Three-dimensional optical tomography of the premature infant brain

Neuroimaging of structural and functional connectivity in preterm infants with intraventricular hemorrhage

Preterm infants with intraventricular hemorrhage (IVH) are known to have some of the worst neurodevelopmental outcomes in all of neonatal medicine, with a growing body of evidence relating these outcomes to underlying disruptions in brain structure and function. This review begins by summarizing state-of-the-art neuroimaging techniques delineating structural and functional connectivity (diffusion and resting state functional MRI) and their application in infants with IVH, including unique technical challenges and emerging methods. We then review studies of altered structural and functional connectivity, highlighting the role of IVH severity and location. We subsequently detail investigations linking structural and functional findings in infancy to later outcomes in early childhood. We conclude with future directions including methodologic considerations for prospective and potentially interventional studies designed to mitigate disruptions to underlying structural and functional connections and improve neurodevelopmental outcomes in this high-risk population.

A Model-Based Iterative Learning Approach for Diffuse Optical Tomography

Diffuse optical tomography (DOT) utilises near-infrared light for imaging spatially distributed optical parameters, typically the absorption and scattering coefficients. The image reconstruction problem of DOT is an ill-posed inverse problem, due to the non-linear light propagation in tissues and limited boundary measurements. The ill-posedness means that the image reconstruction is sensitive to measurement and modelling errors. The Bayesian approach for the inverse problem of DOT offers the possibility of incorporating prior information about the unknowns, rendering the problem less ill-posed. It also allows marginalisation of modelling errors utilising the so-called Bayesian approximation error method. A more recent trend in image reconstruction techniques is the use of deep learning, which has shown promising results in various applications from image processing to tomographic reconstructions. In this work, we study the non-linear DOT inverse problem of estimating the (absolute) absorption and scattering coefficients utilising a 'model-based' learning approach, essentially intertwining learned components with the model equations of DOT. The proposed approach was validated with 2D simulations and 3D experimental data. We demonstrated improved absorption and scattering estimates for targets with a mix of smooth and sharp image features, implying that the proposed approach could learn image features that are difficult to model using standard Gaussian priors. Furthermore, it was shown that the approach can be utilised in compensating for modelling errors due to coarse discretisation enabling computationally efficient solutions. Overall, the approach provided improved computation times compared to a standard Gauss-Newton iteration.

Spatially offset Raman spectroscopy for biomedical applications

In recent years, Raman spectroscopy has undergone major advancements in its ability to probe deeply through turbid media such as biological tissues. This progress has been facilitated by the advent of a range of specialist techniques based around spatially offset Raman spectroscopy (SORS) to enable non-invasive probing of living tissue through depths of up to 5 cm. This represents an improvement in depth penetration of up to two orders of magnitude compared to what can be achieved with conventional Raman methods. In combination with the inherently high molecular specificity of Raman spectroscopy, this has therefore opened up entirely new prospects for a range of new analytical applications across multiple fields including medical diagnosis and disease monitoring. This article discusses SORS and related variants of deep Raman spectroscopy such as transmission Raman spectroscopy (TRS), micro-SORS and surface enhanced spatially offset Raman spectroscopy (SESORS), and reviews the progress made in this field during the past 5 years including advances in non-invasive cancer diagnosis, monitoring of neurotransmitters, and assessment of bone disease.

Noncontact optical imaging of brain hemodynamics in preterm infants: a preliminary study

Extremely preterm infants' hemodynamic instability places them at high risk of brain injury. Currently there is no reliable bedside method to continuously monitor cerebral hemodynamics in the neonatal intensive care unit (NICU). This paper reports a feasibility study to adapt and test an innovative speckle contrast diffuse correlation tomography (scDCT) device for noncontact, high-density, 3D imaging of cerebral blood flow (CBF) in preterm infants. The scDCT scans a focused point near-infrared illumination to multiple source positions for deep tissue penetration, and controls an electron multiplying charge-coupled-device camera with thousands of pixels to achieve a high-density sampling. The optimized scDCT for use in preterm infants was first evaluated against an established diffuse correlation spectroscopy in an infant-head-simulating phantom with known properties. The observed significant correlation between the two measurements verified the capability of scDCT for transcranial brain imaging. The insignificant influence of transparent incubator wall on scDCT measurements was then confirmed by comparing adult forearm blood flow responses to artery cuff occlusions measured inside and outside the incubator. Finally, the scDCT device was moved to the NICU to image CBF variations in two preterm infants. Infant #1 with no major organ deficits showed little CBF fluctuation over the first 3 weeks of life. Infant #2 showed a significant CBF increase after the 2 h pharmacotherapy for patent ductus arteriosus closure. While these CBF variations meet physiological expectations, the fact that no significant changes are noted with peripheral monitoring of blood oxygen saturation suggests necessity of direct cerebral monitoring. This feasibility study with timely technology development is an important and necessary step towards larger clinical studies with more subjects to further validate it for continuous monitoring and instant management of cerebral pathologies and interventions in the NICU.

Evaluation of temporal moments and Fourier transformed data in time-domain diffuse optical tomography

Time-domain diffuse optical tomography (TD-DOT) uses near-infrared pulsed lasers as light sources to measure time-varying exitance on the boundary of the target. These are used to estimate optical properties of the imaged target. Several integral-transform-based moments of the time-resolved data have been utilized in TD-DOT, the most common being the mean time of flight and variance. Recently, it has been shown that Fourier transforming the time-domain data to frequency domain enables utilization of these data at one or several frequencies, producing equally as good estimates as the whole time-domain data. In this work, we present a systematic comparison of the usage of the temporal moments and Fourier transformed data in TD-DOT. Both absolute and difference imaging are evaluated using numerical simulations. The simulations show that utilizing temporal moments and Fourier transformed data in TD-DOT provides good quality reconstructions with a good estimation accuracy. These estimates are improved if more than one data type is used. Furthermore, the simulations show that the frequency-domain computations enable computationally cheaper and straightforward implementation of the inverse solver when compared to the temporal moments.

Cap-Based Transcranial Optical Tomography in an Awake Infant

Although Blood Oxygenation Level Dependent (BOLD) functional MRI (fMRI) is widely used to examine brain function in adults, the need for general anesthesia limits its practical utility in infants and small children. Functional Near-Infrared Spectroscopy - Diffuse Optical Tomography (fNIRS-DOT) imaging promises to be an alternative brain network imaging technique. Yet current versions of continuous-wave fNIRS-DOT systems are restricted to the cortical surface measurements and do not probe deep structures that are frequently injured especially in premature infants. Herein we report a transcranial near infrared optical imaging system, called Cap-based Transcranial Optical Tomography (CTOT) able to image whole brain hemodynamic activity with 3 seconds of data acquisition time. We show the system is capable of whole brain oxygenation mapping in an awake child, and that tomographically reconstructed static CTOT-derived oxy- and deoxygenated blood volumes are spatially correlated with the time-averaged BOLD fMRI volumes. By removing time bottlenecks in the current system, dynamic CTOT mapping should be possible, which would then enable evaluation of functional connectivity in awake infants.

Time-domain diffuse optical tomography utilizing truncated Fourier series approximation

Diffuse optical tomography (DOT) uses near infrared light for in vivo imaging of spatially varying optical parameters in biological tissues. It is known that time-resolved measurements provide the richest information on soft tissues, among other measurement types in DOT such as steady-state and intensity-modulated measurements. Therefore, several integral-transform-based moments of the time-resolved DOT measurements have been considered to estimate spatially distributed optical parameters. However, the use of such moments can result in low-contrast images and cross-talks between the reconstructed optical parameters, limiting their accuracy. In this work, we propose to utilize a truncated Fourier series approximation in time-resolved DOT. Using this approximation, we obtained optical parameter estimates with accuracy comparable to using whole time-resolved data that uses low computational time and resources. The truncated Fourier series approximation based estimates also displayed good contrast and minimal parameter cross-talk, and the estimates further improved in accuracy when multiple Fourier frequencies were used.

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.

Hemodynamic responses to emotional speech in two-month-old infants imaged using diffuse optical tomography

Emotional speech is one of the principal forms of social communication in humans. In this study, we investigated neural processing of emotional speech (happy, angry, sad and neutral) in the left hemisphere of 21 two-month-old infants using diffuse optical tomography. Reconstructed total hemoglobin (HbT) images were analysed using adaptive voxel-based clustering and region-of-interest (ROI) analysis. We found a distributed happy > neutral response within the temporo-parietal cortex, peaking in the anterior temporal cortex; a negative HbT response to emotional speech (the average of the emotional speech conditions < baseline) in the temporo-parietal cortex, neutral > angry in the anterior superior temporal sulcus (STS), happy > angry in the superior temporal gyrus and posterior superior temporal sulcus, angry < baseline in the insula, superior temporal sulcus and superior temporal gyrus and happy < baseline in the anterior insula. These results suggest that left STS is more sensitive to happy speech as compared to angry speech, indicating that it might play an important role in processing positive emotions in two-month-old infants. Furthermore, happy speech (relative to neutral) seems to elicit more activation in the temporo-parietal cortex, thereby suggesting enhanced sensitivity of temporo-parietal cortex to positive emotional stimuli at this stage of infant development.

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.

Ray tracing in ellipsoidal reflectors for optical biometry of media

In this paper, an analytical basis of ray tracing for optical biometry of media by ellipsoidal reflectors was developed. A ray-tracing algorithm was created, which involves determining the point of interaction of the incident beam with the ellipsoidal reflector, calculating the direction of the reflected beam, and determining the intersection point of the reflected ray with the second ellipsoid focal plane, taking into account the statistical weight of photons. For imaging in the optical biometry of media by ellipsoidal reflectors, the results of a real experiment and a Monte Carlo simulation for chicken muscle tissue samples of different thicknesses for the wavelength of 632.8 nm are used.

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.

The Advents of Hybrid Imaging Modalities: A New Era in Neuroimaging Applications

Hybrid Imaging modalities have shown great potential in medical imaging and diagnosis. A more comprehensive and targeted view of neurological disorders can be achieved by blending the anatomical and functional perspectives through hybridization. With consistently improving technologies, there have been many developments in fused imaging techniques over the past few decades. This article provides an overview of various bimodal and trimodal hybrid imaging techniques being developed and explored for neuroimaging applications. Recent advancements and potentials are discussed for single photon emission computed tomography-computed tomography (SPECT-CT), positron emission tomography-CT (PET-CT), PET-magnetic resonance imaging (PET-MRI), electroencephalography-functional magnetic resonance imaging (EEG-fMRI), magnetoencephalography-fMRI (MEG-fMRI), EEG-near-infrared spectroscopy (EEG-NIRS), magnetic resonance-PET-EEG (MR-PET-EEG) and MR-PET-CT in the perspective of neuroimaging. A comparison of these hybrid approaches is provided on a single platform to analyze their performance on the basis of several common factors essential for imaging and analyzing neurological disorders and in vivo molecular processes. This article also provides an overview of recently developed advanced imaging technologies that are being hybridized with other imaging modalities and being explored as potential techniques for neuroscience. Novel approaches and clinical applications of hybrid neuroimaging are anticipated with inclusion of new technologies, better sensing capabilities, multimodal probes, and improved hybridization.

Experimental verification of reconstructed absorbers embedded in scattering media by optical power ratio distribution

Experimental investigation to show the effectiveness of the extraction method of absorber information in a scattering medium by taking the output power ratio distribution is presented. In the experiment, two metallic wires sandwiched by three homogeneous scattering media are used as absorbers in transmission geometry. The output power ratio distributions can extract the influence of the absorbers to enhance the optical signal. The peak position of the output power ratio distributions agree with the results suggested by numerical simulation. From the reconstructed results of tomography in the scattering media, we have confirmed that the tomographic image of two wires can distinguish them successfully from 41×21 output power ratio distributions by using continuous-wave light.

Hemodynamic signals in fNIRS

Near-infrared spectroscopy (NIRS) was originally designed for clinical monitoring of tissue oxygenation, and it has also been developed into a useful tool in neuroimaging studies, with the so-called functional NIRS (fNIRS). With NIRS, cerebral activation is detected by measuring the cerebral hemoglobin (Hb), where however, the precise correlation between NIRS signal and neural activity remains to be fully understood. This can in part be attributed to the situation that NIRS signals are inherently subject to contamination by signals arising from extracerebral tissue. In recent years, several approaches have been investigated to distinguish between NIRS signals originating in cerebral tissue and signals originating in extracerebral tissue. Selective measurements of cerebral Hb will enable a further evolution of fNIRS. This chapter is divided into six sections: first a summary of the basic theory of NIRS, NIRS signals arising in the activated areas, correlations between NIRS signals and fMRI signals, correlations between NIRS signals and neural activities, and the influence of a variety of extracerebral tissue on NIRS signals and approaches to this issue are reviewed. Finally, future prospects of fNIRS are described.

Fluorescence suppression using micro-scale spatially offset Raman spectroscopy

We present a new concept of fluorescence suppression in Raman microscopy based on micro-spatially offset Raman spectroscopy which is applicable to thin stratified turbid (diffusely scattering) matrices permitting the retrieval of the Raman signals of sublayers below intensely fluorescing turbid over-layers.

Micro-scale spatially offset Raman spectroscopy for non-invasive subsurface analysis of turbid materials

This article reviews a very recent field of noninvasive analysis of turbid media using micro-scale Spatially Offset Raman Spectroscopy - micro-SORS. The technique combines conventional SORS with microscopy concepts and represents a new imaging modality in Raman microscopy. Micro-SORS facilitates analytical capability for investigating non-destructively the chemical composition of subsurface, micrometer-scale-thick diffusely scattering layers at depths more than an order of magnitude larger than those accessible with the depth resolving power of conventional confocal Raman microscopy. Potential application areas include nondestructive subsurface analysis of painted layers in cultural heritage, characterization of stratified polymer systems, analysis of layered biological samples or forensic analysis. The article discusses the basic principles of the technique, its variants and outlines emerging applications in this rapidly evolving field.

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.

Functional Imaging of the Developing Brain at the Bedside Using Diffuse Optical Tomography

While histological studies and conventional magnetic resonance imaging (MRI) investigations have elucidated the trajectory of structural changes in the developing brain, less is known regarding early functional cerebral development. Recent investigations have demonstrated that resting-state functional connectivity MRI (fcMRI) can identify networks of functional cerebral connections in infants. However, technical and logistical challenges frequently limit the ability to perform MRI scans early or repeatedly in neonates, particularly in those at greatest risk for adverse neurodevelopmental outcomes. High-density diffuse optical tomography (HD-DOT), a portable imaging modality, potentially enables early continuous and quantitative monitoring of brain function in infants. We introduce an HD-DOT imaging system that combines advancements in cap design, ergonomics, and data analysis methods to allow bedside mapping of functional brain development in infants. In a cohort of healthy, full-term neonates scanned within the first days of life, HD-DOT results demonstrate strong congruence with those obtained using co-registered, subject-matched fcMRI and reflect patterns of typical brain development. These findings represent a transformative advance in functional neuroimaging in infants, and introduce HD-DOT as a powerful and practical method for quantitative mapping of early functional brain development in normal and high-risk neonates.

Three-dimensional fuse deposition modeling of tissue-simulating phantom for biomedical optical imaging

Biomedical optical devices are widely used for clinical detection of various tissue anomalies. However, optical measurements have limited accuracy and traceability, partially owing to the lack of effective calibration methods that simulate the actual tissue conditions. To facilitate standardized calibration and performance evaluation of medical optical devices, we develop a three-dimensional fuse deposition modeling (FDM) technique for freeform fabrication of tissue-simulating phantoms. The FDM system uses transparent gel wax as the base material, titanium dioxide (TiO2 ) powder as the scattering ingredient, and graphite powder as the absorption ingredient. The ingredients are preheated, mixed, and deposited at the designated ratios layer-by-layer to simulate tissue structural and optical heterogeneities. By printing the sections of human brain model based on magnetic resonance images, we demonstrate the capability for simulating tissue structural heterogeneities. By measuring optical properties of multilayered phantoms and comparing with numerical simulation, we demonstrate the feasibility for simulating tissue optical properties. By creating a rat head phantom with embedded vasculature, we demonstrate the potential for mimicking physiologic processes of a living system.

Comparison of key modalities of micro-scale spatially offset Raman spectroscopy

We compare several basic embodiments of a recently proposed and demonstrated micrometer-scale Spatially Offset Raman Spectroscopy (micro-SORS).

Compensation of modeling errors due to unknown domain boundary in diffuse optical tomography

Diffuse optical tomography is a highly unstable problem with respect to modeling and measurement errors. During clinical measurements, the body shape is not always known, and an approximate model domain has to be employed. The use of an incorrect model domain can, however, lead to significant artifacts in the reconstructed images. Recently, the Bayesian approximation error theory has been proposed to handle model-based errors. In this work, the feasibility of the Bayesian approximation error approach to compensate for modeling errors due to unknown body shape is investigated. The approach is tested with simulations. The results show that the Bayesian approximation error method can be used to reduce artifacts in reconstructed images due to unknown domain shape.

Reconstruction of localized fluorescent target from multi-view continuous-wave surface images of small animal with lp sparsity regularization

Fluorescence diffuse optical tomography using a multi-view continuous-wave and non-contact measurement system and an algorithm incorporating the lp (0 < p ≤ 1) sparsity regularization reconstructs a localized fluorescent target in a small animal. The measurement system provides a total of 25 fluorescence surface 2D-images of an object, which are acquired by a CCD camera from five different angles of view with excitation from five different angles. Fluorescence surface emissions from five different angles of view are simultaneously imaged on the CCD sensor, thus leading to fast acquisition of the 25 images within three minutes. The distributions of the fluorophore are reconstructed by solving the inverse problem based on the photon diffusion equations. In the reconstruction process incorporating the lp sparsity regularization, the regularization term is reformulated as a differentiable function for gradient-based non-linear optimization. Numerical simulations and phantom experiments show that the use of the lp sparsity regularization improves the localization of the target and quantitativeness of the fluorophore concentration. A mouse experiment demonstrates that a localized fluorescent target in a mouse is successfully reconstructed.

MONSTIR II: a 32-channel, multispectral, time-resolved optical tomography system for neonatal brain imaging

We detail the design, construction and performance of the second generation UCL time-resolved optical tomography system, known as MONSTIR II. Intended primarily for the study of the newborn brain, the system employs 32 source fibres that sequentially transmit picosecond pulses of light at any four wavelengths between 650 and 900 nm. The 32 detector channels each contain an independent photo-multiplier tube and temporally correlated photon-counting electronics that allow the photon transit time between each source and each detector position to be measured with high temporal resolution. The system's response time, temporal stability, cross-talk, and spectral characteristics are reported. The efficacy of MONSTIR II is demonstrated by performing multi-spectral imaging of a simple phantom.

Three-dimensional transillumination image reconstruction for small animal with new scattering suppression technique

To realize three-dimensional (3D) optical imaging of the internal structure of an animal body, we have developed a new technique to reconstruct optical computed tomography (optical CT) images from two-dimensional (2D) transillumination images. In transillumination imaging of an animal body using near-infrared light, the image is blurred because of the strong scattering in the tissue. To overcome this problem, we propose a novel technique to apply the point spread function (PSF) for a light source located inside the medium to the transilluminated image of light-absorbing structure. The problem of the depth-dependence of PSF was solved in the calculation of the projection image in the filtered back-projection method. The effectiveness of the proposed technique was assessed in the experiments with a model phantom and a mouse. These analyses verified the feasibility of the practical 3D imaging of the internal light-absorbing structure of a small animal.

Performance evaluation of typical approximation algorithms for nonconvex ℓp-minimization in diffuse optical tomography

The sparse estimation methods that utilize the ℓp-norm, with p being between 0 and 1, have shown better utility in providing optimal solutions to the inverse problem in diffuse optical tomography. These ℓp-norm-based regularizations make the optimization function nonconvex, and algorithms that implement ℓp-norm minimization utilize approximations to the original ℓp-norm function. In this work, three such typical methods for implementing the ℓp-norm were considered, namely, iteratively reweighted ℓ1-minimization (IRL1), iteratively reweighted least squares (IRLS), and the iteratively thresholding method (ITM). These methods were deployed for performing diffuse optical tomographic image reconstruction, and a systematic comparison with the help of three numerical and gelatin phantom cases was executed. The results indicate that these three methods in the implementation of ℓp-minimization yields similar results, with IRL1 fairing marginally in cases considered here in terms of shape recovery and quantitative accuracy of the reconstructed diffuse optical tomographic images.

Incoherence-based optimal selection of independent measurements in diffuse optical tomography

An optimal measurement selection strategy based on incoherence among rows (corresponding to measurements) of the sensitivity (or weight) matrix for the near infrared diffuse optical tomography is proposed. As incoherence among the measurements can be seen as providing maximum independent information into the estimation of optical properties, this provides high level of optimization required for knowing the independency of a particular measurement on its counterparts. The proposed method was compared with the recently established data-resolution matrix-based approach for optimal choice of independent measurements and shown, using simulated and experimental gelatin phantom data sets, to be superior as it does not require an optimal regularization parameter for providing the same information.

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

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

In vivo photoacoustic lifetime imaging of tumor hypoxia in small animals

Tumor hypoxia is an important factor in assessment of both cancer progression and cancer treatment efficacy. This has driven a substantial effort toward development of imaging modalities that can directly measure oxygen distribution and therefore hypoxia in tissue. Although several approaches to measure hypoxia exist, direct measurement of tissue oxygen through an imaging approach is still an unmet need. To address this, we present a new approach based on in vivo application of photoacoustic lifetime imaging (PALI) to map the distribution of oxygen partial pressure (pO2) in tissue. This method utilizes methylene blue, a dye widely used in clinical applications, as an oxygen-sensitive imaging agent. PALI measurement of oxygen relies upon pO2-dependent excitation lifetime of the dye. A multimodal imaging system was designed and built to achieve ultrasound (US), photoacoustic, and PALI imaging within the same system. Nude mice bearing LNCaP xenograft hindlimb tumors were used as the target tissue. Hypoxic regions were identified within the tumor in a combined US/PALI image. Finally, the statistical distributions of pO2 in tumor, normal, and control tissues were compared with measurements by a needle-mounted oxygen probe. A statistically significant drop in mean pO2 was consistently detected by both methods in tumors.

Time-domain reflectance diffuse optical tomography with Mellin-Laplace transform for experimental detection and depth localization of a single absorbing inclusion

We show how to apply the Mellin-Laplace transform to process time-resolved reflectance measurements for diffuse optical tomography. We illustrate this method on simulated signals incorporating the main sources of experimental noise and suggest how to fine-tune the method in order to detect the deepest absorbing inclusions and optimize their localization in depth, depending on the dynamic range of the measurement. To finish, we apply this method to measurements acquired with a setup including a femtosecond laser, photomultipliers and a time-correlated single photon counting board. Simulations and experiments are illustrated for a probe featuring the interfiber distance of 1.5 cm and show the potential of time-resolved techniques for imaging absorption contrast in depth with this geometry.

Singlet oxygen luminescence detection with a fiber-coupled superconducting nanowire single-photon detector

Direct monitoring of singlet oxygen (¹O₂) luminescence is a particularly challenging infrared photodetection problem. ¹O₂, an excited state of the oxygen molecule, is a crucial intermediate in many biological processes. We employ a low noise superconducting nanowire single-photon detector to record ¹O₂ luminescence at 1270 nm wavelength from a model photosensitizer (Rose Bengal) in solution. Narrow band spectral filtering and chemical quenching is used to verify the ¹O₂ signal, and lifetime evolution with the addition of protein is studied. Furthermore, we demonstrate the detection of ¹O₂ luminescence through a single optical fiber, a marked advance for dose monitoring in clinical treatments such as photodynamic therapy.

Recent advances in the development of Raman spectroscopy for deep non-invasive medical diagnosis

Raman spectroscopy has recently undergone major advances in the area of deep non-invasive characterisation of biological tissues. The progress stems from the development of spatially offset Raman spectroscopy (SORS) and renaissance of transmission Raman spectroscopy permitting the assessment of diffusely scattering samples at depths several orders of magnitude deeper than possible with conventional Raman spectroscopy. Examples of emerging applications include non-invasive diagnosis of bone disease, cancer and monitoring of glucose levels. This article reviews this fast moving field focusing on recent developments within the medical area.

Time-resolved diffuse optical tomography using fast-gated single-photon avalanche diodes

We present the first experimental results of reflectance Diffuse Optical Tomography (DOT) performed with a fast-gated single-photon avalanche diode (SPAD) coupled to a time-correlated single-photon counting system. The Mellin-Laplace transform was employed to process time-resolved data. We compare the performances of the SPAD operated in the gated mode vs. the non-gated mode for the detection and localization of an absorbing inclusion deeply embedded in a turbid medium for 5 and 15 mm interfiber distances. We demonstrate that, for a given acquisition time, the gated mode enables the detection and better localization of deeper absorbing inclusions than the non-gated mode. These results obtained on phantoms demonstrate the efficacy of time-resolved DOT at small interfiber distances. By achieving depth sensitivity with limited acquisition times, the gated mode increases the relevance of reflectance DOT at small interfiber distance for clinical applications.

NIRViz: 3D visualization software for multimodality optical imaging using visualization toolkit (VTK) and insight segmentation toolkit (ITK)

Optical imaging using near-infrared light is used for noninvasive probing of tissues to recover vascular and molecular status of healthy and diseased tissues using hemoglobin contrast arising due to absorption of light. While multimodality optical techniques exist, visualization techniques in this area are limited. Addressing this issue, we present a simple framework for image overlay of optical and magnetic resonance (MRI) or computerized tomographic images which is intuitive and easily usable, called NIRViz. NIRViz is a multimodality software platform for the display and navigation of Digital Imaging and Communications in Medicine (DICOM) MRI datasets and 3D optical image solutions geared toward visualization and coregistration of optical contrast in diseased tissues such as cancer. We present the design decisions undertaken during the design of the software, the libraries used in the implementation, and other implementation details as well as preliminary results from the software package. Our implementation uses the Visualization Toolkit library to do most of the work, with a Qt graphical user interface for the front end. Challenges encountered include reslicing DICOM image data and coregistration of image space and mesh space. The resulting software provides a simple and customized platform to display surface and volume meshes with optical parameters such as hemoglobin concentration, overlay them on magnetic resonance images, allow the user to interactively change transparency of different image sets, rotate geometries, clip through the resulting datasets, obtain mesh and optical solution information, and successfully interact with both functional and structural medical image information.

Diffuser-aided diffuse optical imaging for breast tumor: a feasibility study based on time-resolved three-dimensional Monte Carlo modeling

This study proposed diffuser-aided diffuse optical imaging (DADOI) as a new approach to improve the performance of the conventional diffuse optical tomography (DOT) approach for breast imaging. The 3-D breast model for Monte Carlo simulation is remodeled from clinical MRI image. The modified Beer-Lambert's law is adopted with the DADOI approach to substitute the complex algorithms of inverse problem for mapping of spatial distribution, and the depth information is obtained based on the time-of-flight estimation. The simulation results demonstrate that the time-resolved Monte Carlo method can be capable of performing source-detector separations analysis. The dynamics of photon migration with various source-detector separations are analyzed for the characterization of breast tissue and estimation of optode arrangement. The source-detector separations should be less than 4 cm for breast imaging in DOT system. Meanwhile, the feasibility of DADOI was manifested in this study. In the results, DADOI approach can provide better imaging contrast and faster imaging than conventional DOT measurement. The DADOI approach possesses great potential to detect the breast tumor in early stage and chemotherapy monitoring that implies a good feasibility for clinical application.

A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping

Functional neuroimaging commands a dominant role in current neuroscience research. However its use in bedside clinical and certain neuro-scientific studies has been limited because the current tools lack the combination of being non-invasive, non-ionizing and portable while maintaining moderate resolution and localization accuracy. Optical neuroimaging satisfies many of these requirements, but, until recent advances in high-density diffuse optical tomography (HD-DOT), has been hampered by limited resolution. While early results of HD-DOT have been promising, a quantitative voxel-wise comparison and validation of HD-DOT against the gold standard of functional magnetic resonance imaging (fMRI) has been lacking. Herein, we provide such an analysis within the visual cortex using matched visual stimulation protocols in a single group of subjects (n=5) during separate HD-DOT and fMRI scanning sessions. To attain the needed voxel-to-voxel co-registration between HD-DOT and fMRI image spaces, we implemented subject-specific head modeling that incorporated MRI anatomy, detailed segmentation, and alignment of source and detector positions. Comparisons of the visual responses found an average localization error between HD-DOT and fMRI of 4.4+/-1mm, significantly less than the average distance between cortical gyri. This specificity demonstrates that HD-DOT has sufficient image quality to be useful as a surrogate for fMRI.

Improvement of image quality of time-domain diffuse optical tomography with l sparsity regularization

An l(p) (0 < p ≤ 1) sparsity regularization is applied to time-domain diffuse optical tomography with a gradient-based nonlinear optimization scheme to improve the spatial resolution and the robustness to noise. The expression of the l(p) sparsity regularization is reformulated as a differentiable function of a parameter to avoid the difficulty in calculating its gradient in the optimization process. The regularization parameter is selected by the L-curve method. Numerical experiments show that the l(p) sparsity regularization improves the spatial resolution and recovers the difference in the absorption coefficients between two targets, although a target with a small absorption coefficient may disappear due to the strong effect of the l(p) sparsity regularization when the value of p is too small. The l(p) sparsity regularization with small p values strongly localizes the target, and the reconstructed region of the target becomes smaller as the value of p decreases. A phantom experiment validates the numerical simulations.

Towards the next generation of near-infrared spectroscopy

Although near-infrared spectroscopy (NIRS) was originally designed for clinical monitoring of tissue oxygenation, it has also been developing into a useful tool for neuroimaging studies (functional NIRS). Over the past 30 years, technology has developed and NIRS has found a wide range of applications. However, the accuracy and reliability of NIRS have not yet been widely accepted, mainly because of the difficulties in selective and quantitative detection of signals arising in cerebral tissue, which subject the use of NIRS to a number of practical restrictions. This review summarizes the strengths and advantages of NIRS over other neuroimaging modalities and demonstrates specific examples. The issues of selective quantitative measurement of cerebral haemoglobin during brain activation are also discussed, together with the problems of applying the methods of functional magnetic resonance imaging data analysis to NIRS data analysis. Finally, near-infrared optical tomography--the next generation of NIRS--is described as a potential technique to overcome the limitations of NIRS.

Non-invasive optical imaging of stroke

The acute onset of a neurological deficit is the key clinical feature of stroke. In most cases, however, pathophysiological changes in the cerebral vasculature precede the event, often by many years. Persisting neurological deficits may also require long-term rehabilitation. Hence, stroke may be considered a chronic disease, and diagnostic and therapeutic efforts must include identification of specific risk factors, and the monitoring of and interventions in the acute and subacute stages, and should aim at a pathophysiologically based approach to optimize the rehabilitative effort. Non-invasive optical techniques have been experimentally used in all three stages of the disease and may complement the established diagnostic and monitoring tools. Here, we provide an overview of studies using the methodology in the context of stroke, and we sketch perspectives of how they may be integrated into the assessment of the highly dynamic pathophysiological processes during the acute and subacute stages of the disease and also during rehabilitation and (secondary) prevention of stroke.

Quantitative effect of the neonatal fontanel on synthetic near infrared spectroscopy measurements

Near infrared spectroscopy (NIRS) is a functional imaging technique allowing measurement of local cerebral oxygenation. This modality is particularly adapted to critically ill neonates, as it can be used at the bedside and is a suitable and noninvasive tool for carrying out longitudinal studies. However, NIRS is sensitive to the imaged medium and consequently to the optical properties of biological tissues in which photons propagate. In this study, the effect of the neonatal fontanel was investigated by predicting photon propagation using a probabilistic Monte Carlo approach. Two anatomical newborn head models were created from computed tomography and magnetic resonance images: (1) a realistic model including the fontanel tissue and (2) a model in which the fontanel was replaced by skull tissue. Quantitative change in absorption due to simulated activation was compared for the two models for specific regions of activation and optical arrays simulated in the temporal area. A correction factor was computed to quantify the effect of the fontanel and defined by the ratio between the true and recovered change. The results show that recovered changes in absorption were more precise when determined with the anatomical model including the fontanel. The results suggest that the fontanel should be taken into account in quantification of NIRS responses to avoid misinterpretation in experiments involving temporal areas, such as language or auditory studies.

Reduction of image artifacts induced by change in the optode coupling in time-resolved diffuse optical tomography

Tomographic images of the optical properties can be reconstructed using inversion algorithms for diffuse optical tomography (DOT); however, changes in the optode coupling that occurs while obtaining an object's measurements may often lead to the presence of artifacts in the reconstructed images. To reduce the number of artifacts induced by optode coupling, previous studies have introduced (unknown) coupling coefficients in reconstruction algorithms, which were found to be effective for continuous wave- and frequency-domain DOT. This study aims to investigate the effects of optode calibration on the reconstructed images of time-domain DOT. Here, coupling coefficients are incorporated into the time-domain DOT algorithm based on a modified generalized pulse spectrum technique. The images of the absorption coefficient are reconstructed in various numerical simulations, phantom experiments, and in vivo experiments of time-domain DOT. As a result, the artifacts resulting from changes in optode coupling are reduced in the reconstructed images of the absorption coefficient, thereby demonstrating that introduction of coupling coefficients is effective in time-domain DOT. Moreover, numerical simulations, phantom experiments, and in vivo studies have validated this algorithm.