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There has been considerable interest in applying electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) simultaneously for multimodal assessment of brain function. EEG–fNIRS can provide a comprehensive picture of brain electrical and hemodynamic function and has been applied across various fields of brain science. The development of wearable, mechanically and electrically integrated EEG–fNIRS technology is a critical next step in the evolution of this field. A suitable system design could significantly increase the data/image quality, the wearability, patient/subject comfort, and capability for long-term monitoring. Here, we present a concise, yet comprehensive, review of the progress that has been made toward achieving a wearable, integrated EEG–fNIRS system. Significant marks of progress include the development of both discrete component-based and microchip-based EEG–fNIRS technologies; modular systems; miniaturized, lightweight form factors; wireless capabilities; and shared analogue-to-digital converter (ADC) architecture between fNIRS and EEG data acquisitions. In describing the attributes, advantages, and disadvantages of current technologies, this review aims to provide a roadmap toward the next generation of wearable, integrated EEG–fNIRS systems.

The concept of region of sensitivity is central to the field of diffuse optics and is closely related to the Jacobian matrix used to solve the inverse problem in imaging. It is well known that, in diffuse reflectance, the region of sensitivity associated with a given source–detector pair is shaped as a banana, and features maximal sensitivity to the portions of the sample that are closest to the source and the detector. We have recently introduced a dual-slope (DS) method based on a special arrangement of two sources and two detectors, which results in deeper and more localized regions of sensitivity, resembling the shapes of different kinds of nuts. Here, we report the regions of sensitivity associated with a variety of source–detector arrangements for DS measurements of intensity and phase with frequency-domain spectroscopy (modulation frequency: 140MHz) in a medium with absorption and reduced scattering coefficients of 0.1 and 12 cm−1, respectively. The main result is that the depth of maximum sensitivity, considering only cases that use source-detector separations of 25 and 35 mm, progressively increases as we consider single-distance intensity (2.0mm), DS intensity (4.6mm), single-distance phase (7.5mm), and DS phase (10.9mm). These results indicate the importance of DS measurements, and even more so of phase measurements, when it is desirable to selectively probe deeper portions of a sample with diffuse optics. This is certainly the case in non-invasive optical studies of brain, muscle, and breast tissue, which are located underneath the superficial tissue at variable depths.

We describe an approach that combines clinical ultrasound and photon migration techniques to enhance the sensitivity and information content of diffuse optical tomography. Measurements were performed on a postmenopausal woman with a single 1.8 x 0.9 cm malignant ductal carcinoma in situ approximately 7.4 mm beneath the skin surface (UCI IRB protocol 95-563). The ultrasound-derived information about tumor geometry enabled us to segment the breast tissue into tumor and background regions. Optical data was obtained with a multifrequency, multiwavelength hand-held frequency-domain photon migration backscattering probe. The optical properties of the tumor and background were then computed using the ultrasound-derived geometrical constraints. An iterative perturbative approach, using parallel processing, provided quantitative information about scattering and absorption simultaneously with the ability to incorporate and resolve complex boundary conditions and geometries. A three to four fold increase in the tumor absorption coefficient and nearly 50% reduction in scattering coefficient relative to background was observed (lambda = 674, 782, 803, and 849 nm). Calculations of the mean physiological parameters reveal fourfold greater tumor total hemoglobin concentration [Hbtot] than normal breast (67 microM vs 16 microM) and tumor hemoglobin oxygen saturation (SOx) values of 63% (vs 73% and 68% in the region surrounding the tumor and the opposite normal tissue, respectively). Comparison of semi-infinite to heterogeneous models shows superior tumor/background contrast for the latter in both absorption and scattering. Sensitivity studies assessing the impact of tumor size and refractive index assumptions, as well as scan direction, demonstrate modest effects on recovered properties.

EIT-MESHER (https://github.com/EIT-team/Mesher) is C++ software, based on the CGAL library, which generates high quality Finite Element Model tetrahedral meshes from binary masks of 3D volume segmentations. Originally developed for biomedical applications in Electrical Impedance Tomography (EIT) to address the need for custom, non-linear refinement in certain areas (e.g. around electrodes), EITMESHER can also be used in other fields where custom FEM refinement is required, such as Diffuse Optical Tomography (DOT). [ABSTRACT FROM AUTHOR]

The concept of region of sensitivity is central to the field of diffuse optics and is closely related to the Jacobian matrix used to solve the inverse problem in imaging. It is well known that, in diffuse reflectance, the region of sensitivity associated with a given source–detector pair is shaped as a banana, and features maximal sensitivity to the portions of the sample that are closest to the source and the detector. We have recently introduced a dual-slope (DS) method based on a special arrangement of two sources and two detectors, which results in deeper and more localized regions of sensitivity, resembling the shapes of different kinds of nuts. Here, we report the regions of sensitivity associated with a variety of source–detector arrangements for DS measurements of intensity and phase with frequency-domain spectroscopy (modulation frequency: 140 MHz) in a medium with absorption and reduced scattering coefficients of 0.1 and 12 cm − 1 , respectively. The main result is that the depth of maximum sensitivity, considering only cases that use source-detector separations of 25 and 35 mm, progressively increases as we consider single-distance intensity (2.0 mm), DS intensity (4.6 mm), single-distance phase (7.5 mm), and DS phase (10.9 mm). These results indicate the importance of DS measurements, and even more so of phase measurements, when it is desirable to selectively probe deeper portions of a sample with diffuse optics. This is certainly the case in non-invasive optical studies of brain, muscle, and breast tissue, which are located underneath the superficial tissue at variable depths. [ABSTRACT FROM AUTHOR]

Time-resolved diffuse optical tomography is a technique used to recover the optical properties of an unknown diffusive medium by solving an ill-posed inverse problem. In time-domain, reconstructions based on datatypes are used for their computational efficiency. In practice, most used datatypes are temporal windows and Fourier transform. Nevertheless, neither theoretical nor numerical studies assessing different datatypes have been clearly expressed. In this paper, we propose an overview and a new process to compute efficiently a long set of temporal windows in order to perform diffuse optical tomography. We did a theoretical comparison of these large set of temporal windows. We also did simulations in a reflectance geometry with a spherical inclusion at different depths. The results are presented in terms of inclusion localization and its absorption coefficient recovery. We show that (1) the new windows computed with the developed method improve inclusion localization for inclusions at deep layers, (2) inclusion absorption quantification is improved at all depths and, (3) in some cases these windows can be equivalent to frequency based reconstruction at GHz order. [ABSTRACT FROM AUTHOR]

This article presents a promising dual-wavelength continuous wave (CW) diffuse optical tomography (DOT) system for direct estimation of concentrations and hemodynamic parameters for potential application in detection of rheumatoid arthritis (RA). The generalized curved-beam reconstruction technique is modified for direct estimation of hemodynamic parameters. The Rosenbrock’s function is fit to estimate the photon path as curved one followed by majority photons that enabled the use of modified Beer–Lambert law (MBLL) in differential form with assumption that unknown absorption coefficient ($\mu _{a}$) varies from one path to another. The $\mu _{a}$ values are calculated and back-projected along the photon paths for image reconstruction without solving the inverse problem. Thus, stability is not an issue in image reconstruction. Also, there is no need for baseline measurement and prior information on perturbation, unlike the iterative methods used for dynamic imaging. The reconstructed images of the distal interphalangeal (DIP) and proximal interphalangeal (PIP) joints of a healthy male volunteer showed good consistency and are used for direct optical estimation of the physiological parameters. A novel application of optical imaging beyond biomedical applications is demonstrated by imaging the gradual dispersion of viscous Indian ink and glycerin mixture in turbid water with encouraging results. [ABSTRACT FROM AUTHOR]

Featured Application: The present work represents a preliminary performance assessment of a simulated system for Time Domain Diffuse Optical Tomography, in view of the upcoming development of a real system for breast cancer imaging, which shall feature a reduced number of sources and detectors, compact silicon-based detectors, and that shall avoid exceedingly long breast examination times. These features make the proposed system suitable to be integrated into a compact hand-held probe for breast lesion characterization (malignant vs. benign). To improve the reconstructions, morphological information will be provided by ultrasound imaging, integrating an ultrasound transducer in the probe along with the TD-DOT instrumentation. Time Domain Diffuse Optical Tomography (TD-DOT) enables a full 3D reconstruction of the optical properties of tissue, and could be used for non-invasive and cost-effective in-depth body exploration (e.g., thyroid and breast imaging). Performance quantification is crucial for comparing results coming from different implementations of this technique. A general-purpose simulation platform for TD-DOT clinical systems was developed with a focus on performance assessment through meaningful figures of merit. The platform was employed for assessing the feasibility and characterizing a compact hand-held probe for breast imaging and characterization in reflectance geometry. Important parameters such as hardware gating of the detector, photon count rate and inclusion position were investigated. Results indicate a reduced error (<10%) on the absorption coefficient quantification of a simulated inclusion up to 2-cm depth if a photon count rate ≥ 106 counts per second is used along with a good localization (error < 1 mm down to 25 mm-depth). [ABSTRACT FROM AUTHOR]

• FD-DOT is demonstrated for nondestructive detection of underlying lesions of apple. • 10 mm cylindrical moldy lesion in apple at controlled center depth was identified. • Freeform lesions in 8 grossly unremarkable apples were identified. • Condition of identifying moldy-core is discussed based on Contrast-detail-analysis. Nondestructive tomographic identification of underlying moldy lesions of apple is demonstrated experimentally, for the first time, by using frequency domain diffuse optical tomography (FD-DOT). The custom applicator-probe had 18 optodes distributed on a spheroid apple-size imaging domain. The 12 source channels were time-multiplexed to a laser source modulated at 110 MHz, and the 6 detector channels were individually conditioned for parallel heterodyning at 10 kHz. The iterative image reconstruction was performed without priors in an open-source finite-element-method (FEM) package with custom meshing of the imaging domain. Cylindrical moldy lesions in apple at controlled center depths ranging from 10 mm to 35 mm were established using 10 mm diameter cylinder inclusions harvested from mildew flesh, and freeform lesions in apple were developed by injecting colonies of Alternaria alternate. The moldy lesions not deeper than 20 mm from the peel were resolvable on the absorption images. The moldy lesions were unremarkable on the reduced scattering images. Contrast-detail-analysis is also performed in simulation to assess the condition of identifying a moldy-core lesion by FD-DOT. [ABSTRACT FROM AUTHOR]

Diffuse optical tomography (DOT) is a promising noninvasive imaging modality and is capable of providing functional characteristics of biological tissue by quantifying optical parameters. The DOT image reconstruction is ill-posed and ill-conditioned, due to the highly diffusive nature of light propagation in biological tissues and limited boundary measurements. The widely used regularization technique for DOT image reconstruction is Tikhonov regularization, which tends to yield oversmoothed and low-quality images containing severe artifacts. It is necessary to accurately choose a regularization parameter for Tikhonov regularization. To overcome these limitations, we develop a noniterative reconstruction method, whereby optical properties are recovered based on a back-propagation neural network (BPNN). We train the parameters of BPNN before DOT image reconstruction based on a set of training data. DOT image reconstruction is achieved by implementing a single evaluation of the trained network. To demonstrate the performance of the proposed algorithm, we compare with the conventional Tikhonov regularization-based reconstruction method. The experimental results demonstrate that image quality and quantitative accuracy of reconstructed optical properties are significantly improved with the proposed algorithm. [ABSTRACT FROM AUTHOR]

Ultrasound (US) guided diffuse optical tomography has demonstrated great potential for breast cancer diagnosis, treatment monitoring, and chemotherapy response prediction. Optical measurements of four different wavelengths are used to reconstruct unknown optical absorption maps, which are then used to calculate the hemoglobin concentration distribution of the US visible lesion. Reconstructed absorption maps are prone to image artifacts from outliers in measurement data from tissue heterogeneity, bad coupling between tissue and light guides, and motion by patient or operator. We propose an automated iterative perturbation correction algorithm to reduce image artifacts based on the structural similarity index (SSIM) of absorption maps of four optical wavelengths. The initial image is estimated from the truncated pseudoinverse solution. The SSIM was calculated for each wavelength to assess its similarity with other wavelengths. An absorption map is repeatedly reconstructed and projected back into measurement space to quantify projection error. Outlier measurements with highest projection errors are iteratively removed until all wavelength images are structurally similar with SSIM values greater than a threshold. Clinical data demonstrate statistically significant improvement in image artifact reduction. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Preterm infants (born at 24–34 weeks of gestational age) suffer from a high incidence of neurological complications. Cerebrovascular lesions (intraventricular hemorrhages, IVH, and ischemic injury) due to the immaturity of the vascular system and its inability to adapt to the extra-uterine environment are the major causes of adverse neurological outcomes. We investigated the feasibility of assessing cerebrovascular status in preterm infants using a novel non-invasive optical procedure, pulse-DOT, usable within the incubator. Pulse-DOT, validated in adults, provides estimates of cerebral arterial status based on optical measurements of the pulse wave. These measurements are taken with a high-density optode montage and provide accurate spatial and temporal information. We found that two pulse parameters (pulse relaxation function, PReFx, and pulse rise time, PRT) in the investigated frontotemporal region, correlated with infant's age at recording, indexing cerebrovascular development. Moreover, PRT differentiated infants with and without concurrent IVH (sensitivity = 100%, specificity = 70%). These values are at least as high as those of the resistivity index obtained with transcranial Doppler of the middle cerebral artery, the current clinical method of choice for investigating arterial elasticity in preterm infants. This makes pulse-DOT a promising tool for investigating cerebrovascular risk factors and related pathologies in preterm infants. [ABSTRACT FROM AUTHOR]

Diffuse optical tomography (DOT) is an emerging modality that reconstructs the optical properties in a highly scattering medium from measured boundary data. One way to solve DOT and recover the quantities of interest is by an inverse problem approach, which requires the choice of an optimization algorithm for the iterative approximation of the solution. However, the well-established and proven fact of the no free lunch principle holds in general. This paper aims to compare the behavior of three gradient descent-based optimizers on solving the DOT inverse problem by running randomized simulation and analyzing the generated data in order to shade light on any significant difference—if existing at all—in performance among these optimizers in our specific context of DOT. The major practical problems when selecting or using an optimization algorithm in a production context for a DOT system is to be confident that the algorithm will have a high convergence rate to the true solution, reasonably fast speed and high quality of the reconstructed image in terms of good localization of the inclusions and good agreement with the true image. In this work, we harnessed carefully designed randomized simulations to tackle the practical problem of choosing the right optimizer with the right parameters in the context of practical DOT applications, and derived statistical results concerning rate of convergence, speed, and quality of image reconstruction. The statistical analysis performed on the generated data and the main results for convergence rate, reconstruction speed, and quality between three optimization algorithms are presented in the paper at hand.

Near-infrared diffuse optical tomography is a non-invasive photonics-based imaging technology suited to functional brain imaging applications. Recent developments have proved that it is possible to build a compact time-domain diffuse optical tomography system based on silicon photomultipliers (SiPM) detectors. The system presented in this paper was equipped with the same eight SiPM probe-hosted detectors, but was upgraded with six injection fibers to shine the sample at several points. Moreover, an automatic switch was included enabling a complete measurement to be performed in less than one second. Further, the system was provided with a dual-wavelength (670 n m and 820 n m ) light source to quantify the oxy- and deoxy-hemoglobin concentration evolution in the tissue. This novel system was challenged against a solid phantom experiment, and two in-vivo tests, namely arm occlusion and motor cortex brain activation. The results show that the tomographic system makes it possible to follow the evolution of brain activation over time with a 1 s -resolution.

This work reviews physical concepts, technologies and applications of time-domain diffuse optics based on time-gated single-photon detection. This particular photon detection strategy is of the utmost importance in the diffuse optics field as it unleashes the full power of the time-domain approach by maximizing performances in terms of contrast produced by a localized perturbation inside the scattering medium, signal-to-noise ratio, measurement time and dynamic range, penetration depth and spatial resolution. The review covers 15 years of theoretical studies, technological progresses, proof of concepts and design of laboratory systems based on time-gated single-photon detection with also few hints on other fields where the time-gated detection strategy produced and will produce further impact.

Highlights • We proposed a procedure for personalized fNIRS investigations. • We developed a method to estimate the optimal optode positions over target brain regions. • Optodes will be attached with a clinical adhesive. • Personalized fNIRS montages allowed accurate local reconstructions along the cortex. • The procedure will allow conducting studies under realistic lifestyle conditions. Abstract Background Application of functional Near InfraRed Spectroscopy (fNIRS) in neurology is still limited as a good optical coupling and optimized optode coverage of specific brain regions remains challenging, notably for prolonged monitoring. Methods We propose to evaluate a new procedure allowing accurate investigation of specific brain regions. The procedure consists in: (i) A priori maximization of spatial sensitivity of fNIRS measurements targeting specific brain regions, while reducing the number of applied optodes in order to decrease installation time and improve subject comfort. (ii) Utilization of a 3D neuronavigation device and usage of collodion to glue optodes on the scalp, ensuring good optical contact for prolonged investigations. (iii) Local reconstruction of the hemodynamic activity along the cortical surface using inverse modelling. Results Using realistic simulations, we demonstrated that maps derived from optimal montage acquisitions showed, after reconstruction, spatial resolution only slightly lower to that of ultra high density montages while significantly reducing the number of optodes. The optimal montages provided overall good quantitative accuracy especially at the peak of the spatially reconstructed map. We also evaluated real motor responses in two healthy subjects and obtained reproducible motor responses over different sessions. Comparison with existing methods We are among the first to propose a mathematical optimization strategy, allowing high sensitivity measurements. Conclusions Our results support that using personalized optimal montages should allow to conduct accurate fNIRS studies in clinical settings and realistic lifestyle conditions. [ABSTRACT FROM AUTHOR]

The image reconstruction algorithm of diffuse optical tomography (DOT) is based on the diffusion equation and involves both the forward problem and inverse solution. The forward problem solves the diffusion equation using the finite element method for calculating the transmitted light distribution under the condition of presumed light source and optical coefficient. The inverse solution reconstructs the optical property coefficient distribution using Newton's method. The work within this study develops an image reconstruction algorithm for frequency-domain DOT. A numerical simulations approach to light propagation in the tissue is conducted, while the optical property is reconstructed employing data around the boundary. We implement different designated simulation cases, including different contrast ratios of absorption and reduced scattering coefficient of inclusion with respect to the background used for verifying the results of the forward problem and the developed reconstruction algorithm. Reconstruction results indicate that the quality of reconstructed images can be effective for screening breast cancer. [ABSTRACT FROM AUTHOR]

We introduce the FullMonte tetrahedral 3-D Monte Carlo (MC) software package for simulation, visualization, and analysis of light propagation in heterogeneous turbid media including tissue. It provides the highest computational performance and richest set of input, output, and analysis facilities of any open-source tetrahedral- mesh MC light simulator. It also provides a robust framework for statistical verification. A scripting interface makes set-up of simulation runs simple, including parameter sweeps, while simultaneously providing customization options. Data formats shared with class-leading visualization tools, VTK and Paraview, facilitate interactive generation of publication-quality fluence and irradiance maps. The simulator can read and write file formats supported by other similar simulators, such as TIM-OS, MMC, COMSOL (finite-element simulations), and MCML to support comparison. Where simulator features permit, FullMonte can take a single test case, run it in multiple software packages, and load the results together for comparison. Example meshes, optical properties, set-up scripts, and output files are provided for user convenience. We demonstrate its use in several test cases, including photodynamic therapy of the brain, bioluminescence imaging (BLI) in a mouse phantom, and a comparison against MCML for layered geometries. Application domains that can benefit from use of FullMonte include photodynamic, photothermal, and photobiomodulation therapies, BLI, diffuse optical tomography, MC software development, and biophotonics education. Since MC results may be used for preclinical or even clinical experiments, a robust and rigorous verification process is essential. Being a stochastic numerical method, MC simulation has unique challenges associated with verification of output results since observed differences may be due simply to output variance or actual differences in expected output. We describe and have implemented a rigorous and statistically justified framework for comparing between simulators of the same class and for performing regression testing. [ABSTRACT FROM AUTHOR]

The brain is a central component of cognitive and physical human performance. Measures, including functional brain activation, cerebral perfusion, cerebral oxygenation, evoked electrical responses, and resting hemodynamic and electrical activity are all related to, or can predict, health status or performance decrements. However, measuring brain physiology typically requires large, stationary machines that are not suitable for mobile or self-monitoring. Moreover, when individuals are ambulatory, systemic physiological fluctuations- e.g., in heart rate, blood pressure, skin perfusion, and more-can interfere with noninvasive brain measurements. In efforts to address the physiological monitoring and performance assessment needs for astronauts during spaceflight, we have developed easy-to-use, wearable prototypes, such as NINscan, for near-infrared scanning, which can collect synchronized multimodal physiology data, including hemodynamic deep-tissue imaging (including brain and muscles), electroencephalography, electrocardiography, electromyography, electrooculography, accelerometry, gyroscopy, pressure, respiration, and temperature measurements. Given their self-contained and portable nature, these devices can be deployed in a much broader range of settings-including austere environments- thereby, enabling a wider range of novel medical and research physiology applications. We review these, including high-altitude assessments, self-deployable multimodal e.g., (polysomnographic) recordings in remote or low-resource environments, fluid shifts in variable-gravity, or spaceflight analog environments, intracranial brain motion during high-impact sports, and long-duration monitoring for clinical symptom-capture in various clinical conditions. In addition to further enhancing sensitivity and miniaturization, advanced computational algorithms could help support real-time feedback and alerts regarding performance and health. [ABSTRACT FROM AUTHOR]

Advances in epilepsy studies have shown that specific changes in hemodynamics precede and accompany seizure onset and propagation. However, it has been challenging to noninvasively detect these changes in real time and in humans, due to the lack of fast functional neuroimaging tools. In this study, we present a functional diffuse optical tomography (DOT) method with the guidance of an anatomical human head atlas for 3‐dimensionally mapping the brain in real time. Central to our DOT system is a human head interface coupled with a technique that can incorporate topological information of the brain surface into the DOT image reconstruction. The performance of the DOT system was tested by imaging motor tasks‐involved brain activities on N = 6 subjects (3 epilepsy patients and 3 healthy controls). We observed diffuse areas of activations from the reconstructed [HbT] images of patients, relative to more focal activations for healthy subjects. Moreover, significant pretask hemodynamic activations were also seen in the motor cortex of patients, which indicated abnormal activities persistent in the brain of an epilepsy patient. This work demonstrates that fast functional DOT is a valuable tool for noninvasive 3‐dimensional mapping of brain hemodynamics. [ABSTRACT FROM AUTHOR]

Ultrasound (US)-guided diffuse optical tomography (DOT) has demonstrated great potential for breast cancer diagnosis in which real-time or near real-time diagnosis with high accuracy is desired. We aim to use US-guided DOT to achieve an automated, fast, and accurate classification of breast lesions. We propose a two-stage classification strategy with deep learning. In the first stage, US images and histograms created from DOT perturbation measurements are combined to predict benign lesions. Then the non-benign suspicious lesions are passed through to the second stage, which combine US image features, DOT histogram features, and 3D DOT reconstructed images for final diagnosis. The first stage alone identified 73.0% of benign cases without image reconstruction. In distinguishing between benign and malignant breast lesions in patient data, the two-stage classification approach achieved an area under the receiver operating characteristic curve of 0.946, outperforming the diagnoses of all single-modality models and of a single-stage classification model that combines all US images, DOT histogram, and imaging features. The proposed two-stage classification strategy achieves better classification accuracy than single-modality-only models and a single-stage classification model that combines all features. It can potentially distinguish breast cancers from benign lesions in near real-time. [ABSTRACT FROM AUTHOR]

The paper presents the results from a study of the breast oxygen status by diffuse optical tomography (DOT). Detection of breast tissue at wavelengths of 684, 794, and 850 nm could provide information on the distribution of basic tissue chromophores: oxygenized and deoxygenized hemoglobin. Normal breast tissue was characterized by the even distribution of these compounds and stabilization of their level. In breast cancer, the distribution of oxy- and deoxyhemoglobin was noted for uneven distribution and blood oxygen saturation was lower in the projection of a tumor nodule. The blood oxygen saturation data obtained by DOT demonstrate physiological differ- ences between normal and tumor tissues in different tumor areas.

Time Domain Diffuse Optical Tomography (TD-DOT) enables a full 3D reconstruction of the optical properties of tissue, and could be used for non-invasive and cost-effective in-depth body exploration (e.g., thyroid and breast imaging). Performance quantification is crucial for comparing results coming from different implementations of this technique. A general-purpose simulation platform for TD-DOT clinical systems was developed with a focus on performance assessment through meaningful figures of merit. The platform was employed for assessing the feasibility and characterizing a compact hand-held probe for breast imaging and characterization in reflectance geometry. Important parameters such as hardware gating of the detector, photon count rate and inclusion position were investigated. Results indicate a reduced error (6 counts per second is used along with a good localization (error < 1 mm down to 25 mm-depth).

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.