Image correction algorithm for functional three-dimensional diffuse optical tomography brain imaging

Nonlinear approach to difference imaging in diffuse optical tomography

Difference imaging aims at recovery of the change in the optical properties of a body based on measurements before and after the change. Conventionally, the image reconstruction is based on using difference of the measurements and a linear approximation of the observation model. One of the main benefits of the linearized difference reconstruction is that the approach has a good tolerance to modeling errors, which cancel out partially in the subtraction of the measurements. However, a drawback of the approach is that the difference images are usually only qualitative in nature and their spatial resolution can be weak because they rely on the global linearization of the nonlinear observation model. To overcome the limitations of the linear approach, we investigate a nonlinear approach for difference imaging where the images of the optical parameters before and after the change are reconstructed simultaneously based on the two datasets. We tested the feasibility of the method with simulations and experimental data from a phantom and studied how the approach tolerates modeling errors like domain truncation, optode coupling errors, and domain shape errors.

Feasibility of near-infrared spectroscopic tomography for intraoperative functional cerebral monitoring: a primate study

OBJECTIVE

The wide-ranging manipulations to the cardiovascular system that frequently occur during cardiac surgery can expose the brain to variations in its blood supply that could prove deleterious. As a first step to developing a resource suitable for monitoring such changes, we detected the hemodynamic events induced in the brain of a primate model, using high-density near-infrared spectroscopy combined with tomographic reconstruction methods and validated the findings using established radiologic and histologic techniques.

METHODS

Continuous monitoring of the relative changes in the components of the cerebral hemoglobin signal was performed using high-density near-infrared spectroscopy (270 source-detector channel array) in anesthetized bonnet macaques with the brain exposed to induced ischemia and other acute events. A comparative analysis (exact binomial test) applied to reconstructed 3-dimensional images before and after the events and between cerebral hemispheres, combined with postprocedure magnetic resonance imaging, and postmortem histopathologic examination of the macaques' brains was performed to document and validate the spatial features revealed by the optical findings.

RESULTS

Relative changes in the measured and calculated components of the hemoglobin signal, in response to the performed manipulations, revealed substantial concurrence among the reconstructed 3-dimensional images, magnetic resonance imaging of the macaques' brains, and postmortem histopathologic examination findings. Concurrence was seen when the manipulated hemoglobin concentration and associated oxygenation levels were either increased or decreased, and whether they were bilateral or restricted to a specified hemisphere.

CONCLUSIONS

Continuous near-infrared spectroscopy tomography has been shown to accurately capture and localize cerebral ischemia, vasodilatation, and hemorrhage in primates in real time. These findings are directly applicable to clinical intraoperative functional cerebral monitoring.

Brain structure and spatial sensitivity profile assessing by near-infrared spectroscopy modeling based on 3D MRI data

The goal of this study is to prove that the light propagation in the head by used the 3-D optical model from in vivo MRI data set can also provide significant characteristics on the spatial sensitivity of cerebral cortex folding geometry based on Monte Carlo simulation. Thus, we proposed a MRI based approach for 3-D brain modeling of near-infrared spectroscopy (NIRS). In the results, the spatial sensitivity profile of the cerebral cortex folding geometry and the arrangement of source-detector separation have being necessarily considered for applications of functional NIRS. The optimal choice of source-detector separation is suggested within 3-3.5 cm by the received intensity with different source-detector separations and the ratio of received light from the gray and white matter layer is greater than 50%. Additionally, this study has demonstrated the capability of NIRS in not only assessing the functional but also detecting the structural change of the brain by taking advantage of the low scattering and absorption coefficients observed in CSF of sagittal view.

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

Background

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

Methods

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

Results

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

Conclusions

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

Spatiotemporal relations of primary sensorimotor and secondary motor activation patterns mapped by NIR imaging

Functional near infrared (fNIR) imaging was used to identify spatiotemporal relations between spatially distinct cortical regions activated during various hand and arm motion protocols. Imaging was performed over a field of view (FOV, 12 x 8.4 cm) including the secondary motor, primary sensorimotor, and the posterior parietal cortices over a single brain hemisphere. This is a more extended FOV than typically used in current fNIR studies. Three subjects performed four motor tasks that induced activation over this extended FOV. The tasks included card flipping (pronation and supination) that, to our knowledge, has not been performed in previous functional magnetic resonance imaging (fMRI) or fNIR studies. An earlier rise and a longer duration of the hemodynamic activation response were found in tasks requiring increased physical or mental effort. Additionally, analysis of activation images by cluster component analysis (CCA) demonstrated that cortical regions can be grouped into clusters, which can be adjacent or distant from each other, that have similar temporal activation patterns depending on whether the performed motor task is guided by visual or tactile feedback. These analyses highlight the future potential of fNIR imaging to tackle clinically relevant questions regarding the spatiotemporal relations between different sensorimotor cortex regions, e.g. ones involved in the rehabilitation response to motor impairments.

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.

Measurement of layer-like hemodynamic trends in scalp and cortex: implications for physiological baseline suppression in functional near-infrared spectroscopy

A multidetector, continuous wave, near-infrared spectroscopy (NIRS) system is developed to examine whether the hemodynamics of the scalp and brain in adults contain significant layer-like hemodynamic trends. NIRS measurements are made using contrasting geometries, one with four detectors equidistant from a source 33 mm away, and one with detectors collinear with the source (5 to 33 mm away). When NIRS time series are acquired over the prefrontal cortex from resting adults using both geometries, variations among the time series are consistent with a substantially homogeneous two-layer model (p<0.001) and inconsistent with one dominated by heterogeneities. Additionally, when time series measured 5 mm from the source are subtracted from corresponding 33-mm signals via a least-squares algorithm, 60% of the hemoglobin changes are on average removed. These results suggest that hemodynamic trends present in the scalp can contribute significantly to NIRS measurements, and that attempts to reduce this noise by subtracting a simultaneous near-channel measurement using a two-layer model are justified. Such subtractions are then performed on NIRS measurements from two stimulus protocols. For systemic stimulations (Valsalva maneuver), the subtraction cancels the hemodynamic response, as desired. For localized stimulation of the occipital lobe (viewing a flickering pattern), the subtraction isolated a stimulus-correlated hemodynamic feature from background noise.

Multipixel system for gigahertz frequency-domain optical imaging of finger joints

Frequency-domain optical imaging systems have shown great promise for characterizing blood oxygenation, hemodynamics, and other physiological parameters in human and animal tissues. However, most of the frequency domain systems presented so far operate with source modulation frequencies below 150 MHz. At these low frequencies, their ability to provide accurate data for small tissue geometries such as encountered in imaging of finger joints or rodents is limited. Here, we present a new system that can provide data up to 1 GHz using an intensity modulated charged coupled device camera. After data processing, the images show the two-dimensional distribution of amplitude and phase of the light modulation on the finger surface. The system performance was investigated and test measurements on optical tissue phantoms were taken to investigate whether higher frequencies yield better signal-to-noise ratios (SNRs). It could be shown that local changes in optical tissue properties, as they appear in the initial stages of rheumatoid arthritis in a finger joint, are detectable by simple image evaluation, with the range of modulation frequency around 500 MHz proving to yield the highest SNR.

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.