Spectrum analysis of photoacoustic imaging data from prostate adenocarcinoma tumors in a murine model

Abstract

Spectrum analysis of the radio-frequency signals from photoacoustic imaging is performed to generate parameters for tissue characterization that are calibrated for the response of the imaging system. Calibrated photoacoustic spectra were obtained by dividing the photoacoustic spectra from tissue by the spectrum of a point absorber. The resulting quasi-linear spectra were fit by linear regression, and midband fit, slope, and intercept were computed from the best-fit line. These spectral parameters were compared between tumors resulting from a prostate adenocarcinoma model and adjacent normal tissue in a murine model. The mean midband fit and intercept showed significant differences between regions of tumor and adjacent normal tissue. These initial results suggest that such frequency-domain analysis can provide a quantitative method for tissue characterization using photoacoustic imaging.