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Proceedings Paper

Ultrasound spectral analysis of photoacoustic signals from red blood cell populations at different optical wavelengths
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Paper Abstract

Spectral analysis of photoacoustic (PA) signals in the ultrasound frequency domain is a method that analyzes the power spectrum of PA signals to quantify tissue microstructures. PA spectral analysis has been correlated to changes in the size, morphology and concentration of absorbers that are smaller than the system spatial resolution. However, the calculated spectral parameters are still not system independent due to difficulty in eliminating variations in the light distribution for different optical wavelengths. Changes in spectral parameters for the same absorber geometry but different optical illumination wavelengths needs to be carefully examined. A gelatin vessel phantom is used. The vessels contain red blood cells comprised of oxy, deoxy and methemoglobin induced using oxygen, sodium hydrosulfite and sodium nitrite, respectively. The samples were imaged using the VevoLAZR system at wavelengths 680 – 905 nm in steps of 15 nm. The radiofrequency (RF) signals were analyzed to calculate the spectral slope. The results were compared to simulated RF signals acquired using the mcxyz Monte Carlo package coupled to the solution of the PA wave equation using the Green’s function approach. Changes in the spectral slope as a function of optical wavelength were detected. For longer optical wavelengths, the spectral slope increased for deoxyhemoglobin, but decreased for oxyhemoglobin and methemoglobin. The changes in the spectral slope were correlated to changes in the fluence distribution as optical properties change for different wavelengths. The change in the spectral slope as a function of optical wavelength and chromophore content can potentially be used in spectral unmixing for better estimation of hemoglobin content.

Paper Details

Date Published: 23 March 2017
PDF: 9 pages
Proc. SPIE 10064, Photons Plus Ultrasound: Imaging and Sensing 2017, 1006417 (23 March 2017); doi: 10.1117/12.2253542
Show Author Affiliations
Muhannad N. Fadhel, Ryerson Univ. (Canada)
Li Ka Shing Knowledge Institute (Canada)
Michael C. Kolios, Ryerson Univ. (Canada)
Li Ka Shing Knowledge Institute (Canada)


Published in SPIE Proceedings Vol. 10064:
Photons Plus Ultrasound: Imaging and Sensing 2017
Alexander A. Oraevsky; Lihong V. Wang, Editor(s)

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