Quantification of multiphoton and fluorescence images of reproductive tissues from a mouse ovarian cancer model shows promise for early disease detection
Author
Sawyer, Travis WKoevary, Jennifer W
Rice, Faith P S
Howard, Caitlin C
Austin, Olivia J
Connolly, Denise C
Cai, Kathy Q
Barton, Jennifer K
Affiliation
Univ Arizona, Dept Biomed EngnUniv Arizona, Coll Opt Sci
Issue Date
2019-09-30
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Travis W. Sawyer, Jennifer W. Koevary, Faith P. S. Rice, Caitlin C. Howard, Olivia J. Austin, Denise C. Connolly, Kathy Q. Cai, and Jennifer K. Barton "Quantification of multiphoton and fluorescence images of reproductive tissues from a mouse ovarian cancer model shows promise for early disease detection," Journal of Biomedical Optics 24(9), 096010 (30 September 2019). https://doi.org/10.1117/1.JBO.24.9.096010Journal
JOURNAL OF BIOMEDICAL OPTICSRights
Copyright © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Ovarian cancer is the deadliest gynecologic cancer due predominantly to late diagnosis. Early detection of ovarian cancer can increase 5-year survival rates from 40% up to 92%, yet no reliable early detection techniques exist. Multiphoton microscopy (MPM) is a relatively new imaging technique sensitive to endogenous fluorophores, which has tremendous potential for clinical diagnosis, though it is limited in its application to the ovaries. Wide-field fluorescence imaging (WFI) has been proposed as a complementary technique to MPM, as it offers high-resolution imagery of the entire organ and can be tailored to target specific biomarkers that are not captured by MPM imaging. We applied texture analysis to MPM images of a mouse model of ovarian cancer. We also conducted WFI targeting the folate receptor and matrix metalloproteinases. We find that texture analysis of MPM images of the ovary can differentiate between genotypes, which is a proxy for disease, with high statistical significance (p < 0.001). The wide-field fluorescence signal also changes significantly between genotypes (p < 0.01). We use the features to classify multiple tissue groups to over 80% accuracy. These results suggest that MPM and WFI are promising techniques for the early detection of ovarian cancer. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License.Note
Open access articleISSN
1083-3668PubMed ID
31571434Version
Final published versionSponsors
Graduate Research Fellowship Program, National Science Foundation (NSF) [DGE-1143953]; National Institutes of Health under National Cancer Institute [1R01CA195723]; University of Arizona Cancer Center [3P30CA023074]; Theresa F. Jennings Memorial Scholarship; FCCC Core [NCI P30 CA006927]; FCCC Biosample Repository Facility; FCCC Histopathology Facilityae974a485f413a2113503eed53cd6c53
10.1117/1.JBO.24.9.096010
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