Modeling anisotropic light propagation in a realistic model of the human head

Model-based prediction of optogenetic sound encoding in the human cochlea by future optical cochlear implants

When hearing fails, electrical cochlear implants (eCIs) partially restore hearing by direct stimulation of spiral ganglion neurons (SGNs). As light can be better confined in space than electrical current, optical CIs (oCIs) provide more spectral information promising a fundamental improvement of hearing restoration by cochlear implants. Here, we turned to computer modelling for predicting the outcome of optogenetic hearing restoration by future oCIs in humans. We combined three-dimensional reconstruction of the human cochlea with ray-tracing simulation of emission from LED or laser-coupled waveguide emitters of the oCI. Irradiance was read out at the somata of SGNs. The irradiance values reached with waveguides were about 14 times higher than with LEDs, at the same radiant flux of the emitter. Moreover, waveguides outperformed LEDs regarding spectral selectivity. oCIs with either emitter type showed greater spectral selectivity when compared to eCI. In addition, modeling the effects of the source-to-SGN distance, orientation of the sources and impact of scar tissue further informs the development of optogenetic hearing restoration.

Truncated Fourier-series approximation of the time-domain radiative transfer equation using finite elements

The radiative transfer equation (RTE) is widely accepted to accurately describe light transport in a medium with scattering particles, and it has been successfully applied as a light-transport model, for example, in diffuse optical tomography. Due to the computationally expensive nature of the RTE, most of these applications have been in the frequency domain. In this paper, an efficient solution method for the time-domain RTE is proposed. The method is based on solving the frequency-domain RTE at multiple modulation frequencies and using the Fourier-series representation of the radiance to obtain approximation of the time-domain solution. The approach is tested with simulations. The results show that the method can be used to obtain the solution of the time-domain RTE with good accuracy and with significantly fewer computational resources than are needed in the direct time-domain solution.

Patient-oriented simulation based on Monte Carlo algorithm by using MRI data

Background

Although Monte Carlo simulations of light propagation in full segmented three-dimensional MRI based anatomical models of the human head have been reported in many articles. To our knowledge, there is no patient-oriented simulation for individualized calibration with NIRS measurement. Thus, we offer an approach for brain modeling based on image segmentation process with in vivo MRI T1 three-dimensional image to investigate the individualized calibration for NIRS measurement with Monte Carlo simulation.

Methods

In this study, an individualized brain is modeled based on in vivo MRI 3D image as five layers structure. The behavior of photon migration was studied for this individualized brain detections based on three-dimensional time-resolved Monte Carlo algorithm. During the Monte Carlo iteration, all photon paths were traced with various source-detector separations for characterization of brain structure to provide helpful information for individualized design of NIRS system.

Results

Our results indicate that the patient-oriented simulation can provide significant characteristics on the optimal choice of source-detector separation within 3.3 cm of individualized design in this case. Significant distortions were observed around the cerebral cortex folding. The spatial sensitivity profile penetrated deeper to the brain in the case of expanded CSF. This finding suggests that the optical method may provide not only functional signal from brain activation but also structural information of brain atrophy with the expanded CSF layer. The proposed modeling method also provides multi-wavelength for NIRS simulation to approach the practical NIRS measurement.

Conclusions

In this study, the three-dimensional time-resolved brain modeling method approaches the realistic human brain that provides useful information for NIRS systematic design and calibration for individualized case with prior MRI data.

Comparison of principal and independent component analysis in removing extracerebral interference from near-infrared spectroscopy signals

Near-infrared spectroscopy (NIRS) is a method for noninvasive estimation of cerebral hemodynamic changes. Principal component analysis (PCA) and independent component analysis (ICA) can be used for decomposing a set of signals to underlying components. Our objective is to determine whether PCA or ICA is more efficient in identifying and removing scalp blood flow interference from multichannel NIRS signals. Concentration changes of oxygenated (HbO(2)) and deoxygenated (HbR) hemoglobin are measured on the forehead with multichannel NIRS during hyper- and hypocapnia. PCA and ICA are used separately to identify and remove signal contribution from extracerebral tissue, and the resulting estimates of cerebral responses are compared to the expected cerebral responses. Both methods were able to reduce extracerebral contribution to the signals, but PCA typically performs equal to or better than ICA. The improvement in 3-cm signal quality achieved with both methods is comparable to increasing the source-detector separation from 3 to 5 cm. Especially PCA appears to be well suited for use in NIRS applications where the cerebral activation is diffuse, such as monitoring of global cerebral oxygenation and hemodynamics. Performance differences between PCA and ICA could be attributed primarily to different criteria for identifying the surface effect.

Near-infrared microspectroscopic analysis of rat skin tissue heterogeneity in relation to noninvasive glucose sensing

BACKGROUND

Noninvasive glucose measurements are possible by analysis of transmitted near-infrared light over the 4000- to 5000-cm(-1) spectral range. Such measurements are highly sensitive to the exact position of the fiber-optic interface on the surface of the skin sample. A critical question is the degree of heterogeneity of the major chemical components of the skin matrix in relation to the size of the fiber-optic probed used to collect noninvasive spectra. Microscopic spectral mapping is used to map the chemical distribution for a set of excised sections of rat skin.

METHOD

A Fourier transform near-infrared microspectrometer was used to collect transmission spectra from 16 tissue samples harvested from a set of four healthy Harlan-Sprague male rats. A reference point in the center of the tissue sample was probed regularly to track dehydration, changes in tissue composition, and changes in instrument performance. Amounts of the major skin constituents were determined by fitting microspectra to a set of six pure component absorbance spectra corresponding to water, type I collagen protein, keratin protein, fat, an offset term, and a slope term.

RESULTS

Microspectroscopy provides spectra with root mean square noise levels on 100% lines between 418 and 1475 microabsorbance units, which is sufficient for measuring the main chemical components of skin. The estimated spatial resolution of the microscope is 220 microm. The amounts of each tissue matrix component were determined for each 480 x 360-microm(2) location of a 4.8 x 3.6-mm(2) rectangular block of skin tissue. These spectra were used to generate two-dimensional distribution maps for each of the principal skin components.

CONCLUSIONS

Distribution of the chemical components of rat skin is significant relative to the dimensions of noninvasive glucose sensing. Chemical distribution maps reveal that variations in the chemical composition of the skin samples are on the same length scale as the fiber-optic probe used to collect noninvasive near-infrared spectra. Analysis of variance between tissue slices collected for one animal and analysis of variations between animals indicate that animal-to-animal variation for all four chemical components is significantly higher than variations between samples for a given animal. These findings justify the collection and interpretation of near-infrared microspectroscopic maps of human skin to establish chemical heterogeneity and its impact on noninvasive glucose sensing for the management of diabetes.

Significance of background optical properties, time-resolved information and optode arrangement in diffuse optical imaging of term neonates

The significance of accurate knowledge of background optical properties and time-resolved information in reconstructing images of hemodynamic changes in the neonatal brain from diffuse optical imaging data was studied using Monte Carlo (MC) simulation. A segmented anatomical magnetic resonance (MR) image and literature-derived optical properties for each tissue type were used to create a voxel-based anatomical model. Small absorbing perturbations were introduced into the anatomical model to simulate localized hemodynamic responses related to brain activation. Perturbation MC (pMC) was used as the primary method of image reconstruction. For comparison, reconstructions were also performed using the finite element method (FEM) to solve the diffusion approximation (DA) to the radiative transfer equation (RTE). The effect of optode layout was investigated using three different grids. Of the factors studied, the density of the optode grid was found to have the greatest effect on image quality. The use of time-resolved information significantly improved the spatial accuracy with all optode grids. Adequate knowledge and modeling of the optical properties of the background was found to significantly improve the spatial accuracy of the reconstructed images and make the recovery of contrast of absorption changes more consistent over simplified modeling. Localization accuracy of small perturbations was found to be 2-3 mm with accurate a priori knowledge of the background optical properties, when a grid with high optode density (>1 optode cm(-2)) was used.

Optical brain imaging in vivo: techniques and applications from animal to man

Optical brain imaging has seen 30 years of intense development, and has grown into a rich and diverse field. In-vivo imaging using light provides unprecedented sensitivity to functional changes through intrinsic contrast, and is rapidly exploiting the growing availability of exogenous optical contrast agents. Light can be used to image microscopic structure and function in vivo in exposed animal brain, while also allowing noninvasive imaging of hemodynamics and metabolism in a clinical setting. This work presents an overview of the wide range of approaches currently being applied to in-vivo optical brain imaging, from animal to man. Techniques include multispectral optical imaging, voltage sensitive dye imaging and speckle-flow imaging of exposed cortex, in-vivo two-photon microscopy of the living brain, and the broad range of noninvasive topography and tomography approaches to near-infrared imaging of the human brain. The basic principles of each technique are described, followed by examples of current applications to cutting-edge neuroscience research. In summary, it is shown that optical brain imaging continues to grow and evolve, embracing new technologies and advancing to address ever more complex and important neuroscience questions.

Controlled Monte Carlo method for light propagation in tissue of semi-infinite geometry

The controlled Monte Carlo method is generalized to model photon migration in turbid media of arbitrary geometries. Its implementation for the reflection geometry is exemplified in this paper. The most probable diffuse direction of light is used as the local attractive vector that serves as the basis of biased sampling of scattering angles. Consequently, path-length resolved photon trajectories can be generated with a significantly improved efficiency. We report a more than 29 times reduction in simulation time for early arriving photons in a typical configuration.

Significance of tissue anisotropy in optical tomography of the infant brain

We study the effect of tissue anisotropy in optical tomography of neonates. A Monte Carlo method capable of modeling photon migration in an arbitrary 3D tissue model with spatially varying optical properties and tissue anisotropy is used for simulating measurements of neonates. Anatomical and diffusion tensor magnetic resonance imaging of neonates are used for creating the anatomical models. We find that tissue anisotropy affects the measured signal and the pattern of sensitivity in optical measurements.

An application of perturbation Monte Carlo in optical tomography

Haemodynamic changes related to activation of the human visual cortex were studied using optical imaging. The change in oxyhaemoglobin concentration in the visual cortex was estimated using a perturbation Monte Carlo (pMC) method. Comparison to a topographic map obtained using the modified Beer-Lambert law and interpolation is given.

Phase function measurements on nonspherical scatterers using a two-axis goniometer

We present a two-axis goniometer for measuring the phase function of scattering media with an angular resolution of about 0.2 deg having 12 decades of dynamic range and covering almost the full solid angle. The setup is evaluated with polystyrene spheres and with perpendicularly and obliquely illuminated thin glass cylinders. The scattering pattern and its intensity distribution are in excellent agreement with analytical theory. A multiple scattering configuration composed of two parallel cylinders is also examined. Finally, the phase function of dentin slabs is measured and its dependence on the dental microstructure is discussed.

Coupled radiative transfer equation and diffusion approximation model for photon migration in turbid medium with low-scattering and non-scattering regions

In this paper, a coupled radiative transfer equation and diffusion approximation model is extended for light propagation in turbid medium with low-scattering and non-scattering regions. The light propagation is modelled with the radiative transfer equation in sub-domains in which the assumptions of the diffusion approximation are not valid. The diffusion approximation is used elsewhere in the domain. The two equations are coupled through their boundary conditions and they are solved simultaneously using the finite element method. The streamline diffusion modification is used to avoid the ray-effect problem in the finite element solution of the radiative transfer equation. The proposed method is tested with simulations. The results of the coupled model are compared with the finite element solutions of the radiative transfer equation and the diffusion approximation and with results of Monte Carlo simulation. The results show that the coupled model can be used to describe photon migration in turbid medium with low-scattering and non-scattering regions more accurately than the conventional diffusion model.