Dizem Arifler

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.

Determination of epithelial tissue scattering coefficient using confocal microscopy

Most models of light propagation through tissue assume the scattering properties of the various tissue layers are the same. The authors present evidence that the scattering coefficient of normal cervical epithelium is significantly lower than values previously reported for bulk epithelial tissue. They estimated the scattering coefficient of normal and precancerous cervical epithelium using measurements of the reflectance as a function of depth from confocal images. Reflectance measurements were taken from ex vivo cervical biopsies and fit to an exponential function based upon Beers law attenuation. The mean scattering coefficients derived were 22 cm/sup -1/ for normal tissue and 69 cm/sup -1/ for precancerous tissue. These values are significantly lower than previously reported for bulk epithelial tissues and suggest that scattering of bulk tissue is dominated by the stroma. They also suggest that computational models to describe light propagation in epithelial tissue must incorporate different scattering coefficients for the epithelium and stroma. Further, the lower scattering of the epithelium suggests greater probing depths for fiber optic probes used by optical diagnostic devices which measure reflectance and fluorescence in epithelial tissue. The difference in scattering between normal and precancerous tissue is attributed to increased nuclear size, optical density, and chromatin texture. The scattering coefficients measured here are consistent with predictions of numerical solutions to Maxwells equations for epithelial cell scattering.

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.

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.

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.

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.

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.