Research Papers: Imaging

Wide-field spectral imaging of human ovary autofluorescence and oncologic diagnosis via previously collected probe data

[+] Author Affiliations
Timothy E. Renkoski

University of Arizona, College of Optical Sciences, 1630 East University Boulevard, Tucson, Arizona 85721

Kenneth D. Hatch

University of Arizona, Arizona Health Sciences Center, Department of Obstetrics and Gynecology, North Campbell Avenue, Tucson, Arizona 85724

Urs Utzinger

University of Arizona, College of Optical Sciences, 1630 East University Boulevard, Tucson, Arizona 85721

University of Arizona, Arizona Health Sciences Center, Department of Obstetrics and Gynecology, North Campbell Avenue, Tucson, Arizona 85724

University of Arizona, Department of Biomedical Engineering, 1127 East James E. Rogers Way, Tucson, Arizona 85721

J. Biomed. Opt. 17(3), 036003 (Mar 29, 2012). doi:10.1117/1.JBO.17.3.036003
History: Received August 21, 2011; Revised December 2, 2011; Accepted January 4, 2012
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Abstract.  With no sufficient screening test for ovarian cancer, a method to evaluate the ovarian disease state quickly and nondestructively is needed. The authors have applied a wide-field spectral imager to freshly resected ovaries of 30 human patients in a study believed to be the first of its magnitude. Endogenous fluorescence was excited with 365-nm light and imaged in eight emission bands collectively covering the 400- to 640-nm range. Linear discriminant analysis was used to classify all image pixels and generate diagnostic maps of the ovaries. Training the classifier with previously collected single-point autofluorescence measurements of a spectroscopic probe enabled this novel classification. The process by which probe-collected spectra were transformed for comparison with imager spectra is described. Sensitivity of 100% and specificity of 51% were obtained in classifying normal and cancerous ovaries using autofluorescence data alone. Specificity increased to 69% when autofluorescence data were divided by green reflectance data to correct for spatial variation in tissue absorption properties. Benign neoplasm ovaries were also found to classify as nonmalignant using the same algorithm. Although applied ex vivo, the method described here appears useful for quick assessment of cancer presence in the human ovary.

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© 2012 Society of Photo-Optical Instrumentation Engineers

Citation

Timothy E. Renkoski ; Kenneth D. Hatch and Urs Utzinger
"Wide-field spectral imaging of human ovary autofluorescence and oncologic diagnosis via previously collected probe data", J. Biomed. Opt. 17(3), 036003 (Mar 29, 2012). ; http://dx.doi.org/10.1117/1.JBO.17.3.036003


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