Influence of Systematic Errors in Reference States on Image Quality and on Stability of Derived Information for dc Optical Imaging

Hemoglobin signal network mapping reveals novel indicators for precision medicine

Precision medicine currently relies on a mix of deep phenotyping strategies to guide more individualized healthcare. Despite being widely available and information-rich, physiological time-series measures are often overlooked as a resource to extend insights gained from such measures. Here we have explored resting-state hemoglobin measures applied to intact whole breasts for two subject groups - women with confirmed breast cancer and control subjects - with the goal of achieving a more detailed assessment of the cancer phenotype from a non-invasive measure. Invoked is a novel ordinal partition network method applied to multivariate measures that generates a Markov chain, thereby providing access to quantitative descriptions of short-term dynamics in the form of several classes of adjacency matrices. Exploration of these and their associated co-dependent behaviors unexpectedly reveals features of structured dynamics, some of which are shown to exhibit enzyme-like behaviors and sensitivity to recognized molecular markers of disease. Thus, findings obtained strongly indicate that despite the use of a macroscale sensing method, features more typical of molecular-cellular processes can be identified. Discussed are factors unique to our approach that favor a deeper depiction of tissue phenotypes, its extension to other forms of physiological time-series measures, and its expected utility to advance goals of precision medicine.

Diffuse optical tomography in the human brain: A briefly review from the neurophysiology to its applications

The present work describes the use of noninvasive diffuse optical tomography (DOT) technology to measure hemodynamic changes, providing relevant information which helps to understand the basis of neurophysiology in the human brain. Advantages such as portability, direct measurements of hemoglobin state, temporal resolution, non‐restricted movements as occurs in magnetic resonance imaging (MRI) devices mean that DOT technology can be used in research and clinical fields. In this review we covered the neurophysiology, physical principles underlying optical imaging during tissue‐light interactions, and technology commonly used during the construction of a DOT device including the source‐detector requirements to improve the image quality. DOT provides 3D cerebral activation images due to complex mathematical models which describe the light propagation inside the tissue head. Moreover, we describe briefly the use of Bayesian methods for raw DOT data filtering as an alternative to linear filters widely used in signal processing, avoiding common problems such as the filter selection or a false interpretation of the results which is sometimes due to the interference of background physiological noise with neural activity.

Diffuse optical tomography to measure functional changes during motor tasks: a motor imagery study

The present work shows the spatial reliability of the diffuse optical tomography (DOT) system in a group of healthy subjects during a motor imagery task. Prior to imagery task performance, the subjects executed a motor task based on the finger to thumb opposition for motor training, and to corroborate the DOT spatial localization during the motor execution. DOT technology and data treatment allows us to distinguish oxy- and deoxyhemoglobin at the cerebral gyri level unlike the cerebral activations provided by fMRI series that were processed using different approaches. Here we show the DOT reliability showing functional activations at the cerebral gyri level during motor execution and motor imagery, which provide subtler cerebral activations than the motor execution. These results will allow the use of the DOT system as a monitoring device in a brain computer interface.

Mechanical and hemodynamic responses of breast tissue under mammographic-like compression during functional dynamic optical imaging

Studying tissue hemodynamics following breast compression has the potential to reveal new contrast mechanisms for evaluating breast cancer. However, how compression will be distributed and, consequently, how hemodynamics will be altered inside the compressed breast remain unclear. To explore the effect of compression, 12 healthy volunteers were studied by applying a step compression increase (4.5-53.4 N) using an optical imaging system capable of concurrently measuring pressure distribution and hemodynamic responses. Finite element analysis was used to predict the distribution of internal fluid pressure (IFP) in breast models. Comparisons between the measured pressure distribution and the reconstructed hemodynamic images for the healthy volunteers indicated significant (p < 0.05) negative correlations. The findings from a breast cancer patient showed that IFP distribution during compression strongly correlates with the observed differential hemodynamic images. We concluded that dynamic breast compression results in non-uniform internal pressure distribution throughout the breast that could potentially drive directed blood flow. The encouraging results obtained highlight the promise of developing dynamic optical imaging biomarkers for breast cancer by interpreting differential hemodynamic images of breast tissue during compression in the context of measured pressure distribution and predicted IFP.

Is it possible to measure hemodynamic changes in the prefrontal cortex through the frontal sinus using continuous wave DOT systems?

The present work shows the capability of near infrared (NIR) light to reach the cerebral cortex through the frontal sinus using continuous-wave techniques (CW-DOT) in a dual study. On the one hand, changes in time during the tracking of a blood dye in the prefrontal cortex were monitored. On the other hand, hemodynamic changes induced by low frequency of transcranial magnetic stimulation applied on the prefrontal cortex were recorded. The results show how NIR light projected through the frontal sinus reaches the cerebral cortex target, providing enough information to have a reliable measurement of cortical hemodynamic changes using CW-DOT.

Hemoglobin state-flux: A finite-state model representation of the hemoglobin signal for evaluation of the resting state and the influence of disease

SUMMARY

In this report we introduce a weak-model approach for examination of the intrinsic time-varying properties of the hemoglobin signal, with the aim of advancing the application of functional near infrared spectroscopy (fNIRS) for the detection of breast cancer, among other potential uses. The developed methodology integrates concepts from stochastic network theory with known modulatory features of the vascular bed, and in doing so provides access to a previously unrecognized dense feature space that is shown to have promising diagnostic potential. Notable features of the methodology include access to this information solely from measures acquired in the resting state, and analysis of these by treating the various components of the hemoglobin (Hb) signal as a co-varying interacting system.

APPROACH

The principal data-transform kernel projects Hb state-space trajectories onto a coordinate system that constitutes a finite-state representation of covariations among the principal elements of the Hb signal (i.e., its oxygenated (ΔoxyHb) and deoxygenated (ΔdeoxyHb) forms and the associated dependent quantities: total hemoglobin (ΔtotalHb = ΔoxyHb + ΔdeoxyHb), hemoglobin oxygen saturation (ΔHbO2Sat = 100Δ(oxyHb/totalHb)), and tissue-hemoglobin oxygen exchange (ΔHbO2Exc = ΔdeoxyHb-ΔoxyHb)). The resulting ten-state representation treats the evolution of this signal as a one-space, spatiotemporal network that undergoes transitions from one state to another. States of the network are defined by the algebraic signs of the amplitudes of the time-varying components of the Hb signal relative to their temporal mean values. This assignment produces several classes of coefficient arrays, most with a dimension of 10×10.

BIOLOGICAL MOTIVATION

Motivating our approach is the understanding that effector mechanisms that modulate blood delivery to tissue operate on macroscopic scales, in a spatially and temporally varying manner. Also recognized is that this behavior is sensitive to nonlinear actions of these effectors, which include the binding properties of hemoglobin. Accessible phenomenology includes measures of the kinetics and probabilities of network dynamics, which we treat as surrogates for the actions of feedback mechanisms that modulate tissue-vascular coupling.

FINDINGS

Qualitative and quantitative features of this space, and their potential to serve as markers of disease, have been explored by examining continuous-wave fNIRS 3D tomographic time series obtained from the breasts of women who do and do not have breast cancer. Inspection of the coefficient arrays reveals that they are governed predominantly by first-order rate processes, and that each array class exhibits preferred structure that is mainly independent of the others. Discussed are strategies that may serve to extend evaluation of the accessible feature space and how the character of this information holds potential for development of novel clinical and preclinical uses.

Comparing diffuse optical tomography and functional magnetic resonance imaging signals during a cognitive task: pilot study

Diffuse optical tomography (DOT) measures concentration changes in both oxy- and deoxyhemoglobin providing three-dimensional images of local brain activations. A pilot study, which compares both DOT and functional magnetic resonance imaging (fMRI) volumes through t-maps given by canonical statistical parametric mapping (SPM) processing for both data modalities, is presented. The DOT series were processed using a method that is based on a Bayesian filter application on raw DOT data to remove physiological changes and minimum description length application index to select a number of singular values, which reduce the data dimensionality during image reconstruction and adaptation of DOT volume series to normalized standard space. Therefore, statistical analysis is performed with canonical SPM software in the same way as fMRI analysis is done, accepting DOT volumes as if they were fMRI volumes. The results show the reproducibility and ruggedness of the method to process DOT series on group analysis using cognitive paradigms on the prefrontal cortex. Difficulties such as the fact that scalp-brain distances vary between subjects or cerebral activations are difficult to reproduce due to strategies used by the subjects to solve arithmetic problems are considered. T-images given by fMRI and DOT volume series analyzed in SPM show that at the functional level, both DOT and fMRI measures detect the same areas, although DOT provides complementary information to fMRI signals about cerebral activity.

Enhanced resting-state dynamics of the hemoglobin signal as a novel biomarker for detection of breast cancer

PURPOSE

The work presented here demonstrates an application of diffuse optical tomography (DOT) to the problem of breast-cancer diagnosis. The potential for using spatial and temporal variability measures of the hemoglobin signal to identify useful biomarkers was studied.

METHODS

DOT imaging data were collected using two instrumentation platforms the authors developed, which were suitable for exploring tissue dynamics while performing a simultaneous bilateral exam. For each component of the hemoglobin signal (e.g., total, oxygenated), the image time series was reduced to eight scalar metrics that were affected by one or more dynamic properties of the breast microvasculature (e.g., average amplitude, amplitude heterogeneity, strength of spatial coordination). Receiver-operator characteristic (ROC) analyses, comparing groups of subjects with breast cancer to various control groups (i.e., all noncancer subjects, only those with diagnosed benign breast pathology, and only those with no known breast pathology), were performed to evaluate the effect of cancer on the magnitudes of the metrics and of their interbreast differences and ratios.

RESULTS

For women with known breast cancer, simultaneous bilateral DOT breast measures reveal a marked increase in the resting-state amplitude of the vasomotor response in the hemoglobin signal for the affected breast, compared to the contralateral, noncancer breast. Reconstructed 3D spatial maps of observed dynamics also show that this behavior extends well beyond the tumor border. In an effort to identify biomarkers that have the potential to support clinical aims, a group of scalar quantities extracted from the time series measures was systematically examined. This analysis showed that many of the quantities obtained by computing paired responses from the bilateral scans (e.g., interbreast differences, ratios) reveal statistically significant differences between the cancer-positive and -negative subject groups, while the corresponding measures derived from individual breast scans do not. ROC analyses yield area-under-curve values in the 77%-87% range, depending on the metric, with sensitivity and specificity values ranging from 66% to 91%. An interesting result is the initially unexpected finding that the hemodynamic-image metrics are only weakly dependent on the tumor burden, implying that the DOT technique employed is sensitive to tumor-induced changes in the vascular dynamics of the surrounding breast tissue as well. Computational modeling studies serve to identify which properties of the vasomotor response (e.g., average amplitude, amplitude heterogeneity, and phase heterogeneity) principally determine the values of the metrics and their codependences. Findings from the modeling studies also serve to clarify the influence of spatial-response heterogeneity and of system-design limitations, and they reveal the impact that a complex dependence of metric values on the modeled behaviors has on the success in distinguishing between cancer-positive and -negative subjects.

CONCLUSIONS

The authors identified promising hemoglobin-based biomarkers for breast cancer from measures of the resting-state dynamics of the vascular bed. A notable feature of these biomarkers is that their spatial extent encompasses a large fraction of the breast volume, which is mainly independent of tumor size. Tumor-induced induction of nitric oxide synthesis, a well-established concomitant of many breast cancers, is offered as a plausible biological causal factor for the reported findings.

Reproducibility of parameters of postocclusive reactive hyperemia measured by diffuse optical tomography

The application of near-infrared spectroscopy (NIRS) to assess microvascular function has shown promising results. An important limitation when using a single source-detector pair, however, is the lack of depth sensitivity. Diffuse optical tomography (DOT) overcomes this limitation using an array of sources and detectors that allow the reconstruction of volumetric hemodynamic changes. This study compares the key parameters of postocclusive reactive hyperemia measured in the forearm using standard NIRS and DOT. We show that while the mean parameter values are similar for the two techniques, DOT achieves much better reproducibility, as measured by the intraclass correlation coefficient (ICC). We show that DOT achieves high reproducibility for muscle oxygen consumption (ICC: 0.99), time to maximal HbO2 (ICC: 0.94), maximal HbO2 (ICC: 0.99), and time to maximal HbT (ICC: 0.99). Absolute reproducibility as measured by the standard error of measurement is consistently smaller and close to zero (ideal value) across all parameters measured by DOT compared to NIRS. We conclude that DOT provides a more robust characterization of the reactive hyperemic response and show how the availability of volumetric hemodynamic changes allows the identification of areas of temporal consistency, which could help characterize more precisely the microvasculature.

Hemodynamic correlates of spontaneous neural activity measured by human whole-head resting state EEG+fNIRS

The brains of awake, resting human subjects display spontaneously occurring neural activity patterns whose magnitude is typically many times greater than those triggered by cognitive or perceptual performance. Evoked and resting state activations affect local cerebral hemodynamic properties through processes collectively referred to as neurovascular coupling. Its investigation calls for an ability to track both the neural and vascular aspects of brain function. We used scalp electroencephalography (EEG), which provided a measure of the electrical potentials generated by cortical postsynaptic currents. Simultaneously we utilized functional near-infrared spectroscopy (NIRS) to continuously monitor hemoglobin concentration changes in superficial cortical layers. The multi-modal signal from 18 healthy adult subjects allowed us to investigate the association of neural activity in a range of frequencies over the whole-head to local changes in hemoglobin concentrations. Our results verified the delayed alpha (8-16Hz) modulation of hemodynamics in posterior areas known from the literature. They also indicated strong beta (16-32Hz) modulation of hemodynamics. Analysis revealed, however, that beta modulation was likely generated by the alpha-beta coupling in EEG. Signals from the inferior electrode sites were dominated by scalp muscle related activity. Our study aimed to characterize the phenomena related to neurovascular coupling observable by practical, cost-effective, and non-invasive multi-modal techniques.

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.

Quantitative evaluation of atlas-based high-density diffuse optical tomography for imaging of the human visual cortex

Image recovery in diffuse optical tomography (DOT) of the human brain often relies on accurate models of light propagation within the head. In the absence of subject specific models for image reconstruction, the use of atlas based models are showing strong promise. Although there exists some understanding in the use of some limited rigid model registrations in DOT, there has been a lack of a detailed analysis between errors in geometrical accuracy, light propagation in tissue and subsequent errors in dynamic imaging of recovered focal activations in the brain. In this work 11 different rigid registration algorithms, across 24 simulated subjects, are evaluated for DOT studies in the visual cortex. Although there exists a strong correlation (R(2) = 0.97) between geometrical surface error and internal light propagation errors, the overall variation is minimal when analysing recovered focal activations in the visual cortex. While a subject specific mesh gives the best results with a 1.2 mm average location error, no single algorithm provides errors greater than 4.5 mm. This work demonstrates that the use of rigid algorithms for atlas based imaging is a promising route when subject specific models are not available.

A programmable laboratory testbed in support of evaluation of functional brain activation and connectivity

An important determinant of the value of quantitative neuroimaging studies is the reliability of the derived information, which is a function of the data collection conditions. Near infrared spectroscopy (NIRS) and electroencelphalography are independent sensing domains that are well suited to explore principal elements of the brain's response to neuroactivation, and whose integration supports development of compact, even wearable, systems suitable for use in open environments. In an effort to maximize the translatability and utility of such resources, we have established an experimental laboratory testbed that supports measures and analysis of simulated macroscopic bioelectric and hemodynamic responses of the brain. Principal elements of the testbed include 1) a programmable anthropomorphic head phantom containing a multisignal source array embedded within a matrix that approximates the background optical and bioelectric properties of the brain, 2) integrated translatable headgear that support multimodal studies, and 3) an integrated data analysis environment that supports anatomically based mapping of experiment-derived measures that are directly and not directly observable. Here, we present a description of system components and fabrication, an overview of the analysis environment, and findings from a representative study that document the ability to experimentally validate effective connectivity models based on NIRS tomography.

Optomechanical imaging system for breast cancer detection

Imaging studies of the breast comprise three principal sensing domains: structural, mechanical, and functional. Combinations of these domains can yield either additive or wholly new information, depending on whether one domain interacts with the other. In this report, we describe a new approach to breast imaging based on the interaction between controlled applied mechanical force and tissue hemodynamics. Presented is a description of the system design, performance characteristics, and representative clinical findings for a second-generation dynamic near-infrared optical tomographic breast imager that examines both breasts simultaneously, under conditions of rest and controlled mechanical provocation. The expected capabilities and limitations of the developed system are described in relation to the various sensing domains for breast imaging.

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.

Contrast enhanced high-resolution diffuse optical tomography of the human brain using ICG

Non-invasive diffuse optical tomography (DOT) of the adult brain has recently been shown to improve the spatial resolution for functional brain imaging applications. Here we show that high-resolution (HR) DOT is also advantageous for clinical perfusion imaging using an optical contrast agent. We present the first HR-DOT results with a continuous wave near infrared spectroscopy setup using a dense grid of optical fibers and indocyanine green (ICG) as an exogenic contrast agent. We find an early arrival of the ICG bolus in the intracerebral tissue and a delayed arrival of the bolus in the extracerebral tissue, achieving the separation of both layers. This demonstrates the method's potential for brain perfusion monitoring in neurointensive care patients.

Digital optical tomography system for dynamic breast imaging

Diffuse optical tomography has shown promising results as a tool for breast cancer screening and monitoring response to chemotherapy. Dynamic imaging of the transient response of the breast to an external stimulus, such as pressure or a respiratory maneuver, can provide additional information that can be used to detect tumors. We present a new digital continuous-wave optical tomography system designed to simultaneously image both breasts at fast frame rates and with a large number of sources and detectors. The system uses a master-slave digital signal processor-based detection architecture to achieve a dynamic range of 160 dB and a frame rate of 1.7 Hz with 32 sources, 64 detectors, and 4 wavelengths per breast. Included is a preliminary study of one healthy patient and two breast cancer patients showing the ability to identify an invasive carcinoma based on the hemodynamic response to a breath hold.

PDE-constrained multispectral imaging of tissue chromophores with the equation of radiative transfer

We introduce a transport-theory-based PDE-constrained multispectral model for direct imaging of the spatial distributions of chromophores concentrations in biological tissue. The method solves the forward problem (boundary radiance at each wavelength) and the inverse problem (spatial distribution of chromophores concentrations), in an all-at-once manner in the framework of a reduced Hessian sequential quadratic programming method. To illustrate the code's performance, we present numerical and experimental studies involving tumor bearing mice. It is shown that the PDE-constrained multispectral method accelerates the reconstruction process by up to 15 times compared to unconstrained reconstruction algorithms and provides more accurate results as compared to the so-called two-step approach to multi-wavelength imaging.

Diffuse Optics for Tissue Monitoring and Tomography

This review describes the diffusion model for light transport in tissues and the medical applications of diffuse light. Diffuse optics is particularly useful for measurement of tissue hemodynamics, wherein quantitative assessment of oxy- and deoxy-hemoglobin concentrations and blood flow are desired. The theoretical basis for near-infrared or diffuse optical spectroscopy (NIRS or DOS, respectively) is developed, and the basic elements of diffuse optical tomography (DOT) are outlined. We also discuss diffuse correlation spectroscopy (DCS), a technique whereby temporal correlation functions of diffusing light are transported through tissue and are used to measure blood flow. Essential instrumentation is described, and representative brain and breast functional imaging and monitoring results illustrate the workings of these new tissue diagnostics.

High-resolution optical functional mapping of the human somatosensory cortex

Non-invasive optical imaging of brain function has been promoted in a number of fields in which functional magnetic resonance imaging (fMRI) is limited due to constraints induced by the scanning environment. Beyond physiological and psychological research, bedside monitoring and neurorehabilitation may be relevant clinical applications that are yet little explored. A major obstacle to advocate the tool in clinical research is insufficient spatial resolution. Based on a multi-distance high-density optical imaging setup, we here demonstrate a dramatic increase in sensitivity of the method. We show that optical imaging allows for the differentiation between activations of single finger representations in the primary somatosensory cortex (SI). Methodologically our findings confirm results in a pioneering study by Zeff et al. (2007) and extend them to the homuncular organization of SI. After performing a motor task, eight subjects underwent vibrotactile stimulation of the little finger and the thumb. We used a high-density diffuse-optical sensing array in conjunction with optical tomographic reconstruction. Optical imaging disclosed three discrete activation foci one for motor and two discrete foci for vibrotactile stimulation of the first and fifth finger, respectively. The results were co-registered to the individual anatomical brain anatomy (MRI) which confirmed the localization in the expected cortical gyri in four subjects. This advance in spatial resolution opens new perspectives to apply optical imaging in the research on plasticity notably in patients undergoing neurorehabilitation.

Using co-variations in the Hb signal to detect visual activation: a near infrared spectroscopic imaging study

The premise of this report is that functional Near Infrared Spectroscopy (fNIRS) imaging data contain valuable physiological information that can be extracted by using analysis techniques that simultaneously consider the components of the measured hemodynamic response [i.e., levels of oxygenated, deoxygenated and total hemoglobin (oxyHb, deoxyHb and totalHb, respectively)]. We present an algorithm for examining the spatiotemporal co-variations among the Hb components, and apply it to the data obtained from a demonstrational study that employed a well-established visual stimulation paradigm: a contrast-reversing checkerboard. Our results indicate that the proposed method can identify regions of tissue that participate in the hemodynamic response to neuronal activation, but are distinct from the areas identified by conventional analyses of the oxyHb, deoxyHb and totalHb data. A discussion is provided that compares these findings to other recent studies using fNIRS techniques.

Dynamic optical imaging of vascular and metabolic reactivity in rheumatoid joints

Dynamic optical imaging is increasingly applied to clinically relevant areas such as brain and cancer imaging. In this approach, some external stimulus is applied and changes in relevant physiological parameters (e.g., oxy- or deoxyhemoglobin concentrations) are determined. The advantage of this approach is that the prestimulus state can be used as a reference or baseline against which the changes can be calibrated. Here we present the first application of this method to the problem of characterizing joint diseases, especially effects of rheumatoid arthritis (RA) in the proximal interphalangeal finger joints. Using a dual-wavelength tomographic imaging system together with previously implemented model-based iterative image reconstruction schemes, we have performed initial dynamic imaging case studies on a limited number of healthy volunteers and patients diagnosed with RA. Focusing on three cases studies, we illustrated our major finds. These studies support our hypothesis that differences in the vascular reactivity exist between affected and unaffected joints.

Image correction scheme applied to functional diffuse optical tomography scattering images

We have extended our investigation on the use of a linear algorithm for enhancing the accuracy of diffuse optical tomography (DOT) images, to include spatial maps of the diffusion coefficient. The results show that the corrected images are markedly improved in terms of estimated size, spatial resolution, two-object resolving power, and quantitative accuracy. These image-enhancing effects are significant at expected levels of diffusion-coefficient contrast in tissue and noise levels typical of experimental DOT data. Overall, the types and magnitudes of image-enhancing effects obtained here are qualitatively similar to those seen in previous studies on mu(a) perturbations. The implications for practical implementations of DOT time-series imaging are discussed.

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

We outline a computationally efficient image correction algorithm, which we have applied to diffuse optical tomography (DOT) image time series derived from a magnetic resonance imaging (MRI)-based brain model. Results show that the algorithm increases spatial resolution, decreases spatial bias, and only modestly reduces temporal accuracy for noise levels typically seen in experiment, and produces results comparable to image reconstructions that incorporate information from MRI priors. We demonstrate that this algorithm has robust performance in the presence of noise, background heterogeneity, irregular external and internal boundaries, and error in the initial guess. However, the algorithm introduces artifacts when the absorption and scattering coefficients of the reference medium are overestimated--a situation that is easily avoided in practice. The considered algorithm offers a practical approach to improving the quality of images from time-series DOT, even without the use of MRI priors.

Reconstruction method with data from a multiple-site continuous-wave source for three-dimensional optical tomography

A method is presented for reconstruction of the optical absorption coefficient from transmission near-infrared data with a cw source. As it is distinct from other available schemes such as optimization or Newton's iterative method, this method resolves the inverse problem by solving a boundary value problem for a Volterra-type integral-differential equation. It is demonstrated in numerical studies that this technique has a better than average stability with respect to the discrepancy between the initial guess and the actual unknown absorption coefficient. The method is particularly useful for reconstruction from a large data set obtained from a CCD camera. Several numerical reconstruction examples are presented.

Image quality improvement via spatial deconvolution in optical tomography: time-series imaging

We present the fourth in a series of studies devoted to the issue of improving image quality in diffuse optical tomography (DOT) by using a spatial deconvolution operation that seeks to compensate for the information-blurring property of first-order perturbation algorithms. Our earlier reports consider only static target media. Here we report spatial deconvolution applied to media with time-varying optical properties, as a model of tissue dynamics resulting from varying metabolic demand and modulation of the vascular bed. Issues under study include the influence of deconvolution on the accuracy of the recovered temporal and spatial information. The impact of noise is also explored, and techniques for ameliorating its information-degrading effects are examined. At low noise levels (i.e, < or = 5% of the time-varying signal amplitude), spatial deconvolution markedly improves the accuracy of recovered information. Temporal information is more seriously degraded by noise than is spatial information, and the impact of noise increases with the complexity of the time-varying signal. These effects, however, can be significantly reduced using simple noise suppression techniques (e.g., low-pass filtering). Results suggest that the deconvolution scheme should provide considerable enhancement of the quality of spatiotemporal information recovered from dynamic DOT techniques applied to tissue studies.

Improved accuracy of reconstructed diffuse optical tomographic images by means of spatial deconvolution: two-dimensional quantitative characterization

Systematic characterization studies are presented, relating to a previously reported spatial deconvolution operation that seeks to compensate for the information-blurring property of first-order perturbation algorithms for diffuse optical tomography (DOT) image reconstruction. In simulation results that are presented, this deconvolution operation has been applied to two-dimensional DOT images reconstructed by solving a first-order perturbation equation. Under study was the effect on algorithm performance of control parameters in the measurement (number and spatial distribution of sources and detectors, presence of noise, and presence of systematic error), target (medium shape; and number, location, size, and contrast of inclusions), and computational (number of finite-element-method mesh nodes, length of filter-generating linear system, among others) parameter spaces associated with computation and the use of the deconvolution operators. Substantial improvements in reconstructed image quality, in terms of recovered inclusion location, size, and contrast, are found in all cases. A finding of practical importance is that the method is robust to appreciable differences between the optical coefficients of the media used for filter generation and those of the target media to which the filters are subsequently applied.

Design and implementation of dynamic near-infrared optical tomographic imaging instrumentation for simultaneous dual-breast measurements

Dynamic near-infrared optical tomographic measurement instrumentation capable of simultaneous bilateral breast imaging, having a capability of four source wavelengths and 32 source-detector fibers for each breast, is described. The system records dynamic optical data simultaneously from both breasts, while verifying proper optical fiber contact with the tissue through implementation of automatic schemes for evaluating data integrity. Factors influencing system complexity and performance are discussed, and experimental measurements are provided to demonstrate the repeatability of the instrumentation. Considerations in experimental design are presented, as well as techniques for avoiding undesirable measurement artifacts, given the high sensitivity and dynamic range (1:10(9)) of the system. We present exemplary clinical results comparing the measured physiologic response of a healthy individual and of a subject with breast cancer to a Valsalva maneuver.

Spatial deconvolution technique to improve the accuracy of reconstructed three-dimensional diffuse optical tomographic images

A straightforward spatial deconvolution operation is presented that seeks to invert the information-blurring property of first-order perturbation algorithms for diffuse optical tomography (DOT) image reconstruction. The method that was developed to generate these deconvolving operators, or filters, was conceptually based on the frequency-encoding process used in magnetic resonance imaging. The computation of an image-correcting filter involves the solution of a large system of linear equations, in which known true distributions and the corresponding recovered distributions are compared. Conversely, application of a filter involves only a simple matrix multiplication. Simulation results show that application of this deconvolution operation to three-dimensional DOT images reconstructed by the solution of a first-order perturbation equation (Born approximation) can yield marked enhancement of image quality. In the examples considered, use of image-correcting filters produces obvious improvements in image quality, in terms of both location and mirco(a) of the inclusions. The displacements between the true and recovered locations of an inclusion's centroid location are as small as 1 mm, in an 8-cm-diameter medium with 1.5-cm-diameter inclusions, and the peak value of the recovered micro(a) for the inclusions deviates from the true value by as little as 5%.

Optical tomographic imaging of small animals

Diffuse optical tomography is emerging as a viable new biomedical imaging modality. Using visible and near-infrared light this technique can probe the absorption and scattering properties of biological tissues. The main applications are currently in brain, breast, limb and joint imaging; however, optical tomographic imaging of small animals is attracting increasing attention. This interest is fuelled by recent advances in the transgenic manipulation of small animals that has led to many models of human disease. In addition, an ever increasing number of optically reactive biochemical markers has become available, which allow diseases to be detected at the molecular level long before macroscopic symptoms appear. The past three years have seen an array of novel technological developments that have led to the first optical tomographic studies of small animals in the areas of cerebral ischemia and cancer.

Three-dimensional optical tomographic brain imaging in small animals, part 1: hypercapnia

In this study, we explore the potential of diffuse optical tomography for brain oximetry. While several groups have already reported on the sensitivity of optical measurements to changes in oxyhemoglobin, deoxyhemoglobin, and blood volume, these studies were often limited to single source-detector geometries or topographic maps, where signals obtained from within the brain are projected onto 2-D surface maps. In this two-part study, we report on our efforts toward developing a volumetric optical imaging system that allows one to spatially resolve 3-D hemodynamic effects in rat brains. In part 1, we describe the instrumentation, optical probe design, and the model-based iterative image reconstruction algorithm employed in this work. Consideration of how a priori anatomical knowledge can be incorporated in the reconstruction process is presented. This system is then used to monitor global hemodynamic changes that occur in the brain under various degrees of hypercapnia. The physiologic cerebral response to hypercapnia is well known and therefore allows an initial performance assessment of the imaging system. As expected, we observe global changes in blood volume and oxygenation, which vary linearly as a function of the concentration of the inspired carbon dioxide. Furthermore, experiments are designed to determine the sensitivity of the reconstructions of only 1 mm to inaccurate probe positioning. We determine that shifts can significantly influence the reconstructions. In part 2 we focus on more local hemodynamic changes that occur during unilateral carotid occlusion performed at lower-than-normal systemic blood pressure. In this case, the occlusion leads to a predominantly monohemispherically localized effect, which is well described in the literature. Having explored the system with a well-characterized physiologic effect, we investigate and discuss the complex compensatory cerebrovascular hemodynamics that occur at normotensive blood pressure. Overall, these studies demonstrate the potential and limitations of our diffuse optical imager for visualizing global and focal hemodynamic phenomenon three dimensionally in the brains of small animals.

Optical tomographic mapping of cerebral haemodynamics by means of time-domain detection: methodology and phantom validation

One of the primary applications of diffuse optical imaging is to localize and quantify the changes in the cerebral oxygenation during functional brain activation. Up to now, data from an optical imager are simply presented as a two-dimensional (2D) topographic map using the modified Beer-Lambert law that assumes homogeneous optical properties beneath each optode. Due to the highly heterogeneous nature of the optical properties in the brain, the assumption is evidently invalid, leading to both low spatial resolution and inaccurate quantification in the assessment of haemodynamic changes. To cope with these difficulties, we propose a nonlinear tomographic image reconstruction algorithm for a two-layered slab geometry that uses time-resolved reflected light. The algorithm is based on the previously developed generalized pulse spectrum technique, and implemented within a semi-three-dimensional (3D) framework to conform to the topographic visualization and to reduce computational load. We demonstrate the advantages of the algorithm in quantifying simulated changes in haemoglobin concentrations and investigate its robustness to the uncertainties in the cortical structure and optical properties, as well as the effects of random noises on image quality. The methodology is also validated by experiments using a solid layered phantom.

Simultaneous reconstruction of absorption and scattering maps with ultrasound localization: feasibility study using transmission geometry

We report the experimental results of the simultaneous reconstruction of absorption and scattering coefficient maps with ultrasound localization. Near-infrared (NIR) data were obtained from frequency domain and dc systems with source and detector fibers configured in transmission geometry. High- or low-contrast targets located close to either the boundary or the center of the turbid medium were reconstructed by using NIR data only and NIR data with ultrasound localization. Results show that the mean reconstructed absorption coefficient and the spatial distribution of the absorption map have been improved significantly with ultrasound localization. The improvements in the mean scattering coefficient and the spatial distribution of the scattering coefficient are moderate. When both the absorption and the scattering coefficients are reconstructed the performance of the frequency-domain systemis much better than that of the dc system.

In vivo continuous-wave optical breast imaging enhanced with Indocyanine Green

We investigate the uptake of a nontargeted contrast agent by breast tumors using a continuous wave diffuse optical tomography apparatus. The instrument operates in the near-infrared spectral window and employs 16 sources and 16 detectors to collect light in parallel on the surface of the tumor-bearing breast (coronal geometry). In our protocol an extrinsic contrast agent, Indocyanine Green (ICG), was injected by bolus. Three clinical scenarios with three different pathologies were investigated. A two-compartment model was used to analyze the pharmacokinetics of ICG and preprocess the data, and diffuse optical tomography was used for imaging. Localization and delineation of the tumor was achieved in good agreement with a priori information. Moreover, different dynamical features were observed for differing pathologies. The malignant cases exhibited slower rate constants (uptake and outflow) compared to healthy tissue. These results provide further evidence that in vivo pharmacokinetics of ICG in breast tumors may be a useful diagnostic tool for differentiation of benign and malignant pathologies.

Semi-three-dimensional algorithm for time-resolved diffuse optical tomography by use of the generalized pulse spectrum technique

Although a foil three-dimensional (3-D) reconstruction with both 3-D forward and inverse models provide, the optimal solution for diffuse optical tomography (DOT), because of the 3-D nature of photon diffusion in tissue, it is computationally costly for both memory requirement and execution time in a conventional computing environment. Thus in practice there is motivation to develop an image reconstruction algorithm with dimensional reduction based on some modeling approximations. Here we have implemented a semi-3-D modified generalized pulse spectrum technique for time-resolved DOT, where a two-dimensional (2-D) distribution of optical properties is approximately assumed, while we retain 3-D distribution of photon migration in tissue. We have validated the proposed algorithm by reconstructing 3-D structural test objects from both numerically simulated and experimental date. We demonstrate our algorithm by comparing it with the calibrated 2-D reconstruction that is in widespread use as a shortcut to 3-D imaging and proving that the semi-3-D algorithm outperforms the calibrated 2-D algorithm.

Absorption and scattering images of heterogeneous scattering media can be simultaneously reconstructed by use of dc data

We present a carefully designed phantom experimental study aimed to provide solid evidence that both absorption and scattering images of heterogeneous scattering media can be reconstructed independently from dc data. We also study the important absorption-scattering cross-talk issue. In this regard, we develop a simple normalizing scheme that is incorporated into our nonlinear finite-element-based reconstruction algorithm. Our results from the controlled phantom experiments show that the cross talk of an absorption object appearing in scattering images can be eliminated and that the cross talk of a scattering object appearing in absorption images can be reduced considerably. In addition, these carefully designed phantom experiments clearly suggest that both absorption and scattering images can be simultaneously recovered and quantitatively separated in highly scattering media by use of dc measurements. Finally, we discuss our results in light of recent theoretical findings on nonuniqueness for dc image reconstruction.

Imaging of spatiotemporal coincident states by DC optical tomography

The utility of optical tomography as a practical imaging modality has, thus far, been limited by its intrinsically low spatial resolution and quantitative accuracy. Recently, we have argued that a broad range of physiological phenomena might be accurately studied by adopting this technology to investigate dynamic states (Schmitz et al., 2000; Barbour et al., 2000; Graber et al., 2000; Barbour et aL, 2001; and Barbour et aL, 1999). One such phenomenon holding considerable significance is the dynamics of the vasculature, which has been well characterized as being both spatially and temporally heterogeneous. In this paper, we have modeled such heterogeneity in the limiting case of spatiotemporal coincident behavior involving optical contrast features, in an effort to define the expected limits with which dynamic states can be characterized using two newly described reconstruction methods that evaluate normalized detector data: the normalized difference method (NDM) and the normalized constraint method (NCM). Influencing the design of these studies is the expectation that spatially coincident temporal variations in both the absorption and scattering properties of tissue can occur in vivo. We have also chosen to model dc illumination techniques, in recognition of their favorable performance and cost for practical systems. This choice was made with full knowledge of theoretical findings arguing that separation of the optical absorption and scattering coefficients under these conditions is not possible. Results obtained show that the NDM algorithm provides for good spatial resolution and excellent characterization of the temporal behavior of optical properties but is subject to interparameter crosstalk. The NCM algorithm, while also providing excellent characterization of temporal behavior, provides for improved spatial resolution, as well as for improved separation of absorption and scattering coefficients. A discussion is provided to reconcile these findings with theoretical expectations.

Charge-coupled-device based scanner for tomography of fluorescent near-infrared probes in turbid media

We present a novel tomographer for three-dimensional reconstructions of fluorochromes in diffuse media. Photon detection is based on charge-coupled device technology that allows the implementation of a large parallel array of detection channels with high sensitivity. Using this instrument we studied the response and detection limits of near-infrared fluorochromes in diffuse media as a function of light intensity and for a wide range of biologically relevant concentrations. We further examined the resolution of the scanner and the reconstruction linearity achieved. We demonstrate that the instrument attains better than 3 mm resolution, is linear within more than two orders of magnitude of fluorochrome concentration, and can detect fluorescent objects at femto-mole quantities in small animal-like geometries. These measurements delineate detection and reconstruction characteristics associated with imaging of novel classes of fluorescent probes developed for in vivo molecular and functional probing of tissues.

Optical tomographic imaging of dynamic features of dense-scattering media

Methods used in optical tomography have thus far proven to produce images of complex target media (e.g., tissue) having, at best, relatively modest spatial resolution. This presents a challenge in differentiating artifact from true features. Further complicating such efforts is the expectation that the optical properties of tissue for any individual are largely unknown and are likely to be quite variable due to the occurrence of natural vascular rhythms whose amplitudes are sensitive to a host of autonomic stimuli that are easily induced. We recognize, however, that rather than frustrating efforts to validate the accuracy of image features, the time-varying properties of the vasculature can be exploited to aid in such efforts, owing to the known structure-dependent frequency response of the vasculature and to the fact that hemoglobin is a principal contrast feature of the vasculature at near-infrared wavelengths. To accomplish this, it is necessary to generate a time series of image data. In this report we have tested the hypothesis that through analysis of time-series data, independent contrast features can be derived that serve to validate, at least qualitatively, the accuracy of imaging data, in effect establishing a self-referencing scheme. A significant finding is the observation that analysis of such data can produce high-contrast images that reveal features that are mainly obscured in individual image frames or in time-averaged image data. Given the central role of hemoglobin in tissue function, this finding suggests that a wealth of new features associated with vascular dynamics can be identified from the analysis of time-series image data.