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Proceedings Paper

An algorithm for sensing venous oxygenation using ultrasound-modulated light enhanced by microbubbles
Author(s): Jack E. Honeysett; Eleanor Stride; Jing Deng; Terence S. Leung
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Paper Abstract

Near-infrared spectroscopy (NIRS) can provide an estimate of the mean oxygen saturation in tissue. This technique is limited by optical scattering, which reduces the spatial resolution of the measurement, and by absorption, which makes the measurement insensitive to oxygenation changes in larger deep blood vessels relative to that in the superficial tissue. Acousto-optic (AO) techniques which combine focused ultrasound (US) with diffuse light have been shown to improve the spatial resolution as a result of US-modulation of the light signal, however this technique still suffers from low signal-to-noise when detecting a signal from regions of high optical absorption. Combining an US contrast agent with this hybrid technique has been proposed to amplify an AO signal. Microbubbles are a clinical contrast agent used in diagnostic US for their ability to resonate in a sound field: in this work we also make use of their optical scattering properties (modelled using Mie theory). A perturbation Monte Carlo (pMC) model of light transport in a highly absorbing blood vessel containing microbubbles surrounded by tissue is used to calculate the AO signal detected on the top surface of the tissue. An algorithm based on the modified Beer-Lambert law is derived which expresses intravenous oxygen saturation in terms of an AO signal. This is used to determine the oxygen saturation in the blood vessel from a dual wavelength microbubble-contrast AO measurement. Applying this algorithm to the simulation data shows that the venous oxygen saturation is accurately recovered, and this measurement is robust to changes in the oxygenation of the superficial tissue layer.

Paper Details

Date Published: 23 February 2012
PDF: 9 pages
Proc. SPIE 8223, Photons Plus Ultrasound: Imaging and Sensing 2012, 82232Z (23 February 2012); doi: 10.1117/12.907952
Show Author Affiliations
Jack E. Honeysett, Univ. College London (United Kingdom)
Eleanor Stride, Univ. of Oxford (United Kingdom)
Jing Deng, Univ. College Hospital (United Kingdom)
Terence S. Leung, Univ. College London (United Kingdom)

Published in SPIE Proceedings Vol. 8223:
Photons Plus Ultrasound: Imaging and Sensing 2012
Alexander A. Oraevsky; Lihong V. Wang, Editor(s)

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