Mesh-based Monte Carlo method using fast ray-tracing in Plücker coordinates

A novel volume integral equation for solving the Electroencephalography forward problem

In this paper, a novel volume integral equation for solving the Electroencephalography forward problem is presented. Differently from other integral equation methods standardly used for the same purpose, the new formulation can handle inhomogeneous and fully anisotropic realistic head models. The new equation is obtained by a suitable use of Green's identities together with an appropriate handling of all boundary conditions for the EEG problem. The new equation is discretized with a consistent choice of volume and boundary elements. Numerical results shows validity and convergence of the approach, together with its applicability to real case models obtained from MRI data.

Generalized mesh-based Monte Carlo for wide-field illumination and detection via mesh retessellation

Monte Carlo methods are commonly used as the gold standard in modeling photon transport through turbid media. With the rapid development of structured light applications, an accurate and efficient method capable of simulating arbitrary illumination patterns and complex detection schemes over large surface area is in great need. Here we report a generalized mesh-based Monte Carlo algorithm to support a variety of wide-field illumination methods, including spatial-frequency-domain imaging (SFDI) patterns and arbitrary 2-D patterns. The extended algorithm can also model wide-field detectors such as a free-space CCD camera. The significantly enhanced flexibility of source and detector modeling is achieved via a fast mesh retessellation process that combines the target domain and the source/detector space in a single tetrahedral mesh. Both simulations of complex domains and comparisons with phantom measurements are included to demonstrate the flexibility, efficiency and accuracy of the extended algorithm. Our updated open-source software is provided at http://mcx.space/mmc.

Evaluating real-time image reconstruction in diffuse optical tomography using physiologically realistic test data

In diffuse optical tomography (DOT), real-time image reconstruction of oxy- and deoxy-haemoglobin changes occurring in the brain could give valuable information in clinical care settings. Although non-linear reconstruction techniques could provide more accurate results, their computational burden makes them unsuitable for real-time applications. Linear techniques can be employed under the assumption that the expected change in absorption is small. Several approaches exist, differing primarily in their handling of regularization and the noise statistics. In real experiments, it is impossible to compute the true noise statistics, because of the presence of physiological oscillations in the measured data. This is even more critical in real-time applications, where no off-line filtering and averaging can be performed to reduce the noise level. Therefore, many studies substitute the noise covariance matrix with the identity matrix. In this paper, we examined two questions: does using the noise model with realistic, imperfect data yield an improvement in image quality compared to using the identity matrix; and what is the difference in quality between online and offline reconstructions. Bespoke test data were created using a novel process through which simulated changes in absorption were added to real resting-state DOT data. A realistic multi-layer head model was used as the geometry for the reconstruction. Results validated our assumptions, highlighting the validity of computing the noise statistics from the measured data for online image reconstruction, which was performed at 2 Hz. Our results can be directly extended to a real application where real-time imaging is required.

OptogenSIM: a 3D Monte Carlo simulation platform for light delivery design in optogenetics

Optimizing light delivery for optogenetics is critical in order to accurately stimulate the neurons of interest while reducing nonspecific effects such as tissue heating or photodamage. Light distribution is typically predicted using the assumption of tissue homogeneity, which oversimplifies light transport in heterogeneous brain. Here, we present an open-source 3D simulation platform, OptogenSIM, which eliminates this assumption. This platform integrates a voxel-based 3D Monte Carlo model, generic optical property models of brain tissues, and a well-defined 3D mouse brain tissue atlas. The application of this platform in brain data models demonstrates that brain heterogeneity has moderate to significant impact depending on application conditions. Estimated light density contours can show the region of any specified power density in the 3D brain space and thus can help optimize the light delivery settings, such as the optical fiber position, fiber diameter, fiber numerical aperture, light wavelength and power. OptogenSIM is freely available and can be easily adapted to incorporate additional brain atlases.

Sensitivity analysis aimed at blood vessels detection using interstitial optical tomography during brain needle biopsy procedures

A brain needle biopsy procedure is performed for suspected brain lesions in order to sample tissue that is subsequently analysed using standard histopathology techniques. A common complication resulting from this procedure is brain hemorrhaging from blood vessels clipped off during tissue extraction. Interstitial optical tomography (iOT) has recently been introduced by our group as a mean to assess the presence of blood vessels in the vicinity of the needle. The clinical need to improve safety requires the detection of blood vessels within 2 mm from the outer surface of the needle, since this distance is representative of the volume of tissue that is aspirated durirng tissue extraction. Here, a sensitivity analysis is presented to establish the intrinsic detection limits of iOT based on simulations and experiments using brain tissue phantoms. It is demonstrated that absorbers can be detected with diameters >300 μm located up to >2 mm from the biopsy needle core for bulk optical properties consistent with brain tissue.

Human temporal-parietal junction spontaneously tracks others' beliefs: A functional near-infrared spectroscopy study

Humans have the unique capacity to actively reflect on the thoughts, beliefs, and knowledge of others, but do we also track mental states spontaneously when observing other people? We asked this question by monitoring brain activity in belief-sensitive cortex using functional near-infrared spectroscopy (fNIRS) during free-viewing of social videos. More specifically, we identified a portion of the right temporal-parietal junction (rTPJ) selective for mental state processing using an established, explicit theory of mind task, and then analyzed the brain response in that region of interest (ROI) during free-viewing of video clips involving people producing goal-directed actions. We found a significant increase in oxygenated hemoglobin concentration in our rTPJ ROI during free-viewing for all of our test videos. Activity in this region was further modulated by the extent to which the knowledge state, or beliefs, of the protagonist regarding the location of an object contrasted with the reality of where the object was hidden. Open-ended questioning suggested our participants were not explicitly focusing on belief states of the characters during free-viewing. Further analyses ruled out lower-level details of the video clips or general attentional differences between conditions as likely explanations for the results. As such, these results call into question the traditional characterization of theory of mind as a resource intensive, deliberate process, and, instead, support an emerging view of theory of mind as a foundation for, rather than the pinnacle of, human social cognition.

Dynamic light scattering Monte Carlo: a method for simulating time-varying dynamics for ordered motion in heterogeneous media

Few methods exist that can accurately handle dynamic light scattering in the regime between single and highly multiple scattering. We demonstrate dynamic light scattering Monte Carlo (DLS-MC), a numerical method by which the electric field autocorrelation function may be calculated for arbitrary geometries if the optical properties and particle motion are known or assumed. DLS-MC requires no assumptions regarding the number of scattering events, the final form of the autocorrelation function, or the degree of correlation between scattering events. Furthermore, the method is capable of rapidly determining the effect of particle motion changes on the autocorrelation function in heterogeneous samples. We experimentally validated the method and demonstrated that the simulations match both the expected form and the experimental results. We also demonstrate the perturbation capabilities of the method by calculating the autocorrelation function of flow in a representation of mouse microvasculature and determining the sensitivity to flow changes as a function of depth.

Modeling the propagation of light in realistic tissue structures with MMC-fpf: a meshed Monte Carlo method with free phase function

Monte Carlo methods commonly used in tissue optics are limited to a layered tissue geometry and thus provide only a very rough approximation for many complex media such as biological structures. To overcome these limitations, a Meshed Monte Carlo method with flexible phase function choice (fpf-MC) has been developed to function in a mesh. This algorithm can model the light propagation in any complexly shaped structure, by attributing optical properties to the different mesh elements. Furthermore, this code allows the use of different discretized phase functions for each tissue type, which can be simulated from the microstructural properties of the tissue, in combination with a tool for simulating the bulk optical properties of polydisperse suspensions. As a result, the scattering properties of tissues can be estimated from information on the microstructural properties of the tissue. This is important for the estimation of the bulk optical properties that can be used for the light propagation model, since many types of tissue have never been characterized in literature. The combination of these contributions, made it possible to use the MMC-fpf for modeling the light porapagation in plant tissue. The developed Meshed Monte Carlo code with flexible phase function choice (MMC-fpf) was successfully validated in simulation through comparison with the Monte Carlo code in Multi-Layered tissues (R2 > 0.9999) and experimentally by comparing the measured and simulated reflectance (RMSE = 0.015%) and transmittance (RMSE = 0.0815%) values for tomato leaves.

Impact of vessel diameter and bandwidth of illumination in sidestream dark-field oximetry

We investigate the possibility of oxygen saturation estimation from images obtained by the sidestream dark-field (SDF) technique. The SDF technique is a method for microvascular imaging. In SDF imaging, light enters a tissue directly from illumination sources configured around a camera and then the camera captures the light scattered by the tissue. To advance the capability of the SDF imaging system, we develop a SDF oximetry method with LED illumination sources. In this paper, we evaluate some SDF oximetry methods from virtual SDF images obtained by the Monte Carlo photon propagation simulation. As a result, we verify that SDF imaging allows the estimation of oxygen saturation of the individual vessels from virtual images using the average extinction coefficients considering the bandwidth of the illumination and the effect of the integration of the camera.

Mesh Optimization for Monte Carlo-Based Optical Tomography

Mesh-based Monte Carlo techniques for optical imaging allow for accurate modeling of light propagation in complex biological tissues. Recently, they have been developed within an efficient computational framework to be used as a forward model in optical tomography. However, commonly employed adaptive mesh discretization techniques have not yet been implemented for Monte Carlo based tomography. Herein, we propose a methodology to optimize the mesh discretization and analytically rescale the associated Jacobian based on the characteristics of the forward model. We demonstrate that this method maintains the accuracy of the forward model even in the case of temporal data sets while allowing for significant coarsening or refinement of the mesh.

Anatomical guidance for functional near-infrared spectroscopy: AtlasViewer tutorial

Functional near-infrared spectroscopy (fNIRS) is an optical imaging method that is used to noninvasively measure cerebral hemoglobin concentration changes induced by brain activation. Using structural guidance in fNIRS research enhances interpretation of results and facilitates making comparisons between studies. AtlasViewer is an open-source software package we have developed that incorporates multiple spatial registration tools to enable structural guidance in the interpretation of fNIRS studies. We introduce the reader to the layout of the AtlasViewer graphical user interface, the folder structure, and user files required in the creation of fNIRS probes containing sources and detectors registered to desired locations on the head, evaluating probe fabrication error and intersubject probe placement variability, and different procedures for estimating measurement sensitivity to different brain regions as well as image reconstruction performance. Further, we detail how AtlasViewer provides a generic head atlas for guiding interpretation of fNIRS results, but also permits users to provide subject-specific head anatomies to interpret their results. We anticipate that AtlasViewer will be a valuable tool in improving the anatomical interpretation of fNIRS studies.

Red and NIR light dosimetry in the human deep brain

Photobiomodulation (PBM) appears promising to treat the hallmarks of Parkinson's Disease (PD) in cellular or animal models. We measured light propagation in different areas of PD-relevant deep brain tissue during transcranial, transsphenoidal illumination (at 671 and 808 nm) of a cadaver head and modeled optical parameters of human brain tissue using Monte-Carlo simulations. Gray matter, white matter, cerebrospinal fluid, ventricles, thalamus, pons, cerebellum and skull bone were processed into a mesh of the skull (158 × 201 × 211 voxels; voxel side length: 1 mm). Optical parameters were optimized from simulated and measured fluence rate distributions. The estimated μeff for the different tissues was in all cases larger at 671 than at 808 nm, making latter a better choice for light delivery in the deep brain. Absolute values were comparable to those found in the literature or slightly smaller. The effective attenuation in the ventricles was considerably larger than literature values. Optimization yields a new set of optical parameters better reproducing the experimental data. A combination of PBM via the sphenoid sinus and oral cavity could be beneficial. A 20-fold higher efficiency of light delivery to the deep brain was achieved with ventricular instead of transcranial illumination. Our study demonstrates that it is possible to illuminate deep brain tissues transcranially, transsphenoidally and via different application routes. This opens therapeutic options for sufferers of PD or other cerebral diseases necessitating light therapy.

Monte Carlo modeling of light propagation in the human head for applications in sinus imaging

Sinus blockages are a common reason for physician visits, affecting one out of seven people in the United States, and often require medical treatment. Diagnosis in the primary care setting is challenging because symptom criteria (via detailed clinical history) plus objective imaging [computed tomography (CT) or endoscopy] are recommended. Unfortunately, neither option is routinely available in primary care. We previously demonstrated that low-cost near-infrared (NIR) transillumination correlates with the bulk findings of sinus opacity measured by CT. We have upgraded the technology, but questions of source optimization, anatomical influence, and detection limits remain. In order to begin addressing these questions, we have modeled NIR light propagation inside a three-dimensional adult human head constructed via CT images using a mesh-based Monte Carlo algorithm (MMCLAB). In this application, the sinus itself, which when healthy is a void region (e.g., nonscattering), is the region of interest. We characterize the changes in detected intensity due to clear (i.e., healthy) versus blocked sinuses and the effect of illumination patterns. We ran simulations for two clinical cases and compared simulations with measurements. The simulations presented herein serve as a proof of concept that this approach could be used to understand contrast mechanisms and limitations of NIR sinus imaging.

Macroscopic-imaging technique for subsurface quantification of near-infrared markers during surgery

Obtaining accurate quantitative information on the concentration and distribution of fluorescent markers lying at a depth below the surface of optically turbid media, such as tissue, is a significant challenge. Here, we introduce a fluorescence reconstruction technique based on a diffusion light transport model that can be used during surgery, including guiding resection of brain tumors, for depth-resolved quantitative imaging of near-infrared fluorescent markers. Hyperspectral fluorescence images are used to compute a topographic map of the fluorophore distribution, which yields structural and optical constraints for a three-dimensional subsequent hyperspectral diffuse fluorescence reconstruction algorithm. Using the model fluorophore Alexa Fluor 647 and brain-like tissue phantoms, the technique yielded estimates of fluorophore concentration within ±25% of the true value to depths of 5 to 9 mm, depending on the concentration. The approach is practical for integration into a neurosurgical fluorescence microscope and has potential to further extend fluorescence-guided resection using objective and quantified metrics of the presence of residual tumor tissue.

Dynamic causal modelling for functional near-infrared spectroscopy

Functional near-infrared spectroscopy (fNIRS) is an emerging technique for measuring changes in cerebral hemoglobin concentration via optical absorption changes. Although there is great interest in using fNIRS to study brain connectivity, current methods are unable to infer the directionality of neuronal connections. In this paper, we apply Dynamic Causal Modelling (DCM) to fNIRS data. Specifically, we present a generative model of how observed fNIRS data are caused by interactions among hidden neuronal states. Inversion of this generative model, using an established Bayesian framework (variational Laplace), then enables inference about changes in directed connectivity at the neuronal level. Using experimental data acquired during motor imagery and motor execution tasks, we show that directed (i.e., effective) connectivity from the supplementary motor area to the primary motor cortex is negatively modulated by motor imagery, and this suppressive influence causes reduced activity in the primary motor cortex during motor imagery. These results are consistent with findings of previous functional magnetic resonance imaging (fMRI) studies, suggesting that the proposed method enables one to infer directed interactions in the brain mediated by neuronal dynamics from measurements of optical density changes.

Optical properties of rabbit brain in the red and near-infrared: changes observed under in vivo, postmortem, frozen, and formalin-fixated conditions

The outcome of light-based therapeutic approaches depends on light propagation in biological tissues, which is governed by their optical properties. The objective of this study was to quantify optical properties of brain tissue in vivo and postmortem and assess changes due to tissue handling postmortem. The study was carried out on eight female New Zealand white rabbits. The local fluence rate was measured in the VIS/NIR range in the brain in vivo, just postmortem, and after six weeks’ storage of the head at −20°C or in 10% formaldehyde solution. Only minimal changes in the effective attenuation coefficient μeff were observed for two methods of sacrifice, exsanguination or injection of KCl. Under all tissue conditions, μeff decreased with increasing wavelengths. After long-term storage for six weeks at −20°C, μeff decreased, on average, by 15 to 25% at all wavelengths, while it increased by 5 to 15% at all wavelengths after storage in formaldehyde. We demonstrated that μeff was not very sensitive to the method of animal sacrifice, that tissue freezing significantly altered tissue optical properties, and that formalin fixation might affect the tissue’s optical properties.)

Boundary discretization in the numerical simulation of light propagation in skin tissue: problem and strategy

To adapt the complex tissue structure, laser propagation in a two-layered skin model is simulated to compare voxel-based Monte Carlo (VMC) and tetrahedron-based MC (TMC) methods with a geometry-based MC (GMC) method. In GMC, the interface is mathematically defined without any discretization. GMC is the most accurate but is not applicable to complicated domains. The implementation of VMC is simple because of its structured voxels. However, unavoidable errors are expected because of the zigzag polygonal interface. Compared with GMC and VMC, TMC provides a balance between accuracy and flexibility by the tetrahedron cells. In the present TMC, the body-fitted tetrahedra are generated in different tissues. No interface tetrahedral cells exist, thereby avoiding the photon reflection error in the interface cells in VMC. By introducing a distance threshold, the error caused by confused optical parameters between neighboring cells when photons are incident along the cell boundary can be avoided. The results show that the energy deposition error by TMC in the interfacial region is one-tenth to one-fourth of that by VMC, yielding more accurate computations of photon reflection, refraction, and energy deposition. The results of multilayered and n-shaped vessels indicate that a laser with a 1064-nm wavelength should be introduced to clean deep-buried vessels.

A statistical thermodynamic model for investigating the stability of DNA sequences from oligonucleotides to genomes

We describe the development and testing of a simple statistical mechanics methodology for duplex DNA applicable to sequences of any composition and extensible to genomes. The microstates of a DNA sequence are modeled in terms of blocks of basepairs that are assumed to be fully closed (paired) or open. This approach generates an ensemble of bubblelike microstates that are used to calculate the corresponding partition function. The energies of the microstates are calculated as additive contributions from hydrogen bonding, basepair stacking, and solvation terms parameterized from a comprehensive series of molecular dynamics simulations including solvent and ions. Thermodynamic properties and nucleotide stability constants for DNA sequences follow directly from the partition function. The methodology was tested by comparing computed free energies per basepair with the experimental melting temperatures of 60 oligonucleotides, yielding a correlation coefficient of -0.96. The thermodynamic stability of genic/nongenic regions was tested in terms of nucleotide stability constants versus sequence for the Escherichia coli K-12 genome. It showed clear differentiation of the genes from promoters and captures genic regions with a sensitivity of 0.94. The statistical thermodynamic model presented here provides a seemingly new handle on the challenging problem of interpreting genomic sequences.

FDTD-based Transcranial Magnetic Stimulation model applied to specific neurodegenerative disorders

Non-invasive treatment of neurodegenerative diseases is particularly challenging in Western countries, where the population age is increasing. In this work, magnetic propagation in human head is modelled by Finite-Difference Time-Domain (FDTD) method, taking into account specific characteristics of Transcranial Magnetic Stimulation (TMS) in neurodegenerative diseases. It uses a realistic high-resolution three-dimensional human head mesh. The numerical method is applied to the analysis of magnetic radiation distribution in the brain using two realistic magnetic source models: a circular coil and a figure-8 coil commonly employed in TMS. The complete model was applied to the study of magnetic stimulation in Alzheimer and Parkinson Diseases (AD, PD). The results show the electrical field distribution when magnetic stimulation is supplied to those brain areas of specific interest for each particular disease. Thereby the current approach entails a high potential for the establishment of the current underdeveloped TMS dosimetry in its emerging application to AD and PD.

Selection of voxel size and photon number in voxel-based Monte Carlo method: criteria and applications

The voxel-based Monte Carlo method (VMC) is now a gold standard in the simulation of light propagation in turbid media. For complex tissue structures, however, the computational cost will be higher when small voxels are used to improve smoothness of tissue interface and a large number of photons are used to obtain accurate results. To reduce computational cost, criteria were proposed to determine the voxel size and photon number in 3-dimensional VMC simulations with acceptable accuracy and computation time. The selection of the voxel size can be expressed as a function of tissue geometry and optical properties. The photon number should be at least 5 times the total voxel number. These criteria are further applied in developing a photon ray splitting scheme of local grid refinement technique to reduce computational cost of a nonuniform tissue structure with significantly varying optical properties. In the proposed technique, a nonuniform refined grid system is used, where fine grids are used for the tissue with high absorption and complex geometry, and coarse grids are used for the other part. In this technique, the total photon number is selected based on the voxel size of the coarse grid. Furthermore, the photon-splitting scheme is developed to satisfy the statistical accuracy requirement for the dense grid area. Result shows that local grid refinement technique photon ray splitting scheme can accelerate the computation by 7.6 times (reduce time consumption from 17.5 to 2.3 h) in the simulation of laser light energy deposition in skin tissue that contains port wine stain lesions.

Lensed fiber-optic probe design for efficient photon collection in scattering media

Measurement of bioluminescent or fluorescent optical reporters with an implanted fiber-optic probe is a promising approach to allow real-time monitoring of molecular and cellular processes in conscious behaving animals. Technically, this approach relies on sensitive light detection due to the relatively limited light signal and inherent light attenuation in scattering tissue. In this paper, we show that specific geometries of lensed fiber probes improve photon collection in turbid tissue such as brain. By employing Monte Carlo simulation and experimental measurement, we demonstrate that hemispherical- and axicon-shaped lensed fibers increase collection efficiency by up to 2-fold when compared with conventional bare fiber. Additionally we provide theoretical evidence that axicon lenses with specific angles improve photon collection over a wider axial range while conserving lateral collection when compared to hemispherical lensed fiber. These findings could guide the development of a minimally-invasive highly sensitive fiber optic-based light signal monitoring technique and may have broad implications such as fiber-based detection used in diffuse optical spectroscopy.

Experimental recovery of intrinsic fluorescence and fluorophore concentration in the presence of hemoglobin: spectral effect of scattering and absorption on fluorescence

The ability to recover the intrinsic fluorescence of biological fluorophores is crucial to accurately identify the fluorophores and quantify their concentrations in the media. Although some studies have successfully retrieved the fluorescence spectral shape of known fluorophores, the techniques usually came with heavy computation costs and did not apply for strongly absorptive media, and the intrinsic fluorescence intensity and fluorophore concentration were not recovered. In this communication, an experimental approach was presented to recover intrinsic fluorescence and concentration of fluorescein in the presence of hemoglobin (Hb). The results indicated that the method was efficient in recovering the intrinsic fluorescence peak and fluorophore concentration with an error of 3% and 10%, respectively. The results also suggested that chromophores with irregular absorption spectra (e.g., Hb) have more profound effects on fluorescence spectral shape than chromophores with monotonic absorption and scattering spectra (e.g., black India ink and polystyrene microspheres).

Hierarchical Bayesian Model for Diffuse Optical Tomography of the Human Brain: Human Experimental Study

Diffuse optical tomography (DOT) is an emerging technology for improving the spatial resolution of conventional multi-channel near infrared spectroscopy (NIRS). The hemodynamics changes in two distinct anatomical layers, the scalp and the cortex, are known as the main contributor of NIRS measurement. Although any DOT algorithm has the ability to reconstruct scalp and cortical hemodynamics changes in their respective layers, no DOT algorithm has used a model characterizing the distinct nature of scalp and cortical hemodynamics changes to achieve accurate separation. Previously, we have proposed a hierarchical Bayesian model for DOT in which distinct prior distributions for the scalp and the cortical hemodynamics changes are assumed and then verified the reconstruction performance with a phantom experiment and a computer simulation of a real human head model (Shimokawa et al. 2013, Biomedical Optical Express). Here, we investigate the reconstruction accuracy of the proposed algorithm using human experimental data for the first time. We measured the brain activities of a single subject during a finger extension task with NIRS and fMRI. Our DOT reconstruction was compared with the fMRI localization results. Consequently, a remarkable consistency between fMRI and our DOT reconstruction was observed both in the spatial and temporal patterns. By extending the advantages of NIRS such as low running cost and portability with our DOT method, it might be possible to advance brain research in a real environment, which cannot be done with fMRI.

Correspondence of electroencephalography and near-infrared spectroscopy sensitivities to the cerebral cortex using a high-density layout

This study investigates the correspondence of the cortical sensitivity of electroencephalography (EEG) and near-infrared spectroscopy (NIRS). EEG forward model sensitivity to the cerebral cortex was calculated for 329 EEG electrodes following the 10-5 EEG positioning system using a segmented structural magnetic resonance imaging scan of a human subject. NIRS forward model sensitivity was calculated for the same subject using 156 NIRS source-detector pairs selected from 32 source and 32 detector optodes positioned on the scalp using a subset of the 10-5 EEG positioning system. Sensitivity correlations between colocalized NIRS source-detector pair groups and EEG channels yielded R = 0.46 ± 0.08. Groups of NIRS source-detector pairs with maximum correlations to EEG electrode sensitivities are tabulated. The mean correlation between the point spread functions for EEG and NIRS regions of interest (ROI) was R = 0.43 ± 0.07. Spherical ROIs with radii of 26 mm yielded the maximum correlation between EEG and NIRS averaged across all cortical mesh nodes. These sensitivity correlations between EEG and NIRS should be taken into account when designing multimodal studies of neurovascular coupling and when using NIRS as a statistical prior for EEG source localization.

Analytical model of optical fluence inside multiple cylindrical inhomogeneities embedded in an otherwise homogeneous turbid medium for quantitative photoacoustic imaging

We present an analytical model of optical fluence for multiple cylindrical inhomogeneities embedded in an otherwise homogeneous turbid medium. The model is based on the diffusion equation and represents the optical fluence distribution inside and outside inhomogeneities as a series of modified Bessel functions. We take into account the interplay between cylindrical inhomogeneities by introducing new boundary conditions on the surface of inhomogeneities. The model is compared with the numerical solution of the diffusion equation with NIRFAST software. The fluences inside the inhomogeneities obtained by the two methods are in close agreement. This permits the use of the model as a forward model for quantitative photoacoustic imaging.

Event-Related Potential, Time-frequency, and Functional Connectivity Facets of Local and Global Auditory Novelty Processing: An Intracranial Study in Humans

Auditory novelty detection has been associated with different cognitive processes. Bekinschtein et al. (2009) developed an experimental paradigm to dissociate these processes, using local and global novelty, which were associated, respectively, with automatic versus strategic perceptual processing. They have mostly been studied using event-related potentials (ERPs), but local spiking activity as indexed by gamma (60-120 Hz) power and interactions between brain regions as indexed by modulations in beta-band (13-25 Hz) power and functional connectivity have not been explored. We thus recorded 9 epileptic patients with intracranial electrodes to compare the precise dynamics of the responses to local and global novelty. Local novelty triggered an early response observed as an intracranial mismatch negativity (MMN) contemporary with a strong power increase in the gamma band and an increase in connectivity in the beta band. Importantly, all these responses were strictly confined to the temporal auditory cortex. In contrast, global novelty gave rise to a late ERP response distributed across brain areas, contemporary with a sustained power decrease in the beta band (13-25 Hz) and an increase in connectivity in the alpha band (8-13 Hz) within the frontal lobe. We discuss these multi-facet signatures in terms of conscious access to perceptual information.

A 4D neonatal head model for diffuse optical imaging of pre-term to term infants

Diffuse optical tomography is most accurate when an individual's MRI data can be used as a spatial prior for image reconstruction and for visualization of the resulting images of changes in oxy- and deoxy-hemoglobin concentration. As this necessitates an MRI scan to be performed for each study, which undermines many of the advantages of diffuse optical methods, the use of registered atlases to model the individual's anatomy is becoming commonplace. Infant studies require carefully age-matched atlases because of the rapid growth and maturation of the infant brain. In this paper, we present a 4D neonatal head model which, for each week from 29 to 44 weeks post-menstrual age, includes: 1) a multi-layered tissue mask which identifies extra-cerebral layers, cerebrospinal fluid, gray matter, white matter, cerebellum and brainstem, 2) a high-density tetrahedral head mesh, 3) surface meshes for the scalp, gray-matter and white matter layers and 4) cranial landmarks and 10-5 locations on the scalp surface. This package, freely available online at www.ucl.ac.uk/medphys/research/4dneonatalmodel can be applied by users of near-infrared spectroscopy and diffuse optical tomography to optimize probe locations, optimize image reconstruction, register data to cortical locations and ultimately improve the accuracy and interpretation of diffuse optical techniques in newborn populations.

Monte Carlo simulation of laser beams interaction with the human eye using Geant4

Background

Due to the unique characteristics of the eye, ophthalmologic diagnostic techniques often rely on the photons interaction with the retina to infer its internal structure. Although these techniques are widely used, the interpretation of the generated images is not always fully understood, as in scanning laser ophthalmoscopy dark field imaging. This limits the exploitation of its full potential as a diagnostic tool for deep abnormalities in the retina, as in the situation of drusen.

Methods

With the aim of better understanding the retinal diagnostic images, we have carried out computer simulations of incident laser beams interacting with different structures of the human eye, including a retina with and without drusen. We have used the Geant4 simulation toolkit, applying the optical package of the electromagnetic (EM) physics working group, to simulate the physical processes of reflection, refraction, absorption, and scattering of low energy photons (2 eV) in biological tissues. For each simulation it was used a single beam of orange light, with a Gaussian profile, that travels through all optical elements of the eye. The reflected beam characteristics were analyzed by virtual detectors in different locations, which collected information about the number and position of photons. The geometry and optical properties of all components of the eye were considered according to the published data.

Results

Simulation results put in evidence that the presence of drusen influences the profile of the reflected beams. It changes the mean free path of the photons, modifying its reflection pattern, which depends on the area illuminated by the incident beam. This result is also visible when the reflected beam is analyzed outside of the eye, when the profile has no longer a symmetrical Gaussian distribution. These results will support the retinal diagnostic images that will be obtained in a near future with a new developed ophthalmic apparatus.

Conclusions

The shape analysis of the reflected beams in retinal laser scanning techniques could increase its potential as a diagnostic examination tool for the deeper structures of the retina.

Monte Carlo simulation of light transport in turbid medium with embedded object--spherical, cylindrical, ellipsoidal, or cuboidal objects embedded within multilayered tissues

Monte Carlo modeling of light transport in multilayered tissue (MCML) is modified to incorporate objects of various shapes (sphere, ellipsoid, cylinder, or cuboid) with a refractive-index mismatched boundary. These geometries would be useful for modeling lymph nodes, tumors, blood vessels, capillaries, bones, the head, and other body parts. Mesh-based Monte Carlo (MMC) has also been used to compare the results from the MCML with embedded objects (MCML-EO). Our simulation assumes a realistic tissue model and can also handle the transmission/reflection at the object-tissue boundary due to the mismatch of the refractive index. Simulation of MCML-EO takes a few seconds, whereas MMC takes nearly an hour for the same geometry and optical properties. Contour plots of fluence distribution from MCML-EO and MMC correlate well. This study assists one to decide on the tool to use for modeling light propagation in biological tissue with objects of regular shapes embedded in it. For irregular inhomogeneity in the model (tissue), MMC has to be used. If the embedded objects (inhomogeneity) are of regular geometry (shapes), then MCML-EO is a better option, as simulations like Raman scattering, fluorescent imaging, and optical coherence tomography are currently possible only with MCML.

Extension of the GATE Monte-Carlo simulation package to model bioluminescence and fluorescence imaging

The Geant4 Application for Emission Tomography (GATE) is an advanced open-source software dedicated to Monte-Carlo (MC) simulations in medical imaging involving photon transportation (Positron emission tomography, single photon emission computed tomography, computed tomography) and in particle therapy. In this work, we extend the GATE to support simulations of optical imaging, such as bioluminescence or fluorescence imaging, and validate it against the MC for multilayered media standard simulation tool for biomedical optics in simple geometries. A full simulation set-up for molecular optical imaging (bioluminescence and fluorescence) is implemented in GATE, and images of the light distribution emitted from a phantom demonstrate the relevance of using GATE for optical imaging simulations.

Effects of spatial pattern scale of brain activity on the sensitivity of DOT, fMRI, EEG and MEG

The objective of this work is to quantify how patterns of cortical activity at different spatial scales are measured by noninvasive functional neuroimaging sensors. We simulated cortical activation patterns at nine different spatial scales in a realistic head model and propagated this activity to magnetoencephalography (MEG), electroencephalography (EEG), diffuse optical tomography (DOT), and functional magnetic resonance imaging (fMRI) sensors in arrangements that are typically used in functional neuroimaging studies. We estimated contrast transfer functions (CTF), correlation distances in sensor space, and the minimum resolvable spatial scale of cortical activity for each modality. We found that CTF decreases as the spatial extent of cortical activity decreases, and that correlations between nearby sensors depend on the spatial extent of cortical activity. For cortical activity on the intermediate spatial scale of 6.7 cm(2), the correlation distances (r>0.5) were 1.0 cm for fMRI, 2.0 cm for DOT, 12.8 for EEG, 9.5 cm for MEG magnetometers and 9.7 cm for MEG gradiometers. The resolvable spatial pattern scale was found to be 1.43 cm(2) for MEG magnetometers, 0.88 cm(2) for MEG gradiometers, 376 cm(2) for EEG, 0.75 cm(2) for DOT, and 0.072 cm(2) for fMRI. These findings show that sensitivity to cortical activity varies substantially as a function of spatial scale within and between the different imaging modalities. This information should be taken into account when interpreting neuroimaging data and when choosing the number of nodes for network analyses in sensor space.

Time-domain geometrical localization of point-like fluorescence inclusions in turbid media with early photon arrival times

We introduce a novel approach for localizing a plurality of discrete point-like fluorescent inclusions embedded in a thick turbid medium using time-domain measurements. The approach uses early photon information contained in measured time-of-flight distributions originating from fluorescence emission. Fluorescence time point-spread functions (FTPSFs) are acquired with ultrafast time-correlated single photon counting after short pulse laser excitation. Early photon arrival times are extracted from the FTPSFs obtained from several source-detector positions. Each source-detector measurement allows defining a geometrical locus where an inclusion is to be found. These loci take the form of ovals in 2D or ovoids in 3D. From these loci a map can be built, with the maxima thereof corresponding to positions of inclusions. This geometrical approach is supported by Monte Carlo simulations performed for biological tissue-like media with embedded fluorescent inclusions. To validate the approach, several experiments are conducted with a homogeneous phantom mimicking tissue optical properties. In the experiments, inclusions filled with indocyanine green are embedded in the phantom and the fluorescence response to a short pulse of excitation laser is recorded. With our approach, several inclusions can be localized with low millimeter positional error. Our results support the approach as an accurate, efficient, and fast method for localizing fluorescent inclusions embedded in highly turbid media mimicking biological tissues. Further Monte Carlo simulations on a realistic mouse model show the feasibility of the technique for small animal imaging.

Spatial registration for functional near-infrared spectroscopy: from channel position on the scalp to cortical location in individual and group analyses

Functional near-infrared spectroscopy (fNIRS) has now become widely accepted as a common functional imaging modality. In order for fNIRS to achieve genuine neuroimaging citizenship, it would ideally be equipped with functional and structural image analyses. However, fNIRS measures cortical activities from the head surface without anatomical information of the object being measured. In this review article, we will present a methodological overview of spatial registration of fNIRS data to overcome this technical drawback of fNIRS. We first introduce and explore the use of standard stereotaxic space and anatomical labeling. Second, we explain different ways of describing scalp landmarks using 10-20 based systems. Third, we describe the simplest case of fNIRS data co-registration to a subject's own MRI. Fourth, we extend the concept to fNIRS data registration of group data. Fifth, we describe probabilistic registration methods, which use a reference-MRI database instead of a subject's own MRIs, and thus enable MRI-free registration for standalone fNIRS data. Sixth, we further extend the concept of probabilistic registration to three-dimensional image reconstruction in diffuse optical tomography. Seventh, we describe a 3D-digitizer-free method for the virtual registration of fNIRS data. Eighth, we provide practical guidance on how these techniques are implemented in software. Finally, we provide information on current resources and limitations for spatial registration of child and infant data. Through these technical descriptions, we stress the importance of presenting fNIRS data on a common platform to facilitate both intra- and inter-modal data sharing among the neuroimaging community.

Use of optical imaging to progress novel therapeutics to the clinic

There is an undisputed need for employment and improvement of robust technology for real-time analyses of therapeutic delivery and responses in clinical translation of gene and cell therapies. Over the past decade, optical imaging has become the in vivo imaging modality of choice for many preclinical laboratories due to its efficiency, practicality and affordability, while more recently, the clinical potential for this technology is becoming apparent. This review provides an update on the current state of the art in in vivo optical imaging and discusses this rapidly improving technology in the context of it representing a translation enabler or indeed a future clinical imaging modality in its own right.

A GAMOS plug-in for GEANT4 based Monte Carlo simulation of radiation-induced light transport in biological media

We describe a tissue optics plug-in that interfaces with the GEANT4/GAMOS Monte Carlo (MC) architecture, providing a means of simulating radiation-induced light transport in biological media for the first time. Specifically, we focus on the simulation of light transport due to the Čerenkov effect (light emission from charged particle's traveling faster than the local speed of light in a given medium), a phenomenon which requires accurate modeling of both the high energy particle and subsequent optical photon transport, a dynamic coupled process that is not well-described by any current MC framework. The results of validation simulations show excellent agreement with currently employed biomedical optics MC codes, [i.e., Monte Carlo for Multi-Layered media (MCML), Mesh-based Monte Carlo (MMC), and diffusion theory], and examples relevant to recent studies into detection of Čerenkov light from an external radiation beam or radionuclide are presented. While the work presented within this paper focuses on radiation-induced light transport, the core features and robust flexibility of the plug-in modified package make it also extensible to more conventional biomedical optics simulations. The plug-in, user guide, example files, as well as the necessary files to reproduce the validation simulations described within this paper are available online at http://www.dartmouth.edu/optmed/research-projects/monte-carlo-software.

Comparison of an accelerated weighted fluorescence Monte Carlo simulation method with reference methods in multi-layered turbid media

Monte Carlo (MC) simulations are frequently used to simulate the radial distribution of remitted fluorescence light from tissue surfaces upon pencil beam excitation to gather information about influences of different tissue parameters. Here, the "weighted direct emission method" (WDEM) is proposed, which uses a weighted MC simulation approach for both excitation and fluorescence photons, and is compared to four other methods in terms of accuracy and speed, and using a broad range of tissue-relevant optical parameters. The WDEM is 5.2× faster on average than a fixed weight MC approach while still preserving its accuracy. Additional gain of speed can be achieved by implementing it on graphics processing units.

Extended hierarchical Bayesian diffuse optical tomography for removing scalp artifact

Functional near-infrared spectroscopy (fNIRS) can non-invasively measure hemodynamic responses in the cerebral cortex with a portable apparatus. However, the observation signal in fNIRS measurements is contaminated by the artifact signal from the hemodynamic response in the scalp. In this paper, we propose a method to separate the signals from the cortex and the scalp by estimating both hemodynamic changes by diffuse optical tomography (DOT). In the inverse problem of DOT, we introduce smooth regularization to the hemodynamic change in the scalp and sparse regularization to that in the cortex based on the nature of the hemodynamic responses. These appropriate regularization models, with the spatial information of optical paths of many measurement channels, allow three-dimensional reconstruction of both hemodynamic changes. We validate our proposed method through two-layer phantom experiments and MRI-based head-model simulations. In both experiments, the proposed method simultaneously estimates the superficial smooth activity in the scalp area and the deep localized activity in the cortical area.

Accelerating mesh-based Monte Carlo method on modern CPU architectures

In this report, we discuss the use of contemporary ray-tracing techniques to accelerate 3D mesh-based Monte Carlo photon transport simulations. Single Instruction Multiple Data (SIMD) based computation and branch-less design are exploited to accelerate ray-tetrahedron intersection tests and yield a 2-fold speed-up for ray-tracing calculations on a multi-core CPU. As part of this work, we have also studied SIMD-accelerated random number generators and math functions. The combination of these techniques achieved an overall improvement of 22% in simulation speed as compared to using a non-SIMD implementation. We applied this new method to analyze a complex numerical phantom and both the phantom data and the improved code are available as open-source software at http://mcx.sourceforge.net/mmc/.

Mesh-based Monte Carlo method in time-domain widefield fluorescence molecular tomography

We evaluated the potential of mesh-based Monte Carlo (MC) method for widefield time-gated fluorescence molecular tomography, aiming to improve accuracy in both shape discretization and photon transport modeling in preclinical settings. An optimized software platform was developed utilizing multithreading and distributed parallel computing to achieve efficient calculation. We validated the proposed algorithm and software by both simulations and in vivo studies. The results establish that the optimized mesh-based Monte Carlo (mMC) method is a computationally efficient solution for optical tomography studies in terms of both calculation time and memory utilization. The open source code, as part of a new release of mMC, is publicly available at http://mcx.sourceforge.net/mmc/.

Micro-computed tomography-guided, non-equal voxel Monte Carlo method for reconstruction of fluorescence molecular tomography

The study of dual-modality technology which combines microcomputed tomography (micro-CT) and fluorescence molecular tomography (FMT) has become one of the main focuses in FMT. However, because of the diversity of the optical properties and irregular geometry for small animals, a reconstruction method that can effectively utilize the high-resolution structural information of micro-CT for tissue with arbitrary optical properties is still one of the most challenging problems in FMT. We develop a micro-CT-guided non-equal voxel Monte Carlo method for FMT reconstruction. With the guidance of micro-CT, precise voxel binning can be conducted on the irregular boundary or region of interest. A modified Laplacian regularization method is also proposed to accurately reconstruct the distribution of the fluorescent yield for non-equal space voxels. Simulations and phantom experiments show that this method not only effectively reduces the loss of high-resolution structural information of micro-CT in irregular boundaries and increases the accuracy of the FMT algorithm in both forward and inverse problems, but the method also has a small Jacobian matrix and a short reconstruction time. At last, we performed small animal imaging to validate our method.

Validating atlas-guided DOT: a comparison of diffuse optical tomography informed by atlas and subject-specific anatomies

We describe the validation of an anatomical brain atlas approach to the analysis of diffuse optical tomography (DOT). Using MRI data from 32 subjects, we compare the diffuse optical images of simulated cortical activation reconstructed using a registered atlas with those obtained using a subject's true anatomy. The error in localization of the simulated cortical activations when using a registered atlas is due to a combination of imperfect registration, anatomical differences between atlas and subject anatomies and the localization error associated with diffuse optical image reconstruction. When using a subject-specific MRI, any localization error is due to diffuse optical image reconstruction only. In this study we determine that using a registered anatomical brain atlas results in an average localization error of approximately 18 mm in Euclidean space. The corresponding error when the subject's own MRI is employed is 9.1 mm. In general, the cost of using atlas-guided DOT in place of subject-specific MRI-guided DOT is a doubling of the localization error. Our results show that despite this increase in error, reasonable anatomical localization is achievable even in cases where the subject-specific anatomy is unavailable.

Quantitative assessment of diffuse optical tomography sensitivity to the cerebral cortex using a whole-head probe

We quantify the variability in diffuse optical tomography (DOT) sensitivity over the cortical surface in eight young adult subjects. We use the 10/5 electroencephalography system as a basis for our whole-head optical high-density probe design. The contrast-to-noise ratio (CNR) is calculated along with the percentage of the cortex that is above a CNR = 0 dB threshold. We also quantify the effect of including vasculature on the forward model and list our assumptions that allow us to estimate light penetration depth in the head. We show that using the 10/5 system for the optical probe design allows for the measurement of 37% of the cortical surface on average, with a mean CNR in the visible region of 5.5 dB. Certain anatomical regions, such as the lateral occipital cortex, had a very high percentage above the CNR threshold, while other regions such as the cingulate cortex were not measurable. Vasculature blocked optical sensitivity over 1% of the cortex. Cortical coverage was positively correlated with intracranial volume and relative cerebrospinal fluid volume, and negatively correlated with relative scalp volume and skull volume. These contributions allow experimenters to understand how anatomical variation in a subject population may impact DOT or functional near-infrared spectroscopy measurements.

Highly parallel Monte-Carlo simulations of the acousto-optic effect in heterogeneous turbid media

The development of a highly parallel simulation of the acousto-optic effect is detailed. The simulation supports optically heterogeneous simulation domains under insonification by arbitrary monochromatic ultrasound fields. An adjoint method for acousto-optics is proposed to permit point-source/point-detector simulations. The flexibility and efficiency of this simulation code is demonstrated in the development of spatial absorption sensitivity maps which are in broad agreement with current experimental investigations. The simulation code has the potential to provide guidance in the feasibility and optimization of future studies of the acousto-optic technique, and its speed may permit its use as part of an iterative inversion model.

Monte Carlo simulation of photon migration in a cloud computing environment with MapReduce

Monte Carlo simulation is considered the most reliable method for modeling photon migration in heterogeneous media. However, its widespread use is hindered by the high computational cost. The purpose of this work is to report on our implementation of a simple MapReduce method for performing fault-tolerant Monte Carlo computations in a massively-parallel cloud computing environment. We ported the MC321 Monte Carlo package to Hadoop, an open-source MapReduce framework. In this implementation, Map tasks compute photon histories in parallel while a Reduce task scores photon absorption. The distributed implementation was evaluated on a commercial compute cloud. The simulation time was found to be linearly dependent on the number of photons and inversely proportional to the number of nodes. For a cluster size of 240 nodes, the simulation of 100 billion photon histories took 22 min, a 1258 × speed-up compared to the single-threaded Monte Carlo program. The overall computational throughput was 85,178 photon histories per node per second, with a latency of 100 s. The distributed simulation produced the same output as the original implementation and was resilient to hardware failure: the correctness of the simulation was unaffected by the shutdown of 50% of the nodes.

Somatosensory activation of two fingers can be discriminated with ultrahigh-density diffuse optical tomography

Topographic non-invasive near infrared spectroscopy (NIRS) has become a well-established tool for functional brain imaging. Applying up to 100 optodes over the head of a subject, allows achieving a spatial resolution in the centimeter range. This resolution is poor compared to other functional imaging tools. However, recently it was shown that diffuse optical tomography (DOT) as an extension of NIRS based on high-density (HD) probe arrays and supplemented by an advanced image reconstruction procedure allows describing activation patterns with a spatial resolution in the millimeter range. Building on these findings, we hypothesize that HD-DOT may render very focal activations accessible which would be missed by the traditionally used sparse arrays. We examined activation patterns in the primary somatosensory cortex, since its somatotopic organization is very fine-grained. We performed a vibrotactile stimulation study of the first and fifth finger in eight human subjects, using a 900-channel continuous-wave DOT imaging system for achieving a higher resolution than conventional topographic NIRS. To compare the results to a well-established high-resolution imaging technique, the same paradigm was investigated in the same subjects by means of functional magnetic resonance imaging (fMRI). In this work, we tested the advantage of ultrahigh-density probe arrays and show that highly focal activations would be missed by classical next-nearest neighbor NIRS approach, but also by DOT, when using a sparse probe array. Distinct activation patterns for both fingers correlated well with the expected neuroanatomy in five of eight subjects. Additionally we show that activation for different fingers is projected to different tissue depths in the DOT image. Comparison to the fMRI data yielded similar activation foci in seven out of ten finger representations in these five subjects when comparing the lateral localization of DOT and fMRI results.

Online object oriented Monte Carlo computational tool for the needs of biomedical optics

Conceptual engineering design and optimization of laser-based imaging techniques and optical diagnostic systems used in the field of biomedical optics requires a clear understanding of the light-tissue interaction and peculiarities of localization of the detected optical radiation within the medium. The description of photon migration within the turbid tissue-like media is based on the concept of radiative transfer that forms a basis of Monte Carlo (MC) modeling. An opportunity of direct simulation of influence of structural variations of biological tissues on the probing light makes MC a primary tool for biomedical optics and optical engineering. Due to the diversity of optical modalities utilizing different properties of light and mechanisms of light-tissue interactions a new MC code is typically required to be developed for the particular diagnostic application. In current paper introducing an object oriented concept of MC modeling and utilizing modern web applications we present the generalized online computational tool suitable for the major applications in biophotonics. The computation is supported by NVIDEA CUDA Graphics Processing Unit providing acceleration of modeling up to 340 times.