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Journal of Biomedical Optics • Open Access

Spectral areas and ratios classifier algorithm for pancreatic tissue classification using optical spectroscopy
Author(s): Malavika Chandra; James Scheiman; Diane Simeone; Barbara McKenna; Julianne Purdy; Mary-Ann Mycek

Paper Abstract

Pancreatic adenocarcinoma is one of the leading causes of cancer death, in part because of the inability of current diagnostic methods to reliably detect early-stage disease. We present the first assessment of the diagnostic accuracy of algorithms developed for pancreatic tissue classification using data from fiber optic probe-based bimodal optical spectroscopy, a real-time approach that would be compatible with minimally invasive diagnostic procedures for early cancer detection in the pancreas. A total of 96 fluorescence and 96 reflectance spectra are considered from 50 freshly excised tissue sites-including human pancreatic adenocarcinoma, chronic pancreatitis (inflammation), and normal tissues-on nine patients. Classification algorithms using linear discriminant analysis are developed to distinguish among tissues, and leave-one-out cross-validation is employed to assess the classifiers' performance. The spectral areas and ratios classifier (SpARC) algorithm employs a combination of reflectance and fluorescence data and has the best performance, with sensitivity, specificity, negative predictive value, and positive predictive value for correctly identifying adenocarcinoma being 85, 89, 92, and 80%, respectively.

Paper Details

Date Published: 1 January 2010
PDF: 3 pages
J. Biomed. Opt. 15(1) 010514 doi: 10.1117/1.3314900
Published in: Journal of Biomedical Optics Volume 15, Issue 1
Show Author Affiliations
Malavika Chandra, Univ. of Michigan (United States)
James Scheiman, Univ. of Michigan Health System (United States)
Diane Simeone, Univ. of Michigan Medical School (United States)
Barbara McKenna, Univ. of Michigan Medical School (United States)
Julianne Purdy, Univ. of Michigan Medical School (United States)
Mary-Ann Mycek, Univ. of Michigan (United States)

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