Assessment of internal refractive index profile of stochastically inhomogeneous nuclear models via analysis of two-dimensional optical scattering patterns.

SIGNIFICANCE: Optical scattering signals obtained from tissue constituents contain a wealth of structural information. Conventional intensity features, however, are mostly dictated by the overall morphology and mean refractive index of these constituents, making it very difficult to exclusively sense internal refractive index fluctuations. AIM: We perform a systematic analysis to elucidate how changes in internal refractive index profile of cell nuclei can best be detected via optical scattering. APPROACH: We construct stochastically inhomogeneous nuclear models and numerically simulate their azimuth-resolved scattering patterns. We then process these two-dimensional patterns with the goal of identifying features that directly point to subnuclear structure. RESULTS: Azimuth-dependent intensity variations over the side scattering range provide significant insights into subnuclear refractive index profile. A particular feature we refer to as contrast ratio is observed to be highly sensitive to the length scale and extent of refractive index fluctuations; further, this feature is not susceptible to changes in the overall size and mean refractive index of nuclei, thereby allowing for selective tracking of subnuclear structure that can be linked to chromatin distribution. CONCLUSIONS: Our analysis will potentially pave the way for scattering-based assessment of chromatin reorganization that is considered to be a key hallmark of precancer progression.

Monte Carlo Analysis of Molecule Absorption Probabilities in Diffusion-Based Nanoscale Communication Systems with Multiple Receivers.

For biomedical applications of nanonetworks, employing molecular communication for information transport is advantageous over nano-electromagnetic communication: molecular communication is potentially biocompatible and inherently energy-efficient. Recently, several studies have modeled receivers in diffusion-based molecular communication systems as "perfectly monitoring" or "perfectly absorbing" spheres based on idealized descriptions of chemoreception. In this paper, we focus on perfectly absorbing receivers and present methods to improve the accuracy of simulation procedures that are used to analyze these receivers. We employ schemes available from the chemical physics and biophysics literature and outline a Monte Carlo simulation algorithm that accounts for the possibility of molecule absorption during discrete time steps, leading to a more accurate analysis of absorption probabilities. Unlike most existing studies that consider a single receiver, this paper analyzes absorption probabilities for multiple receivers deterministically or randomly deployed in a region. For random deployments, the ultimate absorption probabilities as a function of transmitter-receiver distance are shown to fit well to power laws; the exponents derived become more negative as the number of receivers increases up to a limit beyond which no additional receivers can be "packed" in the deployment region. This paper is expected to impact the design of molecular nanonetworks with multiple absorbing receivers.

Optimal wavelength combinations for near-infrared spectroscopic monitoring of changes in brain tissue hemoglobin and cytochrome c oxidase concentrations.

We analyze broadband near-infrared spectroscopic measurements obtained from newborn piglets subjected to hypoxia-ischemia and we aim to identify optimal wavelength combinations for monitoring cerebral tissue chromophores. We implement an optimization routine based on the genetic algorithm to perform a heuristic search for discrete wavelength combinations that can provide accurate concentration information when benchmarked against the gold standard of 121 wavelengths. The results indicate that it is possible to significantly reduce the number of measurement wavelengths used in conjunction with spectroscopic algorithms and still achieve a high performance in estimating changes in concentrations of oxyhemoglobin, deoxyhemoglobin, and oxidized cytochrome c oxidase. While the use of a 3-wavelength combination leads to mean recovery errors of up to 10%, these errors drop to less than 4% with 4 or 5 wavelengths and to even less than 2% with 8 wavelengths.

Numerical investigation of two-dimensional light scattering patterns of cervical cell nuclei to map dysplastic changes at different epithelial depths.

We use an extensive set of quantitative histopathology data to construct realistic three-dimensional models of normal and dysplastic cervical cell nuclei at different epithelial depths. We then employ the finite-difference time-domain method to numerically simulate the light scattering response of these representative models as a function of the polar and azimuthal scattering angles. The results indicate that intensity and shape metrics computed from two-dimensional scattering patterns can be used to distinguish between different diagnostic categories. Our numerical study also suggests that different epithelial layers and angular ranges need to be considered separately to fully exploit the diagnostic potential of two-dimensional light scattering measurements.

Nanoplatform-based optical contrast enhancement in epithelial tissues: quantitative analysis via Monte Carlo simulations and implications on precancer diagnostics.

This paper presents a comprehensive computational analysis of the spectral optical response of epithelial tissues labeled with gold nanoparticles. Monte Carlo modeling is employed to simulate nanoparticle-induced changes in reflectance signals and to assess whether labeling can generate sufficient exogenous contrast that can better pinpoint precancer progression. Simulation results suggest that the observed contrast profile is highly dependent on a series of factors including the labeling scheme, optical sensor geometry, and wavelength. It is evident, however, that selection of an optimal labeling and sensing strategy can lead to a significant enhancement of the inherent positive or negative contrast and can improve the diagnostic potential of optical measurements.

Influence of phase function on modeled optical response of nanoparticle-labeled epithelial tissues.

Metal nanoparticles can be functionalized with biomolecules to selectively localize in precancerous tissues and can act as optical contrast enhancers for reflectance-based diagnosis of epithelial precancer. We carry out Monte Carlo (MC) simulations to analyze photon propagation through nanoparticle-labeled tissues and to reveal the importance of using a proper form of phase function for modeling purposes. We first employ modified phase functions generated with a weighting scheme that accounts for the relative scattering strengths of unlabeled tissue and nanoparticles. To present a comparative analysis, we repeat our MC simulations with simplified functions that only approximate the angular scattering properties of labeled tissues. The results obtained for common optical sensor geometries and biologically relevant labeling schemes indicate that the exact form of the phase function used as model input plays an important role in determining the reflectance response and approximating functions often prove inadequate in predicting the extent of contrast enhancement due to labeling. Detected reflectance intensities computed with different phase functions can differ up to ∼60% and such a significant deviation may even alter the perceived contrast profile. These results need to be taken into account when developing photon propagation models to assess the diagnostic potential of nanoparticle-enhanced optical measurements.

Sensitivity of spatially resolved reflectance signals to coincident variations in tissue optical properties.

Canonical correlation analysis, a multivariate statistical technique, was used to investigate the degree of association between tissue optical properties and spatially resolved reflectance signals. Monte Carlo modeling was employed to simulate signals corresponding to different combinations of optical properties and these data sets were fed as input to statistical analysis. The results show that it is possible to adjust the separation and angular orientation of source and detector fibers such that the effect of a particular optical property will be augmented among coincident variations in other properties. The trends observed exhibit differences when compared with a conventional univariate sensitivity analysis in which only a single property is varied whereas all other parameters of interest are kept constant.

Combined Monte Carlo and finite-difference time-domain modeling for biophotonic analysis: implications on reflectance-based diagnosis of epithelial precancer.

Monte Carlo (MC) modeling of photon transport in tissues is generally performed using simplified functions that only approximate the angular scattering properties of tissue constituents. However, such approximations may not be sufficient for fully characterizing tissue scatterers such as cells. Finite-difference time-domain (FDTD) modeling provides a flexible approach to compute realistic tissue phase functions that describe probability of scattering at different angles. We describe a computational framework that combines MC and FDTD modeling, and allows random sampling of scattering directions from FDTD phase functions. We carry out simulations to assess the influence of incorporating realistic FDTD phase functions on modeling spectroscopic reflectance signals obtained from normal and precancerous epithelial tissues. Simulations employ various fiber optic probe designs to analyze the sensitivity of different probe geometries to FDTD-generated phase functions. Combined MC/FDTD modeling results indicate that the form of the phase function used is an important factor in determining the reflectance profile of tissues, and detected reflectance intensity can change up to approximately 30% when a realistic FDTD phase function is used instead of an approximating function. The results presented need to be taken into account when developing photon propagation models or implementing inverse algorithms to extract optical properties from measurements.

Light scattering from collagen fiber networks: micro-optical properties of normal and neoplastic stroma.

Development of epithelial precancer and cancer leads to well-documented molecular and structural changes in the epithelium. Recently, it has been recognized that stromal biology is also altered significantly with preinvasive disease. We used the finite-difference time-domain method, a popular technique in computational electromagnetics, to model light scattering from heterogeneous collagen fiber networks and to analyze how neoplastic changes alter stromal scattering properties. Three-dimensional optical images from the stroma of fresh normal and neoplastic oral-cavity biopsies were acquired using fluorescence confocal microscopy. These optical sections were then processed to create realistic three-dimensional collagen networks as model input. Image analysis revealed that the volume fraction of collagen fibers in the stroma decreases with precancer and cancer progression, and fibers tend to be shorter and more disconnected in neoplastic stroma. The finite-difference time-domain modeling results showed that neoplastic fiber networks have smaller scattering cross sections compared to normal networks. Computed scattering-phase functions indicate that high-angle scattering probabilities tend to be higher for neoplastic networks. These results provide valuable insight into the micro-optical properties of normal and neoplastic stroma. Characterization of optical signals obtained from epithelial tissues can aid in development of optical spectroscopic and imaging techniques for noninvasive monitoring of early neoplastic changes.

Spatially resolved reflectance spectroscopy for diagnosis of cervical precancer: Monte Carlo modeling and comparison to clinical measurements.

We present Monte Carlo modeling studies to provide a quantitative understanding of contrast observed in spatially resolved reflectance spectra of normal and highly dysplastic cervical tissue. Simulations have been carried out to analyze the sensitivity of spectral measurements to a range of changes in epithelial and stromal optical properties that are reported to occur as dysplasia develops and to predict reflectance spectra of normal and highly dysplastic tissue at six different source-detector separations. Simulation results provide important insights into specific contributions of different optical parameters to the overall spectral response. Predictions from simulations agree well with in vivo measurements from cervical tissue and successfully describe spectral differences observed in reflectance measurements from normal and precancerous tissue sites. Penetration depth statistics of photons detected at the six source-detector separations are also presented to reveal the sampling depth profile of the fiber-optic probe geometry simulated. The modeling studies presented provide a framework to meaningfully interpret optical signals obtained from epithelial tissues and to optimize design of optical sensors for in vivo reflectance measurements for precancer detection. Results from this study can facilitate development of analytical photon propagation models that enable inverse estimation of diagnostically relevant optical parameters from in vivo reflectance measurements.

Reflectance spectroscopy for diagnosis of epithelial precancer: model-based analysis of fiber-optic probe designs to resolve spectral information from epithelium and stroma.

Reflectance spectroscopy is a promising technology for detection of epithelial precancer. Fiber-optic probes that selectively collect scattered light from both the epithelium and the underlying stroma are likely to improve diagnostic performance of in vivo reflectance spectroscopy by revealing diagnostic features unique to each layer. We present Monte Carlo models with which to evaluate fiber-optic probe geometries with respect to sampling depth and depth resolution. We propose a probe design that utilizes half-ball lens coupled source and detector fibers to isolate epithelial scattering from stromal scattering and hence to resolve spectral information from the two layers. The probe is extremely compact and can provide easy access to different organ sites.

Ball lens coupled fiber-optic probe for depth-resolved spectroscopy of epithelial tissue.

A ball lens coupled fiber-optic probe design is described for depth-resolved measurements of the fluorescence and reflectance properties of epithelial tissue. A reflectance target, fluorescence targets, and a two-layer tissue phantom consisting of fluorescent microspheres suspended in collagen are used to characterize the performance of the probe. Localization of the signal to within 300 microm of the probe tip is observed by use of reflectance and fluorescence targets in air. Differential enhancement of the fluorescence signal from the top layer of the two-layer tissue phantom is observed.

Analytical model to describe fluorescence spectra of normal and preneoplastic epithelial tissue: comparison with Monte Carlo simulations and clinical measurements.

Fluorescence spectroscopy has shown promise for the detection of precancerous changes in vivo. The epithelial and stromal layers of tissue have very different optical properties; the albedo is relatively low in the epithelium and approaches one in the stroma. As precancer develops, the optical properties of the epithelium and stroma are altered in markedly different ways: epithelial scattering and fluorescence increase, and stromal scattering and fluorescence decrease. We present an analytical model of the fluorescence spectrum of a two-layer medium such as epithelial tissue. Our hypothesis is that accounting for the two different tissue layers will provide increased diagnostic information when used to analyze tissue fluorescence spectra measured in vivo. The Beer-Lambert law is used to describe light propagation in the epithelial layer, while light propagation in the highly scattering stromal layer is described with diffusion theory. Predictions of the analytical model are compared to results from Monte Carlo simulations of light propagation under a range of optical properties reported for normal and precancerous epithelial tissue. In all cases, the mean square error between the Monte Carlo simulations and the analytical model are within 15%. Finally, model predictions are compared to fluorescence spectra of normal and precancerous cervical tissue measured in vivo; the lineshape of fluorescence agrees well in both cases, and the decrease in fluorescence intensity from normal to precancerous tissue is correctly predicted to within 5%. Future work will explore the use of this model to extract information about changes in epithelial and stromal optical properties from clinical measurements and the diagnostic value of these parameters.

Light scattering from normal and dysplastic cervical cells at different epithelial depths: finite-difference time-domain modeling with a perfectly matched layer boundary condition.

The finite-difference time-domain (FDTD) method provides a flexible approach to studying the scattering that arises from arbitrarily inhomogeneous structures. We implemented a three-dimensional FDTD program code to model light scattering from biological cells. The perfectly matched layer (PML) boundary condition has been used to terminate the FDTD computational grid. We investigated differences in angle-dependent scattering properties of normal and dysplastic cervical cells. Specifically, the scattering patterns and phase functions have been computed for normal and dysplastic cervical cells at three different epithelial depths, namely, basal/parabasal, intermediate, and superficial. Construction of cervical cells within the FDTD computational grid is based on morphological and chromatin texture features obtained from quantitative histopathology. The results show that angle-dependent scattering characteristics are different not only for normal and dysplastic cells but also for cells at different epithelial depths. The calculated scattering cross-sections are significantly greater for dysplastic cells. The scattering cross-sections of cells at different depths indicate that scattering decreases in going from the superficial layer to the intermediate layer, but then increases in the basal/parabasal layer. This trend for epithelial cell scattering has also been observed in confocal images of ex vivo cervical tissue.

Endoscopic microscopy.

In vivo endoscopic optical microscopy provides a tool to assess tissue architecture and morphology with contrast and resolution similar to that provided by standard histopathology--without need for physical tissue removal. In this article, we focus on optical imaging technologies that have the potential to dramatically improve the detection, prevention, and therapy of epithelial cancers. Epithelial pre-cancers and cancers are associated with a variety of morphologic, architectural, and molecular changes, which currently can be assessed only through invasive, painful biopsy. Optical imaging is ideally suited to detecting cancer-related alterations because it can detect biochemical and morphologic alterations with sub-cellular resolution throughout the entire epithelial thickness. Optical techniques can be implemented non-invasively, in real time, and at low cost to survey the tissue surface at risk. Our manuscript focuses primarily on modalities that currently are the most developed: reflectance confocal microscopy (RCM) and optical coherence tomography (OCT). However, recent advances in fluorescence-based endoscopic microscopy also are reviewed briefly. We discuss the basic principles of these emerging technologies and their current and potential applications in early cancer detection. We also present research activities focused on development of exogenous contrast agents that can enhance the morphological features important for cancer detection and that have the potential to allow vital molecular imaging of cancer-related biomarkers. In conclusion, we discuss future improvements to the technology needed to develop robust clinical devices.