Research Papers

Model-based analysis of reflectance and fluorescence spectra for in vivo detection of cervical dysplasia and cancer

[+] Author Affiliations
Crystal Redden Weber

Rice University, Department of Chemistry, Houston, Texas 77005

Richard A. Schwarz

Rice University, Department of Bioengineering, Houston, Texas 77005

E. Neely Atkinson

University of Texas M.D. Anderson Cancer Center, Department of Biostatistics, Houston, Texas 77030

Dennis D. Cox

Rice University, Department of Statistics, Houston, Texas 77005

Calum MacAulay

British Columbia Cancer Research Centre, Department of Cancer Imaging, Vancouver, British Columbia V5Z 1 L3, Canada

Michele Follen

University of Texas M.D. Anderson Cancer Center, Department of Gynecologic Oncology, Houston, Texas 77030

Rebecca Richards-Kortum

Rice University, Department of Bioengineering, Houston, Texas 77005

J. Biomed. Opt. 13(6), 064016 (November 10, 2008). doi:10.1117/1.3013307
History: Received June 25, 2008; Accepted September 16, 2008; Published November 10, 2008
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Development, validation, and implementation of an analytical model to extract biologically and diagnostically relevant parameters from measured cervical tissue reflectance and fluorescence spectra are presented. Monte Carlo simulations of tissue reflectance are used to determine the relative contribution of the signal from the epithelium and stroma. The results indicate that the clinical probe used collects a majority of its reflectance signal from the stroma; therefore, a one-layer analytical model of reflectance is used. Two analytical approaches to calculate reflectance spectra are compared to Monte Carlo simulations, and a diffusion theory-based model is implemented. The model is validated by fitting spectra generated from Monte Carlo simulations and comparing the input and output parameters. Median agreement between extracted optical properties and input parameters is 10.6%. The reflectance model is used together with an analytical model of tissue fluorescence to extract optical properties and fluorophore concentrations from 748 clinical measurements of cervical tissue. A diagnostic algorithm based on these extracted parameters is developed and evaluated using cross-validation. The sensitivity/specificity of this algorithm relative to the gold standard of histopathology per measurement are 8551%; this is comparable to accuracy reported in other studies of optical technologies for detection of cervical cancer and its precursors.

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© 2008 Society of Photo-Optical Instrumentation Engineers

Citation

Crystal Redden Weber ; Richard A. Schwarz ; E. Neely Atkinson ; Dennis D. Cox ; Calum MacAulay, et al.
"Model-based analysis of reflectance and fluorescence spectra for in vivo detection of cervical dysplasia and cancer", J. Biomed. Opt. 13(6), 064016 (November 10, 2008). ; http://dx.doi.org/10.1117/1.3013307


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