Mass stranding of live whales has been explained by proposing many natural or human-related causes. Recent necropsy reports suggest a link between the mass stranding of beaked whales and the use of naval mid-frequency sonar. Surprisingly, whales have experienced symptoms similar to those caused by inert gas bubbles in human divers. Our goal is to develop a compact optical sensor to monitor the consumption of the oxygen stores in the muscle of freely diving whales. To this end we have proposed the use of a near-infrared phase-modulated frequency-domain spectrophotometer, in reflectance mode, to probe tissue oxygenation. Our probe consists of three main components: radiofrequency (RF) modulated light sources, a high-bandwidth avalanche photodiode with transimpedance amplifier, and a RF gain and phase detector. In this work, we concentrate on the design and performance of the light sensor, and its corresponding amplifier unit. We compare three state-of-the-art avalanche photodiodes: one through-hole device and two surface-mount detectors. We demonstrate that the gain due to the avalanche effect differs between sensors. The avalanche gain near maximum bias of the through-hole device exceeds by a factor of 2.5 and 8.3 that of the surface-mount detectors. We present the behavior of our assembled through-hole detector plus high-bandwidth transimpedance amplifier, and compare its performance to that of a commercially available module. The assembled unit enables variable gain, its phase noise is qualitatively lower, and the form factor is significantly smaller. Having a detecting unit that is compact, flexible, and functional is a milestone in the development of our tissue oxygenation tag.

Optical spectroscopy has shown potential as a tool for precancer detection by discriminating alterations in the optical properties within epithelial tissues. Identifying depth-dependent alterations associated with the progression of epithelial cancerous lesions can be especially challenging in the oral cavity due to the variable thickness of the epithelium and the presence of keratinization. Optical spectroscopy of epithelial tissue with improved depth resolution would greatly assist in the isolation of optical properties associated with cancer progression. Here, we report a fiber optic probe for oblique polarized reflectance spectroscopy (OPRS) that is capable of depth sensitive detection by combining the following three approaches: multiple beveled fibers, oblique collection geometry, and polarization gating. We analyze how probe design parameters are related to improvements in collection efficiency of scattered photons from superficial tissue layers and to increased depth discrimination within epithelium. We have demonstrated that obliquely-oriented collection fibers increase both depth selectivity and collection efficiency of scattering signal. Currently, we evaluate this technology in a clinical trial of patients presenting lesions suspicious for dysplasia or carcinoma in the oral cavity. We use depth sensitive spectroscopic data to develop automated algorithms for analysis of morphological and architectural changes in the context of the multilayer oral epithelial tissue. Our initial results show that OPRS has the potential to improve the detection and monitoring of epithelial precancers in the oral cavity.

In this paper we present results of real-time imaging through biological tissues by means of nonlinear three-wave mixing phase conjugation process. Biological tissues with thicknesses up to 5 mm are used and the imaging process is performed at a near infrared wavelength included in the therapeutic window. Furthermore we show that real-time compensation of turbidity of biological tissues allowed with this method can be applied to scattering media in motion, with a significant improvement of the signal to noise ratio and resolution of the restored images.

Texture analysis of light scattering in tissue is proposed to obtain diagnostic information from breast cancer specimens. Light scattering measurements are minimally invasive, and allow the estimation of tissue morphology to guide the surgeon in resection surgeries. The usability of scatter signatures acquired with a micro-sampling reflectance spectral imaging system was improved utilizing an empirical approximation to the Mie theory to estimate the scattering power on a per-pixel basis. Co-occurrence analysis is then applied to the scattering power images to extract the textural features. A statistical analysis of the features demonstrated the suitability of the autocorrelation for the classification of notmalignant (normal epithelia and stroma, benign epithelia and stroma, inflammation), malignant (DCIS, IDC, ILC) and adipose tissue, since it reveals morphological information of tissue. Non-malignant tissue shows higher autocorrelation values while adipose tissue presents a very low autocorrelation on its scatter texture, being malignant the middle ground. Consequently, a fast linear classifier based on the consideration of just one straightforward feature is enough for providing relevant diagnostic information. A leave-one-out validation of the linear classifier on 29 samples with 48 regions of interest showed classification accuracies of 98.74% on adipose tissue, 82.67% on non-malignant tissue and 72.37% on malignant tissue, in comparison with the biopsy H and E gold standard. This demonstrates that autocorrelation analysis of scatter signatures is a very computationally efficient and automated approach to provide pathological information in real-time to guide surgeon during tissue resection.

A computationally efficient method of simulating illumination in Optical Projection Tomographic Microscopy (OPTM) is presented to analyze the effect of microsphere axial displacement on image reconstruction using the filtered backprojection. OPTM reconstructs three-dimensional images of single cells from two-dimensional projection images in a fashion similar to Computed Tomography (CT). Projection images are acquired from circumferential positions around the cell by scanning the objective focal plane through the cell, while the condenser focal plane remains stationary. Unlike CT, the cell rotates between the source and detector in a microcapillary where it is not necessarily positioned at the optical axis. As the cell rotates, its axial position changes relative to the condenser focal plane for every projection. These differences in illumination have an impact on the overall reconstruction that cannot be understood experimentally. The computational model presented in this work relies on an alternative method of calculating illumination using a matrix formalism with near-field Mie theory. This method provides the ability to calculate the response of a microsphere illuminated with plane waves propagating from different directions. The response from each plane wave is subsequently summed to determine the total response. The power of this method is provided by the ability to arbitrarily choose the microsphere position after calculating the plane wave response, meaning illumination for all axial displacements can be computed in approximately the same time as a single position. Projection images are computed for microspheres at intervals away from the optical axis to understand how the axial displacement degrades the reconstructed image.

Emerging clinical applications including bioluminescence imaging require fast and accurate modelling of light propagation through turbid media with complex geometries. Monte Carlo simulations are widely recognized as the standard for high-quality modelling of light propagation in turbid media, albeit with high computational requirements. We present FullMonte: a flexible, extensible software framework for Monte Carlo modelling of light transport from extended sources through general 3D turbid media including anisotropic scattering and refractive index changes. The problem geometry is expressed using a tetrahedral mesh, giving accurate surface normals and avoiding artifacts introduced by voxel approaches. The software uses multithreading, Intel SSE vector instructions, and optimized data structures. It incorporates novel hardware-friendly performance optimizations that are also useful for software implementations. Results and performance are compared against existing implementations. We present a discussion of current state-of-the-art algorithms and accelerated implementations of the modelling problem. A new parameter permitting accuracy-performance tradeoffs is also shown which has significant implications including performance gains of over 25% for real applications. The advantages and limitations of both CPU and GPU implementations are discussed, with observations important to future advances. We also point the way towards custom hardware implementations with potentially large gains in performance and energy efficiency.

Oblique incidence reflectometry (OIR) is an established technique for estimation of tissue optical properties, however, a sensing footprint of a few transport mean-free paths is often needed when diffusion-regime-based algorithms are used. Smaller-footprint probes require improved light-propagation models and inversion schemes for diffuse reflectance close to the point-of-entry but might enable micro-endoscopic form factors for clinical assessments of cancers and pre-cancers. In this paper we extend the phase-function corrected diffusion-theory presented by Vitkin et al. (Nat. Comm 2011) to the case of pencil beams obliquely incident on a semi-infinite turbid medium. The model requires minimal computational resources and offers improved accuracy over more traditional diffusion-theory approximations models when validated against Monte Carlo simulations. The computationally efficient nature of the models may lend themselves to rapid fitting procedures for inverse problems.

Knowledge of which cellular structures scatter light is needed to fully utilize the information available from light scattering measurements of cells and tissues. To determine how specific organelles contribute to light scattering, wide angle side scattering was imaged simultaneously with fluorescence from specific organelles for thousands of cells using flow cytometry. Images were obtained with different depth of field conditions and analyzed with different assumptions. Both sets of data demonstrated that mitochondria and lysosomes, contribute similarly to side scatter. The nucleus contributes as much or more light scatter than either the mitochondria or the lysosomes.

Transmission bright-field microscopy is the clinical mainstay for disease diagnosis where image contrast is provided by absorptive and refractive index differences between tissue and the surrounding media. Different microscopy techniques often assume one of the two contrast mechanisms is negligible as a means to better understand the tissue scattering processes. This particular work provides better understanding of the role of refractive index and absorption within Optical Projection Tomographic Microscopy (OPTM) through the development of a generalized computational model based upon the Finite-Difference Time-Domain method. The model mimics OPTM by simulating axial scanning of the objective focal plane through the cell to produce projection images. These projection images, acquired from circumferential positions around the cell, are reconstructed into isometric three-dimensional images using the filtered backprojection normally employed in Computed Tomography (CT). The model provides a platform to analyze all aspects of bright-field microscopes, such as the degree of refractive index matching and the numerical aperture, which can be varied from air-immersion to high NA oil-immersion. In this preliminary work, the model is used to understand the effects of absorption and refraction on image formation using micro-shells and idealized nuclei. Analysis of absorption and refractive index separately provides the opportunity to better assess their role together as a complex refractive index for improved interpretation of bright-field scattering, essential for OPTM image reconstruction. This simulation, as well as ones in the future looking at other effects, will be used to optimize OPTM imaging parameters and triage efforts to further improve the overall system design.

Aminolevulinic acid (ALA) is converted to protoporphyrin-IX (PpIX) within mitochondria, causing the assumption that ALA-mediated photodynamic therapy (PDT) results in mitochondrial damage and therefore an apoptotic response. Mitochondria within apoptosing cells swell, forming pores in their outer mitochondrial membranes which release cytochrome-c, triggering apoptosis. Optical scatter imaging (OSI) makes use of scattered fields in order to indicate the morphology of subcellular components, and is used here in order to measure changes in mitochondrial size as a response to ALA-mediated PDT. Two images of the same field of view are spatially filtered in the Fourier plane of a 4-F system. Both spatial filters block directly transmitted light, while accepting different angles of scattered light through an adjustable iris. The optical scatter image ratio (OSIR) of the local intensities of these two spatially filtered images is indicative of scattering particle size. Mie theory is used to calculate the predicted OSIR as a function of scattering particle size. In this fashion, the OSI system is calibrated using polystyrene microspheres of know sizes. Comparison of the measured OSIR from cellular images to theoretical values predicted for mitochondria then serves as an indication as to whether cells are apoptosing. Cells are treated at varying concentrations of ALA and varying exposures of 635 nm light and imaged at varying time points in order to develop a broader understanding of an apoptotic response of cells undergoing ALA mediated PDT.

Label-free measurement of subcellular morphology can be used to track dynamically cellular function under various conditions and has important applications in cellular monitoring and in vitro cell assays. We show that optical filtering of scattered light by two-dimensional Gabor filters allows for direct and highly sensitive measurement of sample structure. The Gabor filters, which are defined by their spatial frequency, orientation and Gaussian envelope, can be used to track locally and in situ the characteristic size and orientation of structures within the sample. Our method consists of sequentially implementing a set of Gabor filters via a spatial light modulator placed in a conjugate Fourier plane during optical imaging and identifying the filters that yield maximum signal. Using this setup, we show that Gabor filtering of light forward-scattered by spheres yields an optical response which varies linearly with diameter between 100nm and 2000nm. The optical filtering sensitivity to changes in diameter is on the order of 20nm and can be achieved at low image resolution. We use numerical simulations to demonstrate that this linear response can be predicted from scatter theory and does not vary significantly with changes in refractive index ratio. By applying this Fourier filtering method in samples consisting of diatoms and cells, we generate false-color images of the object that encode at each pixel the size of the local structures within the object. The resolution of these encoded size maps in on the order of 0.36μm. The pixel histograms of these encoded images directly provide 20nm resolved “size spectra”, depicting the size distribution of structures within the analyzed object. We use these size spectra to differentiate the morphology of apoptosis-competent and bax/bak null apoptosis-resistant cells during cell death. We also utilize the sensitivity of the Gabor filters to object orientation to track changes in organelle morphology, and detect mitochondrial fission in cells undergoing apoptosis.

Diffuse reflectance spectroscopy is a technique widely used to determine optical properties of tissues: scattering and absorption coefficients. In this study, we present the development of a low-cost optical instrument usable in a clinical environment based upon the spatially resolved diffuse reflectance spectroscopy approach. This instrument has been used in a clinical study to support the diagnosis of tuberculosis. The idea is to establish a new scanning method for an early detection of inflammation due to a reagent injection, before the onset of visual signs. Results comparing the instrumental and classical clinical readings are presented.

Elastic scattering of light in tissue offers a natural biologic contrast that can be used to classify tissue for diagnostic purposes. For a single fiber reflectance spectroscopy setup, which uses a single multimode optical fiber with diameter dfib for both illumination and detection, our group has previously reported a relationship between the single fiber reflectance (SFR) signal and the dimensionless scattering (μ′_sd_fib). Based on this relationship, the multi-diameter single fiber reflectance method (MDSFR), was developed. This method allows the extraction of μ′_S and a phase function dependent parameter γ=(1-g₂) / (1-g₁) from tissue by taking multiple SFR measurements with different fiber diameters. Limitations and the sensitivity of the MDSFR method have been discussed previously based on an in silico analysis and the feasibility of the method has been proven experimentally during measurements in scattering phantoms containing polystyrene spheres. In the current study we will present data from an in-vivo clinical study utilizing MDSFR to determine tissue scattering properties of healthy and malignant breast tissue, on patients undergoing biopsy of a suspicious lesion found during mammographic breast imaging. Here MDSFR measurements are performed with a custom made disposable probe, incorporating two fiber diameters (0.4 and 0.8 mm), which is inserted through the biopsy needle before the biopsy is taken, allowing in vivo spectroscopic measurements of tumor center and healthy tissue.

Different techniques have been developed to determine the optical properties of turbid media, which include collimated transmission, diffuse reflectance, adding-doubling and goniometry. While goniometry can be used to determine the anisotropy of scattering (g), other techniques are used to measure the absorption coefficient and reduced scattering coefficient (μs(1-g)). But separating scattering coefficient (μs) and anisotropy of scattering from reduced scattering coefficient has been tricky. We developed an algorithm to determine anisotropy of scattering from the depth dependent decay of reflectance-mode confocal scanning laser microscopy (rCSLM) data. This report presents the testing of the algorithm on tissue phantoms with different anisotropies (g = 0.127 to 0.868, at 488 nm wavelength). Tissue phantoms were made from polystyrene microspheres (6 sizes 0.1-0.5 μm dia.) dispersed in both aqueous solutions and agarose gels. Three dimensional images were captured. The rCSLM-signal followed an exponential decay as a function of depth of the focal volume, R(z)ρexp(-μz) where ρ (dimensionless, ρ = 1 for a mirror) is the local reflectivity and μ [cm-1] is the exponential decay constant. The theory was developed to uniquely map the experimentally determined μ and ρ into the optical scattering properties μs and g. The values of μs and g depend on the composition and microstructure of tissues, and allow characterization of a tissue.

Clinical tissue processing such as formalin fixing, paraffin-embedding and histological staining alters significantly the optical properties of the tissue. We document the alterations in the optical properties of prostate cancer tissue specimens in the 500nm to 700nm spectral range caused by histological processing with quantitative differential interference contrast (qDIC) microscopy. A simple model to explain these alterations is presented at the end.

Fractal analysis combined with a label-free scattering technique is proposed for describing the pathological architecture of tumors. Clinicians and pathologists are conventionally trained to classify abnormal features such as structural irregularities or high indices of mitosis. The potential of fractal analysis lies in the fact of being a morphometric measure of the irregular structures providing a measure of the object’s complexity and self-similarity. As cancer is characterized by disorder and irregularity in tissues, this measure could be related to tumor growth. Fractal analysis has been probed in the understanding of the tumor vasculature network. This work addresses the feasibility of applying fractal analysis to the scattering power map (as a physical modeling) and principal components (as a statistical modeling) provided by a localized reflectance spectroscopic system. Disorder, irregularity and cell size variation in tissue samples is translated into the scattering power and principal components magnitude and its fractal dimension is correlated with the pathologist assessment of the samples. The fractal dimension is computed applying the box-counting technique. Results show that fractal analysis of ex-vivo fresh tissue samples exhibits separated ranges of fractal dimension that could help classifier combining the fractal results with other morphological features. This contrast trend would help in the discrimination of tissues in the intraoperative context and may serve as a useful adjunct to surgeons.

Spectroscopic optical coherence tomography (OCT) is an extension of the standard backscattering intensity analysis of OCT. It enables depth resolved monitoring of molecular and structural differences of tissue. One drawback of most methods to calculate the spectroscopic data is the long processing time. Also systematic and stochastic errors make the interpretation of the results challenging. Our approach combines modern signal processing tools with powerful graphics processing unit (GPU) programming. The processing speed for the spectroscopic analysis is nearly 3 mega voxel per second. This allows us to analyze multiple B-Scans in a few seconds and to display the results as a three dimensional data set. Our algorithm contains the following steps in addition to the conventional processing for frequency domain OCT: a quality map to exclude noisy parts of the data, spectral analysis by short time Fourier transform, feature reduction by Principal Component Analysis, unsupervised pattern recognition with K-means and rendering of the gray scale backscattering OCT data which is superimposed with a color map that is based on the results of the pattern recognition algorithm. Our set up provides a spectral range from 650-950nm and is optimized to suppress chromatic errors. In a proof-of-principle attempt, we already achieved additional spectroscopic contrast in phantom samples including scattering microspheres of different sizes and ex vivo biological tissue. This is an important step towards a system for real time spectral analysis of OCT data, which would be a powerful diagnosis tool for many diseases e.g. cancer detection at an early stage.

In this paper we attempted to simulate the macroscopic light scattering phenomenon of optical coherence tomography. Numerical solutions of Maxwell’s equations were computed to accurately account for phase and amplitude of light. According to the simulation results, the qualitative and quantitative characterization may provide important information for future development of this technique, especially on the index mapping of biological cells.

The growing interest in biomedical optics to the polarimetric methods push researchers to better understand of light depolarization during scattering in and on the surface of biological tissues. Here we study the depolarization of light propagated in silicone phantoms. The phantoms with variety of surface roughness and bulk optical properties are designed to imitate human skin. Free-space speckle patterns in parallel (I^II) and perpendicular (I⊥) direction in respect to incident polarization are used to get the depolarization ratio of backscattered light DR = (I_II - I⊥)/( I_II + I⊥). The Monte Carlo model developed in house is also applied to compare simulated DR with experimentally measured. DR dependence on roughness, concentration and size of scattering particles is analysed. A weak depolarization and negligible response to scattering of the medium are observed for phantoms with smooth surfaces, whereas for the surface roughness in order to the mean free path the depolarization ratio decreases and reveals dependence on the bulk scattering coefficient. In is shown that the surface roughness could be a key factor triggering the ability of tissues’ characterization by depolarization ratio.

We re-evaluate the Macdonald-Vaughan model for Raman depth profiling [J. Raman Spectrosc. 38, 584 (2007)]. The model is an geometrical description of the sample regions from which Raman signal is collected in a confocal geometry and indicates that Raman signal also originates from far outside the focus. Although correct shapes of Raman depth profiles were obtained, quantitatively the results were not satisfactory, in view of the highly deviating values of the fitted extinction coefficients of the sample material. Our re-evaluation, based on a new numerical implementation of the model, indicates that the model is not only capable of predicting the proper profiles but also yields the right extinction coefficients. As a result, the model now is highly useful for interpretation of depth profiles, also for biomedical samples such as the human skin.

We report on the modeling of a photopolymerizable hydrogel and its application as a replacement of the interior of the intervertebral disc (so called Nucleus Pulposus). The hydrogel is initially injected in its liquid form and then photopolymerized via a small catheter. Therefore, also the light necessary for the photopolymerization is constrained to a small light guide to keep the surgical procedure as minimally invasive as possible. Hence, the hydrogel is photopolymerized inside.

For applications with restricted physical access and illumination time, such as an Nucleus Pulposus replacement, photopolymerization of volumes with a large volume/illumination-area ratio becomes highly challenging. During polymerization, the material’s absorption and scattering coefficients change and directly influence local polymerization rates. By understanding and controlling such polymerization patterns, local material properties can be engineered (e.g. elastic modulus, swelling ratio), to match the set of mechanical requirements for the implant. Thus, it is essential to better understand and model photopolymerization reactions.

Experiments were conducted by polymerizing a hydrogel in a column-like volume using an optical fiber for light delivery. Quantitative scattering and absorption values as well as monomer conversion rates of the hydrogel sample were validated using a newly established Monte Carlo model for photopolymerization. The results were used to study and predict 3D polymerization patterns for different illumination configurations. In particular, we show an example of a lumbar intervertebral disc replacement where the jelly core of the intervertebral disc (Nucleus Pulposus) is replaced by an in situ photopolymerized hydrogel.

The results provide insights for the development of novel endoscopic light-scattering polymerization probes paving the way for a new generation of implantable hydrogels.

This PDF file contains the front matter associated with SPIE Proceedings Volume 8592, including the Title Page, Copyright Information, Table of Contents, and the Conference Committee listing.