Multispectral photoacoustic decomposition with localized regularization for detecting targeted contrast agent

Targeted contrast agents can improve the sensitivity of imaging systems for cancer detection and monitoring the treatment. In order to accurately detect contrast agent concentration from photoacoustic images, we developed a decomposition algorithm to separate photoacoustic absorption spectrum into components from individual absorbers. In this study, we evaluated novel prostate-specific membrane antigen (PSMA) targeted agents for imaging prostate cancer. Three agents were synthesized through conjugating PSMA-targeting urea with optical dyes ICG, IRDye800CW and ATTO740 respectively. In our preliminary PA study, dyes were injected in a thin wall plastic tube embedded in water tank. The tube was illuminated with pulsed laser light using a tunable Q-switch ND-YAG laser. PA signal along with the B-mode ultrasound images were detected with a diagnostic ultrasound probe in orthogonal mode. PA spectrums of each dye at 0.5 to 20 μM concentrations were estimated using the maximum PA signal extracted from images which are obtained at illumination wavelengths of 700nm-850nm. Subsequently, we developed nonnegative linear least square optimization method along with localized regularization to solve the spectral unmixing. The algorithm was tested by imaging mixture of those dyes. The concentration of each dye was estimated with about 20% error on average from almost all mixtures albeit the small separation between dyes spectrums.