Distinction of directional coupling in sensorimotor networks between active and passive finger movements using fNIRS

The purpose of this study is to investigate cerebral cortex activation during active movement and passive movement by using a functional near-infrared spectroscopy (fNIRS). Tasks were the flexion/extension of the right hand finger by active movement and passive movement. Oxy-hemoglobin concentration changes calculated from fNIRS and analyzed the activation and connectivity so as to understand dynamical brain relationship. The results demonstrated that the brain activation in passive movements is similar to motor execution. During active movement, the estimated causality patterns showed significant causality value from the supplementary motor area (SMA) to the primary motor cortex (M1). During the passive movement, the causality from the primary somatosensory cortex (S1) to the primary motor cortex (M1) was stronger than active movement. These results demonstrated that active and passive movements had a direct effect on the cerebral cortex but the stimulus pathway of active and passive movement is different. This study may contribute to better understanding how active and passive movements can be expressed into cortical activation by means of fNIRS.

Analysis of dermal composite conditions using collagen absorption characteristics in the THz range

The absorption characteristics of the dermis were reviewed in the terahertz range from 0.2 to 2 THz. The absorption magnitude of the dermis was higher than that of the epidermis model owing to the inclusion of collagen fibers. The heat denaturation of the collagen and the decrease of water content in the dermis caused a decrease in the absorption magnitude of the dermis. We verified that the absorption magnitude of collagen sheets at 1 THz similarly decreased by nearly 43% upon the heat treatment at approximately 70° C. When the heat-treated sheet was used as a scaffold for cell culture, the average growth rate of the fibroblast increased. These findings suggest that variation in the ability of cell growth in the dermis can be predicted using the absorption of the collagen or the difference between the absorptions of dermis and water.

Analysis of hepatitis C infection using Raman spectroscopy and proximity based classification in the transformed domain

This work presents a diagnostic system for the hepatitis C infection using Raman spectroscopy and proximity based classification. The proposed method exploits transformed Raman spectra using the proximity based machine learning technique and is denoted as RS-PCA-Prox. First, Raman spectral data is baseline corrected by subtracting noise and low intensity background. After this, a feature transformation of Raman spectra is adopted, not only to reduce the feature's dimensionality but also to learn different deviations in Raman shifts. The proposed RS-PCA-Prox shows significant diagnostic power in terms of accuracy, sensitivity, and specificity as 95%, 0.97 and 0.94 in PCA based transformed domain. The comparison of the RS-PCA-Prox with linear and ensemble based classifiers shows that proximity based classification performs better for the discrimination of HCV infected individuals and is able to differentiate the infected individuals from normal ones on the basis of molecular spectral information. Furthermore, it is observed that characteristic spectral changes are due to variation in the intensity of lectin, chitin, lipids, ammonia and viral protein as a consequence of the HCV infection.

Terahertz time-domain spectroscopy of chondroitin sulfate

Chondroitin sulfate (CS), derived from cartilage tissues, is an important type of biomacromolecule. In this paper, the terahertz time-domain spectroscopy (THz-TDS) was investigated as a potential method for content detection of CS. With the increase of the CS content, the THz absorption coefficients of the CS/polyethylene mixed samples linearly increase. The refractive indices of the mixed samples also increase when the CS content increases. The extinction coefficient of CS demonstrates the THz frequency dependence to be approximately the power of 1.4, which can be explained by the effects of CS granular solids on THz scattering.

Mitigating fringing in discrete frequency infrared imaging using time-delayed integration

Infrared (IR) spectroscopic microscopes provide the potential for label-free quantitative molecular imaging of biological samples, which can be used to aid in histology, forensics, and pharmaceutical analysis. Most IR imaging systems use broadband illumination combined with a spectrometer to separate the signal into spectral components. This technique is currently too slow for many biomedical applications such as clinical diagnosis, primarily due to the availability of bright mid-infrared sources and sensitive MCT detectors. There has been a recent push to increase throughput using coherent light sources, such as synchrotron radiation and quantum cascade lasers. While these sources provide a significant increase in intensity, the coherence introduces fringing artifacts in the final image. We demonstrate that applying time-delayed integration in one dimension can dramatically reduce fringing artifacts with minimal alterations to the standard infrared imaging pipeline. The proposed technique also offers the potential for less expensive focal plane array detectors, since linear arrays can be more readily incorporated into the proposed framework.

Raman spectroscopy combined with a support vector machine for differentiating between feeding male and female infants mother's milk

This study presents differentiation in milk samples of mother's feeding male and female infants using Raman spectroscopy combined with a support vector machine (SVM). Major differences have been observed in the Raman spectra of both types of milk based on their chemical compositions. Overall, it has been found that milk samples of mother's having a female infant are richer in fatty acids, phospholipids, and tryptophan. In contrast, milk samples of mother's having a male infant contain more carotenoids and saccharides. Principal component analysis and SVM further highlighted the differences between the two groups on the basis of differentiating features obtained from their Raman spectra. The SVM model with two different kernels, i.e. polynomial kernel function (order-2) and Gaussian radial basis function (RBF sigma-2), are used for gender based milk differentiations. The performance of the proposed model in terms of accuracy, precision, sensitivity, and specificity using the polynomial kernel function of order-2 have been found to be 86%, 88%, 85% and 88%, respectively.

Correction of an adding-doubling inversion algorithm for the measurement of the optical parameters of turbid media

We present broadband measurements of the optical properties of tissue-mimicking solid phantoms using a single integrating sphere to measure the hemispherical reflectance and transmittance under a direct illumination at the normal incident angle. These measurements are traceable to reflectance and transmittance scales. An inversion routine using the output of the adding-doubling algorithm restricted to the reflectance and transmittance under a direct illumination was developed to produce the optical parameters of the sample along with an uncertainty budget at each wavelength. The results for two types of phantoms are compared to measurements by time-resolved approaches. The results between our method and these independent measurements agree within the estimated measurement uncertainties.

Pencil-like imaging spectrometer for bio-samples sensing

Spectrally-resolved imaging techniques are becoming central to the investigation of bio-samples. In this paper, we demonstrate the use of a WIFI-camera as a detection module to assemble a pencil-like imaging spectrometer, which weighs only 140 g and has a size of 3.1 cm in diameter and 15.5 cm in length. The spectrometer is standalone, and works wirelessly. A smartphone or network computer can serve as the data receiver and processor. The wavelength resolution of the spectrometer is about 17 nm, providing repeatable measurements of spatial two-dimensional images at various wavelengths for various bio-samples, including bananas, meat, and human hands. The detected spectral range is 400 nm - 675 nm and a white LED array lamp is selected as the light source. Based on the detected spectra, we can monitor the impacts of chlorophyll, myoglobin, and hemoglobin on bananas, pork, and human hands, respectively. For human hand scanning, a 3D spectral image data cube, which exhibits excellent signal to background noise ratio, can be obtained within 16 sec. We envisage that the adaptation of imaging spectrometer devices to the widely-accepted smartphone technology will help to carry out on-site studies in various applications. Besides, our pencil-like imaging spectrometer is cost-effective (<$300) and easy to assemble. This portable imaging spectrometer can facilitate the collection of large amounts of spectral image data. With the help of machine learning, we can realize object recognition based on spectral classification in the future.

Development of thin skin mimicking bilayer solid tissue phantoms for optical spectroscopic studies

In vivo spectroscopic measurements have the proven potential to provide important insight about the changes in tissue during the development of malignancies and thus help to diagnose tissue pathologies. Extraction of intrinsic data in the presence of varying amounts of scatterers and absorbers offers great challenges in the development of such techniques to the clinical level. Fabrication of optical phantoms, tailored to the biochemical as well as morphological features of the target tissue, can help to generate a spectral database for a given optical spectral measurement system. Such databases, along with appropriate pattern matching algorithms, could be integrated with in vivo measurements for any desired quantitative analysis of the target tissue. This paper addresses the fabrication of such soft, photo stable, thin bilayer phantoms, mimicking skin tissue in layer dimensions and optical properties. The performance evaluation of the fabricated set of phantoms is carried out using a portable fluorescence spectral measurement system. The alterations in flavin adenine dinucleotide (FAD)-a tissue fluorophore that provides important information about dysplastic progressions in tissues associated with cancer development based on changes in emission spectra-fluorescence with varied concentrations of absorbers and scatterers present in the phantom are analyzed and the results are presented. Alterations in the emission intensity, shift in emission wavelength and broadening of the emission spectrum were found to be potential markers in the assessment of biochemical changes that occur during the progression of dysplasia.

Lactate based optical screening of dengue virus infection in human sera using Raman spectroscopy

This study presents the screening of dengue virus (DENV) infection in human blood sera based on lactate concentration using Raman spectroscopy. A total of 70 samples, 50 from confirmed DENV infected patients and 20 from healthy volunteers have been used in this study. Raman spectra of all these samples have been acquired in the spectral range from 600 cm^-1 to 1800 cm^-1 using a 532 nm laser as an excitation source. Spectra of all these samples have been analyzed for assessing the biochemical changes resulting from infection. In DENV infected samples three prominent Raman peaks have been found at 750, 830 and 1450 cm^-1. These peaks are most probably attributed to an elevated level of lactate due to an impaired function of different body organs in dengue infected patients. This has been proven by an addition of lactic acid solution to the healthy serum in a controlled manner. By the addition of lactic acid solution, the intense Raman bands at 1003, 1156 and 1516 cm^-1 found in the spectrum of healthy serum got suppressed when the new peaks appeared around 750, 830, 925, 950, 1123, 1333, 1450, 1580 and 1730 cm^-1. The current study predicts that lactate may possibly be a potential biomarker for the diagnosis of DENV infection.

Detection and classification of three-class initial dips from prefrontal cortex

In this paper, the use of initial dips using functional near-infrared spectroscopy (fNIRS) for brain-computer interface (BCI) is investigated. Features and window sizes for detecting initial dips are also discussed. Three mental tasks including mental arithmetic, mental counting, and puzzle solving are performed in obtaining fNIRS signals from the prefrontal cortex. Vector-based phase analysis method combined with a threshold circle, as a decision criterion, are used to detect the initial dips. Eight healthy subjects participate in experiment. Linear discriminant analysis is used as a classifier. To classify initial dips, five features (signal mean, peak value, signal slope, skewness, and kurtosis) of oxy-hemoglobin (HbO) and four different window sizes (0~1, 0~1.5, 0~2, and 0~2.5 sec) are examined. It is shown that a combination of signal mean and peak value and a time period of 0~2.5 sec provide the best average classification accuracy of 57.5% for three classes. To further validate the result, three-class classification using the conventional hemodynamic response (HR) is also performed, in which two features (signal mean and signal slope) and 2~7 sec window size have yielded the average classification accuracy of 65.9%. This reveals that fNIRS-based BCI using initial dip detection can reduce the command generation time from 7 sec to 2.5 sec while the classification accuracy is a bit sacrificed from 65.9% to 57.5% for three mental tasks. Further improvement can be made by using deoxy hemoglobin signals in coping with the slow HR problem.

PHOEBE: a method for real time mapping of optodes-scalp coupling in functional near-infrared spectroscopy

Recent functional near-infrared spectroscopy (fNIRS) instrumentation encompasses several dozen of optodes to enable reconstructing a hemodynamic image of the entire cerebral cortex. Despite its potential clinical applicability, widespread use of fNIRS with human subjects is currently limited by unresolved issues, namely the collection from the entirety of optical channels of signals with a signal-to-noise ratio (SNR) sufficient to carry out a reliable estimation of cortical hemodynamics, and the considerable amount of time that placing numerous optodes take with individuals for whom achieving good optical coupling to the scalp is difficult due to thick or dark hair. To address these issues, we developed a numerical method that: 1) at the channel level, computes an objective measure of the signal-to-noise ratio (SNR) related to its optical coupling to the scalp, akin to electrode conductivity used in electroencephalography (EEG), and 2) at the optode level, determines and displays the coupling status of all individual optodes in real time on a model of a human head. This approach aims to shorten the pre-acquisition preparation time by visually displaying which optodes require further adjustment for optimum scalp coupling, and to maximize the signal-to-noise ratio (SNR) of all optical channels contributing to the functional hemodynamic mapping. The methodology described in this paper has been implemented in a software tool named PHOEBE (placing headgear optodes efficiently before experimentation) that is freely available for use by the fNIRS community.

Spectrometer calibration for spectroscopic Fourier domain optical coherence tomography

We propose a simple and robust procedure for Fourier domain optical coherence tomography (FdOCT) that allows to linearize the detected FdOCT spectra to wavenumber domain and, at the same time, to determine the wavelength of light for each point of detected spectrum. We show that in this approach it is possible to use any measurable physical quantity that has linear dependency on wavenumber and can be extracted from spectral fringes. The actual values of the measured quantity have no importance for the algorithm and do not need to be known at any stage of the procedure. As example we calibrate a spectral OCT spectrometer using Doppler frequency. The technique of spectral calibration can be in principle adapted to of all kind of Fourier domain OCT devices.

Using DRS during breast conserving surgery: identifying robust optical parameters and influence of inter-patient variation

Successful breast conserving surgery consists of complete removal of the tumor while sparing healthy surrounding tissue. Despite currently available imaging and margin assessment tools, recognizing tumor tissue at a resection margin during surgery is challenging. Diffuse reflectance spectroscopy (DRS), which uses light for tissue characterization, can potentially guide surgeons to prevent tumor positive margins. However, inter-patient variation and changes in tissue physiology occurring during the resection might hamper this light-based technology. Here we investigate how inter-patient variation and tissue status (in vivo vs ex vivo) affect the performance of the DRS optical parameters. In vivo and ex vivo measurements of 45 breast cancer patients were obtained and quantified with an analytical model to acquire the optical parameters. The optical parameter representing the ratio between fat and water provided the best discrimination between normal and tumor tissue, with an area under the receiver operating characteristic curve of 0.94. There was no substantial influence of other patient factors such as menopausal status on optical measurements. Contrary to expectations, normalization of the optical parameters did not improve the discriminative power. Furthermore, measurements taken in vivo were not significantly different from the measurements taken ex vivo. These findings indicate that DRS is a robust technology for the detection of tumor tissue during breast conserving surgery.

Bundled-optode implementation for 3D imaging in functional near-infrared spectroscopy

The paper presents a functional near-infrared spectroscopy (fNIRS)-based bundled-optode method for detection of the changes of oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR) concentrations. fNIRS with 32 optodes is utilized to measure five healthy male subjects' brain-hemodynamic responses to arithmetic tasks. Specifically, the coordinates of 256 voxels in the three-dimensional (3D) volume are computed according to the known probe geometry. The mean path length factor in the Beer-Lambert equation is estimated as a function of the emitter-detector distance, which is utilized for computation of the absorption coefficient. The mean values of HbO and HbR obtained from the absorption coefficient are then applied for construction of a 3D fNIRS image. Our results show that the proposed method, as compared with the conventional approach, can detect brain activity with higher spatial resolution. This method can be extended for 3D fNIRS imaging in real-time applications.

Depth-resolved measurements with elliptically polarized reflectance spectroscopy

The ability of elliptical polarized reflectance spectroscopy (EPRS) to detect spectroscopic alterations in tissue mimicking phantoms and in biological tissue in situ is demonstrated. It is shown that there is a linear relationship between light penetration depth and ellipticity. This dependence is used to demonstrate the feasibility of a depth-resolved spectroscopic imaging using EPRS. The advantages and drawbacks of EPRS in evaluation of biological tissue are analyzed and discussed.

Analysis of dengue infection based on Raman spectroscopy and support vector machine (SVM)

The current study presents the use of Raman spectroscopy combined with support vector machine (SVM) for the classification of dengue suspected human blood sera. Raman spectra for 84 clinically dengue suspected patients acquired from Holy Family Hospital, Rawalpindi, Pakistan, have been used in this study.The spectral differences between dengue positive and normal sera have been exploited by using effective machine learning techniques. In this regard, SVM models built on the basis of three different kernel functions including Gaussian radial basis function (RBF), polynomial function and linear functionhave been employed to classify the human blood sera based on features obtained from Raman Spectra.The classification model have been evaluated with the 10-fold cross validation method. In the present study, the best performance has been achieved for the polynomial kernel of order 1. A diagnostic accuracy of about 85% with the precision of 90%, sensitivity of 73% and specificity of 93% has been achieved under these conditions.

Quantitative and simultaneous non-invasive measurement of skin hydration and sebum levels

We report a method on quantitative and simultaneous non-contact in-vivo hydration and sebum measurements of the skin using an infrared optical spectroscopic set-up. The method utilizes differential detection with three wavelengths 1720, 1750, and 1770 nm, corresponding to the lipid vibrational bands that lay "in between" the prominent water absorption bands. We have used an emulsifier containing hydro- and lipophilic components to mix water and sebum in various volume fractions which was applied to the skin to mimic different oily-dry skin conditions. We also measured the skin sebum and hydration values on the forehead under natural conditions and its variations to external stimuli. Good agreement was found between our experimental results and reference values measured using conventional biophysical methods such as Corneometer and Sebumeter.

Characterisation of signal enhancements achieved when utilizing a photon diode in deep Raman spectroscopy of tissue

We characterise the performance of a beam enhancing element ('photon diode') for use in deep Raman spectroscopy (DRS) of biological tissues. The optical component enhances the number of laser photons coupled into a tissue sample by returning escaping photons back into it at the illumination zone. The method is compatible with transmission Raman spectroscopy, a deep Raman spectroscopy concept, and its implementation leads to considerable enhancement of detected Raman photon rates. In the past, the enhancement concept was demonstrated with a variety of samples (pharmaceutical tablets, tissue, etc) but it was not systematically characterized with biological tissues. In this study, we investigate the enhancing properties of the photon diode in the transmission Raman geometry as a function of: a) the depth and b) the optical properties of tissue samples. Liquid tissue phantoms were employed to facilitate systematic variation of optical properties. These were chosen to mimic optical properties of human tissues, including breast and prostate. The obtained results evidence that a photon diode can enhance Raman signals of tissues by a maximum of × 2.4, although it can also decrease the signals created towards the back of samples that exhibit high scattering or absorption properties.

Arduino Due based tool to facilitate in vivo two-photon excitation microscopy

Two-photon excitation spectroscopy is a powerful technique for the characterization of the optical properties of genetically encoded and synthetic fluorescent molecules. Excitation spectroscopy requires tuning the wavelength of the Ti:sapphire laser while carefully monitoring the delivered power. To assist laser tuning and the control of delivered power, we developed an Arduino Due based tool for the automatic acquisition of high quality spectra. This tool is portable, fast, affordable and precise. It allowed studying the impact of scattering and of blood absorption on two-photon excitation light. In this way, we determined the wavelength-dependent deformation of excitation spectra occurring in deep tissues in vivo.

Event-related changes of the prefrontal cortex oxygen delivery and metabolism during driving measured by hyperspectral fNIRS

Recent technological advancements in optical spectroscopy allow for the construction of hyperspectral (broadband) portable tissue oximeters. In a series of our recent papers we have shown that hyperspectral NIRS (hNIRS) has similar or better capabilities in the absolute tissue oximetry as frequency-domain NIRS, and that hNIRS is also very efficient in measuring temporal changes in tissue hemoglobin concentration and oxygenation. In this paper, we extend the application of hNIRS to the measurement of event-related hemodynamic and metabolic functional cerebral responses during simulated driving. In order to check if hNIRS can detect event-related changes in the brain, we measured the concentration changes of oxygenated (HbO2) and deoxygenated (HHb) hemoglobin and of the oxidized state of cytochrome c oxidase, on the right and left prefrontal cortices (PFC) simultaneously during simulated driving on sixteen healthy right-handed participants (aged between 22-32). We used our in-house hNIRS system based on a portable spectrometer with cooled CCD detector and a driving simulator with a fully functional steering wheel and foot pedals. Each participant performed different driving tasks and participants were distracted during some driving conditions by asking general knowledge true/false questions. Our findings suggest that more complex driving tasks (non-distracted) deactivate PFC while distractions during driving significantly activate PFC, which is in agreement with previous fMRI results. Also, we found the changes in the redox state of the cytochrome C oxidase to be very consistent with those in the concentrations of HbO2 and HHb. Overall our findings suggest that in addition to the suitability of absolute tissue oximetry, hyperspectral NIRS may also offer advantages in functional brain imaging. In particular, it can be used to measure the metabolic functional brain activity during actual driving.

Dynamic filtering improves attentional state prediction with fNIRS

Brain activity can predict a person's level of engagement in an attentional task. However, estimates of brain activity are often confounded by measurement artifacts and systemic physiological noise. The optimal method for filtering this noise - thereby increasing such state prediction accuracy - remains unclear. To investigate this, we asked study participants to perform an attentional task while we monitored their brain activity with functional near infrared spectroscopy (fNIRS). We observed higher state prediction accuracy when noise in the fNIRS hemoglobin [Hb] signals was filtered with a non-stationary (adaptive) model as compared to static regression (84% ± 6% versus 72% ± 15%).

Dual-comb spectroscopy

Dual-comb spectroscopy is an emerging new spectroscopic tool that exploits the frequency resolution, frequency accuracy, broad bandwidth, and brightness of frequency combs for ultrahigh-resolution, high-sensitivity broadband spectroscopy. By using two coherent frequency combs, dual-comb spectroscopy allows a sample's spectral response to be measured on a comb tooth-by-tooth basis rapidly and without the size constraints or instrument response limitations of conventional spectrometers. This review describes dual-comb spectroscopy and summarizes the current state of the art. As frequency comb technology progresses, dual-comb spectroscopy will continue to mature and could surpass conventional broadband spectroscopy for a wide range of laboratory and field applications.

Preliminary fsLIBS study on bone tumors

The aim of this study is to evaluate the capability of femtosecond Laser Induced Breakdown Spectroscopy (fsLIBS) to discriminate between normal and cancerous bone, with implications to femtosecond laser surgery procedures. The main advantage of using femtosecond lasers for surgery is that the same laser that is being used to ablate can also be used for a feedback system to prevent ablation of certain tissues. For bone tumor removal, this technique has the potential to reduce the number of repeat surgeries that currently must be performed due to incomplete removal of the tumor mass. In this paper, we performed fsLIBS on primary bone tumor, secondary tumor in bone, and normal bone. These tissues were excised from consenting patients and processed through the UC Davis Cancer Center Biorepository. For comparison, each tumor sample had a matched normal bone sample. fsLIBS was performed to characterize the spectral signatures of each tissue type. A minimum of 20 spectra were acquired for each sample. We did not detect significant differences between the fsLIBS spectra of secondary bone tumors and their matched normal bone samples, likely due to the heterogeneous nature of secondary bone tumors, with normal and cancerous tissue intermingling. However, we did observe an increase in the fsLIBS magnesium peak intensity relative to the calcium peak intensity for the primary bone tumor samples compared to the normal bone samples. These results show the potential of using femtosecond lasers for both ablation and a real-time feedback control system for treatment of primary bone tumors.

Passive BCI based on drowsiness detection: an fNIRS study

We use functional near-infrared spectroscopy (fNIRS) to discriminate the alert and drowsy states for a passive brain-computer interface (BCI). The passive brain signals for the drowsy state are acquired from the prefrontal and dorsolateral prefrontal cortex. The experiment is performed on 13 healthy subjects using a driving simulator, and their brain activity is recorded using a continuous-wave fNIRS system. Linear discriminant analysis (LDA) is employed for training and testing, using the data from the prefrontal, left- and right-dorsolateral prefrontal regions. For classification, eight features are tested: mean oxyhemoglobin, mean deoxyhemoglobin, skewness, kurtosis, signal slope, number of peaks, sum of peaks, and signal peak, in 0~5, 0~10, and 0~15 second time windows, respectively. The results show that the best performance for classification is achieved using mean oxyhemoglobin, the signal peak, and the sum of peaks as features. The average accuracies in the right dorsolateral prefrontal cortex (83.1, 83.4 and 84.9% in the 0~5, 0~10 and 0~15 second time windows, respectively) show that the proposed method has an effective utility for detection of drowsiness for a passive BCI.

Simultaneous FRAP, FLIM and FAIM for measurements of protein mobility and interaction in living cells

We present a novel integrated multimodal fluorescence microscopy technique for simultaneous fluorescence recovery after photobleaching (FRAP), fluorescence lifetime imaging (FLIM) and fluorescence anisotropy imaging (FAIM). This approach captures a series of polarization-resolved fluorescence lifetime images during a FRAP recovery, maximizing the information available from a limited photon budget. We have applied this method to analyse the behaviour of GFP-labelled coxsackievirus and adenovirus receptor (CAR) in living human epithelial cells. Our data reveal that CAR exists in oligomeric states throughout the cell, and that these complexes occur in conjunction with high immobile fractions of the receptor at cell-cell junctions. These findings shed light on previously unknown molecular associations between CAR receptors in intact cells and demonstrate the power of combined FRAP, FLIM and FAIM microscopy as a robust method to analyse complex multi-component dynamics in living cells.

Bedside monitoring of patients with shock using a portable spatially-resolved near-infrared spectroscopy

Clinical monitoring of shock mainly depends on blood-oxygen-indices obtained from invasive blood sample tests. The central internal jugular central vein oxygenation level (ScvO2) has been considered as a gold standard indicator for shock prediction. We developed a noninvasive spatially-resolved near-infrared spectroscopy (SR-NIRS) to measure tissue blood oxygen saturation (StO2) surrounding the region of taking blood sample for the ScvO2 test in 25 patients with shock. StO2 values were found to be highly correlated (r = 0.84, p < 0.001) with ScvO2 levels and the concordance coefficient of 0.80 is high. The results suggest the potential of noninvasive SR-NIRS for bedside shock monitoring.

Spontaneous and coherent anti-Stokes Raman spectroscopy of human gastrocnemius muscle biopsies in CH-stretching region for discrimination of peripheral artery disease

Peripheral Artery Disease (PAD) is a common manifestation of atherosclerosis, characterized by lower leg ischemia and myopathy in association with leg dysfunction. In the present study, Spontaneous and coherent anti-Stokes Raman scattering (CARS) spectroscopic techniques in CH-stretching spectral region were evaluated for discriminating healthy and diseased tissues of human gastrocnemius biopsies of control and PAD patients. Since Raman signatures of the tissues in the fingerprint region are highly complex and CH containing moieties are dense, CH-stretching limited spectral range was used to classify the diseased tissues. A total of 181 Raman spectra from 9 patients and 122 CARS spectra from 12 patients were acquired. Due to the high dimensionality of the data in Raman and CARS measurements, principal component analysis (PCA) was first performed to reduce the dimensionality of the data (6 and 9 principal scores for Raman and CARS, respectively) in the CH-stretching region, followed by a discriminant function analysis (DFA) to classify the samples into different categories based on disease severity. The CH2 and CH3 vibrational signatures were observed in the Raman and CARS spectroscopy. Raman and CARS data in conjunction with PCA-DFA analysis were capable of differentiating healthy and PAD gastrocnemius with an accuracy of 85.6% and 78.7%, respectively.

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.

Spectral and lifetime domain measurements of rat brain tumors

During glioblastoma surgery, delineation of the brain tumor margins is difficult because the infiltrated and normal tissues have the same visual appearance. We use a fiber-optical fluorescence probe for spectroscopic and time domain measurements to assist surgeon in differentiating the healthy and the infiltrated tissues. First study was performed on rats that were previously injected with tumorous cells. Measurements of endogenous tissue fluorescence were performed on fresh and fixed rat tumor brain slices. Spectral characteristics, fluorescence redox ratios and fluorescence lifetime measurements were analyzed. The study aimed at defining an optical index that can act as an indicator for discriminating healthy from tumorous tissue.

Accuracy of oxygen saturation and total hemoglobin estimates in the neonatal brain using the semi-infinite slab model for FD-NIRS data analysis

Frequency domain near-infrared spectroscopy (FD-NIRS) is a non-invasive method for measuring optical absorption in the brain. Common data analysis procedures for FD-NIRS data assume the head is a semi-infinite, homogenous medium. This assumption introduces bias in estimates of absorption (μa ), scattering ( [Formula: see text]), tissue oxygen saturation (StO2), and total hemoglobin (HbT). Previous works have investigated the accuracy of recovered μa values under this assumption. The purpose of this study was to examine the accuracy of recovered StO2 and HbT values in FD-NIRS measurements of the neonatal brain. We used Monte Carlo methods to compute light propagation through a neonate head model in order to simulate FD-NIRS measurements at 690 nm and 830 nm. We recovered μa , [Formula: see text], StO2, and HbT using common analysis procedures that assume a semi-infinite, homogenous medium and compared the recovered values to simulated values. Additionally, we characterized the effects of curvature via simulations on homogenous spheres of varying radius. Lastly, we investigated the effects of varying amounts of extra-axial fluid. Curvature induced underestimation of μa , [Formula: see text], and HbT, but had minimal effects on StO2. For the morphologically normal neonate head model, the mean absolute percent errors (MAPE) of recovered μa values were 12% and 7% for 690 nm and 830 nm, respectively, when source-detector separation was at least 20 mm. The MAPE for recovered StO2 and HbT were 6% and 9%, respectively. Larger relative errors were observed (∼20-30%), especially as StO2 and HbT deviated from normal values. Excess CSF around the brain caused very large errors in μa , [Formula: see text], and HbT, but had little effect on StO2.

State-space models of impulse hemodynamic responses over motor, somatosensory, and visual cortices

THE PAPER PRESENTS STATE SPACE MODELS OF THE HEMODYNAMIC RESPONSE (HR) OF FNIRS TO AN IMPULSE STIMULUS IN THREE BRAIN REGIONS: motor cortex (MC), somatosensory cortex (SC), and visual cortex (VC). Nineteen healthy subjects were examined. For each cortex, three impulse HRs experimentally obtained were averaged. The averaged signal was converted to a state space equation by using the subspace method. The activation peak and the undershoot peak of the oxy-hemoglobin (HbO) in MC are noticeably higher than those in SC and VC. The time-to-peaks of the HbO in three brain regions are almost the same (about 6.76 76 ± 0.2 s). The time to undershoot peak in VC is the largest among three. The HbO decreases in the early stage (~0.46 s) in MC and VC, but it is not so in SC. These findings were well described with the developed state space equations. Another advantage of the proposed method is its easy applicability in generating the expected HR to arbitrary stimuli in an online (or real-time) imaging. Experimental results are demonstrated.

Quantitative physiology and immunohistochemistry of oral lesions

Angiogenesis and hypoxia are reported to correlate with tumor aggressiveness. In this study, we investigated the potential of optically measured total hemoglobin concentration (THC) and blood oxygen saturation (StO2) as a quantitative measure of angiogenesis and hypoxia in oral lesions with an immunohistochemical comparison. 12 normal subjects and 40 oral patients (22 oral squamous cell carcinoma (SCC), 18 benign/premalignant lesions including 11 verrucous hyperplasia (VH) and 7 hyperkeratosis/parakeratosis (HK)) were studied. The results showed that the THC measurement was consistent with vascular endothelial growth factor (VEGF) and microvessel staining in the stromal area, but StO2 was not associated with HIF-1α. We observed inflammation induced neovascular formation in the stromal area of VH and HK that were likely attributed to higher-than-control THC and StO2 and resulted in no difference in optical measurements between all lesions. However, we found that in majority of SCC, the ratio of THC and StO2 levels between lesions and the surrounding tissues provide potential distinguishing characteristics from VH, which are not visually differentiable from SCC, with a sensitivity, specificity, and accuracy of 91%, 68%, and 76%, respectively.

In vitro characterization of genetically expressed absorbing proteins using photoacoustic spectroscopy

Genetically expressed fluorescent proteins have been shown to provide photoacoustic contrast. However, they can be limited by low photoacoustic generation efficiency and low optical absorption at red and near infrared wavelengths, thus limiting their usefulness in mammalian small animal models. In addition, many fluorescent proteins exhibit low photostability due to photobleaching and transient absorption effects. In this study, we explore these issues by synthesizing and characterizing a range of commonly used fluorescent proteins (dsRed, mCherry, mNeptune, mRaspberry, AQ143, E2 Crimson) and novel non-fluorescent chromoproteins (aeCP597 and cjBlue and a non-fluorescent mutant of E2 Crimson). The photoacoustic spectra, photoacoustic generation efficiency and photostability of each fluorescent protein and chromoprotein were measured. Compared to the fluorescent proteins, the chromoproteins were found to exhibit higher photoacoustic generation efficiency due to the absence of radiative relaxation and ground state depopulation, and significantly higher photostability. The feasibility of converting an existing fluorescent protein into a non-fluorescent chromoprotein via mutagenesis was also demonstrated. The chromoprotein mutant exhibited greater photoacoustic signal generation efficiency and better agreement between the photoacoustic and the specific extinction coefficient spectra than the original fluorescent protein. Lastly, the genetic expression of a chromoprotein in mammalian cells was demonstrated. This study suggests that chromoproteins may have potential for providing genetically encoded photoacoustic contrast.

Combining independent component analysis and Granger causality to investigate brain network dynamics with fNIRS measurements

In this study a new strategy that combines Granger causality mapping (GCM) and independent component analysis (ICA) is proposed to reveal complex neural network dynamics underlying cognitive processes using functional near infrared spectroscopy (fNIRS) measurements. The GCM-ICA algorithm implements the following two procedures: (i) extraction of the region of interests (ROIs) of cortical activations by ICA, and (ii) estimation of the direct causal influences in local brain networks using Granger causality among voxels of ROIs. Our results show that the use of GCM in conjunction with ICA is able to effectively identify the directional brain network dynamics in time-frequency domain based on fNIRS recordings.

Autoregressive model based algorithm for correcting motion and serially correlated errors in fNIRS

Systemic physiology and motion-induced artifacts represent two major sources of confounding noise in functional near infrared spectroscopy (fNIRS) imaging that can reduce the performance of analyses and inflate false positive rates (i.e., type I errors) of detecting evoked hemodynamic responses. In this work, we demonstrated a general algorithm for solving the general linear model (GLM) for both deconvolution (finite impulse response) and canonical regression models based on designing optimal pre-whitening filters using autoregressive models and employing iteratively reweighted least squares. We evaluated the performance of the new method by performing receiver operating characteristic (ROC) analyses using synthetic data, in which serial correlations, motion artifacts, and evoked responses were controlled via simulations, as well as using experimental data from children (3-5 years old) as a source baseline physiological noise and motion artifacts. The new method outperformed ordinary least squares (OLS) with no motion correction, wavelet based motion correction, or spline interpolation based motion correction in the presence of physiological and motion related noise. In the experimental data, false positive rates were as high as 37% when the estimated p-value was 0.05 for the OLS methods. The false positive rate was reduced to 5-9% with the proposed method. Overall, the method improves control of type I errors and increases performance when motion artifacts are present.

Comparison of different metrics for analysis and visualization in spectroscopic optical coherence tomography

Spectroscopic Optical Coherence Tomography (S-OCT) extracts depth resolved spectra that are inherently available from OCT signals. The back scattered spectra contain useful functional information regarding the sample, since the light is altered by wavelength dependent absorption and scattering caused by chromophores and structures of the sample. Two aspects dominate the performance of S-OCT: (1) the spectral analysis processing method used to obtain the spatially-resolved spectroscopic information and (2) the metrics used to visualize and interpret relevant sample features. In this work, we focus on the second aspect, where we will compare established and novel metrics for S-OCT. These concepts include the adaptation of methods known from multispectral imaging and modern signal processing approaches such as pattern recognition. To compare the performance of the metrics in a quantitative manner, we use phantoms with microsphere scatterers of different sizes that are below the system's resolution and therefore cannot be differentiated using intensity based OCT images. We show that the analysis of the spectral features can clearly separate areas with different scattering properties in multi-layer phantoms. Finally, we demonstrate the performance of our approach for contrast enhancement in bovine articular cartilage.

Spectral phasor analysis of Pyronin Y labeled RNA microenvironments in living cells

We show that the spectral phasor approach of the fluorescent dye Pyronin Y (PY) can be used to identify specific RNA subspecies of ribonuclear proteins complexes in live cells. We applied spectral phasors to isolate intracellular RNA species with similar spectral properties. We identified at least 4 different PY labeled species in live cells and further spatially mapped their presence at the pixel level. Most notable were transcripts in the nucleoli which were spectrally similar to RNA clusters in the cytoplasm. We propose that these species represent ribosomal RNA and clustered ribonucleoprotein complexes. Further, we observed within this cluster Cajal bodies in the proximity of the nucleolus. In addition, transcripts in the cytoplasm undertook a filamentous morphology composed of multiple puncti structures which individually localized along and close to mitochondria but were distinct from mitochondria.

Čerenkov radiation emission and excited luminescence (CREL) sensitivity during external beam radiation therapy: Monte Carlo and tissue oxygenation phantom studies

Radiotherapy generates Čerenkov radiation emission in tissue, and spectral absorption features appearing in the emission spectrum can be used to quantify blood oxygen saturation (S(t)O(2)) from the known absorptions of hemoglobin. Additionally, the Čerenkov light can be used to excite oxygen-sensitive phosphorescence of probe PtG4, whose emission lifetime directly reports on tissue oxygen partial pressure (pO(2)). Thus, it is feasible to probe both hemoglobin S(t)O(2) and pO(2) using external radiation therapy beam to create as an internal light source in tumor tissue. In this study, the sensitivity and spatial origins of these two signals were examined. Emission was detected using a fiber-optic coupled intensifier-gated CCD camera interfaced to a spectrometer. The phosphorescence lifetimes were quantified and compared with S(t)O(2) changes previously measured. Monte Carlo simulations of the linear accelerator beam were used together with tracking of the optical signals, to predict the spatial distribution and zone sensitivity within the phantom. As the fiber-to-beam distance (FBD) varied from 0 to 30 mm, i.e. the distance from the fiber tip to the nearest side of the radiotherapy beam, the effective sampling depth for CR emission changed from 4 to 29 mm for the wavelengths in the range of 600-1000 nm. For the secondary emission (phosphorescence) the effective sampling depth was determined to be in the range of 9 to 19 mm. These results indicate that sampling of S(t)O(2) and pO(2) in tissue should be feasible during radiation therapy, and that the radiation beam and fiber sampling geometry can be set up to acquire signals that originate as deep as a few centimeters in the tissue.

Introduction: feature issue on phantoms for the performance evaluation and validation of optical medical imaging devices

The editors introduce the Biomedical Optics Express feature issue on "Phantoms for the Performance Evaluation and Validation of Optical Medical Imaging Devices." This topic was the focus of a technical workshop that was held on November 7-8, 2011, in Washington, D.C. The feature issue includes 13 contributions from workshop attendees.

Quantitative phase spectroscopy

Quantitative phase spectroscopy is presented as a novel method of measuring the wavelength-dependent refractive index of microscopic volumes. Light from a broadband source is filtered to an ~5 nm bandwidth and rapidly tuned across the visible spectrum in 1 nm increments by an acousto-optic tunable filter (AOTF). Quantitative phase images of semitransparent samples are recovered at each wavelength using off-axis interferometry and are processed to recover relative and absolute dispersion measurements. We demonstrate the utility of this approach by (i) spectrally averaging phase images to reduce coherent noise, (ii) measuring absorptive and dispersive features in microspheres, and (iii) quantifying bulk hemoglobin concentrations by absolute refractive index measurements. Considerations of using low coherence illumination and the extension of spectral techniques in quantitative phase measurements are discussed.

Conformational changes in quadruplex oligonucleotide structures probed by Raman spectroscopy

Quadruplex structures are higher order structures formed by guanine-rich oligonucleotides. In the present study, temperature-induced conformational changes in the quadruplex structures of aptamers and other guanine-rich oligonucleotides are probed by Raman spectroscopy. In particular, dramatic changes in the fingerprint region are observed in the spectra of thrombin binding aptamer at higher temperatures. These changes are accompanied by a decrease in the intensity of the 1480 cm(-1) peak (attributed to C8 = N7-H2), which is diagnostic of the quadruplex structure. We also show that these changes can be reversed (to a certain extent) by addition of K(+) ions.