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Updated: Jun 3, 2026

Ovarian Cancer Detection Using Photoacoustic Flow Cytometry
Published on: January 17, 2020
Frequency-domain analysis of photoacoustic imaging data from prostate adenocarcinoma tumors in a murine model
Ronald E Kumon1, Cheri X Deng, Xueding Wang
1Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48709, USA.
Abstract:
Photoacoustic imaging is an emerging technique for anatomical and functional sub-surface imaging but previous studies have predominantly focused on time-domain analysis. In this study, frequency-domain analysis of the radio-frequency signals from photoacoustic imaging was performed to generate quantitative parameters for tissue characterization. To account for the response of the imaging system, the photoacoustic spectra were calibrated by dividing the photoacoustic spectra (radio-frequency ultrasound spectra resulting from laser excitation) from tissue by the photoacoustic spectrum of a point absorber excited under the same conditions. The resulting quasi-linear photoacoustic spectra were fit by linear regression and midband fit, slope and intercept were computed from the best-fit line. These photoacoustic spectral parameters were compared between the region-of-interests (ROIs) representing prostate adenocarcinoma tumors and adjacent normal flank tissue in a murine model. The mean midband fit and intercept in the ROIs showed significant differences between cancerous and noncancerous regions. These initial results suggest that such frequency-domain analysis can provide a quantitative method for tumor tissue characterization using photoacoustic imaging in vivo.

