Research Papers: Imaging

Multispectral fluorescence imaging of human ovarian and fallopian tube tissue for early-stage cancer detection

[+] Author Affiliations
Tyler H. Tate, Weston A. Welge

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

Brenda Baggett, Photini F. S. Rice, Jennifer Watson Koevary, Gabriel V. Orsinger, Ariel C. Nymeyer

University of Arizona, Department of Biomedical Engineering, 1657 East Helen Street, Tucson, Arizona 85721, United States

Kathylynn Saboda, Denise J. Roe, Kenneth D. Hatch, Setsuko K. Chambers

University of Arizona Cancer Center, 1515 North Campbell Avenue, Tucson, Arizona 85724, United States

Urs Utzinger, Jennifer Kehlet Barton

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

University of Arizona, Department of Biomedical Engineering, 1657 East Helen Street, Tucson, Arizona 85721, United States

J. Biomed. Opt. 21(5), 056005 (May 24, 2016). doi:10.1117/1.JBO.21.5.056005
History: Received January 26, 2016; Accepted April 25, 2016
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Abstract.  With early detection, 5-year survival rates for ovarian cancer exceed 90%, yet no effective early screening method exists. Emerging consensus suggests over 50% of the most lethal form of the disease originates in the fallopian tube. Twenty-eight women undergoing oophorectomy or debulking surgery provided informed consent for the use of surgical discard tissue samples for multispectral fluorescence imaging. Using multiple ultraviolet and visible excitation wavelengths and emissions bands, 12 fluorescence and 6 reflectance images of 47 ovarian and 31 fallopian tube tissue samples were recorded. After imaging, each sample was fixed, sectioned, and stained for pathological evaluation. Univariate logistic regression showed cancerous tissue samples had significantly lower intensity than noncancerous tissue for 17 image types. The predictive power of multiple image types was evaluated using multivariate logistic regression (MLR) and quadratic discriminant analysis (QDA). Two MLR models each using two image types had receiver operating characteristic curves with area under the curve exceeding 0.9. QDA determined 56 image type combinations with perfect resubstituting using as few as five image types. Adaption of the system for future in vivo fallopian tube and ovary endoscopic imaging is possible, which may enable sensitive detection of ovarian cancer with no exogenous contrast agents.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Tyler H. Tate ; Brenda Baggett ; Photini F. S. Rice ; Jennifer Watson Koevary ; Gabriel V. Orsinger, et al.
"Multispectral fluorescence imaging of human ovarian and fallopian tube tissue for early-stage cancer detection", J. Biomed. Opt. 21(5), 056005 (May 24, 2016). ; http://dx.doi.org/10.1117/1.JBO.21.5.056005


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