This PDF file contains the front matter associated with SPIE Proceedings Volume 10059, including the Title Page, Copyright information, Table of Contents, and Conference Committee listing.

Acousto-optic (AO) modulation of light is used to extract both temporal and spectral information of diffusive media such as biological tissue, where they provide measures of blood flow and oxygen saturation of hemoglobin, respectively. The temporal information is extracted from the width of the power spectrum of the light intensity, whereas the spectral information is calculated from the spatial decay of the cross correlation between the light intensity and the generated ultrasonic signal. The ultrasonic signal is a coded phase modulated signal with a narrow autocorrelation, enabling localization of the measurement volume. Two different liquid phantoms are used, with similar scattering but different absorption properties. The difference in absorption calculated with the AO signal is compared to calculations based on the modified Beer Lambert law. As the same AO signal is used to extract both modalities, it might be used to extract hemodynamic related changes in the brain for diagnostic and functional assessment.

To date, various blood flow measurement systems have been presented. Recently we demonstrated multi-channel diffuse speckle contrast analysis (DSCA) to monitor in-vivo relative blood flow in deep tissues noninvasively. It has a limitation in a long-term use due to camera contamination. Here, we present a novel fiber-lens combined DSCA which can solve it. Also it has been applied to cerebral blood flow monitoring of rats during middle cerebral artery occlusion surgery. As a result, the system showed relative changes of the flow during the arterial perfusion periods. It secures novel applications of the DSCA in in-vivo blood flow measurement.

Diffuse Correlation Spectroscopy (DCS) is an increasingly popular non-invasive optical technique to clinically measure deep tissue blood flow, albeit at slow measurement rates of 0.5-1 Hz. We recently reported the development of a new ‘fast’ DCS instrument that continuously measures blood flow at 50-100 Hz (simultaneously from 8 channels), using conventional DCS sources/detectors, and optimized software computations. A particularly interesting result was our ability to optically record pulsatile micro-vascular blood flow waveforms, and therein readily identify high frequency features such as the dicrotic notch. Here, we showcase the utility and potential of high-speed measurements of blood flow (and arterial blood pressure) in a few clinical applications. First, we employ the fast-DCS instrumentation to measure cerebral autoregulation (CVAR) dynamics. Cerebral autoregulation refers to the mechanism by which cerebral blood flow (CBF) is maintained during fluctuations in blood pressure; CVAR is impaired in the injured brain. We derive an index of autoregulation by measuring the rates of decrease (and recovery) of blood flow and blood pressure following a sudden, induced change in systemic blood pressure (e.g., bilateral thigh cuff deflation). Our pilot experiments in healthy volunteers show that DCS measured rates of micro-vascular regulation are comparable to conventional large vessel regulatory metrics (e.g., measured with transcranial Doppler ultrasound). Second, we utilized pulsatile blood flow oscillations in cerebral arteries to estimate the critical closing pressure (CrCP), i.e., the arterial blood pressure at which CBF approaches zero. Pilot experiments in healthy subjects show good agreement between CrCP measured with DCS and transcranial Doppler ultrasound.

This paper describes the system calibration and demodulation procedures used in an investigation of the scatter-specific tissue contrast that can be obtained by high spatial frequency (HSF) domain imaging and cross- polarization (CP) imaging using an inexpensive color imaging system.

HSF and CP imaging methods are both known to alter the reflectance image sensitivity to diffuse multiply- scattered and superficially backscattered photons. This results in enhanced contrast, compared to standard wide-field imaging, based on tissue surface microstructure and composition. Measurements in tissue-simulating optical phantoms show that CP images display contrast based on both scattering and absorption, while HSF is specifically sensitive to scatter-only contrast, strongly suppressing absorption-based contrast. By altering the frequency used, the degree of contrast suppression or enhancement can be tuned.¹ This suggests that an inexpensive HSF imaging system could have potential to aid diagnostic procedures, where CP is the current state-of-the-art imaging modality.

Mueller matrix polarimetry is a powerful tool for detecting microscopic structures, therefore can be used to monitor physiological changes of tissue samples. Meanwhile, spectral features of scattered light can also provide abundant microstructural information of tissues. In this paper, we take the 2D multispectral backscattering Mueller matrix images of bovine skeletal muscle tissues, and analyze their temporal variation behavior using multispectral Mueller matrix parameters. The 2D images of the Mueller matrix elements are reduced to the multispectral frequency distribution histograms (mFDHs) to reveal the dominant structural features of the muscle samples more clearly. For quantitative analysis, the multispectral Mueller matrix transformation (MMT) parameters are calculated to characterize the microstructural variations during the rigor mortis and proteolysis processes of the skeletal muscle tissue samples. The experimental results indicate that the multispectral MMT parameters can be used to judge different physiological stages for bovine skeletal muscle tissues in 24 hours, and combining with the multispectral technique, the Mueller matrix polarimetry and FDH analysis can monitor the microstructural variation features of skeletal muscle samples. The techniques may be used for quick assessment and quantitative monitoring of meat qualities in food industry.

According to the World Health Organization, breast cancer is the most common cancer among women worldwide, claiming the lives of hundreds of thousands of women each year. Near infrared diffuse optical tomography (DOT) has demonstrated a great potential as an adjunct modality for differentiation of malignant and benign breast lesions and for monitoring treatment response of patients with locally advanced breast cancers. The path toward commercialization of DOT techniques depends upon the improvement of robustness and user-friendliness of this technique in hardware and software. In the past, our group have developed three frequency domain prototype systems which were used in several clinical studies. In this study, we introduce our newly under development US-guided DOT system which is being improved in terms of size, robustness and user friendliness by several custom electronic and mechanical design. A new and robust probe designed to reduce preparation time in clinical process. The processing procedure, data selection and user interface software also updated. With all these improvements, our new system is more robust and accurate which is one step closer to commercialization and wide use of this technology in clinical settings. This system is aimed to be used by minimally trained user in the clinical settings with robust performance. The system performance has been tested in the phantom experiment and initial results are demonstrated in this study. We are currently working on finalizing this system and do further testing to validate the performance of this system. We are aiming toward use of this system in clinical setting for patients with breast cancer.

Diffuse Optical Tomography (DOT) can be described as a highly multidimensional problem generating a huge data set with long acquisition/computational times. Biological tissue behaves as a low pass filter in the spatial frequency domain, hence compressive sensing approaches, based on both patterned illumination and detection, are useful to reduce the data set while preserving the information content. In this work, a multiple-view time-domain compressed sensing DOT system is presented and experimentally validated on non-planar tissue-mimicking phantoms containing absorbing inclusions.

We report an optical mammography study on eight patients with breast cancer who underwent neoadjuvant chemotherapy. Of these eight patients, six were responders (tumor size decreased by more than 50%) and two were nonresponders (tumor size decreased by less than 50%). The goals of this study are (1) to characterize the temporal evolution of the hemoglobin concentration ([HbT]) and saturation (SO₂) in breast tissue during the course of treatment in responders and non-responders, and (2) to define a quantitative index that is capable of identifying responders and nonresponders during treatment. We found that both [HbT] and SO₂ decreased by a greater amount in responders than in non-responders during therapy. This result applied to both cancerous and healthy breast, but the discrimination of responders and non-responders was more significant with SO₂ measurements in the cancerous breast. A cumulative response index defined in terms of SO₂ measurements in the cancerous breast achieved a 100% sensitivity and 100% specificity for the identification of responders and non-responders at therapy midpoint. These results confirm the potential of optical mammography in assessing response to neoadjuvant chemotherapy during treatment, thus offering the opportunity to consider alternative options to ineffective treatment regimens.

We developed a time-resolved reflectance diffuse optical tomography (RDOT) system to measure tumor responses to chemotherapy in breast cancer patients at the bedside. This system irradiates the breast with a three-wavelength pulsed laser (760, 800, and 830 nm) through a source fiber specified by an optical switch. The light collected by detector fibers is guided to a detector unit consisting of variable attenuators and photomultiplier tubes. Thirteen irradiation and 12 detection points were set to a measurement area of 50 × 50 mm for a hand-held probe. The data acquisition time required to obtain the temporal profiles within the measurement area is about 2 minutes. The RDOT system generates topographic and tomographic images of tissue properties such as hemoglobin concentration and tissue oxygen saturation using two imaging methods. Topographic images are obtained from the optical properties determined for each source-detector pair using a curve-fitting method based on the photon diffusion theory, while tomographic images are reconstructed using an iterative image reconstruction method. In an experiment using a tissue-like solid phantom, a tumor-like cylindrical target (15 mm diameter, 15 mm high) embedded in a breast tissue-like background medium was successfully reconstructed. Preliminary clinical measurements indicated that the tumor in a breast cancer patient was detected as a region of high hemoglobin concentration. In addition, the total hemoglobin concentration decreased during chemotherapy. These results demonstrate the potential of RDOT for evaluating the effectiveness of chemotherapy in patients with breast cancer.

The parametric image of Volume Transfer Coefficient (K_trans) in MRI has been used to guide image reconstruction of Near-Infrared Spectral Tomography (NIRST). The image reconstruction used direct regularization, in which no segmentation has been involved. A total of 24 patients were involved in this study and the reconstructed results show that the tumor total hemoglobin (HbT) contrast could be used to differentiate the malignant from the benign cases (p-value= 0.018). The addition of the MRI information allows more accurate and definitive HbT values from the NIRST.

Effective breast cancer treatment requires the assessment of metabolic changes of tumor tissue during chemo- and hormonotherapy for prediction tumor response. Evaluation of the dynamics of tumor oxygen state (by diffuse optical spectroscopy imaging) and tumor vasculature (by ultrasound investigation in power Doppler mode) was performed before treatment beginning and before the second cycle of chemotherapy in 16 patients who received preoperative chemotherapy. Changes of these indicators were compared then with tumor pathologic response. Breast tumors demonstrated different dynamics of tumor oxygenation depending on the changes of tumor tissue. The increase of the tumor oxygenation after the first cycle of chemotherapy was observed in five of six patients with grade 4 and 5 of pathologic tumor response. Decrease of the oxygenation level was revealed in one patient with the 4^th degree of tumor response. Variable changes of the oxygenation level were mentioned in the patients with moderate (the 3^d degree) tumor response. Tumor oxygenation decreased or was unchanged in case of 1 or 2 degree of tumor response in five of six cases. The study of the tumor blood vessels didn't reveal any correlation between vasculature changes and tumor response under the performed treatment. The trend of tumor oxygenation in early time after treatment beginning might be a predictive criterion of tumor sensitivity to chemotherapy.

In this retrospective cohort study, we examine the hypothesis that baseline oxygen saturation (SO₂%) in contralateral normal tissue can be a quantitative measurement for predicting tumor response to neoadjuvant chemotherapy (NAC). Using our dynamic custom-built dual breast dynamic diffuse optical tomography (DOT) imager, we reconstructed SO₂% measurement concentration for 12 stage II or III breast cancer patients. Six patients achieved pCR (RCB-0) and the other half had extensive residual disease (RCB-III). Baseline SO₂% in contralateral normal tissue was statistically significantly higher in RCB-III subjects than in pCR (p = 0.025). From ROC analyses, baseline SO₂% in contralateral normal breast tissue was able to discriminate pCR from RCB-III patients (AUC 0.889) with sensitivity and specificity of 83%.

A portable, 12-wavelength hybrid frequency domain (FD) and continuous wave (CW) near-infrared spectral tomography (NIRST) system was developed for efficient characterization of breast cancer in a clinical oncology setting. Two sets of three FD and three CW measurements were acquired simultaneously. The imaging time was reduced from 90 to 55 seconds with a new gain adjustment scheme of the optical detector. The study of integrating this system into the workflow of clinical oncology practice is ongoing.

We describe a novel approach for monitoring breast lesions, utilizing spatial frequency domain imaging, a diffuse optical imaging method to detect hemoglobin contrast, in combination with mechanical compression of the tissue. The project is motivated by the growing rate of unnecessary breast biopsies, caused by uncertainty in X-ray mammographic diagnoses. We believe there is a need for an alternate means of tracking the progression palpable lesions exhibiting probably benign features, that can be performed non-invasively and hence frequently: at home or in the clinic. The proposed approach capitalizes on two distinguishing properties of cancerous lesions, namely the relative stiffness with respect to surrounding tissue and the optical absorption due to the greater vascularization, hence hemoglobin concentration. The current research project is a pilot study to evaluate the principle on soft, breast tissue-mimicking phantoms containing stiffer, more highly absorbing inclusions. Spatial frequency domain imaging was performed by projecting onto the phantom a series of wide-field patterns at multiple spatial frequencies. Image analysis then was performed to map absorption and scattering properties. The results of the study demonstrate that compression significantly increases the optical contrast observed for inclusions located 10 and 15 mm beneath the surface. In the latter case, the inclusion was not detectable without compression.

We introduce a new Monte-Carlo technique to estimate the radiance distribution in a medium according to the radiative transport equation (RTE). We demonstrate how to form gradients of the forward model, and thus how to employ this technique as part of the inverse problem in Diffuse Optical Tomography (DOT). Use of the RTE over the more typical application of the diffusion approximation permits accurate modelling in the case of short source-detector separation and regions of low scattering, in addition to providing time-domain information without extra computational effort over continuous-wave solutions.

The study of photon migration through highly scattering media opens the way to the non-invasive investigation of biological tissues well below the skin surface. When the medium is addressed in reflectance geometry, a key issue is to maximize the depth reached by migrating photons. By exploiting the Diffusion Approximation of the Radiative Transfer Equation, we calculated the time-resolved and continuous-wave probability density functions for the maximum depth reached by detected photons, for both a homogeneous and a layered laterally-infinite diffusive slab. From the probability density functions it is possible to calculate the mean value of the maximum depth at which detected photons have undergone scattering events.

We have presented a novel Single Snapshot Multiple Frequency Demodulation (SSMD) method enabling single snapshot wide field imaging of optical properties of turbid media in the Spatial Frequency Domain. SSMD makes use of the orthogonality of harmonic functions and extracts the modulation transfer function (MTF) at multiple modulation frequencies and of arbitrary orientations and amplitudes simultaneously from a single structured-illuminated image at once. SSMD not only increases significantly the data acquisition speed and reduces motion artifacts but also exhibits excellent noise suppression in imaging as well. The performance of SSMD-SFDI is demonstrated with experiments on both tissue mimicking phantoms and in vivo for recovering optical properties. SSMD is ideal in the implementation of a real-time spatial frequency domain imaging platform, which will open up SFDI for vast applications in, for example, mapping the optical properties of a dynamic turbid medium or monitoring fast temporal evolutions.

We investigated the feasibility of a two-step scheme for reconstruction of a fluorophore target embedded in a semi-infinite medium. In this scheme, we neglected the presence of the fluorophore target for the excitation light and used an analytical solution of the time-dependent radiative transfer equation (RTE) for the excitation light in a homogeneous semi-infinite media instead of solving the RTE numerically in the forward calculation. In the first step of this reconstruction scheme, we implemented a pixel-based reconstruction using the Landweber method with adjoint fields. The second step uses this result as an initial guess for solving the shape and contrast value reconstruction problem using the level set method. Numerical experiments using Monte Carlo data measurements, show that the proposed scheme provides reconstructions of shape, location and contrast value of the target with rather good accuracy. The computation times of the solution of the forward problem and the whole reconstruction process were reduced by about forty and fifteen percent, respectively.

Fluorescence molecular tomography (FMT) is a promising tool for real time in vivo quantification of neurotransmission (NT) as we pursue in our BRAIN initiative effort. However, the acquired image data are noisy and the reconstruction problem is ill-posed. Further, while spatial sparsity of the NT effects could be exploited, traditional compressive-sensing methods cannot be directly applied as the system matrix in FMT is highly coherent. To overcome these issues, we propose and assess a three-step reconstruction method. First, truncated singular value decomposition is applied on the data to reduce matrix coherence. The resultant image data are input to a homotopy-based reconstruction strategy that exploits sparsity via ℓ₁ regularization. The reconstructed image is then input to a maximum-likelihood expectation maximization (MLEM) algorithm that retains the sparseness of the input estimate and improves upon the quantitation by accurate Poisson noise modeling. The proposed reconstruction method was evaluated in a three-dimensional simulated setup with fluorescent sources in a cuboidal scattering medium with optical properties simulating human brain cortex (reduced scattering coefficient: 9.2 cm⁻¹, absorption coefficient: 0.1 cm⁻¹ and tomographic measurements made using pixelated detectors. In different experiments, fluorescent sources of varying size and intensity were simulated. The proposed reconstruction method provided accurate estimates of the fluorescent source intensity, with a 20% lower root mean square error on average compared to the pure-homotopy method for all considered source intensities and sizes. Further, compared with conventional ℓ₂ regularized algorithm, overall, the proposed method reconstructed substantially more accurate fluorescence distribution. The proposed method shows considerable promise and will be tested using more realistic simulations and experimental setups.

Image reconstruction in diffuse optical tomography (DOT) is challenging because its inverse problem is nonlinear, ill-posed and ill-conditioned. Anatomical guidance from high spatial resolution imaging modalities can substantially improve the quality of reconstructed DOT images. In this paper, inspired by the kernel methods in machine learning, we propose the kernel method to introduce anatomical information into the DOT image reconstruction algorithm. In this kernel method, optical absorption coefficient at each finite element node is represented as a function of a set of features obtained from anatomical images such as computed tomography (CT). The kernel based image model is directly incorporated into the forward model of DOT, which exploits the sparseness of the image in the feature space. Compared with Laplacian approaches to include structural priors, the proposed method does not require the image segmentation of distinct regions. The proposed kernel method is validated with numerical simulations of 3D DOT reconstruction using synthetic CT data. We added 15% Gaussian noise onto both the numerical DOT measurements and the simulated CT image. We have also validated the proposed method by agar phantom experiment with anatomical guidance from a CT scan. We have studied the effects of voxel size and number of nearest neighborhood size in kernel method on the reconstructed DOT images. Our results indicate that the spatial resolution and the accuracy of the reconstructed DOT images have been improved substantially after applying the anatomical guidance with the proposed kernel method.

In pediatrics studies, the quality of functional near infrared spectroscopy (fNIRS) signals is often reduced by motion artifacts. These artifacts likely mislead brain functionality analysis, causing false discoveries. While noise correction methods and their performance have been investigated, these methods require several parameter assumptions that apparently result in noise overfitting. In contrast, the rejection of noisy signals serves as a preferable method because it maintains the originality of the signal waveform. Here, we describe a semi-learning algorithm to detect and eliminate noisy signals. The algorithm dynamically adjusts noise detection according to the predetermined noise criteria, which are spikes, unusual activation values (averaged amplitude signals within the brain activation period), and high activation variances (among trials). Criteria were sequentially organized in the algorithm and orderly assessed signals based on each criterion. By initially setting an acceptable rejection rate, particular criteria causing excessive data rejections are neglected, whereas others with tolerable rejections practically eliminate noises. fNIRS data measured during the attention response paradigm (oddball task) in children with attention deficit/hyperactivity disorder (ADHD) were utilized to evaluate and optimize the algorithm’s performance. This algorithm successfully substituted the visual noise identification done in the previous studies and consistently found significantly lower activation of the right prefrontal and parietal cortices in ADHD patients than in typical developing children. Thus, we conclude that the semi-learning algorithm confers more objective and standardized judgment for noise rejection and presents a promising alternative to visual noise rejection

Near-infrared fluorescence imaging using indocyanine green (ICG) as a tracer is a promising technique for mapping the lymphatic system and for detecting sentinel lymph nodes (SLN) during cancer surgery. In our feasibility study we have investigated the application of a custom-made handheld fluorescence camera system for the detection of lymph nodes in gynecological malignancies. It comprises a low cost CCD camera with enhanced NIR sensitivity and two groups of LEDs emitting at wavelengths of 735 nm and 830 nm for interlaced recording of fluorescence and reflectance images of the tissue, respectively. With the help of our system, surgeons can observe fluorescent tissue structures overlaid onto the anatomical image on a monitor in real-time. We applied the camera system for intraoperative lymphatic mapping in 5 patients with vulvar cancer, 5 patients with ovarian cancer, 3 patients with cervical cancer, and 3 patients with endometrial cancer. ICG was injected at four loci around the primary malignant tumor during surgery. After a residence time of typically 15 min fluorescence images were taken in order to visualize the lymph nodes closest to the carcinomas. In cases with vulvar cancer about half of the lymph nodes detected by routinely performed radioactive SLN mapping have shown fluorescence in vivo as well. In the other types of carcinomas several lymph nodes could be detected by fluorescence during laparotomy. We conclude that our low cost camera system has sufficient sensitivity for lymphatic mapping during surgery.

We used coherent hemodynamics spectroscopy (CHS) and near-infrared spectroscopy (NIRS) to measure the absolute cerebral blood flow (CBF) and cerebral autoregulation efficiency of a patient with intraventricular hemorrhage in the neurocritical care unit. Mean arterial pressure oscillations were induced with cyclic thigh cuff inflations at a super-systolic pressure. The oscillations in oxyhemoglobin ([HbO₂]) and deoxyhemoglobin ([Hb]) cerebral concentrations were used to compute CHS amplitude and phase spectra that were fit with the frequency-domain equations of our hemodynamic model. From the fitted parameters, we obtained measures of local autoregulation efficiency (cutoff frequency: 0.07 ± 0.02 Hz) and absolute regional CBF (33 ± 9 ml/100g/min). We introduce a new approach for computing CHS spectra using coherence criteria and time-varying transfer function analysis. We show that with this approach we can maximize the number of frequency points in the CHS spectra for more effective fitting with our hemodynamic model. Finally, we show how absolute measurements of the cerebral concentrations of [HbO₂] and [Hb] at baseline can be used to further enhance the fitting procedure.

We report preliminary results of a study for investigating the spatial homogeneity of induced and spontaneous oscillations in the concentration of oxyhemoglobin on the scalp/skull layer of two human subjects. Hemodynamic oscillations were induced by modulation of arterial blood pressure, which triggers the cerebral autoregulation mechanism. Induced hemodynamic oscillations are used in coherent hemodynamics spectroscopy to derive physiological parameters of interest for medical diagnostics. For example, our dedicated mathematical model translates typical near-infrared spectroscopy observables, like the amplitude and phase relationship of the oscillations of oxy- and deoxyhemoglobin concentrations into capillary and venous blood transit times, cutoff frequency of the autoregulation process, and other parameters related to microvascular blood volume. In this study, we focused on the phase relationship between the oscillations of oxyhemoglobin concentrations in three optical channels, two of which feature a short (5 mm) source-detector separation (sampling the scalp/skull only) and the third one features a long (30 mm) source-detector separation (sampling both extracerebral and cerebral tissues). The two main goals of the study were: a) to compare the coherence of induced and spontaneous oscillations; b) to assess if induced and spontaneous oscillations may be assumed to be uniform in the extracerebral layer. This was assessed by studying the phase relationship of oscillations in oxyhemoglobin concentration at the two short source-detector separations. About point a) we verified that induced oscillations have a higher incidence of coherence than spontaneous oscillations: 74% for induced oscillations, and 30% for spontaneous oscillations. About point b) the results show an overall trend for both spontaneous and induced oscillations to be homogeneous or “quasi-homogeneous” in the extracerebral tissue; however, we observed cases where a significant non-zero phase difference was measured, indicating spatial heterogeneity. We propose a method for taking into account the possible inhomogeneous behavior of the oscillations in the scalp/skull in order to increase the accuracy of measurements of cerebral hemodynamic oscillations.

Near infrared spectroscopy (NIRS) is an emerging functional brain imaging tool capable of assessing cerebral concentrations of oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (HbR) during brain activation noninvasively. As an extension of NIRS, diffuse optical tomography (DOT) not only shares the merits of providing continuous readings of cerebral oxygenation, but also has the ability to provide spatial resolution in the millimeter scale. Based on the scattering and absorption properties of nonionizing near-infrared light in biological tissue, DOT has been successfully applied in the imaging of breast tumors, osteoarthritis and cortex activations. Here, we present a state-of-art fast high density DOT system suitable for brain imaging. It can achieve up to a 21 Hz sampling rate for a full set of two-wavelength data for 3-D DOT brain image reconstruction. The system was validated using tissue-mimicking brain-model phantom. Then, experiments on healthy subjects were conducted to demonstrate the capability of the system.

The mechanism that maintains a stable blood flow in the brain despite changes in cerebral perfusion pressure (CPP), and therefore guaranties a constant supply of oxygen and nutrients to the neurons, is known as cerebral auto-regulation (CA). In a certain range of CPP, blood flow is mediated by a vasomotor adjustment in vascular resistance through dilation of blood vessels. CA is known to be impaired in diseases like traumatic brain injury, Parkinson’s disease, stroke, hydrocephalus and others. If CA is impaired, blood flow and pressure changes are coupled and thee oxygen supply might be unstable. Lassen’s blood flow auto-regulation curve describes this mechanism, where a plateau of stable blood flow in a specific range of CPP corresponds to intact auto-regulation. Knowing the limits of this plateau and maintaining CPP within these limits can improve patient outcome. Since CPP is influenced by both intracranial pressure and arterial blood pressure, long term changes in either can lead to auto-regulation impairment. Non-invasive methods for monitoring blood flow auto-regulation are therefore needed. We propose too use Near infrared spectroscopy (NIRS) too fill this need. NIRS is an optical technique, which measures microvascular changes in cerebral hemoglobin concentration. We performed experiments on non-human primates during exsanguination to demonstrate that thee limits of blood flow auto-regulation can be accessed with NIRS.

Initial feasibility of a spatial frequency domain imaging system was studied consisting of a hand held miniaturized projector and a rigid endoscope. Three wavelengths and two spatial frequencies were used for imaging. The system was calibrated using tissue mimicking phantoms. In vivo imaging was performed on five live mouse tumor models, and the absorption, scattering, hemoglobin oxygen saturation was measured. The initial promising results indicate that the spatial frequency domain imaging can a very useful tool for quantitative wide field tissue evaluation during minimally invasive image guided surgery.

We present a novel approach for single snapshot determination of absorption coefficient based on multi-frequency modulation transfer function (MTF) characterization from measurement in spatial frequency domain. The adopted Fourier transform domain analysis enables simultaneous extraction of information at multiple applied frequencies and excellent reduction of noise. Simulations were conducted for respectively verifying the feasibility of the MTF based approach and the performance of single snapshot determination of absorption coefficient using multi-frequency measurements. Phantom experiments without reference measurement demonstrated the high accuracy of absolute absorption coefficient determination with a maximum reconstruction error of 0.002 mm^-1.

The epidermis is the outermost layer of skin and is composed of cells primarily containing keratin. It consists of about ten layers of living cells (keratinocytes) and ten layers of dead cells (corneocytes). These cells are continually shed from the outside and replaced from the inside in a process called desquamation which is controlled by two biological events – proliferation and differentiation.

One method to non-invasively study biological changes in the skin is using fluorescence excitation spectroscopy. Several characteristic excitation-emission peaks occur in skin that have been related to the epidermal and dermal composition. The magnitude of the peak that occurs at 295nm excitation (F295) has been linked to changes in skin proliferation, cell turnover, epidermal thickening, and skin aging. We hypothesize that changes in this fluorescent signal could be used to assess the potential activity of cosmetic anti-aging compounds to deliver a benefit to skin.

Previous work with retinol and glycolic acid, two commonly used actives that effect epidermal proliferation and exfoliation, has demonstrated an increase in F295 (attributed to tryptophan excitation fluorescence). In this study we present the results of a placebo controlled study that aims to correlate changes in F295 with biological performance (epidermal thickening and Ki67 expression).

We present a wide-field fluorescence tomography with epi-illumination of sinusoidal pattern. In this scheme, a DMD projector is employed as a spatial light modulator to generate independently wide-field sinusoidal illumination patterns at varying spatial frequencies on a sample, and then the emitted photons at the sample surface were captured with a EM-CCD camera. This method results in a significantly reduced number of the optical field measurements as compared to the point-source-scanning ones and thereby achieves a fast data acquisition that is desired for a dynamic imaging application. Fluorescence yield images are reconstructed using the normalized-Born formulated inversion of the diffusion model. Experimental reconstructions are presented on a phantom embedding the fluorescent targets and compared for a combination of the multiply frequencies. The results validate the ability of the method to determine the target relative depth and quantification with an increasing accuracy.

We studied blood flow dynamics of active skeletal muscle using diffuse correlation spectroscopy (DCS), an emerging optical modality that is suitable for noninvasive quantification of microcirculation level in deep tissue. Seven healthy subjects conducted 0.5 Hz dynamic handgrip exercise for 3 minutes at intensities of 10, 20, 30, and 50 % of maximal voluntary contraction (MVC). DCS could detect the time-dependent increase of the blood flow response of the forearm muscle for continuous exercises, and the increase ratios of the mean blood flow through the exercise periods showed good correlation with the exercise intensities. We also compared blood flow responses detected from DCS with two different photon sampling rates and found that an appropriate photon sampling rates should be selected to follow the wide-ranged increase in the muscle blood flow with dynamic exercise. Our results demonstrate the possibility for utilizing DCS in a field of sports medicine to noninvasively evaluate the dynamics of blood flow in the active muscles.

Endoscopic DOT has the potential to apply to cancer-related imaging in tubular organs. Although the DOT has relatively large tissue penetration depth, the endoscopic DOT is limited by the narrow space of the internal tubular tissue, so as to the relatively small penetration depth. Because some adenocarcinomas including cervical adenocarcinoma are located in deep canal, it is necessary to improve the imaging resolution under the limited measurement condition. To improve the resolution, a new FOCUSS algorithm along with the image reconstruction algorithm based on the effective detection range (EDR) is developed. This algorithm is based on the region of interest (ROI) to reduce the dimensions of the matrix. The shrinking method cuts down the computation burden. To reduce the computational complexity, double conjugate gradient method is used in the matrix inversion. For a typical inner size and optical properties of the cervix-like tubular tissue, reconstructed images from the simulation data demonstrate that the proposed method achieves equivalent image quality to that obtained from the method based on EDR when the target is close the inner boundary of the model, and with higher spatial resolution and quantitative ratio when the targets are far from the inner boundary of the model. The quantitative ratio of reconstructed absorption and reduced scattering coefficient can be up to 70% and 80% under 5mm depth, respectively. Furthermore, the two close targets with different depths can be separated from each other. The proposed method will be useful to the development of endoscopic DOT technologies in tubular organs.

Imaging of tissue with Ultrasound-guided diffuse optical tomography (DOT) is a rising imaging technique to map hemoglobin concentrations within tissue for breast cancer detection and diagnosis. Near-infrared optical imaging received a lot of attention in research as a possible technique to be used for such purpose especially for breast tumors. Since DOT images contrast is closely related to oxygenation and deoxygenating of the hemoglobin, which is an important factor in differentiating malignant and benign tumors. One of the optical imaging modalities used is the diffused optical tomography (DOT); which probes deep scattering tissue (1-5cm) by NIR optical source-detector probe and detects NIR photons in the diffusive regime. The photons in the diffusive regime usually reach the detector without significant information about their source direction and the propagation path. Because of that, the optical reconstruction problem of the medium characteristics is ill-posed even with the tomography and Back-projection techniques. The accurate recovery of images requires an effective image reconstruction method. Here, we illustrate a method in which ultrasound images are encoded as prior for regularization of the inversion matrix. Results were evaluated using phantom experiments of low and high absorption contrasts. This method improves differentiation between the low and the high contrasts targets. Ultimately, this method could improve malignant and benign cases by increasing reconstructed absorption ratio of malignant to benign. Besides that, the phantom results show improvements in target shape as well as the spatial resolution of the DOT reconstructed images.

In this work, two different integrated-optics based spectrometer designs are presented. The first one is called interleaved arrayed waveguide grating (AWG) spectrometer provides large bandwidth (i.e. 30 nm) and high resolution (i.e. 0.1 nm) for a compact size (i.e. 2.4 cm × 3 cm). The second spectrometer is called ultra-high resolution Fourier transform (FT) spectrometer provides 1 pm of resolution for only 2 cm × 0.5 cm (1 cm²) device size at 1.3 μm. For the interleaved AWG spectrometer, the primary AWG has narrow closely spaced passbands (that equal the final desired channel spacing) that repeat N times in the desired wavelength range, using the frequency-cyclic nature of the AWG. The channel spacing of the secondary AWGs should be equal to the free spectral range (FSR) of the primary AWG. In this configuration, the FSR of the secondary AWGs defines the FSR of the overall configuration whereas the channel spacing (resolution) of the primary AWG defines the overall system resolution. The ultra-high resolution FT spectrometer is formed by sequentially-activated 60 Mach-Zehnder interferometers that are connected to photodetectors through very-low-loss beam combiners based on two-mode interference. The long optical delays are provided by tapping the propagating light out at certain locations on the optical waveguides by using electro-optically-controlled directional couplers. A design example with a spectral resolution of 500 MHz (~1 pm) and bandwidth of 15 GHz is presented for a device size of only 2 cm × 0.5 cm (1 cm²).

This experiment was conducted by using the diffuse optical spectroscopy based on near-infrared light. The near-infrared light in the water window was used to see the change of molecular concentration in the living tissue. The experiment subject was New Zealand rabbits weighing 3 ± 0.3 kg. VX2 tumor cells were injected into the inside of the chest wall of rabbits. The concentration of indocyanine green (ICG) has been observed once every three days, after the size of the pleural tumor grew up over 1cm. We used five different wavelengths (732, 758, 805, 840, and 880 nm) with known ICG spectrum. The distance between light source and detector probes was fixed by 1 cm. The probes were placed on the skin right above the tumor with an aid of laparoscope. ICG was injected into rabbits via ear vein. The diffused light was measured through the tumor with time course using a spectrometer. These measured data enabled us to observe the change of ICG concentration in real time with respect to the baseline without ICG. ICG was present longer in tumor compared to normal tissue. This phenomenon is thought to be due to the excessive angiogenesis in the tumor tissue. Since this method can be applied to other cases easily, it is thought that there is a possibility of cancer screening with less cost and simple equipment.

Scalp hemodynamics contaminates the signals from functional near-infrared spectroscopy (fNIRS). Numerous methods have been proposed to reduce this contamination, but no golden standard has yet been established. Here we constructed a multi-layered solid phantom to experimentally validate such methods. This phantom comprises four layers corresponding to epidermides, dermis/skull (upper dynamic layer), cerebrospinal fluid and brain (lower dynamic layer) and the thicknesses of these layers were 0.3, 10, 1, and 50 mm, respectively. The epidermides and cerebrospinal fluid layers were made of polystyrene and an acrylic board, respectively. Both of these dynamic layers were made of epoxy resin. An infrared dye and titanium dioxide were mixed to match their absorption and reduced scattering coefficients (μa and μs’, respectively) with those of biological tissues. The bases of both upper and lower dynamic layers have a slot for laterally sliding a bar that holds an absorber piece. This bar was laterally moved using a programmable stepping motor. The optical properties of dynamic layers were estimated based on the transmittance and reflectance using the Monte Carlo look-up table method. The estimated coefficients for lower and upper dynamic layers approximately coincided with those for biological tissues. We confirmed that the preliminary fNIRS measurement using the fabricated phantom showed that the signals from the brain layer were recovered if those from the dermis layer were completely removed from their mixture, indicating that the phantom is useful for evaluating methods for reducing the contamination of the signals from the scalp.

Fiber structure changes in the various pathological processes, such as the increase of fibrosis in liver diseases, the derangement of fiber in cervical cancer and so on. Currently, clinical pathologic diagnosis is regarded as the golden criterion, but different doctors with discrepancy in knowledge and experience may obtain different conclusions. Up to a point, quantitative evaluation of the fiber structure in the pathological tissue can be of great service to quantitative diagnosis. Mueller matrix measurement is capable of probing comprehensive microstructural information of samples and different wavelength of lights can provide more information. In this paper, we use a Mueller matrix microscope with light sources in six different wavelength. We use unstained, dewaxing liver tissue slices in four stages and the pathological biopsy of the filtration channels from rabbit eyes as samples. We apply the Mueller matrix polar decomposition (MMPD) parameter δ which corresponds to retardance to liver slices. The mean value of abnormal region get bigger when the level of fibrosis get higher and light in short wavelength is more sensitive to the microstructure of fiber. On the other hand, we use the Mueller matrix transformation (MMT) parameter Φ which is associated to the angel of fast axis in the analysis of the slices of the filtration channels from rabbit eyes. The value of kurtosis and the value of skewness shows big difference between new born region and normal region and can reveal the arrangement of fiber. These results indicate that the Mueller matrix microscope has great potential in auxiliary diagnosis.