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Journal of Biomedical Optics

Optical redox imaging indices discriminate human breast cancer from normal tissues
Author(s): He N. Xu; Julia Tchou; Min Feng; Huaqing Zhao; Lin Z. Li
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Paper Abstract

Our long-term goal was to investigate the potential of incorporating redox imaging technique as a breast cancer (BC) diagnosis component to increase the positive predictive value of suspicious imaging finding and to reduce unnecessary biopsies and overdiagnosis. We previously found that precancer and cancer tissues in animal models displayed abnormal mitochondrial redox state. We also revealed abnormal mitochondrial redox state in cancerous specimens from three BC patients. Here, we extend our study to include biopsies of 16 patients. Tissue aliquots were collected from both apparently normal and cancerous tissues from the affected cancer-bearing breasts shortly after surgical resection. All specimens were snap-frozen and scanned with the Chance redox scanner, i.e., the three-dimensional cryogenic NADH/Fp (reduced nicotinamide adenine dinucleotide/oxidized flavoproteins) fluorescence imager. We found both Fp and NADH in the cancerous tissues roughly tripled that in the normal tissues ( p < 0.05 ). The redox ratio Fp/(NADH + Fp) was 27 % higher in the cancerous tissues ( p < 0.05 ). Additionally, Fp, or NADH, or the redox ratio alone could predict cancer with reasonable sensitivity and specificity. Our findings suggest that the optical redox imaging technique can provide parameters independent of clinical factors for discriminating cancer from noncancer breast tissues in human patients.

Paper Details

Date Published: 29 November 2016
PDF: 8 pages
J. Biomed. Opt. 21(11) 114003 doi: 10.1117/1.JBO.21.11.114003
Published in: Journal of Biomedical Optics Volume 21, Issue 11
Show Author Affiliations
He N. Xu, University of Pennsylvania (United States)
University of Pennsylvania (United States)
Julia Tchou, University of Pennsylvania (United States)
University of Pennsylvania (United States)
University of Pennsylvania (United States)
Min Feng, University of Pennsylvania (United States)
University of Pennsylvania (United States)
Huaqing Zhao, Temple University (United States)
Lin Z. Li, University of Pennsylvania (United States)
University of Pennsylvania (United States)
University of Pennsylvania (United States)


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