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Journal of Biomedical Optics • Open Access

Reduced-order modeling of light transport in tissue for real-time monitoring of brain hemodynamics using diffuse optical tomography
Author(s): Ernesto E. Vidal-Rosas; Stephen Billings; Ying Zheng; John E. Mayhew; David K. Johnston; Aneurin J. Kennerley; Daniel Coca

Paper Abstract

This paper proposes a new reconstruction method for diffuse optical tomography using reduced-order models of light transport in tissue. The models, which directly map optical tissue parameters to optical flux measurements at the detector locations, are derived based on data generated by numerical simulation of a reference model. The reconstruction algorithm based on the reduced-order models is a few orders of magnitude faster than the one based on a finite element approximation on a fine mesh incorporating a priori anatomical information acquired by magnetic resonance imaging. We demonstrate the accuracy and speed of the approach using a phantom experiment and through numerical simulation of brain activation in a rat’s head. The applicability of the approach for real-time monitoring of brain hemodynamics is demonstrated through a hypercapnic experiment. We show that our results agree with the expected physiological changes and with results of a similar experimental study. However, by using our approach, a three-dimensional tomographic reconstruction can be performed in ∼3  s per time point instead of the 1 to 2 h it takes when using the conventional finite element modeling approach.

Paper Details

Date Published: 13 February 2014
PDF: 15 pages
J. Biomed. Opt. 19(2) 026008 doi: 10.1117/1.JBO.19.2.026008
Published in: Journal of Biomedical Optics Volume 19, Issue 2
Show Author Affiliations
Ernesto E. Vidal-Rosas, The Univ. of Sheffield (United Kingdom)
Stephen Billings, The Univ. of Sheffield (United Kingdom)
Ying Zheng, The Univ. of Sheffield (United Kingdom)
John E. Mayhew, The Univ. of Sheffield (United Kingdom)
David K. Johnston, The Univ. of Sheffield (United Kingdom)
Aneurin J. Kennerley, The Univ. of Sheffield (United Kingdom)
Daniel Coca, The Univ. of Sheffield (United Kingdom)

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