Effective scattering coefficient of the cerebral spinal fluid in adult head models for diffuse optical imaging
Author(s) -
Anna Custo,
William M. Wells,
Alex H. Barnett,
Elizabeth M. C. Hillman,
David A. Boas
Publication year - 2006
Publication title -
applied optics
Language(s) - English
Resource type - Journals
ISSN - 0003-6935
DOI - 10.1364/ao.45.004747
Subject(s) - monte carlo method , physics , heavy traffic approximation , attenuation coefficient , photon diffusion , optics , scattering , radiative transfer , inverse problem , diffuse optical imaging , computation , human head , photon , diffusion , forward scatter , photon transport in biological tissue , computational physics , absorption (acoustics) , mathematical analysis , tomography , computer science , mathematics , algorithm , direct simulation monte carlo , light source , statistics , dynamic monte carlo method , thermodynamics
An efficient computation of the time-dependent forward solution for photon transport in a head model is a key capability for performing accurate inversion for functional diffuse optical imaging of the brain. The diffusion approximation to photon transport is much faster to simulate than the physically correct radiative transport equation (RTE); however, it is commonly assumed that scattering lengths must be much smaller than all system dimensions and all absorption lengths for the approximation to be accurate. Neither of these conditions is satisfied in the cerebrospinal fluid (CSF). Since line-of-sight distances in the CSF are small, of the order of a few millimeters, we explore the idea that the CSF scattering coefficient may be modeled by any value from zero up to the order of the typical inverse line-of-sight distance, or approximately 0.3 mm(-1), without significantly altering the calculated detector signals or the partial path lengths relevant for functional measurements. We demonstrate this in detail by using a Monte Carlo simulation of the RTE in a three-dimensional head model based on clinical magnetic resonance imaging data, with realistic optode geometries. Our findings lead us to expect that the diffusion approximation will be valid even in the presence of the CSF, with consequences for faster solution of the inverse problem.
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