This PDF file contains the front matter associated with SPIE Proceedings Volume 11253, including the title page, copyright information, table of contents, and author and conference committee lists.

Angle-resolved low-coherence interferometry (a/LCI) is an optical technique which uses inverse models of light scattering to predict the size and density of cell nuclei, a significant biomarker of precancer. In recent years, substantial progress has occurred in a/LCI technology, particularly in novel instrumentation for the detection of dysplasia in the cervix and the esophagus. This abstract summarizes recent developments in a/LCI, with a focus on developments over the previous four years. Clinical studies in the cervix, novel optical instrumentation addressing the cervix and esophagus, and novel applications related to Alzheimer’s disease are discussed.

This Conference Presentation, “In situ molecular characterization and brain cancer detection using macroscopic spontaneous Raman spectroscopy imaging” was recorded at Photonics West held in San Francisco, California, United States.

Biological tissue characterization using optical imaging techniques often focus on optical property quantification, a process that relies on a diffuse or sub-diffuse light transport model. Assumptions associated with each light transport model reduce the applicability and increase the computational and/or experimental complexity of the techniques. Scattering orientation index and texture metrics quantified for human breast tissues are free of light transport assumptions and were quantified using the demodulated reflectance from wide-field structured light imaging. This work suggests that wide-field tissue diagnostics might be possible without model-based optical property quantification and instead using assumption-free scatter orientation and textural information.

We present two new methods used to determine the optical properties in ovarian cancer, idiopathic pulmonary fibrosis and osteoarthritis. The bulk optical properties are determined by a combination of on axis attenuation, goniometry, and Monte Carlo simulations. The resulting wavelength dependent values delineates the importance of both μs’ and the fractal dimension. We also present a new method to determine μs’ on the SHG microscope. By measuring the depth dependence of the SHG emission directionality and performing Monte Carlo simulations, both the relative fibril size distribution and reduced scattering coefficient can be simultaneously determined without the need for bulk measurements.

Near infrared spectroscopy (NIRS) combined with diffuse correlation spectroscopy (DCS) enable non-invasive, bedside assessment of brain blood flow and metabolism. In numerous disease states (e.g., stroke, traumatic brain injury) these hemodynamic parameters are deranged, and these derangements have diagnostic and/or prognostic value. However, to best utilize NIRS/DCS data to guide patient care, we need a mechanistic understanding of the molecular changes underlying hemodynamic and metabolic dysfunction. Using a mouse model of repetitive mild traumatic brain injury, we present an example of how preclinical studies with NIRS/DCS can aid in the interpretation and utility of clinical NIRS/DCS datasets.

Small cellular deformations associated with the changes of cell potential can reveal the underlying physiological activity. Using quantitative phase microscopy, we demonstrate deformations of up to 3nm during action potential in HEK cells, and ~1nm in primary cortical neurons. Phase-resolved OCT with adaptive optics in human eyes revealed rapid axial shrinkage of the cone outer segments, starting within 0.3ms after light stimulus, followed by a gradual expansion that saturates around 500ms. Characteristics of the rapid outer segment contraction are consistent with the early receptor potential, attributed to charge movement across the outer segment disc membranes during photoisomerization.

This Conference Presentation, “Inverse spectroscopic optical coherence tomography to measure tissue ultrastructures and functions” was recorded at Photonics West held in San Francisco, California, United States.

Brillouin light scattering spectroscopy is an emerging technology providing label-free measurements of the viscoelastic properties of biological samples. Traditionally, Brillouin spectroscopy is performed using multipass Fabry Perot spectrometers, which allows high spectral extinction but low speed, or cross-axis Virtually Image Phased Array (VIPA) based spectrometers, with rapid single shot measurements but limited extinction. Here we present a multipass VIPA-based spectrometer, in which light is dispersed along the same axis at every stage and recirculated in the same etalon multiple times. This technical advancement allows single-shot high extinction Brillouin measurements as well as reduced spread of instrumental spectral linewidth.

Angle-resolved light scattering microscopy enables the size distribution of scatterers within a cell to be estimated non-invasively. Our group is working towards obtaining quantitative estimates of mean scatterer size in single cells by comparing the angular distribution of scattered light to Mie theory models. Using quantitative phase imaging, we are able to measure multiple cells at a time and still obtain each cell’s scattering pattern individually. We are now acquiring data from macrophages performing antibody-dependent cellular phagocytosis (ADCP) in hopes of relating the size estimates to the different known stages of the process.

The hyperspectral, interferometric microscopy technique, PWS has demonstrated the ability to measure variance in the nanoscale refractive index (Σ) of chromatin – the macromolecular assembly containing most of a cell’s genetic material. However, the question arises: how does Σ relate to the physical distribution of mass in chromatin, and specifically the organization of chromatin packing. We developed an analytical framework to relate Σ to the mass-density autocorrelation function – which can fully describe the distribution of mass and is characterized by D. This relationship was validated numerically using the rigorous modelling technique FDTD and experimentally with PWS and Chromatin Electron Microscopy (ChromEM).

Due to the multiple scattering of light in biomedical tissue, the imaging depth of conventional optical coherence tomography is limited to 1-2 millimeters. In this research, a reflection-matrix-method-based optical coherence tomography has been developed to extend the imaging depth into scattering medium. After obtaining the matrix, singular value decomposition and imaging reconstruction are carried out in the post-process to recover the target image beneath turbid media. Specifically, in order to speed up the matrix measurement and reduce the phase noises during the acquisition process, wide-field heterodyne detection is adopted in our system by using a high-speed lock-in camera.

Diffuse correlation spectroscopy (DCS) is an established diffuse optical technique that uses the analysis of temporal speckle intensity fluctuations to measure blood flow in tissue. DCS has been shown to be an effective monitor of cerebral blood flow in many neuro-monitoring applications, though still suffers from depth sensitivity issues. Recent studies have shown that moving to 1064 nm when making DCS measurements improves SNR and sensitivity to depth, but detector challenges have slowed the change to that wavelength. Here, we present on a multipixel, interferometric DCS (iDCS) system that improves measurement capabilities at this wavelength.

Surface weighted imaging in a wide-field manner is useful for many biomedical applications such as margin status determination in breast conserving surgery. One technique that has shown promise for this application is modulated imaging at high spatial frequency. A new technique to provide similar information in a more compact manner with the ability to customize based on desired depth penetration was developed. This technique involves quickly scanning a point source over the tissue surface and selective removing diffuse photons in image processing. These two techniques were compared using custom made depth phantoms of tissue equivalent material.

Margin assessment in gross pathology is becoming feasible as various explanatory deep learning-powered methods are able to obtain models for macroscopic textural information, tissue microstructure, and local surface optical properties. Unfortunately, each different method seems to lack enough diagnostic power to perform an adequate classification on its own. This work proposes using several separately trained deep convolutional networks, and averaging their responses, in order to achieve a better margin assessment. Qualitative leave-one-out cross-validation results are discussed for a cohort of 70 samples.

An empirical approach to estimate the reduced scattering (μ_s’) and absorption (μ_a) coefficients of a turbid medium from time-resolved diffuse reflectance detected at multiple source-detector separations (SDS) is described. The dependence of the temporal point spread function (TPSF) on the medium’s optical properties has been previously well studied. Here, we exploit these findings by using the difference in photon arrival-times obtained from a pair of SDS at the (a) peak intensity and (b) longer-time trailing edge of the TPSF to estimate the transport coefficients. This difference may have little dependence on the instrument response functions (IRF). Consequently, real-time quantitation is possible since the method does not depend on non-linear fitting of measured reflectance and/or deconvolving the IRF. The approach uses Monte Carlo simulations to directly translate the difference in arrival times of the temporal reflectance profiles at multiple SDS into the medium’s optical properties. Here, we show that a small range in the optical properties could be defined using a pair of time differences in the TPSF.

Optical Coherence tomography (OCT) is a rapidly developing light based imaging modality that can provide functional information and visualization of tissue morphology and cell death by quantifying the motion of intracellular structures. In this work, Dynamic light scattering (DLS) with OCT, is used to compute the time-dependent fluctuations in scattered light intensity. Using the DLS-OCT method, we have previously shown a higher rate of intracellular motion detected in apoptotic cells compared to viable cells. In this study, we aim to probe the intracellular motion of cells at much higher scan-rates that we have attempted previously to detect sub-cellular motion with greater sensitivity. To validate the DLS-OCT approach, M-mode OCT images were acquired using Thorlabs SS-OCT system (sampling rate of 100 kHz) to measure the Brownian motion in monodisperse microsphere suspensions. The results demonstrate that ACF decays more rapidly for smaller size microspheres and the experimental decorrelation time values matched with the theoretical values calculated using the Einstein-Stokes equation.

Diffuse Correlation Spectroscopy (DCS) is a widely used non-invasive measurement technique to quantitatively estimate deep tissue blood flow. In recent years, newer approaches to blood flow measurement with DCS, Diffuse Speckle Contrast Analysis (DSCA) and Speckle Contrast Optical Spectroscopy (SCOS), have adapted speckle contrast analysis methods to simplify deep tissue blood flow measurements using cameras and SPAD arrays as detectors. In this paper, we introduce and demonstrate a new integrated DCS (iDCS) detector, a novel optical sensor setup which leverages diffuse speckle contrast analysis for probe-level quantitative measurement tissue blood flow. In iDCS, a normal photodiode is used in photovoltaic mode to integrate photon intensity fluctuations over multiple integration times as opposed to the high frequency sampling of photon counts with DCS. The iDCS detector scheme features small form factor, low cost, simple instrument design. Preliminary in-vivo experiments on the forearm of a subject, during arm-cuff occlusion, showed ~100% relative change in blood flow which is comparable to blood flow changes measured using traditional DCS.

Morphological changes in tissue are highly correlated with progression of cancer. Such structural changes lead to fluctuations of refractive index (RI) inside the tissue, which are random and exhibit self-similar properties. Depth distribution in RI of oral tissue samples were studied through Fourier domain low coherence interferometry. A halogen tungsten lamp was used as the source, and an Ocean Optics spectrometer was used for the collection of interference spectra. The experimental system was calibrated using mica sheets of different thick- nesses, polystyrene microspheres and polydimethylsiloxane (PDMS). Multifractal detrended fluctuation analysis (MFDFA) were employed on interference spectra to study and quantify multifractality in depth-wise distribution of the RI in oral tissue sections. The derived multifractal parameters, namely the generalized Hurst exponent and the width of the multifractal spectrum, showed quite significant differences among tissues having three different grades of cancer. The depth-wise variation of the refractive index showed an increase in multifractality with increasing pathological grades of cancer.