Noninvasive determination of the optical properties of two-layered turbid media

Statistics of maximum photon penetration depth in a two-layer diffusive medium

We present numerical results for the probability density function f(z) and for the mean value of photon maximum penetration depth ‹zmax› in a two-layer diffusive medium. Both time domain and continuous wave regime are considered with several combinations of the optical properties (absorption coefficient, reduced scattering coefficient) of the two layers, and with different geometrical configurations (source detector distance, thickness of the upper layer). Practical considerations on the design of time domain and continuous wave systems are derived. The methods and the results are of interest for many research fields such as biomedical optics and advanced microscopy.

Principles, developments, and applications of spatially resolved spectroscopy in agriculture: a review

Agriculture is the primary source of human survival, which provides the most basic living and survival conditions for human beings. As living standards continue to improve, people are also paying more attention to the quality and safety of agricultural products. Therefore, the detection of agricultural product quality is very necessary. In the past decades, the spectroscopy technique has been widely used because of its excellent results in agricultural quality detection. However, traditional spectral inspection methods cannot accurately describe the internal information of agricultural products. With the continuous research and development of optical properties, it has been found that the internal quality of an object can be better reflected by separating the properties of light, such as its absorption and scattering properties. In recent years, spatially resolved spectroscopy has been increasingly used in the field of agricultural product inspection due to its simple compositional structure, low-value cost, ease of operation, efficient detection speed, and outstanding ability to obtain information about agricultural products at different depths. It can also separate optical properties based on the transmission equation of optics, which allows for more accurate detection of the internal quality of agricultural products. This review focuses on the principles of spatially resolved spectroscopy, detection equipment, analytical methods, and specific applications in agricultural quality detection. Additionally, the optical properties methods and direct analysis methods of spatially resolved spectroscopy analysis methods are also reported in this paper.

Real-time and accurate estimation ex vivo of four basic optical properties from thin tissue based on a cascade forward neural network

Double integrating sphere measurements obtained from thin ex vivo tissues provides more spectral information and hence allows full estimation of all basic optical properties (OPs) theoretically. However, the ill-conditioned nature of the OP determination increases excessively with the reduction in tissue thickness. Therefore, it is crucial to develop a model for thin ex vivo tissues that is robust to noise. Herein, we present a deep learning solution to precisely extract four basic OPs in real-time from thin ex vivo tissues, leveraging a dedicated cascade forward neural network (CFNN) for each OP with an additional introduced input of the refractive index of the cuvette holder. The results show that the CFNN-based model enables accurate and fast evaluation of OPs, as well as robustness to noise. Our proposed method overcomes the highly ill-conditioned restriction of OP evaluation and can distinguish the effects of slight changes in measurable quantities without any a priori knowledge.

Handheld diffuse reflectance spectroscopy system for noninvasive quantification of neonatal bilirubin and hemoglobin concentrations: a pilot study

The prevalence rate of neonatal jaundice can reach 80%, of which 5% may develop dangerous hemolytic jaundice. The blood test for obtaining bilirubin and hemoglobin concentration is the gold standard for diagnosing hemolytic jaundice; however, frequently drawing blood from jaundice neonates for the screening purpose is not practical. We have developed a handheld diffuse reflectance spectroscopy system to noninvasively determine the bilirubin and hemoglobin levels in neonates. Our study showed that the correlation coefficients were 0.95 and 0.80 for bilirubin and hemoglobin between the results from the blood tests and our handheld system, respectively. This handheld system could be an effective tool for screening hemolytic jaundice.

Efficient computation of the steady-state and time-domain solutions of the photon diffusion equation in layered turbid media

Accurate and efficient forward models of photon migration in heterogeneous geometries are important for many applications of light in medicine because many biological tissues exhibit a layered structure of independent optical properties and thickness. However, closed form analytical solutions are not readily available for layered tissue-models, and often are modeled using computationally expensive numerical techniques or theoretical approximations that limit accuracy and real-time analysis. Here, we develop an open-source accurate, efficient, and stable numerical routine to solve the diffusion equation in the steady-state and time-domain for a layered cylinder tissue model with an arbitrary number of layers and specified thickness and optical coefficients. We show that the steady-state ([Formula: see text] ms) and time-domain ([Formula: see text] ms) fluence (for an 8-layer medium) can be calculated with absolute numerical errors approaching machine precision. The numerical implementation increased computation speed by 3 to 4 orders of magnitude compared to previously reported theoretical solutions in layered media. We verify our solutions asymptotically to homogeneous tissue geometries using closed form analytical solutions to assess convergence and numerical accuracy. Approximate solutions to compute the reflected intensity are presented which can decrease the computation time by an additional 2-3 orders of magnitude. We also compare our solutions for 2, 3, and 5 layered media to gold-standard Monte Carlo simulations in layered tissue models of high interest in biomedical optics (e.g. skin/fat/muscle and brain). The presented routine could enable more robust real-time data analysis tools in heterogeneous tissues that are important in many clinical applications such as functional brain imaging and diffuse optical spectroscopy.

Quantifying the Cerebral Hemometabolic Response to Blood Transfusion in Pediatric Sickle Cell Disease With Diffuse Optical Spectroscopies

Red blood cell transfusions are common in patients with sickle cell disease who are at increased risk of stroke. Unfortunately, transfusion thresholds needed to sufficiently dilute sickle red blood cells and adequately restore oxygen delivery to the brain are not well defined. Previous work has shown that transfusion is associated with a reduction in oxygen extraction fraction and cerebral blood flow, both of which are abnormally increased in sickle patients. These reductions are thought to alleviate hemometabolic stress by improving the brain's ability to respond to increased metabolic demand, thereby reducing susceptibility to ischemic injury. Monitoring the cerebral hemometabolic response to transfusion may enable individualized management of transfusion thresholds. Diffuse optical spectroscopies may present a low-cost, non-invasive means to monitor this response. In this study, children with SCD undergoing chronic transfusion therapy were recruited. Diffuse optical spectroscopies (namely, diffuse correlation spectroscopy combined with frequency domain near-infrared spectroscopy) were used to quantify oxygen extraction fraction (OEF), cerebral blood volume (CBV), an index of cerebral blood flow (CBF_i), and an index of cerebral oxygen metabolism (CMRO_2i) in the frontal cortex immediately before and after transfusion. A subset of patients receiving regular monthly transfusions were measured during a subsequent transfusion. Data was captured from 35 transfusions in 23 patients. Transfusion increased median blood hemoglobin levels (Hb) from 9.1 to 11.7 g/dL (p < 0.001) and decreased median sickle hemoglobin (HbS) from 30.9 to 21.7% (p < 0.001). Transfusion decreased OEF by median 5.9% (p < 0.001), CBFi by median 21.2% (p = 0.020), and CBV by median 18.2% (p < 0.001). CMRO_2i did not statistically change from pre-transfusion levels (p > 0.05). Multivariable analysis revealed varying degrees of associations between outcomes (i.e., OEF, CBF_i, CBV, and CMRO_2i), Hb, and demographics. OEF, CBF_i, and CBV were all negatively associated with Hb, while CMRO_2i was only associated with age. These results demonstrate that diffuse optical spectroscopies are sensitive to the expected decreases of oxygen extraction, blood flow, and blood volume after transfusion. Diffuse optical spectroscopies may be a promising bedside tool for real-time monitoring and goal-directed therapy to reduce stroke risk for sickle cell disease.

Diffused reflectance measurements to detect tattoo ink location in skin using the crossover point

Tattoos are highly trendy in western culture, but many people regret their tattoos for many reasons. It is essential to be aware of the ink location in advance to reduce the long and short-term side effects. In this study, diffuse reflectance (DR) experiments were conducted on two-layer (2L) tissue-mimicking phantoms, where ink was sandwiched between the layers. An appreciable difference in the DR profile was found between the 2L phantom with and without the tattoo ink using the crossover point (Cp) method. Our technique was applied to ex vivo porcine skin. A point of intersection was found, between the skin and the tattooed skin. In the shorter wavelengths (500-600 nm), a distinguishable 2L behavior was found, and in longer wavelengths (600-850 nm), a single layer behavior was found between the tattooed skin before and after the intersection. In biological tissue, this Cp indeed finds the tattoo ink without harm to the surrounding skin.

Multispectral snapshot imaging of skin microcirculatory hemoglobin oxygen saturation using artificial neural networks trained on in vivo data

SIGNIFICANCE

Developing algorithms for estimating blood oxygenation from snapshot multispectral imaging (MSI) data is challenging due to the complexity of sensor characteristics and photon transport modeling in tissue. We circumvent this using a method where artificial neural networks (ANNs) are trained on in vivo MSI data with target values from a point-measuring reference method.

AIM

To develop and evaluate a methodology where a snapshot filter mosaic camera is utilized for imaging skin hemoglobin oxygen saturation (SO2), using ANNs.

APPROACH

MSI data were acquired during occlusion provocations. ANNs were trained to estimate SO2 with MSI data as input, targeting data from a validated probe-based reference system. Performance of ANNs with different properties and training data sets was compared.

RESULTS

The method enables spatially resolved estimation of skin tissue SO2. Results are comparable to those acquired using a Monte-Carlo-based approach when relevant training data are used.

CONCLUSIONS

Training an ANN on in vivo MSI data covering a wide range of target values acquired during an occlusion protocol enable real-time estimation of SO2 maps. Data from the probe-based reference system can be used as target despite differences in sampling depth and measurement position.

Robustness of diffuse reflectance spectra analysis by inverse adding doubling algorithm

Analysing diffuse reflectance spectra to extract properties of biological tissue requires modelling of light transport within the tissue, considering its absorption, scattering, and geometrical properties. Due to the layered skin structure, skin tissue models are often divided into multiple layers with their associated optical properties. Typically, in the analysis, some model parameters defining these properties are fixed to values reported in the literature to speed up the fitting process and improve its performance. In the absence of consensus, various studies use different approaches in fixing the model parameters. This study aims to assess the effect of fixing various model parameters in the skin spectra fitting process on the accuracy and robustness of a GPU-accelerated two-layer inverse adding-doubling (IAD) algorithm. Specifically, the performance of the IAD method is determined for noiseless simulated skin spectra, simulated spectra with different levels of noise applied, and in-vivo measured reflectance spectra from hyperspectral images of human hands recorded before, during, and after the arterial occlusion. Our results suggest that fixing multiple parameters to a priori known values generally improves the robustness and accuracy of the IAD algorithm for simulated spectra. However, for in-vivo measured spectra, these values are unknown in advance and fixing optical parameters to incorrect values significantly deteriorates the overall performance. Therefore, we propose a method to improve the fitting performance by pre-estimating model parameters. Our findings could be considered in all future research involving the analysis of diffuse reflectance spectra to extract optical properties of skin tissue.

Accuracy of retrieving optical properties from liquid tissue phantoms using a single integrating sphere

Using integrating spheres (ISs) in conjunction with the inverse adding-doubling algorithm (IAD) offers a well-established, rigorous protocol for determining optical absorption (μ_a) and reduced scattering (μs') coefficients of thin, optically homogeneous, turbid media. Here, we report the performance and use of a single IS system for experimentally retrieving optical properties in phantom media whose optical properties were well controlled. The IS system was used to measure the total reflectance and transmittance between 500 and 800 nm in liquid phantoms that were prepared to span a wide range of optical scattering and absorption coefficients. Measurements on phantoms were sequentially made using one of two broadband light sources-a halogen lamp or a supercontinuum laser. We report on the accuracy of IAD-derived optical coefficients using IS measurements made on phantoms-directly or by employing one of two previously reported correction methods. The first (sample-substitution error) correction was experimentally achieved while the second used Monte Carlo-based corrections with IAD. When experimentally calibrated reflectance and transmittance values were directly used as inputs to the IAD, mean absolute errors in recovered optical coefficients were larger than 0.4cm^-1 for absorption and more than 6cm^-1 for scattering across all phantoms and wavelengths measured. These errors reduced to 0.06-0.17cm^-1 and 0.7-2cm^-1 for μ_a and μs', respectively, with the use of corrections. Choice of light sources used, sample geometry (relative to optical coefficients), signal-to-noise of measurements, and the selection of correction methods are discussed.

Bottom layer absorption coefficients extraction from two-layer phantoms based on crossover point in diffuse reflectance

SIGNIFICANCE

Numerous optical imaging and spectroscopy techniques are used to study the tissue-optical properties; the majority of them are limited in information regarding the penetration depth. A simple, safe, easily applicable diagnostic technique is required to get deeper tissue information in a multilayer structure.

AIM

A fiber-based diffuse reflectance (DR) technique is used to extract and quantify the bottom layer absorption coefficients in two-layer (2L) tissue-mimicking solid phantoms. We determine the Indian black ink concentrations in a deep-hidden layer that is sandwiched between agar and silicone-based phantom layers.

APPROACH

A fiber-based DR experiment was performed to study the optical properties of the tissue at higher penetration depth, with different fiber core diameters and a constant numerical aperture (0.5 NA). The optimal core diameter of the fiber was chosen by measuring solid phantoms. In 2L phantoms, the thickness of the top layer was kept 5.5 mm with a constant absorption and reduced scattering coefficients (μa  =  0.045  mm  -  1 and μs  '    =  2.622  mm  -  1), whereas the absorption coefficients of the bottom layers were varied from 0.014 to 0.037  mm  -  1 keeping the μs  '   the same as the top layer. A unique crossover point (Cp) was found in the DR intensity profile against distance. We examined the slope before and after the Cp. These two slopes indicate the difference between the optical properties of the top and bottom layers. Our technique got further verification, as we successfully determined the Cp with different Indian black ink concentrations, placed at the junction between the agar and silicone-based phantom layers.

RESULTS

The DR measurements were applied to 2L phantoms. Two different slopes were found in 2L phantoms compared to the one-layer (optical properties equal to the top layer of 2L). We extracted the slopes before and after the Cp in the 2L phantoms. The calculated absorption coefficients before the Cp were 0.014  ±  0.0004, 0.022  ±  0.0003, 0.028  ±  0.0003, and 0.036  ±  0.0014  mm  -  1, and the absorption coefficients after the Cp were 0.019  ±  0.0013, 0.013  ±  0.0004, 0.014  ±  0.0006, and 0.031  ±  0.0001  mm  -  1, respectively. The calculated absorption coefficients before the Cp were in good agreement with the optical properties of the bottom layer. The calculated absorption coefficients after the Cp were not the same as the top layer. Our DR system successfully determines the crossover points 12.14  ±  0.11 and 11.73  ±  0.15  mm for 70% and 100% ink concentrations placed at the junction of the agar and silicone layers.

CONCLUSIONS

In a 2L tissue structure, the Cp depends on the absorption coefficients of top and bottom layers and the thickness of the top layer. With the help of the Cp and the absorption coefficients, one can determine the thickness of the top layer or vice versa. The slope value before the Cp in the DR profile allowed us to determine the absorption properties of the bottom layer instead of having the average behavior of the 2L phantom in the far detection range (11.0 to 17.0 mm).

Compressed sensing time-resolved spectrometer for quantification of light absorbers in turbid media

Time-resolved (TR) spectroscopy is well-suited to address the challenges of quantifying light absorbers in highly scattering media such as living tissue; however, current TR spectrometers are either based on expensive array detectors or rely on wavelength scanning. Here, we introduce a TR spectrometer architecture based on compressed sensing (CS) and time-correlated single-photon counting. Using both CS and basis scanning, we demonstrate that-in homogeneous and two-layer tissue-mimicking phantoms made of Intralipid and Indocyanine Green-the CS method agrees with or outperforms uncompressed approaches. Further, we illustrate the superior depth sensitivity of TR spectroscopy and highlight the potential of the device to quantify absorption changes in deeper (>1 cm) tissue layers.

Cerebral blood volume increment after resuscitation measured by near-infrared time-resolved spectroscopy can estimate degree of hypoxic-ischemic insult in newborn piglets

Neonatal hypoxic–ischemic encephalopathy is a notable cause of neonatal death and developmental disabilities. To achieve better outcomes, it is important in treatment strategy selection to categorize the degree of hypoxia ischemia and evaluate dose response. In an asphyxia piglet model with histopathological brain injuries that we previously developed, animals survived 5 days after insult and showed changes in cerebral blood volume (CBV) that reflected the severity of injuries. However, little is known about the relationship between changes in CBV during and after insult. In this study, an HI event was induced by varying the amount and timing of inspired oxygen in 20 anesthetized piglets. CBV was measured using near-infrared time-resolved spectroscopy before, during, and 6 h after insult. Change in CBV was calculated as the difference between the peak CBV value during insult and the value at the end of insult. The decrease in CBV during insult was found to correlate with the increase in CBV within 6 h after insult. Heart rate exhibited a similar tendency to CBV, but blood pressure did not. Because the decrement in CBV was larger in severe HI, the CBV increment immediately after insult is considered useful for assessing degree of HI insult.

Sensitivity of frequency-domain optical measurements to brain hemodynamics: simulations and human study of cerebral blood flow during hypercapnia

This study characterizes the sensitivity of noninvasive measurements of cerebral blood flow (CBF) by using frequency-domain near-infrared spectroscopy (FD-NIRS) and coherent hemodynamics spectroscopy (CHS). We considered six FD-NIRS methods: single-distance intensity and phase (SDI and SDϕ), single-slope intensity and phase (SSI and SSϕ), and dual-slope intensity and phase (DSI and DSϕ). Cerebrovascular reactivity (CVR) was obtained from the relative change in measured CBF during a step hypercapnic challenge. Greater measured values of CVR are assigned to a greater sensitivity to cerebral hemodynamics. In a first experiment with eight subjects, CVRSDϕ was greater than CVRSDI (p < 0.01), whereas CVRDSI and CVRDSϕ showed no significant difference (p > 0.5). In a second experiment with four subjects, a 5 mm scattering layer was added between the optical probe and the scalp tissue to increase the extracerebral layer thickness (L ec ), which caused CVRDSϕ to become significantly greater than CVRDSI (p < 0.05). CVRSS measurements yielded similar results as CVRDS measurements but with a greater variability, possibly resulting from instrumental artifacts in SS measurements. Theoretical simulations with two-layered media confirmed that, if the top (extracerebral) layer is more scattering than the bottom (brain) layer, the relative values of CVRDSI and CVRDSϕ depend on L ec . Specifically, the sensitivity to the brain is greater for DSI than DSϕ for a thin extracerebral layer (L ec < 13 mm), whereas it is greater for DSϕ than DSI for a thicker extracerebral layer.

New nonlocal forward model for diffuse optical tomography

The forward model in diffuse optical tomography (DOT) describes how light propagates through a turbid medium. It is often approximated by a diffusion equation (DE) that is numerically discretized by the classical finite element method (FEM). We propose a nonlocal diffusion equation (NDE) as a new forward model for DOT, the discretization of which is carried out with an efficient graph-based numerical method (GNM). To quantitatively evaluate the new forward model, we first conduct experiments on a homogeneous slab, where the numerical accuracy of both NDE and DE is compared against the existing analytical solution. We further evaluate NDE by comparing its image reconstruction performance (inverse problem) to that of DE. Our experiments show that NDE is quantitatively comparable to DE and is up to 64% faster due to the efficient graph-based representation that can be implemented identically for geometries in different dimensions. The proposed discretization method can be easily applied to other imaging techniques like diffuse correlation spectroscopy which are normally modeled by the diffusion equation.

Extended Perfusion Parameter Estimation from Hyperspectral Imaging Data for Bedside Diagnostic in Medicine

Background: Hyperspectral Imaging (HSI) has a strong potential to be established as a new contact-free measuring method in medicine. Hyperspectral cameras and data processing have to fulfill requirements concerning practicability and validity to be integrated in clinical routine processes. Methods: Calculating physiological parameters which are of significant clinical value from recorded remission spectra is a complex challenge. We present a data processing method for HSI remission spectra based on a five-layer model of perfused tissue that generates perfusion parameters for every layer and presents them as depth profiles. The modeling of the radiation transport and the solution of the inverse problem are based on familiar approximations, but use partially heuristic methods for efficiency and to fulfill practical clinical requirements. Results: The parameter determination process is consistent, as the measured spectrum is practically completely reproducible by the modeling sequence; in other words, the whole spectral information is transformed into model parameters which are easily accessible for physiological interpretation. The method is flexible enough to be applicable on a wide spectrum of skin and wounds. Examples of advanced procedures utilizing extended perfusion representation in clinical application areas (flap control, burn diagnosis) are presented.

Hyper-spectral Recovery of Cerebral and Extra-Cerebral Tissue Properties Using Continuous Wave Near-Infrared Spectroscopic Data

Near-infrared spectroscopy (NIRS) is widely used as a non-invasive method to monitor the hemodynamics of biological tissue. A common approach of NIRS relies on continuous wave (CW) methodology, i.e. utilizing intensity-only measurements, and, in general, assumes homogeneity in the optical properties of the biological tissue. However, in monitoring cerebral hemodynamics within humans, this assumption is not valid due to complex layered structure of the head. The NIRS signal that contains information about cerebral blood hemoglobin levels is also contaminated with extra-cerebral tissue hemodynamics, and any recovery method based on such a priori homogenous approximation would lead to erroneous results. In this work, utilization of hyper-spectral intensity only measurements (i.e., CW) at multiple distances are presented and are shown to recover two-layered tissue properties along with the thickness of top layer, using an analytical solution for a two-layered semi-infinite geometry. It is demonstrated that the recovery of tissue oxygenation index (TOI) of both layers can be achieved with an error of 4.4%, with the recovered tissue thickness of 4% error. When the data is measured on a complex tissue such as the human head, it is shown that the semi-infinite recovery model can lead to uncertain results, whereas, when using an appropriate model accounting for the tissue-boundary structure, the tissue oxygenation levels are recovered with an error of 4.2%, and the extra-cerebral tissue thickness with an error of 11.8%. The algorithm is finally used together with human subject data, demonstrating robustness in application and repeatability in the recovered parameters that adhere well to expected published parameters.

Hyperspectral imaging of human skin aided by artificial neural networks

We developed a compact, hand-held hyperspectral imaging system for 2D neural network-based visualization of skin chromophores and blood oxygenation. State-of-the-art micro-optic multichannel matrix sensor combined with the tunable Fabry-Perot micro interferometer enables a portable diagnostic device sensitive to the changes of the oxygen saturation as well as the variations of blood volume fraction of human skin. Generalized object-oriented Monte Carlo model is used extensively for the training of an artificial neural network utilized for the hyperspectral image processing. In addition, the results are verified and validated via actual experiments with tissue phantoms and human skin in vivo. The proposed approach enables a tool combining both the speed of an artificial neural network processing and the accuracy and flexibility of advanced Monte Carlo modeling. Finally, the results of the feasibility studies and the experimental tests on biotissue phantoms and healthy volunteers are presented.

Spatial frequency domain imaging in 2019: principles, applications, and perspectives

Spatial frequency domain imaging (SFDI) has witnessed very rapid growth over the last decade, owing to its unique capabilities for imaging optical properties and chromophores over a large field-of-view and in a rapid manner. We provide a comprehensive review of the principles of this imaging method as of 2019, review the modeling of light propagation in this domain, describe acquisition methods, provide an understanding of the various implementations and their practical limitations, and finally review applications that have been published in the literature. Importantly, we also introduce a group effort by several key actors in the field for the dissemination of SFDI, including publications, advice in hardware and implementations, and processing code, all freely available online.

Head model based on the shape of the subject's head for optical brain imaging

Optical imaging methods such as near-infrared spectroscopy and diffuse optical tomography rely on models to solve the inverse problem. Imaging an adult human head also requires a head model. Using a model, which makes describing the structure of the head better, leads to acquiring a more accurate absorption map. Here, by combining the key features of layered slab models and head atlases, we introduce a new two-layered head model that is based on the surface geometry of the subject's head with variable thickness of the superficial layer. Using the Monte Carlo approach, we assess the performance of our model for fitting the optical properties from simulated time-resolved data of the adult head in a null distance source-detector configuration. Using our model, we observed improved results at 70 percent of the locations on the head and an overall 20 percent reduction in relative error compared to layered slab model.

Spatial frequency domain imaging in 2019: principles, applications, and perspectives

Spatial frequency domain imaging (SFDI) has witnessed very rapid growth over the last decade, owing to its unique capabilities for imaging optical properties and chromophores over a large field-of-view and in a rapid manner. We provide a comprehensive review of the principles of this imaging method as of 2019, review the modeling of light propagation in this domain, describe acquisition methods, provide an understanding of the various implementations and their practical limitations, and finally review applications that have been published in the literature. Importantly, we also introduce a group effort by several key actors in the field for the dissemination of SFDI, including publications, advice in hardware and implementations, and processing code, all freely available online.

A stepwise method for estimating optical properties of two-layer turbid media from spatial-frequency domain reflectance

This research was conducted to estimate the optical absorption and reduced scattering coefficients of two-layer turbid media using a stepwise method from the spatial-frequency domain reflectance generated by Monte Carlo (MC) simulation. The stepwise method's feasibility for optical property estimations was first investigated by comparing the reflectance generated by the diffusion model and MC simulation for one-layer and two-layer turbid media. The results showed that, with proper frequency selection, the one-layer model could be used for estimating the optical properties of the first layer of the two-layer turbid media. A sample-based calibration method was proposed for calibrating discrepancies of the reflectance between the diffusion model and MC simulation. This significantly improved the parameter estimation accuracy. Results showed that the stepwise method's parameter estimation efficacy and accuracy were much better than that for the one-step method. This was especially true when estimating the absorption coefficient. Absolute error contour maps were generated in order to determine the constraining conditions for the first-layer thickness. It was found that, when each layer's optical properties are within the range of 0.005 mm^-1 ≤ μa ≤ 0.04 mm^-1 and 0.69 mm^-1 ≤ μs'≤ 2.2 mm^-1, the first-layer's minimum thickness-for which the first layer's optical properties could be accurately estimated-could be as small as 0.2 mm. Further, the first layer's maximum thickness could not exceed 2.0 mm, in order to have acceptable estimations of the optical properties of the second layer.

Estimation of free hemoglobin concentrations in blood bags by diffuse reflectance spectroscopy

Free hemoglobin (FHB) concentration is considered a prospect quality indicator for erythrocyte suspensions (ES) under storage. Storage lesions alter the optical properties of ES and can be monitored by diffuse reflectance spectroscopy. Due to storage lesions, erythrocytes lyse and release hemoglobin into the extracellular medium. The purpose of the study is to model and assess the quality of ES units in a blood bank with diffuse reflectance measurements together with hematological variables reflecting absorption and scattering characteristics of ES. FHB concentrations were modeled based on the increased scattering in the extracellular medium. A semiempirical model was used for relating optical properties of ES to the diffuse reflectance measurements. The attenuation in the blood bag was computed and its influence was discarded via normalization, in accordance with Monte Carlo simulations. In the experiments, 40 ES units were measured multiple times during prolonged storage of 70 days. A generalized linear model was used for modeling the training set, and, in the validation, the highest correlation coefficient between predicted and actual FHB concentrations was 0.89. Predicting the actual value was accurate at a maximum level of R2  =  0.80. The error rate of the model in diagnosing the true quality was about 10%.

Recovery of layered tissue optical properties from spatial frequency-domain spectroscopy and a deterministic radiative transport solver

We present a method to recover absorption and reduced scattering spectra for each layer of a two-layer turbid media from spatial frequency-domain spectroscopy data. We focus on systems in which the thickness of the top layer is less than the transport mean free path   (  0.1  -  0.8l  *    )  . We utilize an analytic forward solver, based upon the N'th-order spherical harmonic expansion with Fourier decomposition   (  SHEFN  )   method in conjunction with a multistage inverse solver. We test our method with data obtained using spatial frequency-domain spectroscopy with 32 evenly spaced wavelengths within λ  =  450 to 1000 nm on six-layered tissue phantoms with distinct optical properties. We demonstrate that this approach can recover absorption and reduced scattering coefficient spectra for both layers with accuracy comparable with current Monte Carlo methods but with lower computational cost and potential flexibility to easily handle variations in parameters such as the scattering phase function or material refractive index. To our knowledge, this approach utilizes the most accurate deterministic forward solver used in such problems and can successfully recover properties from a two-layer media with superficial layer thicknesses.

Review of structured light in diffuse optical imaging

Diffuse optical imaging probes deep living tissue enabling structural, functional, metabolic, and molecular imaging. Recently, due to the availability of spatial light modulators, wide-field quantitative diffuse optical techniques have been implemented, which benefit greatly from structured light methodologies. Such implementations facilitate the quantification and characterization of depth-resolved optical and physiological properties of thick and deep tissue at fast acquisition speeds. We summarize the current state of work and applications in the three main techniques leveraging structured light: spatial frequency-domain imaging, optical tomography, and single-pixel imaging. The theory, measurement, and analysis of spatial frequency-domain imaging are described. Then, advanced theories, processing, and imaging systems are summarized. Preclinical and clinical applications on physiological measurements for guidance and diagnosis are summarized. General theory and method development of tomographic approaches as well as applications including fluorescence molecular tomography are introduced. Lastly, recent developments of single-pixel imaging methodologies and applications are reviewed.

Time-resolved near infrared light propagation using frequency domain superposition

Time-resolved temporal point spread function (TPSF) measurement of near infrared spectroscopic (NIRS) data allows the estimation of absorption and reduced scattering properties of biological tissues. Such analysis requires an iterative calculation of the theoretical TPSF curve using mathematical and computational models of the domain being imaged which are computationally complex and expensive. In this work, an efficient methodology for representing the TPSF data using a superposition of cosines calculated in frequency domain is presented. The proposed method is outlined and tested on finite element realistic models of the human neck and head. Using an adult head model containing ~140k nodes, the TPSF calculation at each node for one source is accelerated from 3.11 s to 1.29 s within an error limit of ± 5% related to the time domain calculation method.

Quantification of extra-cerebral and cerebral hemoglobin concentrations during physical exercise using time-domain near infrared spectroscopy

Fitness is known to have beneficial effects on brain anatomy and function. However, the understanding of mechanisms underlying immediate and long-term neurophysiological changes due to exercise is currently incomplete due to the lack of tools to investigate brain function during physical activity. In this study, we used time-domain near infrared spectroscopy (TD-NIRS) to quantify and discriminate extra-cerebral and cerebral hemoglobin concentrations and oxygen saturation (SO₂) in young adults at rest and during incremental intensity exercise. In extra-cerebral tissue, an increase in deoxy-hemoglobin (HbR) and a decrease in SO₂ were observed while only cerebral HbR increased at high intensity exercise. Results in extra-cerebral tissue are consistent with thermoregulatory mechanisms to dissipate excess heat through skin blood flow, while cerebral changes are in agreement with cerebral blood flow (CBF) redistribution mechanisms to meet oxygen demand in activated regions during exercise. No significant difference was observed in oxy- (HbO₂) and total hemoglobin (HbT). In addition HbO₂, HbR and HbT increased with subject's peak power output (equivalent to the maximum oxygen volume consumption; VO₂ peak) supporting previous observations of increased total mass of red blood cells in trained individuals. Our results also revealed known gender differences with higher hemoglobin in men. Our approach in quantifying both extra-cerebral and cerebral absolute hemoglobin during exercise may help to better interpret past and future continuous-wave NIRS studies that are prone to extra-cerebral contamination and allow a better understanding of acute cerebral changes due to physical exercise.

Chemotherapeutic drug-specific alteration of microvascular blood flow in murine breast cancer as measured by diffuse correlation spectroscopy

The non-invasive, in vivo measurement of microvascular blood flow has the potential to enhance breast cancer therapy monitoring. Here, longitudinal blood flow of 4T1 murine breast cancer (N=125) under chemotherapy was quantified with diffuse correlation spectroscopy based on layer models. Six different treatment regimens involving doxorubicin, cyclophosphamide, and paclitaxel at clinically relevant doses were investigated. Treatments with cyclophosphamide increased blood flow as early as 3 days after administration, whereas paclitaxel induced a transient blood flow decrease at 1 day after administration. Early blood flow changes correlated strongly with the treatment outcome and distinguished treated from untreated mice individually for effective treatments.

Pressure modulation algorithm to separate cerebral hemodynamic signals from extracerebral artifacts

We introduce and validate a pressure measurement paradigm that reduces extracerebral contamination from superficial tissues in optical monitoring of cerebral blood flow with diffuse correlation spectroscopy (DCS). The scheme determines subject-specific contributions of extracerebral and cerebral tissues to the DCS signal by utilizing probe pressure modulation to induce variations in extracerebral blood flow. For analysis, the head is modeled as a two-layer medium and is probed with long and short source-detector separations. Then a combination of pressure modulation and a modified Beer-Lambert law for flow enables experimenters to linearly relate differential DCS signals to cerebral and extracerebral blood flow variation without a priori anatomical information. We demonstrate the algorithm's ability to isolate cerebral blood flow during a finger-tapping task and during graded scalp ischemia in healthy adults. Finally, we adapt the pressure modulation algorithm to ameliorate extracerebral contamination in monitoring of cerebral blood oxygenation and blood volume by near-infrared spectroscopy.

In-vivo multilaboratory investigation of the optical properties of the human head

The in-vivo optical properties of the human head are investigated in the 600-1100 nm range on different subjects using continuous wave and time domain diffuse optical spectroscopy. The work was performed in collaboration with different research groups and the different techniques were applied to the same subject. Data analysis was carried out using homogeneous and layered models and final results were also confirmed by Monte Carlo simulations. The depth sensitivity of each technique was investigated and related to the probed region of the cerebral tissue. This work, based on different validated instruments, is a contribution to fill the existing gap between the present knowledge and the actual in-vivo values of the head optical properties.

Estimation and imaging of breast lesions using a two-layer tissue structure by ultrasound-guided optical tomography

A new two-step estimation and imaging method is developed for a two-layer breast tissue structure consisting of a breast tissue layer and a chest wall underneath. First, a smaller probe with shorter distance source-detector pairs was used to collect the reflected light mainly from the breast tissue layer. Then, a larger probe with 9×14 source-detector pairs and a centrally located ultrasound transducer was used to collect reflected light from the two-layer tissue structure. The data collected from the smaller probe were used to estimate breast tissue optical properties. With more accurate estimation of the average breast tissue properties, the second layer properties can be assessed from data obtained from the larger probe. Using this approach, the unknown variables have been reduced from four to two and the estimated bulk tissue optical properties are more accurate and robust. In addition, a two-step reconstruction using a genetic algorithm and conjugate gradient method is implemented to simultaneously reconstruct the absorption and reduced scattering maps of targets inside a two-layer tissue structure. Simulations and phantom experiments have been performed to validate the new reconstruction method, and a clinical example is given to demonstrate the feasibility of this approach.

Impact of one-layer assumption on diffuse reflectance spectroscopy of skin

Diffuse reflectance spectroscopy (DRS) can be used to noninvasively measure skin properties. To extract skin properties from DRS spectra, you need a model that relates the reflectance to the tissue properties. Most models are based on the assumption that skin is homogenous. In reality, skin is composed of multiple layers, and the homogeneity assumption can lead to errors. In this study, we analyze the errors caused by the homogeneity assumption. This is accomplished by creating realistic skin spectra using a computational model, then extracting properties from those spectra using a one-layer model. The extracted parameters are then compared to the parameters used to create the modeled spectra. We used a wavelength range of 400 to 750 nm and a source detector separation of 250 μm. Our results show that use of a one-layer skin model causes underestimation of hemoglobin concentration [Hb] and melanin concentration [mel]. Additionally, the magnitude of the error is dependent on epidermal thickness. The one-layer assumption also causes [Hb] and [mel] to be correlated. Oxygen saturation is overestimated when it is below 50% and underestimated when it is above 50%. We also found that the vessel radius factor used to account for pigment packaging is correlated with epidermal thickness.

Influence of nanoparticles accumulation on optical properties of human normal and cancerous liver tissue in vitro estimated by OCT

In this work, the potential use of nanoparticles as contrast agents by using spectral domain optical coherence tomography (SD-OCT) in liver tissue was demonstrated. Gold nanoparticles (average size of 25 and 70 nm), were studied in human normal and cancerous liver tissues in vitro, respectively. Each sample was monitored with SD-OCT functional imaging for 240 min. Continuous OCT monitoring showed that, after application of gold nanoparticles, the OCT signal intensities of normal liver and cancerous liver tissue both increase with time, and the larger nanoparticles tend to produce a greater signal enhancement in the same type of tissue. The results show that the values of attenuation coefficients have significant differences between normal liver tissue and cancerous liver tissue. In addition, 25 nm gold nanoparticles allow higher penetration depth than 70 nm gold nanoparticles in liver tissues.

Automatic diagnosis of melanoma using machine learning methods on a spectroscopic system

Background

Early and accurate diagnosis of melanoma, the deadliest type of skin cancer, has the potential to reduce morbidity and mortality rate. However, early diagnosis of melanoma is not trivial even for experienced dermatologists, as it needs sampling and laboratory tests which can be extremely complex and subjective. The accuracy of clinical diagnosis of melanoma is also an issue especially in distinguishing between melanoma and mole. To solve these problems, this paper presents an approach that makes non-subjective judgements based on quantitative measures for automatic diagnosis of melanoma.

Methods

Our approach involves image acquisition, image processing, feature extraction, and classification. 187 images (19 malignant melanoma and 168 benign lesions) were collected in a clinic by a spectroscopic device that combines single-scattered, polarized light spectroscopy with multiple-scattered, un-polarized light spectroscopy. After noise reduction and image normalization, features were extracted based on statistical measurements (i.e. mean, standard deviation, mean absolute deviation, L₁ norm, and L₂ norm) of image pixel intensities to characterize the pattern of melanoma. Finally, these features were fed into certain classifiers to train learning models for classification.

Results

We adopted three classifiers – artificial neural network, naïve bayes, and k-nearest neighbour to evaluate our approach separately. The naive bayes classifier achieved the best performance - 89% accuracy, 89% sensitivity and 89% specificity, which was integrated with our approach in a desktop application running on the spectroscopic system for diagnosis of melanoma.

Conclusions

Our work has two strengths. (1) We have used single scattered polarized light spectroscopy and multiple scattered unpolarized light spectroscopy to decipher the multilayered characteristics of human skin. (2) Our approach does not need image segmentation, as we directly probe tiny spots in the lesion skin and the image scans do not involve background skin. The desktop application for automatic diagnosis of melanoma can help dermatologists get a non-subjective second opinion for their diagnosis decision.

Robust estimation of cerebral hemodynamics in neonates using multilayered diffusion model for normal and oblique incidences

The diffusion approximation is useful for many optical diagnostics modalities, such as near-infrared spectroscopy. However, the simple normal incidence, semi-infinite layer model may prove lacking in estimation of deep-tissue optical properties such as required for monitoring cerebral hemodynamics, especially in neonates. To answer this need, we present an analytical multilayered, oblique incidence diffusion model. Initially, the model equations are derived in vector-matrix form to facilitate fast and simple computation. Then, the spatiotemporal reflectance predicted by the model for a complex neonate head is compared with time-resolved Monte Carlo (TRMC) simulations under a wide range of physiologically feasible parameters. The high accuracy of the multilayer model is demonstrated in that the deviation from TRMC simulations is only a few percent even under the toughest conditions. We then turn to solve the inverse problem and estimate the oxygen saturation of deep brain tissues based on the temporal and spatial behaviors of the reflectance. Results indicate that temporal features of the reflectance are more sensitive to deep-layer optical parameters. The accuracy of estimation is shown to be more accurate and robust than the commonly used single-layer diffusion model. Finally, the limitations of such approaches are discussed thoroughly.

Measurement of the time of flight of photons into the skin: influence of site, age and gender, correlation with other skin parameters

BACKGROUND/PURPOSE

The speed of light (time of flight) into the skin is obviously relied to its structure, and might appear as a tool for non-invasive investigation of skin physico-chemical properties, among them aging is of primary importance. Though already published, such time of flight measurements have never been extensively correlated with other well-documented skin parameters such as localization, the influence of gender and age, the elasticity and roughness, and the water trans-epidermal diffusion (TEWL).

METHODS

A specific practical device was designed to routinely measure the time of flight (TOF) of the light into the human skin 'in vivo', in a totally non-invasive process. This system was tested on volunteers, to relate the TOF parameter to the widely investigated skin properties already mentioned. An Infra-red laser at 1064 nm delivered powerful pulses of less than 1 ns duration, sent to the skin surface through a lossless fibre. The light backscattered at a given distance was collected and led onto an Avalanche Photodiode, and the mean TOF was measured on a fast sampling scope. A resolution and a reproducibility of a few picoseconds has been achieved. Experiments were carried out on 100 volunteers of both gender, aged from 18 to 65, on 12 different locations.

RESULTS

No matter age and gender, important variations of TOF according to the localization were observed: On the inner forearm, an increase from wrist to elbow, and much higher values on the forehead and neck, whether orientation parallel or perpendicular to Langer lines did not appear significant. Ageing appeared to increase the TOF on forehead and neck, while this effect could not be confirmed on the forearm. Usual skin parameters such as elasticity, roughness and TEWL have been compared to TOF on the same location for each volunteer: TOF and skin roughness were significantly anti-correlated, i.e. the TOF got shorter when the Roughness increased, while a striking correlation was observed between TEWL and TOF.

CONCLUSION

These results assert the dependence of TOF on the nature of the skin upper layers (roughness, water diffusion) and on the dermis layer (ageing), and show the potential capabilities offered by TOF to investigate deeply into the skin structure. They have to be confirmed through further experiments, involving measurements at shorter wavelengths, at which the light path into the skin is much smaller, to get a distribution of the TOF inside the tissue.

Reliable recovery of the optical properties of multi-layer turbid media by iteratively using a layered diffusion model at multiple source-detector separations

Accurately determining the optical properties of multi-layer turbid media using a layered diffusion model is often a difficult task and could be an ill-posed problem. In this study, an iterative algorithm was proposed for solving such problems. This algorithm employed a layered diffusion model to calculate the optical properties of a layered sample at several source-detector separations (SDSs). The optical properties determined at various SDSs were mutually referenced to complete one round of iteration and the optical properties were gradually revised in further iterations until a set of stable optical properties was obtained. We evaluated the performance of the proposed method using frequency domain Monte Carlo simulations and found that the method could robustly recover the layered sample properties with various layer thickness and optical property settings. It is expected that this algorithm can work with photon transport models in frequency and time domain for various applications, such as determination of subcutaneous fat or muscle optical properties and monitoring the hemodynamics of muscle.

Convolution model of the diffuse reflectance for layered tissues

We present an explicit model for the diffuse reflectance due to a collimated beam of light incident normally on layered tissues. This model is derived using the corrected diffusion approximation applied to a layered medium, and it takes the form of a convolution with an explicit kernel and the incident beam profile. This model corrects the standard diffusion approximation over all source-detector separation distances provided the beam is sufficiently wide compared to the scattering mean free path. We validate this model through comparison with Monte Carlo simulations. Then we use this model to estimate the optical properties of an epithelial layer from Monte Carlo simulation data. Using measurements at small source-detector separations and this model, we are able to estimate the absorption coefficient, scattering coefficient, and anisotropy factor of epithelial tissues efficiently with reasonable accuracy.

Comparison of a layered slab and an atlas head model for Monte Carlo fitting of time-domain near-infrared spectroscopy data of the adult head

Near-infrared spectroscopy (NIRS) estimations of the adult brain baseline optical properties based on a homogeneous model of the head are known to introduce significant contamination from extracerebral layers. More complex models have been proposed and occasionally applied to in vivo data, but their performances have never been characterized on realistic head structures. Here we implement a flexible fitting routine of time-domain NIRS data using graphics processing unit based Monte Carlo simulations. We compare the results for two different geometries: a two-layer slab with variable thickness of the first layer and a template atlas head registered to the subject's head surface. We characterize the performance of the Monte Carlo approaches for fitting the optical properties from simulated time-resolved data of the adult head. We show that both geometries provide better results than the commonly used homogeneous model, and we quantify the improvement in terms of accuracy, linearity, and cross-talk from extracerebral layers.

Verification of a two-layer inverse Monte Carlo absorption model using multiple source-detector separation diffuse reflectance spectroscopy

A two-layer Monte Carlo lookup table-based inverse model is validated with two-layered phantoms across physiologically relevant optical property ranges. Reflectance data for source-detector separations of 370 μm and 740 μm were collected from these two-layered phantoms and top layer thickness, reduced scattering coefficient and the top and bottom layer absorption coefficients were extracted using the inverse model and compared to the known values. The results of the phantom verification show that this method is able to accurately extract top layer thickness and scattering when the top layer thickness ranges from 0 to 550 μm. In this range, top layer thicknesses were measured with an average error of 10% and the reduced scattering coefficient was measured with an average error of 15%. The accuracy of top and bottom layer absorption coefficient measurements was found to be highly dependent on top layer thickness, which agrees with physical expectation; however, within appropriate thickness ranges, the error for absorption properties varies from 12-25%.

Optical characterization of two-layered turbid media for non-invasive, absolute oximetry in cerebral and extracerebral tissue

We introduce a multi-distance, frequency-domain, near-infrared spectroscopy (NIRS) method to measure the optical coefficients of two-layered media and the thickness of the top layer from diffuse reflectance measurements. This method features a direct solution based on diffusion theory and an inversion procedure based on the Levenberg-Marquardt algorithm. We have validated our method through Monte Carlo simulations, experiments on tissue-like phantoms, and measurements on the forehead of three human subjects. The Monte Carlo simulations and phantom measurements have shown that, in ideal two-layered samples, our method accurately recovers the top layer thickness (L), the absorption coefficient (µ a ) and the reduced scattering coefficient (µ' s ) of both layers with deviations that are typically less than 10% for all parameters. Our method is aimed at absolute measurements of hemoglobin concentration and saturation in cerebral and extracerebral tissue of adult human subjects, where the top layer (layer 1) represents extracerebral tissue (scalp, skull, dura mater, subarachnoid space, etc.) and the bottom layer (layer 2) represents cerebral tissue. Human subject measurements have shown a significantly greater total hemoglobin concentration in cerebral tissue (82±14 µM) with respect to extracerebral tissue (30±7 µM). By contrast, there was no significant difference between the hemoglobin saturation measured in cerebral tissue (56%±10%) and extracerebral tissue (62%±6%). To our knowledge, this is the first time that an inversion procedure in the frequency domain with six unknown parameters with no other prior knowledge is used for the retrieval of the optical coefficients and top layer thickness with high accuracy on two-layered media. Our absolute measurements of cerebral hemoglobin concentration and saturation are based on the discrimination of extracerebral and cerebral tissue layers, and they can enhance the impact of NIRS for cerebral hemodynamics and oxygenation assessment both in the research arena and clinical practice.

Lawrence K. Improving the depth sensitivity of time-resolved measurements by extracting the distribution of times-of-flight

Time-resolved (TR) techniques provide a means of discriminating photons based on their time-of-flight. Since early arriving photons have a lower probability of probing deeper tissue than photons with long time-of-flight, time-windowing has been suggested as a method for improving depth sensitivity. However, TR measurements also contain instrument contributions (instrument-response-function, IRF), which cause temporal broadening of the measured temporal point-spread function (TPSF) compared to the true distribution of times-of-flight (DTOF). The purpose of this study was to investigate the influence of the IRF on the depth sensitivity of TR measurements. TPSFs were acquired on homogeneous and two-layer tissue-mimicking phantoms with varying optical properties. The measured IRF and TPSFs were deconvolved using a stable algorithm to recover the DTOFs. The microscopic Beer-Lambert law was applied to the TPSFs and DTOFs to obtain depth-resolved absorption changes. In contrast to the DTOF, the latest part of the TPSF was not the most sensitive to absorption changes in the lower layer, which was confirmed by computer simulations. The improved depth sensitivity of the DTOF was illustrated in a pig model of the adult human head. Specifically, it was shown that dynamic absorption changes obtained from the late part of the DTOFs recovered from TPSFs acquired by probes positioned on the scalp were similar to absorption changes measured directly on the brain. These results collectively demonstrate that this method improves the depth sensitivity of TR measurements by removing the effects of the IRF.

Extended hierarchical Bayesian diffuse optical tomography for removing scalp artifact

Functional near-infrared spectroscopy (fNIRS) can non-invasively measure hemodynamic responses in the cerebral cortex with a portable apparatus. However, the observation signal in fNIRS measurements is contaminated by the artifact signal from the hemodynamic response in the scalp. In this paper, we propose a method to separate the signals from the cortex and the scalp by estimating both hemodynamic changes by diffuse optical tomography (DOT). In the inverse problem of DOT, we introduce smooth regularization to the hemodynamic change in the scalp and sparse regularization to that in the cortex based on the nature of the hemodynamic responses. These appropriate regularization models, with the spatial information of optical paths of many measurement channels, allow three-dimensional reconstruction of both hemodynamic changes. We validate our proposed method through two-layer phantom experiments and MRI-based head-model simulations. In both experiments, the proposed method simultaneously estimates the superficial smooth activity in the scalp area and the deep localized activity in the cortical area.

Accurate optical parameter extraction procedure for broadband near-infrared spectroscopy of brain matter

Modeling behavior of broadband (30 to 1000 MHz) frequency modulated near-infrared (NIR) photons through a phantom is the basis for accurate extraction of optical absorption and scattering parameters of biological turbid media. Photon dynamics in a phantom are predicted using both analytical and numerical simulation and are related to the measured insertion loss (IL) and insertion phase (IP) for a given geometry based on phantom optical parameters. Accuracy of the extracted optical parameters using finite element method (FEM) simulation is compared to baseline analytical calculations from the diffusion equation (DE) for homogenous brain phantoms. NIR spectroscopy is performed using custom-designed, broadband, free-space optical transmitter (Tx) and receiver (Rx) modules that are developed for photon migration at wavelengths of 680, 780, and 820 nm. Differential detection between two optical Rx locations separated by 0.3 cm is employed to eliminate systemic artifacts associated with interfaces of the optical Tx and Rx with the phantoms. Optical parameter extraction is achieved for four solid phantom samples using the least-square-error method in MATLAB (for DE) and COMSOL (for FEM) simulation by fitting data to measured results over broadband and narrowband frequency modulation. Confidence in numerical modeling of the photonic behavior using FEM has been established here by comparing the transmission mode's experimental results with the predictions made by DE and FEM for known commercial solid brain phantoms.

Detectability of absorption and reduced scattering coefficients in frequency-domain measurements using a realistic head phantom

Detection limits of the changes in absorption and reduced scattering coefficients were investigated using a frequency-domain near-infrared system in a realistic head phantom. The results were quantified in terms of the maximum detectable depth for different activation volumes in the range of 0.8-20 microliters. The non-linear relation between the maximum detectable depth and the magnitude of changes in the absorption coefficient conform well with the Born approximation to the diffusion equation. The minimal detectable changes in the reduced scattering coefficient measured in terms of the phase signal were found to be approximately twice as large as that of the absorption coefficient using the AC signal for the same volume and at the same depth. The phase delay, which can be used to quantify the fast neuronal optical response in the human brain, showed a linear dependence on the reciprocal of the reduced scattering coefficient, as predicted by the Rytov approximation.

In vivo absorption spectroscopy for absolute measurement

In in vivo spectroscopy, there are differences between individual subjects in parameters such as tissue scattering and sample concentration. We propose a method that can provide the absolute value of a particular substance concentration, independent of these individual differences. Thus, it is not necessary to use the typical statistical calibration curve, which assumes an average level of scattering and an averaged concentration over individual subjects. This method is expected to greatly reduce the difficulties encountered during in vivo measurements. As an example, for in vivo absorption spectroscopy, the method was applied to the reflectance measurement in retinal vessels to monitor their oxygen saturation levels. This method was then validated by applying it to the tissue phantom under a variety of absorbance values and scattering efficiencies.