Paper
14 June 2011 Depth-resolved quantitative measurement of cerebral blood flow using broad-band near infrared spectroscopy and a two-layer head model
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Abstract
We propose an algorithm based on a two-layer optical model to quantify CBF from dynamic contrast-enhanced near-infrared data acquired with a two-channel broadband system. The key novel aspect of the algorithm is the ability to separate the contrast agent concentration, indocyanine green (ICG), in extracerebral (EC) tissue and cerebral cortex by representing the (EC) tissue as the top optical layer and the brain as the bottom optical layer. Experiments were conducted on a juvenile pig model. Broadband near-infrared spectra were acquired at source-detectors distances of 1 and 3 cm. The first step of the algorithm was to find the baseline optical properties of the layers by a multi-parameter wavelength-dependent data fit of a photon diffusion equation solution for a two-layer media. The second step was to use the baseline optical properties to separate the ICG concentration time course in brain from the ICG time course in EC tissue. The final step was to calculate CBF from the cerebral ICG time course. The resulting CBF measurements were in good agreement with concurrent measurements acquired by computed tomography, which a difference of 20%.
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Vladislav Toronov, Jonathan Elliott, Ting-Yim Lee, and Keith St. Lawrence "Depth-resolved quantitative measurement of cerebral blood flow using broad-band near infrared spectroscopy and a two-layer head model", Proc. SPIE 8088, Diffuse Optical Imaging III, 80881J (14 June 2011); https://doi.org/10.1117/12.889739
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KEYWORDS
Tissue optics

Near infrared spectroscopy

Optical properties

Data modeling

Head

Brain

Cerebral blood flow

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