Practical and adequate approach to modeling light propagation in an adult head with low-scattering regions by use of diffusion theory

Diffuse Optical Tomography Using fNIRS Signals Measured from the Skull Surface of the Macaque Monkey

Diffuse optical tomography (DOT), as a functional near-infrared spectroscopy (fNIRS) technique, can estimate three-dimensional (3D) images of the functional hemodynamic response in brain volume from measured optical signals. In this study, we applied DOT algorithms to the fNIRS data recorded from the surface of macaque monkeys’ skulls when the animals performed food retrieval tasks using either the left- or right-hand under head-free conditions. The hemodynamic response images, reconstructed by DOT with a high sampling rate and fine voxel size, demonstrated significant activations at the upper limb regions of the primary motor area in the central sulcus and premotor, and parietal areas contralateral to the hands used in the tasks. The results were also reliable in terms of consistency across different recording dates. Time-series analyses of each brain area revealed preceding activity of premotor area to primary motor area consistent with previous physiological studies. Therefore, the fNIRS–DOT protocol demonstrated in this study provides reliable 3D functional brain images over a period of days under head-free conditions for region-of-interest–based time-series analysis.

Correlating functional near-infrared spectroscopy with underlying cortical regions of 0-, 1-, and 2-year-olds using theoretical light propagation analysis

Significance: The establishment of a light propagation analysis-based scalp-cortex correlation (SCC) between the scalp location of the source-detector (SD) pair and brain regions is essential for measuring functional brain development in the first 2 years of life using functional near-infrared spectroscopy (fNIRS). Aim: We aimed to reveal the optics-based SCC of 0-, 1-, and 2-year-olds (yo) and the suitable SD distance for this age period. Approach: Light propagation analyses using age-appropriate head models were conducted on SD pairs at 10-10 fiducial points on the scalp to obtain optics-based SCC and its metrics: the number of corresponding brain regions ( N C B R ), selectivity and sensitivity of the most likely corresponding brain region (MLCBR), and consistency of the MLCBR across developmental ages. Moreover, we assessed the suitable SD distances for 0-, 1-, and 2-yo by simultaneously considering the selectivity and sensitivity of the MLCBR. Results: Age-related changes in the SCC metrics were observed. For instance, the N C B R of 0-yo was larger than that of 1- and 2-yo. Conversely, the selectivity of 0-yo was lower than that of 1- and 2-yo. The sensitivity of 1-yo was higher than that of 0-yo at 15- to 30-mm SD distances and higher than that of 2-yo at 10-mm SD distance. Notably, the MLCBR of the fiducial points around the longitudinal fissure was inconsistent across age groups. An SD distance between 15 and 25 mm was found to be appropriate for satisfying both sensitivity and selectivity requirements. In addition, this work provides reference tables of optics-based SCC for 0-, 1-, and 2-yo. Conclusions: Optics-based SCC will be informative in designing and explaining child developmental studies using fNIRS. The suitable SD distances were between 15 and 25 mm for the first 2 years of life.

Targeting brain regions of interest in functional near-infrared spectroscopy-Scalp-cortex correlation using subject-specific light propagation models

Targeting specific brain regions of interest by the accurate positioning of optodes (emission and detection probes) on the scalp remains a challenge for functional near‐infrared spectroscopy (fNIRS). Since fNIRS data does not provide any anatomical information on the brain cortex, establishing the scalp‐cortex correlation (SCC) between emission‐detection probe pairs on the scalp and the underlying brain regions in fNIRS measurements is extremely important. A conventional SCC is obtained by a geometrical point‐to‐point manner and ignores the effect of light scattering in the head tissue that occurs in actual fNIRS measurements. Here, we developed a sensitivity‐based matching (SBM) method that incorporated the broad spatial sensitivity of the probe pair due to light scattering into the SCC for fNIRS. The SCC was analyzed between head surface fiducial points determined by the international 10–10 system and automated anatomical labeling brain regions for 45 subject‐specific head models. The performance of the SBM method was compared with that of three conventional geometrical matching (GM) methods. We reveal that the light scattering and individual anatomical differences in the head affect the SCC, which indicates that the SBM method is compulsory to obtain the precise SCC. The SBM method enables us to evaluate the activity of cortical regions that are overlooked in the SCC obtained by conventional GM methods. Together, the SBM method could be a promising approach to guide fNIRS users in designing their probe arrangements and in explaining their measurement data.

Exclusive detection of cerebral hemodynamics in functional near-infrared spectroscopy by reflectance modulation of the scalp surface

SIGNIFICANCE

Functional near-infrared spectroscopy (fNIRS) is a technique for detecting regional hemodynamic responses associated with neural activation in the cerebral cortex. The absorption changes due to hemodynamic changes in the scalp cause considerable signal contamination in the fNIRS measurement. A method for extracting hemodynamic changes in the cerebral tissue is required for reliable fNIRS measurement.

AIM

To exclusively detect cerebral functional hemodynamic changes, we developed an fNIRS technique using reflectance modulation of the scalp surface.

APPROACH

The theoretical feasibility of the proposed method was proven by a simulation calculation of light propagation. Its practical feasibility was evaluated by a phantom experiment and brain activation simulation mimicking human fNIRS experiments.

RESULTS

The simulation calculation revealed that the partial path length of the scalp was changed by reflectance modulation of the scalp surface. The influence of absorption change in the superficial layer was successfully reduced by the proposed method, using only measurement data, in the phantom experiment. The proposed method was applicable to human experiments of standard designs, achieving statistical significance within an acceptable experimental time-frame.

CONCLUSIONS

Removal of the scalp hemodynamic effect by the proposed technique will increase the quality of fNIRS data, particularly in measurements in neonates and infants that typically would require a dense optode arrangement.

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.

Simulation of near-infrared light absorption considering individual head and prefrontal cortex anatomy: implications for optical neuroimaging

Functional near-infrared spectroscopy (fNIRS) is an established optical neuroimaging method for measuring functional hemodynamic responses to infer neural activation. However, the impact of individual anatomy on the sensitivity of fNIRS measuring hemodynamics within cortical gray matter is still unknown. By means of Monte Carlo simulations and structural MRI of 23 healthy subjects (mean age: 25.0±2.8 years), we characterized the individual distribution of tissue-specific NIR-light absorption underneath 24 prefrontal fNIRS channels. We, thereby, investigated the impact of scalp-cortex distance (SCD), frontal sinus volume as well as sulcal morphology on gray matter volumes (V(gray)) traversed by NIR-light, i.e. anatomy-dependent fNIRS sensitivity. The NIR-light absorption between optodes was distributed describing a rotational ellipsoid with a mean penetration depth of (23.6±0.7) mm considering the deepest 5% of light. Of the detected photon packages scalp and bone absorbed (96.4±9.7)% and V(gray) absorbed (3.1±1.8)% of the energy. The mean V(gray) volume (1.1±0.4) cm3 was negatively correlated (r=-.76) with the SCD and frontal sinus volume (r=-.57) and was reduced by 41.5% in subjects with relatively large compared to small frontal sinus. Head circumference was significantly positively correlated with the mean SCD (r=.46) and the traversed frontal sinus volume (r=.43). Sulcal morphology had no significant impact on V(gray). Our findings suggest to consider individual SCD and frontal sinus volume as anatomical factors impacting fNIRS sensitivity. Head circumference may represent a practical measure to partly control for these sources of error variance.

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.

Recording invertebrate nerve activation with modulated light changes

Optical scattering techniques have the potential to provide noninvasive measurements of neural activity with good spatial and temporal resolution. We used the lobster nerve as a model system to investigate and record event-related optical signals with a modulated light source and heterodyne detection system. We observed changes in the transmitted birefringent light intensity, corresponding with electrophysiological measurements of the action potential. The photon delay was below the detection threshold, in part due to the small size of the nerve bundle. Our system allowed us to place an upper bound on the magnitude of the phase change of 0.01 degrees. The physiological stability of the preparation allows comprehensive characterization of biological and instrumentation noise sources for testing optical measurement systems.

Effect of probe arrangement on reproducibility of images by near-infrared topography evaluated by a virtual head phantom

The effect of the probe arrangement on the reproducibility of topographic images of the concentration changes in oxygenated hemoglobin and deoxygenated hemoglobin is evaluated by a virtual head phantom. A virtual head phantom consists of five types of tissue the 3D structure of which is based on a magnetic resonance imaging scan of an adult head. Localized and broadened brain activation is assumed in a virtual head phantom. The topographic images are obtained from the reflectance detected by the standard probe arrangement and the double-density probe arrangement. The uneven thickness of the superficial layer, which cannot be evaluated by the previous slab model, affects the distribution of measured activation in the topographic image, and this reduces the position reproducibility of near-infrared (NIR) topography with the standard probe arrangement. The overlapping measurements by the double-density probe arrangement can improve the reproducibility of the image obtained by NIR topography.

Effective scattering coefficient of the cerebral spinal fluid in adult head models for diffuse optical imaging

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.

Dynamic physiological modeling for functional diffuse optical tomography

Diffuse optical tomography (DOT) is a noninvasive imaging technology that is sensitive to local concentration changes in oxy- and deoxyhemoglobin. When applied to functional neuroimaging, DOT measures hemodynamics in the scalp and brain that reflect competing metabolic demands and cardiovascular dynamics. The diffuse nature of near-infrared photon migration in tissue and the multitude of physiological systems that affect hemodynamics motivate the use of anatomical and physiological models to improve estimates of the functional hemodynamic response. In this paper, we present a linear state-space model for DOT analysis that models the physiological fluctuations present in the data with either static or dynamic estimation. We demonstrate the approach by using auxiliary measurements of blood pressure variability and heart rate variability as inputs to model the background physiology in DOT data. We evaluate the improvements accorded by modeling this physiology on ten human subjects with simulated functional hemodynamic responses added to the baseline physiology. Adding physiological modeling with a static estimator significantly improved estimates of the simulated functional response, and further significant improvements were achieved with a dynamic Kalman filter estimator (paired t tests, n=10, P<0.05). These results suggest that physiological modeling can improve DOT analysis. The further improvement with the Kalman filter encourages continued research into dynamic linear modeling of the physiology present in DOT. Cardiovascular dynamics also affect the blood-oxygen-dependent (BOLD) signal in functional magnetic resonance imaging (fMRI). This state-space approach to DOT analysis could be extended to BOLD fMRI analysis, multimodal studies and real-time analysis.