This paper is devoted to the development and testing of accelerated-time calculation for the spatially resolved reflectance
in multiple layer turbid medium that facilitates the use of Monte Carlo simulation (MC) in medical physics applications.
To mitigate the inconveniences associated to long execution times, the MC code has been speeded up by using efficient
computational hybrid technique computing on graphics processing units (GPU). This method effectively reduces the
simulation time by a factor of 8 compared to the stand-alone GPU-based MC code.
KEYWORDS: Scattering, Diffusion, Monte Carlo methods, Finite element methods, Head, Brain, Light scattering, Reflectivity, Data modeling, Optical properties
In this work, a Finite Element calculations based on diffusion approximation are compared with Monte Carlo transport
data code in time-resolved reflectance simulations of light propagation in a three-layered head model, which can be seen
as a very simplistic approximation of the adult head. We also address the effects caused by the cerebrospinal fluid (CSF),
filling the space between the skull and the brain, on the accuracy of the diffusion approximation for different values of
CSF reduced scattering coefficients μs' varying between 0.1 and 1 mm-1. Significant differences between transport and
diffusion calculations show that diffusion approximation fails to describe accurately light propagation in voidlike region
such as the cerebrospinal fluid (CSF), in which absorption and scattering are very small compared to the surrounding
media, whereas the Monte Carlo predictions are not greatly affected. However, It is shown that the diffusion equation
should provide reasonable solutions with a CSF reduced scattering coefficient μs' = 0.3 mm-1. The results indicate that a
multi-layered model including CSF is more appropriate for the determination of the optical properties of the human head
and to obtain accurate solutions of the forward problem with diffusion approximation.
KEYWORDS: Absorption, Reflectivity, Diffusion, Monte Carlo methods, Finite element methods, Data modeling, Skin, Tissues, Scattering, Near infrared spectroscopy
This work presents results on the modeling of the photon diffusion in a three-layered model, (skin, fat and muscle). The
Finite Element method was performed in order to calculate the temporal response of the above-mentioned structure. The
thickness of the fat layer was varied from 1 to 15 mm to investigate the effects of increasing fat thickness on the muscle
layer absorption coefficient measurements for a source-detector spacing of 30 mm.
The simulated time-resolved reflectance data, at different wavelengths, were fitted to the diffusion model to yield the
scattering and absorption coefficients of muscle. The errors in estimating muscle absorption coefficients &mgr;α depend on
the thickness of the fat layer and its optical properties. In addition, it was shown that it is possible to recover with a good
precision (~2.6 % of error) the absorption coefficient of muscle and this up to a thickness of the fat layer not exceeding
4mm. Beyond this limit a correction is proposed in order to make measurements coherent. The muscle-corrected
absorption coefficient can be then used to calculate hemoglobin oxygenation.
In the last few years, the propagation of diffuse photons in scattering media has become an important field of interest. This is mainly due to the possibility offered by the low absorption of light in the range 700 to 900nm. Indeed, this property leads to a potential deep penetration. But a non negligible limitation appears: the scattering processes strongly reduce both the contrast and the resolution. In this paper, the time-dependent light propagation in highly scattering media containing an inclusion is solved by means of a finite element method, tacking into account Robin type air-tissue boundary conditions. This study is devoted to the depth localization of a tumor enclosed into a breast-like slab. The tissue is modeled by a rectangular meshed domain that mimics a breast compressed between two transparent plates. Cartesian coordinates are used in order to solve the time-dependent diffusion approximation. A short laser pulse of 1ps is considered. The transillumination technique is able to laterally detect the object when the source and detector are moved together on the same axis. In order to perform the localization of the inclusion in this study, the optical properties of the object were varied. Knowing the lateral position of the inclusion, we derive interesting temporal contrast functions based on the mean time of flight of photons. These functions allow to localize in depth the inclusion under the assumption that the object is very diffusing. To conclude, our study demonstrates the possibility to detect laterally and axially a tumor-like inclusion enclosed in breast-like tissues.
Reactive hyperemia signals obtained with laser Doppler flowmetry are currently used to diagnose peripheral arterial occlusive diseases (PAOD). De-noising of such signals could lead to improved diagnoses. For this purpose, the principal components analysis is applied to signals acquired on PAOD and healthy subjects.
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