Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography

X-ray luminescence computed tomography using a hybrid proton propagation model and Lasso-LSQR algorithm

X-ray luminescence computed tomography (XLCT) uses external X-rays for luminescence excitation, which is becoming a promising molecular imaging technique with superb penetration depth and spatial resolution. To achieve the tomographic mapping of luminescence distribution, accurate optical propagation model and suitable reconstruction method are two keys for XLCT, but not satisfied. To overcome the limitation of the single proton propagation model (e.g., DE, SP₃ ), we adopted a hybrid diffusion equation with third order simplified spherical harmonics (DE-SP₃ ) model for XLCT. To enable fast iteration and accurate sparse reconstruction, we also integrated in the inversion optimization, with a novel Least Square QR-factorization based on the Lasso (Lasso-LSQR) algorithm. We first simulated the light propagation in various kinds of organs under DE model and SP₃ model, respectively. By comparison with the Monte Carlo, these tissues can be categorized into two types, namely DE-fitted tissues that include muscle and lung, and SP₃ -fitted tissues including heart, kidney, liver, and stomach. According to the above classification results, we built a hybrid DE-SP₃ model to more accurately describing light transport. Numerical simulations and in vivo experiments illustrated that hybrid DE-SP₃ model achieves superior reconstruction performance in terms of location accuracy, and spatial resolution than DE, and less computational cost than SP₃ . The hybrid DE-SP₃ model materializes a balance between accuracy and efficiency for XLCT.

Clinical Brain Monitoring with Time Domain NIRS: A Review and Future Perspectives

Near-infrared spectroscopy (NIRS) is an optical technique that can measure brain tissue oxygenation and haemodynamics in real-time and at the patient bedside allowing medical doctors to access important physiological information. However, despite this, the use of NIRS in a clinical environment is hindered due to limitations, such as poor reproducibility, lack of depth sensitivity and poor brain-specificity. Time domain NIRS (or TD-NIRS) can resolve these issues and offer detailed information of the optical properties of the tissue, allowing better physiological information to be retrieved. This is achieved at the cost of increased instrument complexity, operation complexity and price. In this review, we focus on brain monitoring clinical applications of TD-NIRS. A total of 52 publications were identified, spanning the fields of neonatal imaging, stroke assessment, traumatic brain injury (TBI) assessment, brain death assessment, psychiatry, peroperative care, neuronal disorders assessment and communication with patient with locked-in syndrome. In all the publications, the advantages of the TD-NIRS measurement to (1) extract absolute values of haemoglobin concentration and tissue oxygen saturation, (2) assess the reduced scattering coefficient, and (3) separate between extra-cerebral and cerebral tissues, are highlighted; and emphasize the utility of TD-NIRS in a clinical context. In the last sections of this review, we explore the recent developments of TD-NIRS, in terms of instrumentation and methodologies that might impact and broaden its use in the hospital.

Time-Domain Near-Infrared Spectroscopy and Imaging: A Review

This article reviews the past and current statuses of time-domain near-infrared spectroscopy (TD-NIRS) and imaging. Although time-domain technology is not yet widely employed due to its drawbacks of being cumbersome, bulky, and very expensive compared to commercial continuous wave (CW) and frequency-domain (FD) fNIRS systems, TD-NIRS has great advantages over CW and FD systems because time-resolved data measured by TD systems contain the richest information about optical properties inside measured objects. This article focuses on reviewing the theoretical background, advanced theories and methods, instruments, and studies on clinical applications for TD-NIRS including some clinical studies which used TD-NIRS systems. Major events in the development of TD-NIRS and imaging are identified and summarized in chronological tables and figures. Finally, prospects for TD-NIRS in the near future are briefly described.

Neonatal brain injury and aberrant connectivity

Brain injury sustained during the neonatal period may disrupt development of critical structural and functional connectivity networks leading to subsequent neurodevelopmental impairment in affected children. These networks can be characterized using structural (via diffusion MRI) and functional (via resting state-functional MRI) neuroimaging techniques. Advances in neuroimaging have led to expanded application of these approaches to study term- and prematurely-born infants, providing improved understanding of cerebral development and the deleterious effects of early brain injury. Across both modalities, neuroimaging data are conducive to analyses ranging from characterization of individual white matter tracts and/or resting state networks through advanced 'connectome-style' approaches capable of identifying highly connected network hubs and investigating metrics of network topology such as modularity and small-worldness. We begin this review by summarizing the literature detailing structural and functional connectivity findings in healthy term and preterm infants without brain injury during the postnatal period, including discussion of early connectome development. We then detail common forms of brain injury in term- and prematurely-born infants. In this context, we next review the emerging body of literature detailing studies employing diffusion MRI, resting state-functional MRI and other complementary neuroimaging modalities to characterize structural and functional connectivity development in infants with brain injury. We conclude by reviewing technical challenges associated with neonatal neuroimaging, highlighting those most relevant to studying infants with brain injury and emphasizing the need for further targeted study in this high-risk population.

Aberrant structural and functional connectivity and neurodevelopmental impairment in preterm children

Background

Despite advances in antenatal and neonatal care, preterm birth remains a leading cause of neurological disabilities in children. Infants born prematurely, particularly those delivered at the earliest gestational ages, commonly demonstrate increased rates of impairment across multiple neurodevelopmental domains. Indeed, the current literature establishes that preterm birth is a leading risk factor for cerebral palsy, is associated with executive function deficits, increases risk for impaired receptive and expressive language skills, and is linked with higher rates of co-occurring attention deficit hyperactivity disorder, anxiety, and autism spectrum disorders. These same infants also demonstrate elevated rates of aberrant cerebral structural and functional connectivity, with persistent changes evident across advanced magnetic resonance imaging modalities as early as the neonatal period. Emerging findings from cross-sectional and longitudinal investigations increasingly suggest that aberrant connectivity within key functional networks and white matter tracts may underlie the neurodevelopmental impairments common in this population.

Main body

This review begins by highlighting the elevated rates of neurodevelopmental disorders across domains in this clinical population, describes the patterns of aberrant structural and functional connectivity common in prematurely-born infants and children, and then reviews the increasingly established body of literature delineating the relationship between these brain abnormalities and adverse neurodevelopmental outcomes. We also detail important, typically understudied, clinical, and social variables that may influence these relationships among preterm children, including heritability and psychosocial risks.

Conclusion

Future work in this domain should continue to leverage longitudinal evaluations of preterm infants which include both neuroimaging and detailed serial neurodevelopmental assessments to further characterize relationships between imaging measures and impairment, information necessary for advancing our understanding of modifiable risk factors underlying these disorders and best practices for improving neurodevelopmental trajectories in this high-risk clinical population.

Hyperspectral wide-field time domain single-pixel diffuse optical tomography platform

We present the design and comprehensive instrumental characterization of a time domain diffuse optical tomography (TD-DOT) platform based on wide-field illumination and wide-field hyperspectral time-resolved single-pixel detection for functional and molecular imaging in turbid media. The proposed platform combines two digital micro-mirror devices (DMDs) to generate structured light and a spectrally resolved multi-anode photomultiplier tube (PMT) detector in time domain for hyperspectral data acquisition over 16 wavelength channels based on the time-correlated single-photon counting (TCSPC) technique. The design of the proposed platform is described in detail and its characteristics in spatial, temporal and spectral dimensions are calibrated and presented. The performance of the system is further validated through a phantom study where two absorbers in glass tubes with spectral contrast are mapped in a turbid medium of ~20 mm thickness. The method presented here offers the potential of accelerating the imaging process and improving reconstruction results in TD-DOT and thus facilitates its wide spread use in preclinical and clinical in vivo imaging scenarios.

Nth-order linear algorithm for diffuse correlation tomography

The current approaches to imaging the tissue blood flow index (BFI) from diffuse correlation tomography (DCT) data are either an analytical solution or a finite element method, both of which are unable to simultaneously account for the tissue heterogeneity and fully utilize the DCT data. In this study, a new imaging concept for DCT, namely NL-DCT, was created by us in which the medical images are combined with light Monte Carlo simulation to provide geometrical and heterogeneous information in tissue. Moreover, the DCT data at multiple delay time are fully utilized via iterative linear regression. The unique merit of NL-DCT in utilizing the medical images as prior information, when combined with a split Bregman algorithm for total variation minimization (Bregman-TV), was validated on a realistic human head model. Computer simulation outcomes demonstrate the accuracy and robustness of NL-DCT in localizing and separating the flow anomalies as well as the capability to preserve edges of anomalies.

Diffuse optical tomography to investigate the newborn brain

Over the past 15 years, functional near-infrared spectroscopy (fNIRS) has emerged as a powerful technology for studying the developing brain. Diffuse optical tomography (DOT) is an extension of fNIRS that combines hemodynamic information from dense optical sensor arrays over a wide field of view. Using image reconstruction techniques, DOT can provide images of the hemodynamic correlates to neural function that are comparable to those produced by functional magnetic resonance imaging. This review article explains the principles of DOT, and highlights the growing literature on the use of DOT in the study of healthy development of the infant brain, and the study of novel pathophysiology in infants with brain injury. Current challenges, particularly around instrumentation and image reconstruction, will be discussed, as will the future of this growing field, with particular focus on whole-brain, time-resolved DOT.

New frontiers in time-domain diffuse optics, a review

The recent developments in time-domain diffuse optics that rely on physical concepts (e.g., time-gating and null distance) and advanced photonic components (e.g., vertical cavity source-emitting laser as light sources, single photon avalanche diode, and silicon photomultipliers as detectors, fast-gating circuits, and time-to-digital converters for acquisition) are focused. This study shows how these tools could lead on one hand to compact and wearable time-domain devices for point-of-care diagnostics down to the consumer level and on the other hand to powerful systems with exceptional depth penetration and sensitivity.

Overview of diffuse optical tomography and its clinical applications

Near-infrared diffuse optical tomography (DOT), one of the most sophisticated optical imaging techniques for observations through biological tissue, allows 3-D quantitative imaging of optical properties, which include functional and anatomical information. With DOT, it is expected to be possible to overcome the limitations of conventional near-infrared spectroscopy (NIRS) as well as offering the potential for diagnostic optical imaging. However, DOT has been under development for more than 30 years, and the difficulties in development are attributed to the fact that light is strongly scattered and that diffusive photons are used for the image reconstruction. The DOT algorithm is based on the techniques of inverse problems. The radiative transfer equation accurately describes photon propagation in biological tissue, while, because of its high computation load, the diffusion equation (DE) is often used as the forward model. However, the DE is invalid in low-scattering and/or highly absorbing regions and in the vicinity of light sources. The inverse problem is inherently ill-posed and highly undetermined. Here, we first summarize NIRS and then describe various approaches in the efforts to develop accurate and efficient DOT algorithms and present some examples of clinical applications. Finally, we discuss the future prospects of DOT.

Fast linear solver for radiative transport equation with multiple right hand sides in diffuse optical tomography

It is well known that radiative transfer equation (RTE) provides more accurate tomographic results than its diffusion approximation (DA). However, RTE-based tomographic reconstruction codes have limited applicability in practice due to their high computational cost. In this article, we propose a new efficient method for solving the RTE forward problem with multiple light sources in an all-at-once manner instead of solving it for each source separately. To this end, we introduce here a novel linear solver called block biconjugate gradient stabilized method (block BiCGStab) that makes full use of the shared information between different right hand sides to accelerate solution convergence. Two parallelized block BiCGStab methods are proposed for additional acceleration under limited threads situation. We evaluate the performance of this algorithm with numerical simulation studies involving the Delta-Eddington approximation to the scattering phase function. The results show that the single threading block RTE solver proposed here reduces computation time by a factor of 1.5~3 as compared to the traditional sequential solution method and the parallel block solver by a factor of 1.5 as compared to the traditional parallel sequential method. This block linear solver is, moreover, independent of discretization schemes and preconditioners used; thus further acceleration and higher accuracy can be expected when combined with other existing discretization schemes or preconditioners.

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.

Multi-channel medical device for time domain functional near infrared spectroscopy based on wavelength space multiplexing

We have designed a compact dual wavelength (687 nm, 826 nm) multi-channel (16 sources, 8 detectors) medical device for muscle and brain imaging based on time domain functional near infrared spectroscopy. The system employs the wavelength space multiplexing approach to reduce wavelength cross-talk and increase signal-to-noise ratio. System performances have been tested on homogeneous and heterogeneous tissue phantoms following specifically designed protocols for photon migration instruments. Preliminary in vivo measurements have been performed to validate the instrument capability to monitor hemodynamic parameters changes in the arm muscle during arterial occlusion and in the adult head during a motor task experiment.

Optical parameters of embedded abnormalities in tissues as determined by Monte Carlo simulation

Photon propagation through tissue phantoms, made of heart, adipose, and spleen tissues was simulated by Monte Carlo procedure. To detect the presence of deep-seated abnormalities, phantoms of heart with adipose and spleen tissues embedded into it were created and simulations were performed to scan the tissue surface with a source and four detector model. Profiles drawn showed variation in parameters such as backscattered intensity in regions where adipose and spleen tissues were embedded. This study shows that depending on the type of embedded tissue the backscattered fraction as measured at 2 mm from the input fiber is altered. This is enhanced for adipose and decreased for spleen tissue. This is not only shown in scanned profiles on the surface but also in constructed images.

In vivo optical imaging and dynamic contrast methods for biomedical research

This paper provides an overview of optical imaging methods commonly applied to basic research applications. Optical imaging is well suited for non-clinical use, since it can exploit an enormous range of endogenous and exogenous forms of contrast that provide information about the structure and function of tissues ranging from single cells to entire organisms. An additional benefit of optical imaging that is often under-exploited is its ability to acquire data at high speeds; a feature that enables it to not only observe static distributions of contrast, but to probe and characterize dynamic events related to physiology, disease progression and acute interventions in real time. The benefits and limitations of in vivo optical imaging for biomedical research applications are described, followed by a perspective on future applications of optical imaging for basic research centred on a recently introduced real-time imaging technique called dynamic contrast-enhanced small animal molecular imaging (DyCE).

Bedside optical imaging of occipital resting-state functional connectivity in neonates

Resting-state networks derived from temporal correlations of spontaneous hemodynamic fluctuations have been extensively used to elucidate the functional organization of the brain in adults and infants. We have previously developed functional connectivity diffuse optical tomography methods in adults, and we now apply these techniques to study functional connectivity in newborn infants at the bedside. We present functional connectivity maps in the occipital cortices obtained from healthy term-born infants and premature infants, including one infant with an occipital stroke. Our results suggest that functional connectivity diffuse optical tomography has potential as a valuable clinical tool for the early detection of functional deficits and for providing prognostic information on future development.

Cerebral monitoring during carotid endarterectomy using near-infrared diffuse optical spectroscopies and electroencephalogram

Intraoperative monitoring of cerebral hemodynamics during carotid endarterectomy (CEA) provides essential information for detecting cerebral hypoperfusion induced by temporary internal carotid artery (ICA) clamping and post-CEA hyperperfusion syndrome. This study tests the feasibility and sensitivity of a novel dual-wavelength near-infrared diffuse correlation spectroscopy technique in detecting cerebral blood flow (CBF) and cerebral oxygenation in patients undergoing CEA. Two fiber-optic probes were taped on both sides of the forehead for cerebral hemodynamic measurements, and the instantaneous decreases in CBF and electroencephalogram (EEG) alpha-band power during ICA clamping were compared to test the measurement sensitivities of the two techniques. The ICA clamps resulted in significant CBF decreases (-24.7 ± 7.3%) accompanied with cerebral deoxygenation at the surgical sides (n = 12). The post-CEA CBF were significantly higher (+43.2 ± 16.9%) than the pre-CEA CBF. The CBF responses to ICA clamping were significantly faster, larger and more sensitive than EEG responses. Simultaneous monitoring of CBF, cerebral oxygenation and EEG power provides a comprehensive evaluation of cerebral physiological status, thus showing potential for the adoption of acute interventions (e.g., shunting, medications) during CEA to reduce the risks of severe cerebral ischemia and cerebral hyperperfusion syndrome.

Near-infrared spectroscopy: a report from the McDonnell infant methodology consortium

Near-infrared spectroscopy (NIRS) is a new and increasingly widespread brain imaging technique, particularly suitable for young infants. The laboratories of the McDonnell Consortium have contributed to the technological development and research applications of this technique for nearly a decade. The present paper provides a general introduction to the technique as well as a detailed report of the methodological innovations developed by the Consortium. The basic principles of NIRS and some of the existing developmental studies are reviewed. Issues concerning technological improvements, parameter optimization, possible experimental designs and data analysis techniques are discussed and illustrated by novel empirical data.

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.

Image reconstruction in diffuse optical tomography based on simplified spherical harmonics approximation

The use of higher order approximations to the Radiative transport equation, through simplified spherical harmonics expansion (SP(N)) in optical tomography are presented. It is shown that, although the anisotropy factor can be modeled in the forward problem, its sensitivity to the measured boundary data is limited to superficial regions and more importantly, due to uniqueness of the inverse problem it cannot be determined using frequency domain data. Image reconstruction through the use of higher ordered models is presented. It is demonstrated that at higher orders (for example SP7) the image reconstruction becomes highly under-determined due to the large increase in the number of unknowns which cannot be adequately recovered. However, reconstruction of diffuse parameters, namely optical absorption and reduced scatter have shown to be more accurate where only the sensitivity matrix used in the inverse problem is based on SP(N) method and image reconstruction is limited to these two diffuse parameters.

Investigation of a probe design for facilitating the uses of the standard photon diffusion equation at short source-detector separations: Monte Carlo simulations

We design a special diffusing probe to investigate the optical properties of human skin in vivo. The special geometry of the probe enables a modified two-layer (MTL) diffusion model to precisely describe the photon transport even when the source-detector separation is shorter than 3 mean free paths. We provide a frequency domain comparison between the Monte Carlo model and the diffusion model in both the MTL geometry and conventional semiinfinite geometry. We show that using the Monte Carlo model as a benchmark method, the MTL diffusion theory performs better than the diffusion theory in the semiinfinite geometry. In addition, we carry out Monte Carlo simulations with the goal of investigating the dependence of the interrogation depth of this probe on several parameters including source-detector separation, sample optical properties, and properties of the diffusing high-scattering layer. From the simulations, we find that the optical properties of samples modulate the interrogation volume greatly, and the source-detector separation and the thickness of the diffusing layer are the two dominant probe parameters that impact the interrogation volume. Our simulation results provide design guidelines for a MTL geometry probe.

Probabilistic atlas can improve reconstruction from optical imaging of the neonatal brain

Diffuse optical imaging is an emerging medical imaging modality based on near-infrared and visible red light. The method can be used for imaging activations in the human brain. In this study, a deformable probabilistic atlas of the distribution of tissue types within the term neonatal head was created based on MR images. The use of anatomical prior information provided by such atlas in reconstructing brain activations from optical imaging measurements was studied using Monte Carlo simulations. The results suggest that use of generic anatomical information can greatly improve the spatial accuracy and robustness of the reconstruction when noise is present in the data.

Diffuse optical imaging

Diffuse optical imaging is a medical imaging technique that is beginning to move from the laboratory to the hospital. It is a natural extension of near-infrared spectroscopy (NIRS), which is now used in certain niche applications clinically and particularly for physiological and psychological research. Optical imaging uses sophisticated image reconstruction techniques to generate images from multiple NIRS measurements. The two main clinical applications--functional brain imaging and imaging for breast cancer--are reviewed in some detail, followed by a discussion of other issues such as imaging small animals and multimodality imaging. We aim to review the state of the art of optical imaging.

The utility of a marched absorbing layer boundary condition in the finite element analysis of diffuse photon density wave propagation in tissues relevant to breast imaging

Here we introduce a marched absorbing layer boundary condition for the finite element analysis of diffuse photon density wave propagation in tissues. We investigated and optimized the parameters required to set up a marched absorbing layer boundary for diffuse photon density wave propagation in media with different absorption and scattering coefficients. Comparing with using a breast model connected to a large substrate and a Robin boundary condition, using a marched absorbing layer boundary condition to replace part of the large base reduced the time for forward modeling by about 30%.

Light transport in biological tissue using three-dimensional frequency-domain simplified spherical harmonics equations

The accuracy of the commonly used diffusion approximation as used in diffuse optical tomography is known to be limited in cases involving strong absorption and in these situations a higher ordered approximation is necessary. In this study, a light transport model has been developed based upon the three-dimensional frequency-domain simplified spherical harmonics (SP(N)) approximation for orders up to N = 7. The SP(N) data are tested against a semi-infinite multi-layered Monte Carlo model. It has been shown that the SP(N) approximation for higher orders (N >1) provides an increase in accuracy over the diffusion equation specifically near sources and at boundaries of regions with increased optical absorption. It is demonstrated that the error of fluence calculated near the sources between the diffusion approximation and the SP(N) model (N = 7) can be as large as 60%, therefore limiting the use of the diffusion approximation for small animal imaging and in situations where optical changes near sources are critical for tomographic reconstructions.

Depth sensitivity and image reconstruction analysis of dense imaging arrays for mapping brain function with diffuse optical tomography

The development of diffuse optical tomography (DOT) instrumentation for neuroimaging of humans is challenging due to the large size and the geometry of the head and the desire to distinguish signals at different depths. One approach to this problem is to use dense imaging arrays that incorporate measurements at different source-detector distances. We previously developed a high-density DOT system that is able to obtain retinotopic measurements in agreement with functional magnetic resonance imaging and positron emission tomography. Further extension of high-density DOT neuroimaging necessitates a thorough study of the measurement and imaging sensitivity that incorporates the complex geometry of the head--including the head curvature and layered tissue structure. We present numerical simulations using a finite element model of the adult head to study the sensitivity of the measured signal as a function of the imaging array and data sampling strategy. Specifically, we quantify the imaging sensitivity available within the brain (including depths beyond superficial cortical gyri) as a function of increasing the maximum source-detector separation included in the data. Through the use of depth related sensitivity analysis, it is shown that for a rectangular grid [with 1.3 cm first nearest neighbor (NN) spacing], second NN measurements are sufficient to record absorption changes along the surface of the brain's cortical gyri (brain tissue depth <5 mm). The use of fourth and fifth NN measurements would permit imaging down into the cortical sulci (brain tissue depth >15 mm).

Significance of background optical properties, time-resolved information and optode arrangement in diffuse optical imaging of term neonates

The significance of accurate knowledge of background optical properties and time-resolved information in reconstructing images of hemodynamic changes in the neonatal brain from diffuse optical imaging data was studied using Monte Carlo (MC) simulation. A segmented anatomical magnetic resonance (MR) image and literature-derived optical properties for each tissue type were used to create a voxel-based anatomical model. Small absorbing perturbations were introduced into the anatomical model to simulate localized hemodynamic responses related to brain activation. Perturbation MC (pMC) was used as the primary method of image reconstruction. For comparison, reconstructions were also performed using the finite element method (FEM) to solve the diffusion approximation (DA) to the radiative transfer equation (RTE). The effect of optode layout was investigated using three different grids. Of the factors studied, the density of the optode grid was found to have the greatest effect on image quality. The use of time-resolved information significantly improved the spatial accuracy with all optode grids. Adequate knowledge and modeling of the optical properties of the background was found to significantly improve the spatial accuracy of the reconstructed images and make the recovery of contrast of absorption changes more consistent over simplified modeling. Localization accuracy of small perturbations was found to be 2-3 mm with accurate a priori knowledge of the background optical properties, when a grid with high optode density (>1 optode cm(-2)) was used.

Early photon tomography allows fluorescence detection of lung carcinomas and disease progression in mice in vivo

Imaging of targeted fluorescent probes offers significant advantages for investigating disease and tissue function in animal models in vivo. Conversely, macroscopic tomographic imaging is challenging because of the high scatter of light in biological tissue and the ill-posed nature of the reconstruction mathematics. In this work, we use the earliest-transmitted photons through Lewis Lung Carcinoma bearing mice, thereby dramatically reducing the effect of tissue scattering. By using a fluorescent probe sensitive to cysteine proteases, the method yielded outstanding imaging performance compared with conventional approaches. Accurate visualization of biochemical abnormalities was achieved, not only in the primary tumor, but also in the surrounding tissue related to cancer progression and inflammatory response at the organ level. These findings were confirmed histologically and with ex vivo fluorescence microscopy. The imaging fidelity demonstrated underscores a method that can use a wide range of fluorescent probes to accurately visualize cellular- and molecular-level events in whole animals in vivo.

Wavelength dependence of sensitivity in spectral diffuse optical imaging: effect of normalization on image reconstruction

Near Infrared Diffuse Optical Tomography has the potential to be used as a non-invasive imaging tool for biological tissue specifically for the diagnosis and characterization of breast cancer. Most model based reconstruction algorithms rely on calculating and inverting a large Jacobian matrix. Although this method is flexible for a wide range of complex problems, it usually results in large image artifacts from hypersensitivity around the detectors. In this work a Jacobian normalization technique is presented which takes into account the varying magnitude of different optical parameters creating a more uniform update within a spectral image reconstruction model. Using simulated data the Jacobian normalization method is used to reconstructed images of absolute chromophore and scattering parameters which are qualitatively and quantitatively as compared to conventional methods. The hypersensitivity resulting in boundary artifacts are shown to be minimized with only a small additional computational cost.

A self-normalized, full time-resolved method for fluorescence diffuse optical tomography

A full time-resolved scheme that has been previously applied in diffuse optical tomography is extended to time-domain fluorescence diffuse optical tomography regime, based on a finite-element-finite-time-difference photon diffusion modeling and a Newton-Raphson inversion framework. The merits of using full time-resolved data are twofold: it helps evaluate the intrinsic performance of time-domain mode for improvement of image quality and set up a valuable reference to the assessment of computationally efficient featured-data-based algorithms, and provides a self-normalized implementation to preclude the necessity of the scaling-factor calibration and spectroscopic-feature assessments of the system as well as to overcome the adversity of system instability. We validate the proposed methodology using simulated data, and evaluate its performances of simultaneous recovery of the fluorescent yield and lifetime as well as its superiority to the featured-data one in the fidelity of image reconstruction.

Optical Clearing of Cranial Bone

We present experimental results on optical properties of cranial bone controlled by administration of propylene glycol and glycerol. Both transmittance and reflectance spectra of human and porcine cranial bone in vitro were measured. For estimation of absorption and reduced scattering coefficients of the bone, the inverse adding-doubling method was used. The decrease of reflectance of the samples under action of the immersion agents was demonstrated. The experiments have shown that administration of the immersion liquids allows for effective controlling of tissue optical characteristics that makes bone more transparent, thereby increasing the ability of light penetration through the tissue. The presented results can be used in developing of functional imaging techniques, including OCT.

Multimodality monitoring in neurocritical care

Multimodality monitoring of cerebral physiology encompasses the application of different monitoring techniques and integration of several measured physiologic and biochemical variables into assessment of brain metabolism, structure, perfusion, and oxygenation status. Novel monitoring techniques include transcranial Doppler ultrasonography, neuroimaging, intracranial pressure, cerebral perfusion, and cerebral blood flow monitors, brain tissue oxygen tension monitoring, microdialysis, evoked potentials, and continuous electroencephalogram. Multimodality monitoring enables immediate detection and prevention of acute neurologic injury as well as appropriate intervention based on patients' individual disease states in the neurocritical care unit. Real-time analysis of cerebral physiologic, metabolic, and cardiovascular parameters simultaneously has broadened knowledge about complex brain pathophysiology and cerebral hemodynamics. Integration of this information allows for more precise diagnosis and optimization of management of patients with brain injury.

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.

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.

Digital-signal-processor-based dynamic imaging system for optical tomography

In this article, we introduce a dynamic optical tomography system that is, unlike currently available analog instrumentation, based on digital data acquisition and filtering techniques. At the core of this continuous wave instrument is a digital signal processor (DSP) that collects, collates, processes, and filters the digitized data set. The processor is also responsible for managing system timing and the imaging routines which can acquire real-time data at rates as high as 150 Hz. Many of the synchronously timed processes are controlled by a complex programmable logic device that is also used in conjunction with the DSP to orchestrate data flow. The operation of the system is implemented through a comprehensive graphical user interface designed with LABVIEW software which integrates automated calibration, data acquisition, data organization, and signal postprocessing. Performance analysis demonstrates very low system noise (approximately 1 pW rms noise equivalent power), excellent signal precision (<0.04%-0.2%) and long term system stability (<1% over 40 min). A large dynamic range (approximately 190 dB) accommodates a wide scope of measurement geometries and tissue types. First experiments on tissue phantoms show that dynamic behavior is accurately captured and spatial location can be correctly tracked using this system.

Optical imaging of the neonatal brain

Optical systems could be valuable tools for assessing cerebral function at the cotside

Noncontact optical imaging in mice with full angular coverage and automatic surface extraction

During the past decade, optical imaging combined with tomographic approaches has proved its potential in offering quantitative three-dimensional spatial maps of chromophore or fluorophore concentration in vivo. Due to its direct application in biology and biomedicine, diffuse optical tomography (DOT) and its fluorescence counterpart, fluorescence molecular tomography (FMT), have benefited from an increase in devoted research and new experimental and theoretical developments, giving rise to a new imaging modality. The most recent advances in FMT and DOT are based on the capability of collecting large data sets by using CCDs as detectors, and on the ability to include multiple projections through recently developed noncontact approaches. For these to be implemented, we have developed an imaging setup that enables three-dimensional imaging of arbitrary shapes in fluorescence or absorption mode that is appropriate for small animal imaging. This is achieved by implementing a noncontact approach both for sources and detectors and coregistering surface geometry measurements using the same CCD camera. A thresholded shadowgrammetry approach is applied to the geometry measurements to retrieve the surface mesh. We present the evaluation of the system and method in recovering three-dimensional surfaces from phantom data and live mice. The approach is used to map the measured in vivo fluorescence data onto the tissue surface by making use of the free-space propagation equations, as well as to reconstruct fluorescence concentrations inside highly scattering tissuelike phantom samples. Finally, the potential use of this setup for in vivo small animal imaging and its impact on biomedical research is discussed.

Spatio-temporal imaging of the hemoglobin in the compressed breast with diffuse optical tomography

We develop algorithms for imaging the time-varying optical absorption within the breast given diffuse optical tomographic data collected over a time span that is long compared to the dynamics of the medium. Multispectral measurements allow for the determination of the time-varying total hemoglobin concentration and of oxygen saturation. To facilitate the image reconstruction, we decompose the hemodynamics in time into a linear combination of spatio-temporal basis functions, the coefficients of which are estimated using all of the data simultaneously, making use of a Newton-based nonlinear optimization algorithm. The solution of the extremely large least-squares problem which arises in computing the Newton update is obtained iteratively using the LSQR algorithm. A Laplacian spatial regularization operator is applied, and, in addition, we make use of temporal regularization which tends to encourage similarity between the images of the spatio-temporal coefficients. Results are shown for an extensive simulation, in which we are able to image and quantify localized changes in both total hemoglobin concentration and oxygen saturation. Finally, a breast compression study has been performed for a normal breast cancer screening subject, using an instrument which allows for highly accurate co-registration of multispectral diffuse optical measurements with an x-ray tomosynthesis image of the breast. We are able to quantify the global return of blood to the breast following compression, and, in addition, localized changes are observed which correspond to the glandular region of the breast.

Time-resolved optical imager for assessment of cerebral oxygenation

A time-resolved optical instrument allowing for noninvasive assessment of cerebral oxygenation is presented. The instrument is equipped with picosecond diode lasers, fast photodetectors, and time-correlated single photon counting electronics. This technology enables depth-resolved estimation of changes in absorption and, in consequence, assessment of changes in hemoglobin concentrations in the brain cortex. Changes in oxyhemoglobin (HbO(2)) and deoxyhemoglobin (Hb) can be evaluated selectively in extra- and intracerebral tissue compartments using the moments of distributions of times of flight of photons measured at two wavelengths in the near-infrared region. The combination of the data acquired from multiple sources and detectors located on the surface of the head with the depth-resolved analysis, based on the moments, enables imaging of cortex oxygenation. Results of the tests on physical phantoms as well as in vivo validation of the instrument during the motor stimulation experiment are presented.

Optical tomography of the neonatal brain

A new method of assessing neurological function and pathology in the newborn infant is being developed based on the transmission of near-infrared light across the brain. Absorption by blood over a range of wavelengths reveals a strong dependency on oxygenation status, and measurements of transmitted light enable the spatial variation in the concentrations of the oxygenated and de-oxygenated forms of hemoglobin to be derived. Optical tomography has so far provided static three-dimensional maps of blood volume and oxygenation as well as dynamic images revealing the brain's response to sensory stimulation and global hemodynamic changes. The imaging modality is being developed as a safe and non-invasive tool that can be utilized at the cotside in intensive care. Optical tomography of the healthy infant brain is also providing a means of studying neurophysiological processes during early development and the potential consequences of prematurity.

Near-infrared laser tomographic imaging with right-angled scattered coherent light using an optical heterodyne-detection-based confocal scanning system

We demonstrate, what is to the best of our knowledge, a novel optical tomographic method for the visualization of the inner structure of scattering media such as biological tissue in the near-infrared region. We constructed a scanning confocal imaging system with a cross-axes arrangement using optical fibers. This system is based on the optical heterodyne technique and enables the detection of very weak coherence photons that are generated in the spatially restricted confocal region and scattered laterally (90 degrees ) against an incident beam. To evaluate the fundamental imaging capabilities of the system, we assessed measurements from scattering phantoms composed of an Intralipid suspension with varying volume concentrations. The results of this study demonstrate that the right-angled scattered light adheres to the Lambert-Beer law and that the present system can detect light propagating through a distance of approximately 31l of the mean free path. An inclusion as small as 100 microm can be discriminated in a scattering media with an optical thickness of 4. We investigated the potential of the proposed system for imaging biological tissues in preliminary experiments using samples of chicken breast tissue.

Subsurface diffuse optical tomography can localize absorber and fluorescent objects but recovered image sensitivity is nonlinear with depth

Subsurface tomography with diffuse light has been investigated with a noncontact approach to characterize the performance of absorption and fluorescence imaging. Using both simulations and experiments, the reconstruction of local subsurface heterogeneity is demonstrated, but the recovery of target size and fluorophore concentration is not linear when changes in depth occur, whereas the mean position of the object for experimental fluorescent and absorber targets is accurate to within 0.5 and 1.45 mm when located within the first 10 mm below the surface. Improvements in the linearity of the response with depth appear to remain challenging and may ultimately limit the approach to detection rather than characterization applications. However, increases in tissue curvature and/or the addition of prior information are expected to improve the linearity of the response. The potential for this type of imaging technique to serve as a surgical guide is highlighted.