA). Having an accurate description of optical fluence distribution in heterogeneous media is essential to obtain absorption estimates. While Monte Carlo simulations and diffusion models are frequently used to approximate fluence distribution, they ignore the unique heterogeneities across imaged samples or individuals. This paper presents a method to estimate the optical fluence distributions in two-dimensional PA images applying image-based iterated corrections of the fluence map. The method was validated using a virtual tissue phantom and consecutive light transport simulations. PA images were generated synthetically, based on the true light distribution, and were subsequently used to correct the estimated fluence distribution. The correlation between the original phantom and each corrected image was measured to quantify the accuracy of the method. We found that each iteration resulted in an increase in the correlation and a qualitative improvement between the original phantom and the corrected image. This method is expected to improve the accuracy of PA imaging, especially in multi-wavelength applications and those affected by strong absorbers such as contrast agents.