Anatomy-Based Algorithms for Detecting Oral Cancer Using Reflectance and Fluorescence Spectroscopy
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McGee_2009.pdf
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Author(s)
McGee, Sasha
Mardirossian, Vartan
Elackattu, Alphi
Mirkovic, Jelena
Pistey, Robert
Gallagher, George
Kabani, Sadru
Yu, Chung-Chieh
Wang, Zimmern
Badizadegan, Kamran
Date Issued
November 2009
Journal
Annals of Otology, Rhinology & Laryngology
Publisher
Annals Publishing Company
Citation
Ann Otol Rhinol Laryngol. 2009 Nov;118(11):817-26.
Version
Author's final manuscript
Abstract
OBJECTIVES: We used reflectance and fluorescence spectroscopy to noninvasively and quantitatively distinguish benign from dysplastic/malignant oral lesions. We designed diagnostic algorithms to account for differences in the spectral properties among anatomic sites (gingiva, buccal mucosa, etc).
METHODS: In vivo reflectance and fluorescence spectra were collected from 71 patients with oral lesions. The tissue was then biopsied and the specimen evaluated by histopathology. Quantitative parameters related to tissue morphology and biochemistry were extracted from the spectra. Diagnostic algorithms specific for combinations of sites with similar spectral properties were developed.
RESULTS: Discrimination of benign from dysplastic/malignant lesions was most successful when algorithms were designed for individual sites (area under the receiver operator characteristic curve [ROC-AUC],0.75 for the lateral surface of the tongue) and was least accurate when all sites were combined (ROC-AUC, 0.60). The combination of sites with similar spectral properties (floor of mouth and lateral surface of the tongue) yielded an ROC-AUC of 0.71.
CONCLUSIONS: Accurate spectroscopic detection of oral disease must account for spectral variations among anatomic sites. Anatomy-based algorithms for single sites or combinations of sites demonstrated good diagnostic performance in distinguishing benign lesions from dysplastic/malignant lesions and consistently performed better than algorithms developed for all sites combined.
MIT Department
Harvard University--MIT Division of Health Sciences and Technology
Massachusetts Institute of Technology. Spectroscopy Laboratory
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DOI of Published Version
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2860948/
