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Proceedings Paper

Frequency analysis of multispectral photoacoustic images for differentiating malignant region from normal region in excised human prostate
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Paper Abstract

Frequency domain analysis of the photoacoustic (PA) radio frequency signals can potentially be used as a tool for characterizing microstructure of absorbers in tissue. This study investigates the feasibility of analyzing the spectrum of multiwavelength PA signals generated by excised human prostate tissue samples to differentiate between malignant and normal prostate regions. Photoacoustic imaging at five different wavelengths, corresponding to peak absorption coefficients of deoxyhemoglobin, whole blood, oxyhemoglobin, water and lipid in the near infrared (NIR) (700 nm – 1000 nm) region, was performed on freshly excised prostate specimens taken from patients undergoing prostatectomy for biopsy confirmed prostate cancer. The PA images were co-registered with the histopathology images of the prostate specimens to determine the region of interest (ROI) corresponding to malignant and normal tissue. The calibrated power spectrum of each PA signal from a selected ROI was fit to a linear model to extract the corresponding slope, midband fit and intercept parameters. The mean value of each parameter corresponding to malignant and adjacent normal prostate ROI was calculated for each of the five wavelengths. The results obtained for 9 different human prostate specimens, show that the mean values of midband fit and intercept are significantly different between malignant and normal regions. In addition, the average midband fit and intercept values show a decreasing trend with increasing wavelength. These preliminary results suggest that frequency analysis of multispectral PA signals can be used to differentiate malignant region from the adjacent normal region in human prostate tissue.

Paper Details

Date Published: 20 March 2014
PDF: 9 pages
Proc. SPIE 9040, Medical Imaging 2014: Ultrasonic Imaging and Tomography, 90400P (20 March 2014); doi: 10.1117/12.2043802
Show Author Affiliations
Saugata Sinha, Rochester Institute of Technology (United States)
Navalgund A. Rao, Rochester Institute of Technology (United States)
Keerthi S. Valluru, Univ. of Rochester (United States)
Bhargava K. Chinni, Univ. of Rochester (United States)
Vikram S. Dogra, Univ. of Rochester (United States)
Maria Helguera, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 9040:
Medical Imaging 2014: Ultrasonic Imaging and Tomography
Johan G. Bosch; Marvin M. Doyley, Editor(s)

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