Document Type
Article
Source Publication Title
Biomedical Optics Express
First Page
1825
DOI
https://doi.org/10.1364/BOE.3.001825
Abstract
This study investigates the use of two spectroscopic techniques, auto-fluorescence lifetime measurement (AFLM) and light reflectance spectroscopy (LRS), for detecting invasive ductal carcinoma (IDC) in human ex vivo breast specimens. AFLM used excitation at 447 nm with multiple emission wavelengths (532, 562, 632, and 644 nm), at which autofluorescence lifetimes and their weight factors were analyzed using a double exponent model. LRS measured reflectance spectra in the range of 500-840 nm and analyzed the spectral slopes empirically at several distinct spectral regions. Our preliminary results based on 93 measured locations (i.e., 34 IDC, 31 benign fibrous, 28 adipose) from 6 specimens show significant differences in 5 AFLM-derived parameters and 9 LRS-based spectral slopes between benign and malignant breast samples. Multinomial logistic regression with a 10-fold cross validation approach was implemented with selected features to classify IDC from benign fibrous and adipose tissues for the two techniques independently as well as for the combined dual-modality approach. The accuracy for classifying IDC was found to be 96.4 ± 0.8%, 92.3 ± 0.8% and 96 ± 1.3% for LRS, AFLM, and dual-modality, respectively.
Disciplines
Biomedical Engineering and Bioengineering | Engineering
Publication Date
8-1-2012
Language
English
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Sharma, Vikrant; Shivalingaiah, Shivaranjani; Peng, Yan; Euhus, David; Gryczynski, Zygmunt; and Liu, Hanli, "Auto-fluorescence lifetime and light reflectance spectroscopy for breast cancer diagnosis: potential tools for intraoperative margin detection" (2012). Bioengineering Faculty Publications. 7.
https://mavmatrix.uta.edu/bioengineering_facpub/7
Comments
The authors thank Dr. Georgios Alexandrakis and Dr. Digant Dave from UT Arlington, for helpful discussions on AFLM measurements. The authors are grateful to Dr. Ignacy Gryczynski from the University of North Texas Health Science Center for his technical suggestions. Also, we thank Dr. Nancy Rowe from UT Arlington for statistics support in mixed model analysis.