Autofluorescence and diffuse reflectance patterns in cervical spectroscopy

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Date

2005

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Marín, Nena Maribel

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Abstract

Fluorescence and diffuse reflectance spectroscopy are two new optical technologies, which have shown promise to aid in the real time, non-invasive identification of cancers and precancers. Spectral patterns carry a fingerprint of scattering, absorption and fluorescence properties in tissue. Scattering, absorption and fluorescence in tissue are directly affected by biological features that are diagnostically significant, such as nuclear size, micro-vessel density, volume fraction of collagen fibers, tissue oxygenation and cell metabolism. Thus, analysis of spectral patterns can unlock a wealth of information directly related with the onset and progression of disease. Data from a Phase II clinical trial to assess the technical efficacy of fluorescence and diffuse reflectance spectroscopy acquired from 850 women at three clinical locations with two research grade optical devices is calibrated and analyzed. Tools to process and standardize spectra so that data from multiple spectrometers can be combined and analyzed are presented. Methodologies for calibration and quality assurance of optical systems are established to simplify design issues and ensure validity of data for future clinical trials. Empirically based algorithms, using multivariate statistical approaches are applied to spectra and evaluated as a clinical diagnostic tool. Physically based algorithms, using mathematical models of light propagation in tissue are presented. The presented mathematical model combines a diffusion theory in P3 approximation reflectance model and a 2-layer fluorescence model using exponential attenuation and diffusion theory. The resulting adjoint fluorescence and reflectance model extracts twelve optical properties characterizing fluorescence efficiency of cervical epithelium and stroma fluorophores, stromal hemoglobin and collagen absorption, oxygen saturation, and stromal scattering strength and shape. Validations with Monte Carlo simulations show that adjoint model extracted optical properties of the epithelium and the stroma can be estimated accurately. Adjoint model is applied to 926 clinical measurements from 503 patients. Mean values of extracted optical properties have demonstrated to characterize the biological changes associated with dysplastic progression. Finally, penalized logistic regression algorithms are applied to discriminate dysplastic stages in tissue based on extracted optical features. This work provides understandable and interpretable information regarding predictive and generalization ability of optical spectroscopy in neoplastic changes using a minimum subset of optical measurements. Ultimately these methodologies would facilitate the transfer of these optical technologies into clinical practice.

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