Overview of diffuse optical tomography and its clinical applications

Imaging the Human Thyroid Using Three-Dimensional Diffuse Optical Tomography: A Preliminary Study

Thyroid cancer is usually diagnosed by ultrasound imaging and fine-needle aspiration biopsy. However, diagnosis of follicular thyroid carcinomas (FTC) is difficult because FTC lacks nuclear atypia and a consensus on histological interpretation. Diffuse optical tomography (DOT) offers the potential to diagnose FTC because it can measure tumor hypoxia, while image reconstruction of the thyroid is still challenging mainly due to the complex anatomical features of the neck. In this study, we attempted to solve this issue by creating a finite element model of the human neck excluding the trachea (a void region). By reconstruction of the absorption coefficients at three wavelengths, 3D tissue oxygen saturation maps of the human thyroid are obtained for the first time by DOT.

Real-time interleaved spectroscopic photoacoustic and ultrasound (PAUS) scanning with simultaneous fluence compensation and motion correction

For over two decades photoacoustic imaging has been tested clinically, but successful human trials have been limited. To enable quantitative clinical spectroscopy, the fundamental issues of wavelength-dependent fluence variations and inter-wavelength motion must be overcome. Here we propose a real-time, spectroscopic photoacoustic/ultrasound (PAUS) imaging approach using a compact, 1-kHz rate wavelength-tunable laser. Instead of illuminating tissue over a large area, the fiber-optic delivery system surrounding an US array sequentially scans a narrow laser beam, with partial PA image reconstruction for each laser pulse. The final image is then formed by coherently summing partial images. This scheme enables (i) automatic compensation for wavelength-dependent fluence variations in spectroscopic PA imaging and (ii) motion correction of spectroscopic PA frames using US speckle tracking in real-time systems. The 50-Hz video rate PAUS system is demonstrated in vivo using a murine model of labelled drug delivery.

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.

Probe-hosted large area silicon photomultiplier and high-throughput timing electronics for enhanced performance time-domain functional near-infrared spectroscopy

Two main bottlenecks prevent time-domain diffuse optics instruments to reach their maximum performances, namely the limited light harvesting capability of the detection chain and the bounded data throughput of the timing electronics. In this work, for the first time to our knowledge, we overcome both those limitations using a probe-hosted large area silicon photomultiplier detector coupled to high-throughput timing electronics. The system performances were assessed based on international protocols for diffuse optical imagers showing better figures with respect to a state-of-the-art device. As a first step towards applications, proof-of-principle in-vivo brain activation measurements demonstrated superior signal-to-noise ratio as compared to current technologies.

Data-specific mask-guided image reconstruction for diffuse optical tomography

Conventional approaches in diffuse optical tomography (DOT) image reconstruction often address the ill-posed inverse problem via regularization with a constant penalty parameter, which uniformly smooths out the solution. In this study, we present a data-specific mask-guided scheme that incorporates a prior mask constraint into the image reconstruction framework. The prior mask was created from the DOT data itself by exploiting the multi-measurement vector formulation. We accordingly propose two methods to integrate the prior mask into the reconstruction process. First, as a soft prior by exploiting a spatially varying regularization. Second, as a hard prior by imposing a region-of-interest-limited reconstruction. Furthermore, the latter method iterates between discrete and continuous steps to update the mask and optical parameters, respectively. The proposed methods showed enhanced optical contrast accuracy, improved spatial resolution, and reduced noise level in DOT reconstructed images compared with the conventional approaches such as the modified Levenberg-Marquardt approach and the l₁-regularization based sparse recovery approach.

Towards shifted position-diffuse reflectance imaging of anatomically correctly scaled human microvasculature

Due to significant advantages, the trend in the field of medical technology is moving towards minimally or even non-invasive examination methods. In this respect, optical methods offer inherent benefits, as does diffuse reflectance imaging (DRI). The present study attempts to prove the suitability of DRI—when implemented alongside a suitable setup and data evaluation algorithm—to derive information from anatomically correctly scaled human capillaries (diameter: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$10\,\upmu \hbox {m}$$\end{document}10μm, length: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$45\,\upmu \hbox {m}$$\end{document}45μm) by conducting extensive Monte–Carlo simulations and by verifying the findings through laboratory experiments. As a result, the method of shifted position-diffuse reflectance imaging (SP-DRI) is established by which average signal modulations of up to 5% could be generated with an illumination wavelength of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda =424\,\hbox {nm}$$\end{document}λ=424nm and a core diameter of the illumination fiber of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$50\,\upmu \hbox {m}$$\end{document}50μm. No reference image is needed for this technique. The present study reveals that the diffuse reflectance data in combination with the SP-DRI normalization are suitable to localize human capillaries within turbid media.

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

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

Recent Developments in Instrumentation of Functional Near-Infrared Spectroscopy Systems

In the last three decades, the development and steady improvement of various optical technologies at the near-infrared region of the electromagnetic spectrum has inspired a large number of scientists around the world to design and develop functional near-infrared spectroscopy (fNIRS) systems for various medical applications. This has been driven further by the availability of new sources and detectors that support very compact and wearable system designs. In this article, we review fNIRS systems from the instrumentation point of view, discussing the associated challenges and state-of-the-art approaches. In the beginning, the fundamentals of fNIRS systems as well as light-tissue interaction at NIR are briefly introduced. After that, we present the basics of NIR systems instrumentation. Next, the recent development of continuous-wave, frequency-domain, and time-domain fNIRS systems are discussed. Finally, we provide a summary of these three modalities and an outlook into the future of fNIRS technology.

Three-dimensional imaging through scattering media based on confocal diffuse tomography

Optical imaging techniques, such as light detection and ranging (LiDAR), are essential tools in remote sensing, robotic vision, and autonomous driving. However, the presence of scattering places fundamental limits on our ability to image through fog, rain, dust, or the atmosphere. Conventional approaches for imaging through scattering media operate at microscopic scales or require a priori knowledge of the target location for 3D imaging. We introduce a technique that co-designs single-photon avalanche diodes, ultra-fast pulsed lasers, and a new inverse method to capture 3D shape through scattering media. We demonstrate acquisition of shape and position for objects hidden behind a thick diffuser (≈6 transport mean free paths) at macroscopic scales. Our technique, confocal diffuse tomography, may be of considerable value to the aforementioned applications.

Photon transport model for dense polydisperse colloidal suspensions using the radiative transfer equation combined with the dependent scattering theory

In near-infrared imaging and spectroscopy, high-fidelity modeling of photon transport for dense polydisperse colloidal suspensions is crucial. We developed photon transport models using the radiative transfer equation (RTE) with the dependent scattering theory (DST) at volume fractions up to 20%. The polydispersity and interference effects strongly influence results of the scattering properties and the RTE in cases of small mean diameter and large variance of the particle size distribution. We compared the RTE-results for the Henyey-Greenstein (conventional) function with those for the phase function using the DST. The RTE-results differ between both functions at low volume fractions for forward scattering media, suggesting the limitation of the conventional function.

New Directions in Exercise Prescription: Is There a Role for Brain-Derived Parameters Obtained by Functional Near-Infrared Spectroscopy?

In the literature, it is well established that regular physical exercise is a powerful strategy to promote brain health and to improve cognitive performance. However, exact knowledge about which exercise prescription would be optimal in the setting of exercise–cognition science is lacking. While there is a strong theoretical rationale for using indicators of internal load (e.g., heart rate) in exercise prescription, the most suitable parameters have yet to be determined. In this perspective article, we discuss the role of brain-derived parameters (e.g., brain activity) as valuable indicators of internal load which can be beneficial for individualizing the exercise prescription in exercise–cognition research. Therefore, we focus on the application of functional near-infrared spectroscopy (fNIRS), since this neuroimaging modality provides specific advantages, making it well suited for monitoring cortical hemodynamics as a proxy of brain activity during physical exercise.

Accelerating Monte Carlo modeling of structured-light-based diffuse optical imaging via "photon sharing"

The increasing use of spatially modulated imaging and single-pixel detection techniques demands computationally efficient methods for light transport modeling. Herein, we report an easy-to-implement yet significantly more efficient Monte Carlo (MC) method for simultaneously simulating spatially modulated illumination and detection patterns accurately in 3D complex domains. We have implemented this accelerated algorithm, named "photon sharing," in our open-source MC simulators, reporting 13.6× and 5.5× speedups in mesh- and voxel-based MC benchmarks, respectively. In addition, the proposed algorithm is readily used to accelerate the solving of inverse problems in spatially modulated imaging systems by building Jacobians of all illumination-detection pattern pairs concurrently, resulting in a 12.4-fold speed improvement.

Convolutional neural network-based approach to estimate bulk optical properties in diffuse optical tomography

Deep learning has been actively investigated for various applications such as image classification, computer vision, and regression tasks, and it has shown state-of-the-art performance. In diffuse optical tomography (DOT), the accurate estimation of the bulk optical properties of a medium is paramount because it directly affects the overall image quality. In this work, we exploit deep learning to propose a novel, to the best of our knowledge, convolutional neural network (CNN)-based approach to estimate the bulk optical properties of a highly scattering medium such as biological tissue in DOT. We validated the proposed method by using experimental, as well as, simulated data. For performance assessment, we compared the results of the proposed method with those of existing approaches. The results demonstrate that the proposed CNN-based approach for bulk optical property estimation outperforms existing methods in terms of estimation accuracy, with lower computation time.

Time-Gated Single-Photon Detection in Time-Domain Diffuse Optics: A Review

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.

Mathematical and numerical challenges in optical screening of female breast

Diffuse optical tomography (DOT) is an emerging imaging technique which uses light for diagnostic purposes in a non-invasive and non-ionizing way. In this paper, we focus on DOT application to female breast screening, where the surface of the breast is illuminated by light sources and the outgoing light is collected on the surface. The comparison of measured light data with the equivalent field obtained from a relevant mathematical model yields the DOT inverse problem whose solution provides an estimate of the optical coefficients of the tissue. These latter, in turn, can be related to clinical markers for cancer detection. The goal of this work is to propose a mathematical and computational approach tailored to the concept of a DOT imaging device able to perform fast and accurate screenings at an affordable cost. Namely, we address two original points about the crucial issue of the solution of the severely ill-conditioned DOT inverse problem: (a) a computational approach based on Green's functions which do not require the exact knowledge of the tissue geometry, proposed here in the declination of the Method of Fundamental Solutions, which allows to enforce correct boundary conditions; (b) the elastic net regularization technique that shares the desirable properties of both the ℓ₂ - and ℓ₁ -norm penalization approaches and opens the possibility for sparsity recognition in the optical coefficients field and refinement procedures.

Ultrasound-modulated laser feedback tomography in the reflective mode

A novel method of ultrasound-modulated optical tomography (UOT) detection based on the laser feedback technology is proposed in this Letter. The system has advantages such as a simple structure, high sensitivity, and reflective configuration. Effective penetration depths of up to 9 cm and 5 cm in phantom and biological tissues, respectively, have been demonstrated experimentally. The detection capability is comparable with the state of the art in the transmission mode but with a much lower photon consumption. Although a lot remains to be improved, the proposed method is promising for further development toward practical applications.

Dual-slope method for enhanced depth sensitivity in diffuse optical spectroscopy

Using diffusion theory, we show that a dual-slope method is more effective than single-slope methods or single-distance methods at enhancing sensitivity to deeper tissue. The dual-slope method requires a minimum of two sources and two detectors arranged in specially configured arrays. In particular, we present diffusion theory results for a symmetrical linear array of two sources (separated by 55 mm) that sandwich two detectors (separated by 15 mm), for which dual slopes achieve maximal sensitivity at a depth of about 5 mm for direct current (DC) intensity (as measured in continuous-wave spectroscopy) and 11 mm for phase (as measured in frequency-domain spectroscopy) under typical values of the tissue optical properties (absorption coefficient: ∼0.01mm^-1, reduced scattering coefficient: ∼1mm^-1). This result is a major advance over single-distance or single-slope data, which feature maximal sensitivity to shallow tissue (<2mm for the intensity, <5mm for the phase).

Spatially-enhanced time-domain NIRS for accurate determination of tissue optical properties

A multivariate method integrating time and space resolved techniques of near-infrared spectroscopy is proposed for simultaneously retrieving the absolute quantities of optical absorption and scattering properties in tissues. The time-domain feature of photon migration is advantageously constrained and regularized by its spatially-resolved amplitude patterns in the inverse procedure. Measurements of tissue-mimicking phantoms with various optical properties are analyzed with Monte-Carlo simulations to validate the method performance. The uniqueness, stability, and uncertainty of the method are discussed.

A Mini-Review on Functional Near-Infrared Spectroscopy (fNIRS): Where Do We Stand, and Where Should We Go?

This mini-review is aimed at briefly summarizing the present status of functional near-infrared spectroscopy (fNIRS) and predicting where the technique should go in the next decade. This mini-review quotes 33 articles on the different fNIRS basics and technical developments and 44 reviews on the fNIRS applications published in the last eight years. The huge number of review articles about a wide spectrum of topics in the field of cognitive and social sciences, functional neuroimaging research, and medicine testifies to the maturity achieved by this non-invasive optical vascular-based functional neuroimaging technique. Today, fNIRS has started to be utilized on healthy subjects while moving freely in different naturalistic settings. Further instrumental developments are expected to be done in the near future to fully satisfy this latter important aspect. In addition, fNIRS procedures, including correction methods for the strong extracranial interferences, need to be standardized before using fNIRS as a clinical tool in individual patients. New research avenues such as interactive neurosciences, cortical activation modulated by different type of sport performance, and cortical activation during neurofeedback training are highlighted.

Dynamic Activation Patterns of the Motor Brain Revealed by Diffuse Optical Tomography. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2019;2019:6028-6031. [PMID: 31947220 DOI: 10.1109/embc.2019.8857370]

Diffuse optical tomography (DOT), a subset of functional near-infrared spectroscopy (fNIRS), is a noninvasive functional imaging modality for studying the human brain in normal and diseased conditions. It measures changes in concentrations of oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (Hb) in the blood vasculature of the brain. In contrast to functional magnetic resonance imaging (fMRI), the gold standard in human brain imaging, DOT offers the advantage of higher temporal resolution, portability, lower cost, multiple contrasts and usability for persons who cannot otherwise utilize MRI-based imaging modalities, including bedridden patients and infants, etc. The goal of the present study was to evaluate performance of a DOT method in studying dynamic patterns of brain activations involving motor control. CW-fNIRS data were acquired in four sessions from a healthy male participant when he performed a motor task in a block-design experiment. Results from experimental data showed pronounced activity in the primary motor cortex (M1), contralateral to the clenching hand. It was further observed that the M1 activity was consistent over four sessions. Furthermore, temporal dynamics of motor activity at each session further revealed well-sequenced activation patterns among M1, premotor cortex (PMC), and supplementary motor area (SMA). Timed ipsilateral motor activity suppression was also observed several seconds after the onset of contralateral M1 activity. More importantly, these temporal dynamics were similarly observed in all four sessions. These preliminary results suggest that the DOT method has the sensitivity, reliability, and spatio-temporal resolutions to study activities originated from the motor cortices. A full-scope evaluation and validation in more participants on the motor system can establish it as a promising neuroimaging tool to study, such as, infants at the risk of cerebral palsy or elders with Parkinson's due to its portability and usability in clinical environments.

In situ estimation of optical properties of rat and monkey brains using femtosecond time-resolved measurements

An accurate knowledge of tissue optical properties (absorption coefficients, μa, and reduced scattering coefficients, μs') is critical for precise modeling of light propagation in biological tissue, essential for developing diagnostic and therapeutic optical techniques that utilize diffusive photons. A great number of studies have explored the optical properties of various tissue, and these values are not known in detail due to difficulties in the experimental determination and significant variations in tissue constitution. Especially, in situ estimates of the optical properties of brain tissue, a common measurement target in optical imaging, is a challenge because of its layer structure (where the thin gray matter covers the white matter). Here, we report an approach to in situ estimates of the μa and μs' of the gray and white matter in living rat and monkey brains by using femtosecond time-resolved measurements and Monte Carlo simulation. The results demonstrate that the μa of the gray matter is larger than that of the white matter, while there was no significant difference in the μs' between the gray and white matter. The optical properties of the rat brain were very similar to those of the monkey brain except for the μa of the gray matter here.

Understanding near infrared spectroscopy and its application to skeletal muscle research

Near infrared spectroscopy (NIRS) is a powerful noninvasive tool with which to study the matching of oxygen delivery to oxygen utilization and the number of new publications utilizing this technique has increased exponentially in the last 20 yr. By measuring the state of oxygenation of the primary heme compounds in skeletal muscle (hemoglobin and myoglobin), greater understanding of the underlying control mechanisms that couple perfusive and diffusive oxygen delivery to oxidative metabolism can be gained from the laboratory to the athletic field to the intensive care unit or emergency room. However, the field of NIRS has been complicated by the diversity of instrumentation, the inherent limitations of some of these technologies, the associated diversity of terminology, and a general lack of standardization of protocols. This Cores of Reproducibility in Physiology (CORP) will describe in basic but important detail the most common methodologies of NIRS, their strengths and limitations, and discuss some of the potential confounding factors that can affect the quality and reproducibility of NIRS data. Recommendations are provided to reduce the variability and errors in data collection, analysis, and interpretation. The goal of this CORP is to provide readers with a greater understanding of the methodology, limitations, and best practices so as to improve the reproducibility of NIRS research in skeletal muscle.

Applications of Functional Near-Infrared Spectroscopy (fNIRS) Neuroimaging in Exercise⁻Cognition Science: A Systematic, Methodology-Focused Review

For cognitive processes to function well, it is essential that the brain is optimally supplied with oxygen and blood. In recent years, evidence has emerged suggesting that cerebral oxygenation and hemodynamics can be modified with physical activity. To better understand the relationship between cerebral oxygenation/hemodynamics, physical activity, and cognition, the application of state-of-the art neuroimaging tools is essential. Functional near-infrared spectroscopy (fNIRS) is such a neuroimaging tool especially suitable to investigate the effects of physical activity/exercises on cerebral oxygenation and hemodynamics due to its capability to quantify changes in the concentration of oxygenated hemoglobin (oxyHb) and deoxygenated hemoglobin (deoxyHb) non-invasively in the human brain. However, currently there is no clear standardized procedure regarding the application, data processing, and data analysis of fNIRS, and there is a large heterogeneity regarding how fNIRS is applied in the field of exercise⁻cognition science. Therefore, this review aims to summarize the current methodological knowledge about fNIRS application in studies measuring the cortical hemodynamic responses during cognitive testing (i) prior and after different physical activities interventions, and (ii) in cross-sectional studies accounting for the physical fitness level of their participants. Based on the review of the methodology of 35 as relevant considered publications, we outline recommendations for future fNIRS studies in the field of exercise⁻cognition science.

Measurement of tissue optical properties in the context of tissue optical clearing

Nowadays, dynamically developing optical (photonic) technologies play an ever-increasing role in medicine. Their adequate and effective implementation in diagnostics, surgery, and therapy needs reliable data on optical properties of human tissues, including skin. This paper presents an overview of recent results on the measurements and control of tissue optical properties. The issues reported comprise a brief review of optical properties of biological tissues and efficacy of optical clearing (OC) method in application to monitoring of diabetic complications and visualization of blood vessels and microcirculation using a number of optical imaging technologies, including spectroscopic, optical coherence tomography, and polarization- and speckle-based ones. Molecular modeling of immersion OC of skin and specific technique of OC of adipose tissue by its heating and photodynamic treatment are also discussed.

Optically derived metabolic and hemodynamic parameters predict hippocampal neurogenesis in the BTBR mouse model of autism

In this study, we made use of dual-wavelength laser speckle imaging (DW-LSI) to assess cerebral blood flow (CBF) in the BTBR-genetic mouse model of autism spectrum disorder, as well as control (C57Bl/6J) mice. Since the deficits in social behavior demonstrated by BTBR mice are attributed to changes in neural tissue structure and function, we postulated that these changes can be detected optically using DW-LSI. BTBR mice demonstrated reductions in both CBF and cerebral oxygen metabolism (CMRO₂ ), as suggested by studies using conventional neuroimaging technologies to reflect impaired neuronal activation and cognitive function. To validate the monitoring of CBF by DW-LSI, measurements with laser Doppler flowmetry (LDF) were also performed which confirmed the lowered CBF in the autistic-like group. Furthermore, we found in vivo cortical CBF measurements to predict the rate of hippocampal neurogenesis, measured ex vivo by the number of neurons expressing doublecortin or the cellular proliferation marker Ki-67 in the dentate gyrus, with a strong positive correlation between CBF and neurogenesis markers (Pearson, r = 0.78; 0.9, respectively). These novel findings identifying cortical CBF as a predictive parameter of hippocampal neurogenesis highlight the power and flexibility of the DW-LSI and LDF setups for studying neurogenesis trends under normal and pathological conditions.

Investigation of the sensitivity of functional near-infrared spectroscopy brain imaging to anatomical variations in 5- to 11-year-old children

Functional near-infrared spectroscopy (fNIRS) is a noninvasive brain imaging technique that uses scalp-placed light sensors to measure evoked changes in cerebral blood oxygenation. The portability, low overhead cost, and ability to use this technology under a wide range of experimental environments make fNIRS well-suited for studies involving infants and children. However, since fNIRS does not directly provide anatomical or structural information, these measurements may be sensitive to individual or group level differences associated with variations in head size, depth of the brain from the scalp, or other anatomical factors affecting the penetration of light into the head. This information is generally not available in pediatric populations, which are often the target of study for fNIRS. Anatomical magnetic resonance imaging information from 90 school-age children (5 to 11 years old) was used to quantify the expected effect on fNIRS measures of variations in cerebral and extracerebral structure. Monte Carlo simulations of light transport in tissue were used to estimate differential and partial optical pathlengths at 690, 780, 808, 830, and 850 nm and their variations with age, sex, and head size. This work provides look-up tables of these values and general guidance for future investigations using fNIRS sans anatomical information in this child population.

Imaging Considerations and Interprofessional Opportunities in the Care of Breast Cancer Patients in the Neoadjuvant Setting

OBJECTIVE

To discuss standard-of-care and emerging imaging techniques employed for screening and detection, diagnosis and staging, monitoring response to therapy, and guiding cancer treatments.

DATA SOURCES

Published journal articles indexed in the National Library of Medicine database and relevant websites.

CONCLUSION

Imaging plays a fundamental role in the care of cancer patients and specifically, breast cancer patients in the neoadjuvant setting, providing an excellent opportunity for interprofessional collaboration between oncologists, researchers, radiologists, and oncology nurses. Quantitative imaging strategies to assess cellular, molecular, and vascular characteristics within the tumor is needed to better evaluate initial diagnosis and treatment response.

IMPLICATIONS FOR NURSING PRACTICE

Nurses caring for patients in all settings must continue to seek education on emerging imaging techniques. Oncology nurses provide education about the test, ensure the patient has appropriate pre-testing instructions, and manage patient expectations about timing of results availability.

Collagen quantification in breast tissue using a 12-wavelength near infrared spectral tomography (NIRST) system

A portable near infrared spectral tomography (NIRST) system was adapted for breast cancer detection and treatment monitoring with improved speed of acquisition for parallel 12 wavelengths of parallel frequency-domain (FD) and continuous-wavelength (CW) measurement. Using a novel gain adjustment scheme in the Photomultiplier Tube detectors (PMTs), the data acquisition time for simultaneous acquisition involving three FD and three CW wavelengths, has been reduced from 90 to 55 seconds, while signal variation was also reduced from 2.1% to 1.1%. Tomographic images of breast collagen content have been recovered for the first time, and image reconstruction approaches with and without collagen content included have been validated in simulation studies and normal subject exams. Simulations indicate that including collagen content into the reconstruction procedure can significantly reduce the overestimation in total hemoglobin, water and lipid by 8.9μM, 1.8% and 15.8%, respectively, and underestimates in oxygen saturation by 9.5%, given an average 10% background collagen content. A breast cancer patient with invasive ductal carcinoma was imaged and the reconstructed images show that the recovered tumor/background contrast in total hemoglobin increased from 1.5 to 1.7 when collagen was included in reconstruction.

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.

Geometrically complex 3D-printed phantoms for diffuse optical imaging

Tissue-equivalent phantoms that mimic the optical properties of human and animal tissues are commonly used in diffuse optical imaging research to characterize instrumentation or evaluate an image reconstruction method. Although many recipes have been produced for generating solid phantoms with specified absorption and transport scattering coefficients at visible and near-infrared wavelengths, the construction methods are generally time-consuming and are unable to create complex geometries. We present a method of generating phantoms using a standard 3D printer. A simple recipe was devised which enables printed phantoms to be produced with precisely known optical properties. To illustrate the capability of the method, we describe the creation of an anatomically accurate, tissue-equivalent premature infant head optical phantom with a hollow brain space based on MRI atlas data. A diffuse optical image of the phantom is acquired when a high contrast target is inserted into the hollow space filled with an aqueous scattering solution.

Roadmap on neurophotonics

Mechanistic understanding of how the brain gives rise to complex behavioral and cognitive functions is one of science's grand challenges. The technical challenges that we face as we attempt to gain a systems-level understanding of the brain are manifold. The brain's structural complexity requires us to push the limit of imaging resolution and depth, while being able to cover large areas, resulting in enormous data acquisition and processing needs. Furthermore, it is necessary to detect functional activities and 'map' them onto the structural features. The functional activity occurs at multiple levels, using electrical and chemical signals. Certain electrical signals are only decipherable with sub-millisecond timescale resolution, while other modes of signals occur in minutes to hours. For these reasons, there is a wide consensus that new tools are necessary to undertake this daunting task. Optical techniques, due to their versatile and scalable nature, have great potentials to answer these challenges. Optical microscopy can now image beyond the diffraction limit, record multiple types of brain activity, and trace structural features across large areas of tissue. Genetically encoded molecular tools opened doors to controlling and detecting neural activity using light in specific cell types within the intact brain. Novel sample preparation methods that reduce light scattering have been developed, allowing whole brain imaging in rodent models. Adaptive optical methods have the potential to resolve images from deep brain regions. In this roadmap article, we showcase a few major advances in this area, survey the current challenges, and identify potential future needs that may be used as a guideline for the next steps to be taken.