Model based and empirical spectral analysis for the diagnosis of breast cancer

Changfang Zhu, Tara M. Breslin, Josephine Harter, Nirmala Ramanujam*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

We explored the use of both empirical (Partial Least Squares, PLS) and Monte Carlo model based approaches for the analysis of fluorescence and diffuse reflectance spectra measured ex vivo from freshly excised breast tissues and for the diagnosis of breast cancer. Features extracted using both approaches, i.e. principal components (PCs) obtained from empirical analysis or tissue properties obtained from model based analysis, displayed statistically significant difference between malignant and non-malignant tissues, and can be used to discriminate breast malignancy with comparable sensitivity and specificity of up to 90%. The PC scores of a subset of PCs also displayed significant correlation with the tissue properties extracted from the model based analysis, suggesting both approaches likely probe the same sources of contrast in the tissue spectra that discriminate between malignant and non-malignant breast tissues but in different ways.

Original languageEnglish (US)
Pages (from-to)14961-14978
Number of pages18
JournalOptics Express
Volume16
Issue number19
DOIs
StatePublished - Sep 15 2008

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

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