Measurement of the absolute optical properties and cerebral blood volume of the adult human head with hybrid differential and spatially resolved spectroscopy

Toward real-time diffuse optical tomography: accelerating light propagation modeling employing parallel computing on GPU and CPU

Parameter recovery in diffuse optical tomography is a computationally expensive algorithm, especially when used for large and complex volumes, as in the case of human brain functional imaging. The modeling of light propagation, also known as the forward problem, is the computational bottleneck of the recovery algorithm, whereby the lack of a real-time solution is impeding practical and clinical applications. The objective of this work is the acceleration of the forward model, within a diffusion approximation-based finite-element modeling framework, employing parallelization to expedite the calculation of light propagation in realistic adult head models. The proposed methodology is applicable for modeling both continuous wave and frequency-domain systems with the results demonstrating a 10-fold speed increase when GPU architectures are available, while maintaining high accuracy. It is shown that, for a very high-resolution finite-element model of the adult human head with ∼600,000 nodes, consisting of heterogeneous layers, light propagation can be calculated at ∼0.25  s/excitation source.

Bundled-Optode Method in Functional Near-Infrared Spectroscopy

In this paper, a theory for detection of the absolute concentrations of oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR) from hemodynamic responses using a bundled-optode configuration in functional near-infrared spectroscopy (fNIRS) is proposed. The proposed method is then applied to the identification of two fingers (i.e., little and thumb) during their flexion and extension. This experiment involves a continuous-wave-type dual-wavelength (760 and 830 nm) fNIRS and five healthy male subjects. The active brain locations of two finger movements are identified based on the analysis of the t- and p-values of the averaged HbOs, which are quite distinctive. Our experimental results, furthermore, revealed that the hemodynamic responses of two-finger movements are different: The mean, peak, and time-to-peak of little finger movements are higher than those of thumb movements. It is noteworthy that the developed method can be extended to 3-dimensional fNIRS imaging.

Fast segmentation and high-quality three-dimensional volume mesh creation from medical images for diffuse optical tomography

Multimodal approaches that combine near-infrared (NIR) and conventional imaging modalities have been shown to improve optical parameter estimation dramatically and thus represent a prevailing trend in NIR imaging. These approaches typically involve applying anatomical templates from magnetic resonance imaging/computed tomography/ultrasound images to guide the recovery of optical parameters. However, merging these data sets using current technology requires multiple software packages, substantial expertise, significant time-commitment, and often results in unacceptably poor mesh quality for optical image reconstruction, a reality that represents a significant roadblock for translational research of multimodal NIR imaging. This work addresses these challenges directly by introducing automated digital imaging and communications in medicine image stack segmentation and a new one-click three-dimensional mesh generator optimized for multimodal NIR imaging, and combining these capabilities into a single software package (available for free download) with a streamlined workflow. Image processing time and mesh quality benchmarks were examined for four common multimodal NIR use-cases (breast, brain, pancreas, and small animal) and were compared to a commercial image processing package. Applying these tools resulted in a fivefold decrease in image processing time and 62% improvement in minimum mesh quality, in the absence of extra mesh postprocessing. These capabilities represent a significant step toward enabling translational multimodal NIR research for both expert and nonexpert users in an open-source platform.

Functional near-infrared spectroscopy for the measurement of propofol effects in conscious sedation during outpatient elective colonoscopy

Endoscopic procedures performed in the United States routinely involve the use of conscious sedation as standard of care. The use of sedation reduces patient discomfort and anxiety while improving the technical quality of the procedure, and as a result, over 98% of clinicians have adopted the practice. The tremendous benefits of sedation are offset by heightened costs, increased patient discharge time, and cardiopulmonary complication risks. The inherent liabilities of putting patients under sedation have necessitated a large number of physiological monitoring systems in order to ensure patient comfort and safety. Currently American Society of Anesthesiologist (ASA) guidelines recommend monitoring of pulse oximetry, blood pressure, heart rate, and end-tidal CO2; although important safeguards, these physiological measurements do not allow for the reliable assessment of patient sedation. Proper monitoring of patient state ensures procedure quality and patient safety; however no "gold-standard" is available to determine the depth of sedation which is comparable to the anesthesiologist's professional judgment. Developments in functional near-infrared spectroscopy (fNIRS) over the past two decades have introduced cost-effective, portable, and non-invasive neuroimaging tools which measure cortical hemodynamic activity as a correlate of neural functions. Anesthetic drugs, such as propofol, operate by suppressing cerebral metabolism. fNIRS imaging methods have the ability to detect these drug related effects as well as neuronal activity through the measurement of local cerebral hemodynamic changes. In the present study, 41 patients were continuously monitored using fNIRS while undergoing outpatient elective colonoscopy with propofol sedation. The preliminary results indicated that oxygenated hemoglobin changes in the dorsolateral prefrontal cortex, as assessed by fNIRS were correlated with changes in response to bolus infusions of propofol, whereas other standard physiological measures were not significantly associated.

Absolute measurement of cerebral optical coefficients, hemoglobin concentration and oxygen saturation in old and young adults with near-infrared spectroscopy

We present near-infrared spectroscopy measurement of absolute cerebral hemoglobin concentration and saturation in a large sample of 36 healthy elderly (mean age, 85 ± 6 years) and 19 young adults (mean age, 28 ± 4 years). Non-invasive measurements were obtained on the forehead using a commercially available multi-distance frequency-domain system and analyzed using a diffusion theory model for a semi-infinite, homogeneous medium with semi-infinite boundary conditions. Our study included repeat measurements, taken five months apart, on 16 elderly volunteers that demonstrate intra-subject reproducibility of the absolute measurements with cross-correlation coefficients of 0.9 for absorption coefficient (μa), oxy-hemoglobin concentration ([HbO2]), and total hemoglobin concentration ([HbT]), 0.7 for deoxy-hemoglobin concentration ([Hb]), 0.8 for hemoglobin oxygen saturation (StO2), and 0.7 for reduced scattering coefficient (μ's). We found significant differences between the two age groups. Compared to young subjects, elderly subjects had lower cerebral [HbO2], [Hb], [HbT], and StO2 by 10 ± 4 μM, 4 ± 3 μM, 14 ± 5 μM, and 6%±5%, respectively. Our results demonstrate the reliability and robustness of multi-distance near-infrared spectroscopy measurements based on a homogeneous model in the human forehead on a large sample of human subjects. Absolute, non-invasive optical measurements on the brain, such as those presented here, can significantly advance the development of NIRS technology as a tool for monitoring resting/basal cerebral perfusion, hemodynamics, oxygenation, and metabolism.

Assessment of the frequency-domain multi-distance method to evaluate the brain optical properties: Monte Carlo simulations from neonate to adult

The near infrared spectroscopy (NIRS) frequency-domain multi-distance (FD-MD) method allows for the estimation of optical properties in biological tissue using the phase and intensity of radiofrequency modulated light at different source-detector separations. In this study, we evaluated the accuracy of this method to retrieve the absorption coefficient of the brain at different ages. Synthetic measurements were generated with Monte Carlo simulations in magnetic resonance imaging (MRI)-based heterogeneous head models for four ages: newborn, 6 and 12 month old infants, and adult. For each age, we determined the optimal set of source-detector separations and estimated the corresponding errors. Errors arise from different origins: methodological (FD-MD) and anatomical (curvature, head size and contamination by extra-cerebral tissues). We found that the brain optical absorption could be retrieved with an error between 8-24% in neonates and infants, while the error increased to 19-44% in adults over all source-detector distances. The dominant contribution to the error was found to be the head curvature in neonates and infants, and the extra-cerebral tissues in adults.

Estimating cerebral oxygen metabolism from fMRI with a dynamic multicompartment Windkessel model

Stimulus evoked changes in cerebral blood flow, volume, and oxygenation arise from responses to underlying neuronally mediated changes in vascular tone and cerebral oxygen metabolism. There is increasing evidence that the magnitude and temporal characteristics of these evoked hemodynamic changes are additionally influenced by the local properties of the vasculature including the levels of baseline cerebral blood flow, volume, and blood oxygenation. In this work, we utilize a physiologically motivated vascular model to describe the temporal characteristics of evoked hemodynamic responses and their expected relationships to the structural and biomechanical properties of the underlying vasculature. We use this model in a temporal curve-fitting analysis of the high-temporal resolution functional MRI data to estimate the underlying cerebral vascular and metabolic responses in the brain. We present evidence for the feasibility of our model-based analysis to estimate transient changes in the cerebral metabolic rate of oxygen (CMRO(2)) in the human motor cortex from combined pulsed arterial spin labeling (ASL) and blood oxygen level dependent (BOLD) MRI. We examine both the numerical characteristics of this model and present experimental evidence to support this model by examining concurrently measured ASL, BOLD, and near-infrared spectroscopy to validate the calculated changes in underlying CMRO(2).

Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction

Diffuse optical tomography, also known as near infrared tomography, has been under investigation, for non-invasive functional imaging of tissue, specifically for the detection and characterization of breast cancer or other soft tissue lesions. Much work has been carried out for accurate modeling and image reconstruction from clinical data. NIRFAST, a modeling and image reconstruction package has been developed, which is capable of single wavelength and multi-wavelength optical or functional imaging from measured data. The theory behind the modeling techniques as well as the image reconstruction algorithms is presented here, and 2D and 3D examples are presented to demonstrate its capabilities. The results show that 3D modeling can be combined with measured data from multiple wavelengths to reconstruct chromophore concentrations within the tissue. Additionally it is possible to recover scattering spectra, resulting from the dominant Mie-type scatter present in tissue. Overall, this paper gives a comprehensive over view of the modeling techniques used in diffuse optical tomographic imaging, in the context of NIRFAST software package.

Progress of near-infrared spectroscopy and topography for brain and muscle clinical applications

This review celebrates the 30th anniversary of the first in vivo near-infrared (NIR) spectroscopy (NIRS) publication, which was authored by Professor Frans Jobsis. At first, NIRS was utilized to experimentally and clinically investigate cerebral oxygenation. Later it was applied to study muscle oxidative metabolism. Since 1993, the discovery that the functional activation of the human cerebral cortex can be explored by NIRS has added a new dimension to the research. To obtain simultaneous multiple and localized information, a further major step forward was achieved by introducing NIR imaging (NIRI) and tomography. This review reports on the progress of the NIRS and NIRI instrumentation for brain and muscle clinical applications 30 years after the discovery of in vivo NIRS. The review summarizes the measurable parameters in relation to the different techniques, the main characteristics of the prototypes under development, and the present commercially available NIRS and NIRI instrumentation. Moreover, it discusses strengths and limitations and gives an outlook into the "bright" future.