20 March 2018 Photoacoustic imaging to assess pixel-based sO2 distributions in experimental prostate tumors
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Abstract
A protocol for photoacoustic imaging (PAI) has been developed to assess pixel-based oxygen saturation (sO2) distributions of experimental tumor models. The protocol was applied to evaluate the dependence of PAI results on measurement settings, reproducibility of PAI, and for the characterization of the oxygenation status of experimental prostate tumor sublines (Dunning R3327-H, -HI, -AT1) implanted subcutaneously in male Copenhagen rats. The three-dimensional (3-D) PA data employing two wavelengths were used to estimate sO2 distributions. If the PA signal was sufficiently strong, the distributions were independent from signal gain, threshold, and positioning of animals. Reproducibility of sO2 distributions with respect to shape and median values was demonstrated over several days. The three tumor sublines were characterized by the shapes of their sO2 distributions and their temporal response after external changes of the oxygen supply (100% O2 or air breathing and clamping of tumor-supplying artery). The established protocol showed to be suitable for detecting temporal changes in tumor oxygenation as well as differences in oxygenation between tumor sublines. PA results were in accordance with histology for hypoxia, perfusion, and vasculature. The presented protocol for the assessment of pixel-based sO2 distributions provides more detailed information as compared to conventional region-of-interest-based analysis of PAI, especially with respect to the detection of temporal changes and tumor heterogeneity.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Alina L. Bendinger, Alina L. Bendinger, Christin Glowa, Christin Glowa, Jörg Peter, Jörg Peter, Christian P. Karger, Christian P. Karger, } "Photoacoustic imaging to assess pixel-based sO2 distributions in experimental prostate tumors," Journal of Biomedical Optics 23(3), 036009 (20 March 2018). https://doi.org/10.1117/1.JBO.23.3.036009 . Submission: Received: 7 November 2017; Accepted: 19 February 2018
Received: 7 November 2017; Accepted: 19 February 2018; Published: 20 March 2018
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